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Batchelor TT, Giri S, Ruppert AS, Geyer S, Smith SE, Mohile N, Swinnen LJ, Friedberg JW, Kahl BS, Bartlett NL, Hsi ED, Cheson BD, Wagner-Johnston ND, Nayak L, Leonard JP, Rubenstein JL. Myeloablative Vs. Non-Myeloablative Consolidation for Primary Central Nervous System Lymphoma: Results of Alliance 51101. Blood Adv 2024:bloodadvances.2023011657. [PMID: 38598710 DOI: 10.1182/bloodadvances.2023011657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 02/12/2024] [Accepted: 03/05/2024] [Indexed: 04/12/2024] Open
Abstract
While it is evident that standard dose whole brain radiotherapy as consolidation is associated with significant neurotoxicity, the optimal consolidative strategy for primary central nervous system lymphoma (PCNSL) is not defined. We performed a randomized phase 2 clinical trial via the U.S. Alliance cancer cooperative group to compare myeloablative consolidation supported by autologous stem cell transplantation with non-myeloablative consolidation after induction therapy for PCNSL. This is the first randomized trial to be initiated that eliminates whole brain radiotherapy as a consolidative approach in newly-diagnosed PCNSL. Patients, age 18-75 years, were randomly assigned in a 1:1 manner to induction therapy (methotrexate, temozolomide, rituximab and cytarabine) followed by consolidation with either thiotepa plus carmustine and autologous stem cell rescue versus induction followed by non-myeloablative, infusional etoposide plus cytarabine (EA) The primary endpoint was progression-free survival (PFS). 113 patients were randomized and 108 (54 in each arm) were evaluable. More patients in the non-myeloablative arm experienced progressive disease or death during induction (28% versus 11%, p = 0.05). Thirty-six patients received autologous stem cell transplant and 34 received non-myeloablative consolidation. The estimated 2-year PFS was higher in the myeloablative versus non-myeloablative arm (73% versus 51%; p= 0.02). However, a planned secondary analysis, landmarked at start of consolidation, revealed that the estimated 2-year PFS in those who completed consolidation therapy was not significantly different between the arms (86% versus 71%; p = 0.21). Both consolidative strategies yielded encouraging efficacy and similar toxicity profiles. Clinicaltrials.gov (NCT01511562).
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Affiliation(s)
| | | | - Amy S Ruppert
- Division of Hematology, Department of Internal Medicine, Ohio State University, Columbus, Ohio, United States
| | - Susan Geyer
- Mayo Clinic, Rochester, Minnesota, United States
| | - Scott E Smith
- Loyola University Chicago, Maywood, Illinois, United States
| | - Nimish Mohile
- University of Rochester Medical Center, Rochester, NY, New York, United States
| | - Lode J Swinnen
- Johns Hopkins University, Baltimore, Maryland, United States
| | | | - Brad S Kahl
- Washington University in St. Louis, Staint Louis, Missouri, United States
| | - Nancy L Bartlett
- Washington University School of Medicine, St. Louis, Missouri, United States
| | - Eric D Hsi
- Wake Forest University Health Sciences, United States
| | | | | | - Lakshmi Nayak
- Dana-Farber Cancer Institute, Boston, Massachusetts, United States
| | - John P Leonard
- Weill Medical College of Cornell University and New York Presbyterian Hospital, New York, New York, United States
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Russler-Germain DA, Krysiak K, Ramirez C, Mosior M, Watkins MP, Gomez F, Skidmore ZL, Trani L, Gao F, Geyer S, Cashen AF, Mehta-Shah N, Kahl BS, Bartlett NL, Alderuccio JP, Lossos IS, Ondrejka SL, Hsi ED, Martin P, Leonard JP, Griffith M, Griffith OL, Fehniger TA. Mutations associated with progression in follicular lymphoma predict inferior outcomes at diagnosis: Alliance A151303. Blood Adv 2023; 7:5524-5539. [PMID: 37493986 PMCID: PMC10514406 DOI: 10.1182/bloodadvances.2023010779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/17/2023] [Accepted: 07/18/2023] [Indexed: 07/27/2023] Open
Abstract
Follicular lymphoma (FL) is clinically heterogeneous, with select patients tolerating extended watch-and-wait, whereas others require prompt treatment, suffer progression of disease within 24 months of treatment (POD24), and/or experience aggressive histologic transformation (t-FL). Because our understanding of the relationship between genetic alterations in FL and patient outcomes remains limited, we conducted a clinicogenomic analysis of 370 patients with FL or t-FL (from Cancer and Leukemia Group B/Alliance trials 50402/50701/50803, or real-world cohorts from Washington University School of Medicine, Cleveland Clinic, or University of Miami). FL subsets by grade, stage, watch-and-wait, or POD24 status did not differ by mutation burden, whereas mutation burden was significantly higher in relapsed/refractory (rel/ref) FL and t-FL than in newly diagnosed (dx) FL. Nonetheless, mutation burden in dx FL was not associated with frontline progression-free survival (PFS). CREBBP was the only gene more commonly mutated in FL than in t-FL yet mutated CREBBP was associated with shorter frontline PFS in FL. Mutations in 20 genes were more common in rel/ref FL or t-FL than in dx FL, including 6 significantly mutated genes (SMGs): STAT6, TP53, IGLL5, B2M, SOCS1, and MYD88. We defined a mutations associated with progression (MAP) signature as ≥2 mutations in these 7 genes (6 rel/ref FL or t-FL SMGs plus CREBBP). Patients with dx FL possessing a MAP signature had shorter frontline PFS, revealing a 7-gene set offering insight into FL progression risk potentially more generalizable than the m7-Follicular Lymphoma International Prognostic Index (m7-FLIPI), which had modest prognostic value in our cohort. Future studies are warranted to validate the poor prognosis associated with a MAP signature in dx FL, potentially facilitating novel trials specifically in this high-risk subset of patients.
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Affiliation(s)
- David A. Russler-Germain
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
| | - Kilannin Krysiak
- Department of Pathology & Immunology, Washington University School of Medicine, St. Louis, MO
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO
| | - Cody Ramirez
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO
| | - Matthew Mosior
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO
| | - Marcus P. Watkins
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
| | - Felicia Gomez
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO
| | - Zachary L. Skidmore
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO
| | - Lee Trani
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO
| | - Feng Gao
- Public Health Sciences Division, Department of Surgery, Washington University School of Medicine, St. Louis, MO
| | - Susan Geyer
- Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, MN
| | - Amanda F. Cashen
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO
| | - Neha Mehta-Shah
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO
| | - Brad S. Kahl
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO
| | - Nancy L. Bartlett
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO
| | - Juan P. Alderuccio
- Division of Hematology, Sylvester Comprehensive Cancer Center, University of Miami School of Medicine, Miami, FL
| | - Izidore S. Lossos
- Division of Hematology, Sylvester Comprehensive Cancer Center, University of Miami School of Medicine, Miami, FL
| | - Sarah L. Ondrejka
- Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH
| | - Eric D. Hsi
- Department of Pathology, Wake Forest Baptist Medical Center, Winston Salem, NC
| | - Peter Martin
- Weill Cornell Medicine and New York Presbyterian Hospital, New York, NY
| | - John P. Leonard
- Weill Cornell Medicine and New York Presbyterian Hospital, New York, NY
| | - Malachi Griffith
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO
- Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Obi L. Griffith
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO
- Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Todd A. Fehniger
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO
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3
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Brastianos PK, Twohy E, Geyer S, Gerstner ER, Kaufmann TJ, Tabrizi S, Kabat B, Thierauf J, Ruff MW, Bota DA, Reardon DA, Cohen AL, De La Fuente MI, Lesser GJ, Campian J, Agarwalla PK, Kumthekar P, Mann B, Vora S, Knopp M, Iafrate AJ, Curry WT, Cahill DP, Shih HA, Brown PD, Santagata S, Barker FG, Galanis E. BRAF-MEK Inhibition in Newly Diagnosed Papillary Craniopharyngiomas. N Engl J Med 2023; 389:118-126. [PMID: 37437144 PMCID: PMC10464854 DOI: 10.1056/nejmoa2213329] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/14/2023]
Abstract
BACKGROUND Craniopharyngiomas, primary brain tumors of the pituitary-hypothalamic axis, can cause clinically significant sequelae. Treatment with the use of surgery, radiation, or both is often associated with substantial morbidity related to vision loss, neuroendocrine dysfunction, and memory loss. Genotyping has shown that more than 90% of papillary craniopharyngiomas carry BRAF V600E mutations, but data are lacking with regard to the safety and efficacy of BRAF-MEK inhibition in patients with papillary craniopharyngiomas who have not undergone previous radiation therapy. METHODS Eligible patients who had papillary craniopharyngiomas that tested positive for BRAF mutations, had not undergone radiation therapy previously, and had measurable disease received the BRAF-MEK inhibitor combination vemurafenib-cobimetinib in 28-day cycles. The primary end point of this single-group, phase 2 study was objective response at 4 months as determined with the use of centrally determined volumetric data. RESULTS Of the 16 patients in the study, 15 (94%; 95% confidence interval [CI], 70 to 100) had a durable objective partial response or better to therapy. The median reduction in the volume of the tumor was 91% (range, 68 to 99). The median follow-up was 22 months (95% CI, 19 to 30) and the median number of treatment cycles was 8. Progression-free survival was 87% (95% CI, 57 to 98) at 12 months and 58% (95% CI, 10 to 89) at 24 months. Three patients had disease progression during follow-up after therapy had been discontinued; none have died. The sole patient who did not have a response stopped treatment after 8 days owing to toxic effects. Grade 3 adverse events that were at least possibly related to treatment occurred in 12 patients, including rash in 6 patients. In 2 patients, grade 4 adverse events (hyperglycemia in 1 patient and increased creatine kinase levels in 1 patient) were reported; 3 patients discontinued treatment owing to adverse events. CONCLUSIONS In this small, single-group study involving patients with papillary craniopharyngiomas, 15 of 16 patients had a partial response or better to the BRAF-MEK inhibitor combination vemurafenib-cobimetinib. (Funded by the National Cancer Institute and others; ClinicalTrials.gov number, NCT03224767.).
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Affiliation(s)
- Priscilla K Brastianos
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Erin Twohy
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Susan Geyer
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Elizabeth R Gerstner
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Timothy J Kaufmann
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Shervin Tabrizi
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Brian Kabat
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Julia Thierauf
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Michael W Ruff
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Daniela A Bota
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - David A Reardon
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Adam L Cohen
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Macarena I De La Fuente
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Glenn J Lesser
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Jian Campian
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Pankaj K Agarwalla
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Priya Kumthekar
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Bhupinder Mann
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Shivangi Vora
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Michael Knopp
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - A John Iafrate
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - William T Curry
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Daniel P Cahill
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Helen A Shih
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Paul D Brown
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Sandro Santagata
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Fred G Barker
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
| | - Evanthia Galanis
- From Massachusetts General Hospital Cancer Center, Harvard Medical School (P.K.B., E.R.G., S.T., J.T., A.J.I., W.T.C., D.P.C., H.A.S., F.G.B.), Dana-Farber Cancer Institute (D.A.R.), and Brigham and Women's Hospital, Harvard Program in Therapeutic Science, Dana-Farber Partners CancerCare (S.S.) - all in Boston; Alliance Statistics and Data Management Center (E.T., S.G., B.K.), Mayo Clinic (T.J.K., M.W.R., P.D.B., E.G.), Rochester, MN; UC Irvine-Chao Family Comprehensive Cancer Center, Orange, CA (D.A.B.); Huntsman Cancer Institute, University of Utah, Salt Lake City (A.L.C.); Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami (M.I.D.L.F.); Wake Forest University School of Medicine, Winston-Salem, NC (G.J.L.); Washington University School of Medicine, St. Louis (J.C.); Rutgers Cancer Institute, New Brunswick, NJ (P.K.A.); Northwestern University, Chicago (P.K.); the Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD (B.M.); and Ohio State University Comprehensive Cancer Center, Columbus (S.V., M.K.)
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4
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Abdallah NH, Smith AN, Geyer S, Binder M, Greipp PT, Kapoor P, Dispenzieri A, Gertz MA, Baughn LB, Lacy MQ, Hayman SR, Buadi FK, Dingli D, Hwa YL, Lin Y, Kourelis T, Warsame R, Kyle RA, Rajkumar SV, Kumar SK. Conditional survival in multiple myeloma and impact of prognostic factors over time. Blood Cancer J 2023; 13:78. [PMID: 37188699 DOI: 10.1038/s41408-023-00852-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/22/2023] [Accepted: 05/03/2023] [Indexed: 05/17/2023] Open
Abstract
Overall survival estimates from diagnosis are valuable for guiding treatment, but do not consider the years already survived. Conditional survival (CS) provides dynamic survival predictions over time. This study was conducted to estimate CS at 1-8 years from diagnosis and the impact of baseline prognostic factors on CS in multiple myeloma (MM) patients. This is a retrospective study including 2556 MM patients diagnosed between 2004 and 2019. CS (t | s) was defined as the probability of surviving t years given survival of s years. Median age was 64 years. Median follow-up was 6.2 years and median overall survival from diagnosis was 7.5 years. The 5-year CS estimates at s = 0, 1, 2, 3, and 5 years were 0.64, 0.61, 0.61, 0.61, and 0.58, respectively. On multivariate analysis, age ≥ 65 and proteasome inhibitor+immunomodulatory-based induction were associated with decreased survival and increased survival, respectively, retained at 5 years. The adverse impact of 1q gain/amplification, high-risk IgH translocation, and ISS-3 was significant at 1 and 3 years but not 5 years. Chromosome 17 abnormality was associated with decreased survival only at 1 year. Among MM patients, 5-year CS was stable at 1-5 years from diagnosis. The prognostic impact of high-risk cytogenetic factors decreased with additional years survived.
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Affiliation(s)
| | | | - Susan Geyer
- Department of biostatistics, Mayo Clinic, Rochester, MN, USA
| | - Moritz Binder
- Division of Hematology, Mayo Clinic, Rochester, MN, USA
| | - Patricia T Greipp
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Morie A Gertz
- Division of Hematology, Mayo Clinic, Rochester, MN, USA
| | - Linda B Baughn
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Martha Q Lacy
- Division of Hematology, Mayo Clinic, Rochester, MN, USA
| | | | | | - David Dingli
- Division of Hematology, Mayo Clinic, Rochester, MN, USA
| | - Yi L Hwa
- Division of Hematology, Mayo Clinic, Rochester, MN, USA
| | - Yi Lin
- Division of Hematology, Mayo Clinic, Rochester, MN, USA
| | | | - Rahma Warsame
- Division of Hematology, Mayo Clinic, Rochester, MN, USA
| | - Robert A Kyle
- Division of Hematology, Mayo Clinic, Rochester, MN, USA
| | | | - Shaji K Kumar
- Division of Hematology, Mayo Clinic, Rochester, MN, USA.
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5
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Rödiger T, Geyer S, Odeh T, Siebert C. Data scarce modelling the impact of present and future groundwater development on Jordan multiaquifer groundwater resources. Sci Total Environ 2023; 870:161729. [PMID: 36682544 DOI: 10.1016/j.scitotenv.2023.161729] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 01/16/2023] [Accepted: 01/16/2023] [Indexed: 06/17/2023]
Abstract
Rapidly growing demands and climate change stresses water resources worldwide and leads to highly competitive situations between the environment and socio-economic development of a region, calling for a smart and modelling driven water resources management. However, data scarcity often prevents the realisation of a comprehensive, nation-wide resources model, which provides reliable and spatially discretized results of water resources development. We present a workflow approach to set up a large-scale multi-aquifer model, overcoming data shortage by stepwise calibration and integrating hydrological and numerical groundwater flow modelling into a coupled system. The study aims to develop such a system to assess how groundwater resources react on anthropogenic impacts on the example of the Kingdom of Jordan, one of the water poorest countries on globe. Simulated heads reliably resembled the monitored ones in >70 % of the observation wells. That makes us confident, the model represents all the states well from 1970, prior to the intense development of the country until 2015. The water balance shows an annual deficit of 1.16 million cubic meter (MCM) due to an overdraft. The discharge to the Dead Sea increased from 564 MCM/yr to 696 MCM/yr over the time period. Regional drawdowns of >250 m and groundwater depression with an extension of approx.100 km are observable in both large aquifer complexes. Most severe areas in the upper calcareous aquifer are located in the north of Amman and practically in all urban and agricultural agglomerations across the country. Groundwater tables in the deeper sandstone aquifer are particularly affected in the south as well as in the wider vicinity of the Dead Sea as consequence of its continuous dropping. Simulations of the future development of the groundwater tables indicate a severe deterioration of the situation with further declines in groundwater levels of up to 70 m.
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Affiliation(s)
- T Rödiger
- Helmholtz-Centre for Environmental Research UFZ, Dept. Catchment Hydrology, Theodor-Lieser-Str. 4, 06120 Halle, Germany.
| | - S Geyer
- Helmholtz-Centre for Environmental Research UFZ, Dept. Catchment Hydrology, Theodor-Lieser-Str. 4, 06120 Halle, Germany
| | - T Odeh
- The Hashemite University, Prince Al Hassan bin Talal College for Natural Resources and Environment, Dept. of Water Management and Environment, Zarqa, Jordan
| | - C Siebert
- Helmholtz-Centre for Environmental Research UFZ, Dept. Catchment Hydrology, Theodor-Lieser-Str. 4, 06120 Halle, Germany
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6
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Rahman R, Polley MYC, Alder L, Brastianos PK, Anders CK, Tawbi HA, Mehta M, Wen PY, Geyer S, de Groot J, Zadeh G, Piantadosi S, Galanis E, Khasraw M. Current drug development and trial designs in neuro-oncology: report from the first American Society of Clinical Oncology and Society for Neuro-Oncology Clinical Trials Conference. Lancet Oncol 2023; 24:e161-e171. [PMID: 36990614 PMCID: PMC10401610 DOI: 10.1016/s1470-2045(23)00005-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 12/11/2022] [Accepted: 01/05/2023] [Indexed: 03/29/2023]
Abstract
Successful drug development for people with cancers of the CNS has been challenging. There are multiple barriers to successful drug development including biological factors, rarity of the disease, and ineffective use of clinical trials. Based upon a series of presentations at the First Central Nervous System Clinical Trials Conference hosted by the American Society of Clinical Oncology and the Society for Neuro-Oncology, we provide an overview on drug development and novel trial designs in neuro-oncology. This Review discusses the challenges of therapeutic development in neuro-oncology and proposes strategies to improve the drug discovery process by enriching the pipeline of promising therapies, optimising trial design, incorporating biomarkers, using external data, and maximising efficacy and reproducibility of clinical trials.
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Affiliation(s)
- Rifaquat Rahman
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Mei-Yin C Polley
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Laura Alder
- Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA
| | - Priscilla K Brastianos
- Massachusetts General Hospital, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Carey K Anders
- Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA
| | | | - Minesh Mehta
- Miami Cancer Institute, Baptist Hospital, Miami, FL, USA
| | - Patrick Y Wen
- Centre for Neuro-Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Center for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Susan Geyer
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - John de Groot
- University of California San Francisco Brain Tumor Center, San Francisco, CA, USA
| | - Gelareh Zadeh
- Department of Neurological Surgery University of Toronto, Toronto, ON, Canada
| | - Steven Piantadosi
- Department of Surgery, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Evanthia Galanis
- Department of Oncology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, MN, USA
| | - Mustafa Khasraw
- Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA
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7
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Brastianos PK, Twohy EL, Gerstner ER, Kaufmann TJ, Iafrate AJ, Lennerz J, Jeyapalan S, Piccioni DE, Monga V, Fadul CE, Schiff D, Taylor JW, Chowdhary SA, Bettegowda C, Ansstas G, De La Fuente M, Anderson MD, Shonka N, Damek D, Carrillo J, Kunschner-Ronan LJ, Chaudhary R, Jaeckle KA, Senecal FM, Kaley T, Morrison T, Thomas AA, Welch MR, Iwamoto F, Cachia D, Cohen AL, Vora S, Knopp M, Dunn IF, Kumthekar P, Sarkaria J, Geyer S, Carrero XW, Martinez-Lage M, Cahill DP, Brown PD, Giannini C, Santagata S, Barker FG, Galanis E. Alliance A071401: Phase II Trial of Focal Adhesion Kinase Inhibition in Meningiomas With Somatic NF2 Mutations. J Clin Oncol 2023; 41:618-628. [PMID: 36288512 PMCID: PMC9870228 DOI: 10.1200/jco.21.02371] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 07/14/2022] [Accepted: 09/09/2022] [Indexed: 01/27/2023] Open
Abstract
PURPOSE Patients with progressive or recurrent meningiomas have limited systemic therapy options. Focal adhesion kinase (FAK) inhibition has a synthetic lethal relationship with NF2 loss. Given the predominance of NF2 mutations in meningiomas, we evaluated the efficacy of GSK2256098, a FAK inhibitor, as part of the first genomically driven phase II study in recurrent or progressive grade 1-3 meningiomas. PATIENTS AND METHODS Eligible patients whose tumors screened positively for NF2 mutations were treated with GSK2256098, 750 mg orally twice daily, until progressive disease. Efficacy was evaluated using two coprimary end points: progression-free survival at 6 months (PFS6) and response rate by Macdonald criteria, where PFS6 was evaluated separately within grade-based subgroups: grade 1 versus 2/3 meningiomas. Per study design, the FAK inhibitor would be considered promising in this patient population if either end point met the corresponding decision criteria for efficacy. RESULTS Of 322 patients screened for all mutation cohorts of the study, 36 eligible and evaluable patients with NF2 mutations were enrolled and treated: 12 grade 1 and 24 grade 2/3 patients. Across all grades, one patient had a partial response and 24 had stable disease as their best response to treatment. In grade 1 patients, the observed PFS6 rate was 83% (10/12 patients; 95% CI, 52 to 98). In grade 2/3 patients, the observed PFS6 rate was 33% (8/24 patients; 95% CI, 16 to 55). The study met the PFS6 efficacy end point both for the grade 1 and the grade 2/3 cohorts. Treatment was well tolerated; seven patients had a maximum grade 3 adverse event that was at least possibly related to treatment with no grade 4 or 5 events. CONCLUSION GSK2256098 was well tolerated and resulted in an improved PFS6 rate in patients with recurrent or progressive NF2-mutated meningiomas, compared with historical controls. The criteria for promising activity were met, and FAK inhibition warrants further evaluation for this patient population.
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Affiliation(s)
| | - Erin L. Twohy
- Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, MN
| | | | | | - A. John Iafrate
- Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Jochen Lennerz
- Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | | | | | | | | | - David Schiff
- University of Virginia Medical Center, Charlottesville, VA
| | - Jennie W. Taylor
- University of California, San Francisco Brain Tumor Center, San Francisco, CA
| | - Sajeel A. Chowdhary
- Lynn Cancer Institute, Boca Raton Regional Hospital/Baptist Hospital South Florida, Boca Raton, FL
| | | | | | | | | | | | | | | | | | | | | | | | - Thomas Kaley
- Memorial Sloan Kettering Cancer Center, New York, NY
| | | | | | - Mary R. Welch
- Columbia University Irving Medical Center, New York, NY
| | - Fabio Iwamoto
- Columbia University Irving Medical Center, New York, NY
| | | | | | - Shivangi Vora
- The Ohio State University Comprehensive Cancer Center, Columbus, OH
| | - Michael Knopp
- The Ohio State University Comprehensive Cancer Center, Columbus, OH
| | - Ian F. Dunn
- College of Medicine, University of Oklahoma, Oklahoma City, OK
| | | | | | - Susan Geyer
- Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, MN
| | - Xiomara W. Carrero
- Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, MN
| | | | - Daniel P. Cahill
- Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | | | | | - Sandro Santagata
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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8
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Quintanilha JCF, Geyer S, Etheridge AS, Racioppi A, Hammond K, Crona DJ, Peña CE, Jacobson S, Marmorino F, Rossini D, Cremolini C, Sanoff HK, Abou-Alfa GK, Innocenti F. KDR genetic predictor of toxicities induced by sorafenib and regorafenib. Pharmacogenomics J 2022; 22:251-257. [PMID: 35484400 PMCID: PMC9613789 DOI: 10.1038/s41397-022-00279-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/12/2022] [Accepted: 04/13/2022] [Indexed: 01/21/2023]
Abstract
No biomarkers are available to predict toxicities induced by VEGFR TKIs. This study aimed to identify markers of toxicities induced by these drugs using a discovery-validation approach. The discovery set included 140 sorafenib-treated cancer patients (TARGET study) genotyped for SNPs in 56 genes. The most significant SNPs associated with grade ≥2 hypertension, diarrhea, dermatologic toxicities, and composite toxicity (any one of the toxicities) were tested for association with grade ≥2 toxicity in a validation set of 201 sorafenib-treated patients (Alliance/CALGB 80802). The validated SNP was tested for association with grade ≥2 toxicity in 107 (LCCC 1029) and 82 (Italian cohort) regorafenib-treated patients. SNP-toxicity associations were evaluated using logistic regression, and a meta-analysis between the studies was performed by inverse variance. Variant rs4864950 in KDR increased the risk of grade ≥2 composite toxicity in TARGET, Alliance/CALGB 80802, and the Italian cohort (meta-analysis p = 6.79 × 10-4, OR = 2.01, 95% CI 1.34-3.01). We identified a predictor of toxicities induced by VEGFR TKIs. CLINICALTRIALS.GOV IDENTIFIER: NCT00073307 (TARGET), NCT01015833 (Alliance/CALGB 80802), and NCT01298570 (LCCC 1029).
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Affiliation(s)
- Julia C. F. Quintanilha
- UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Correspondence: Julia C. F. Quintanilha. University of North Carolina at Chapel Hill, Eshelman School of Pharmacy, Genetic Medicine Bldg. 120 Mason Farm Rd, Campus Box 7361, Chapel Hill, NC 27599-7361,
| | - Susan Geyer
- Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, Minnesota, USA
| | - Amy S. Etheridge
- UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Alessandro Racioppi
- UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Kelli Hammond
- UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Daniel J. Crona
- UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Carol E. Peña
- Bayer HealthCare Pharmaceuticals, Whippany, New Jersey, USA
| | - Sawyer Jacobson
- Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, Minnesota, USA
| | - Federica Marmorino
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.,Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Daniele Rossini
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.,Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Chiara Cremolini
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.,Unit of Medical Oncology 2, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Hanna K. Sanoff
- UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ghassan K. Abou-Alfa
- Memorial Sloan Kettering Cancer Center, New York, New York, USA.,Weill Medical College at Cornell University, New York, New York, USA
| | - Federico Innocenti
- AbbVie, Inc., South San Francisco, California, USA.,Correspondence: Federico Innocenti, MD, PhD. AbbVie, Inc., South San Francisco, 1000 Gateway Blvd. South San Francisco, California 94080,
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9
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Jacobsen LM, Bundy BN, Ismail HM, Clements M, Warnock M, Geyer S, Schatz DA, Sosenko JM. Index60 Is Superior to HbA1c for Identifying Individuals at High Risk for Type 1 Diabetes. J Clin Endocrinol Metab 2022; 107:2784-2792. [PMID: 35880956 PMCID: PMC9516117 DOI: 10.1210/clinem/dgac440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT HbA1c from ≥ 5.7% to < 6.5% (39-46 mmol/mol) indicates prediabetes according to American Diabetes Association guidelines, yet its identification of prediabetes specific for type 1 diabetes has not been assessed. A composite glucose and C-peptide measure, Index60, identifies individuals at high risk for type 1 diabetes. OBJECTIVE We compared Index60 and HbA1c thresholds as markers for type 1 diabetes risk. METHODS TrialNet Pathway to Prevention study participants with ≥ 2 autoantibodies (GADA, IAA, IA-2A, or ZnT8A) who had oral glucose tolerance tests and HbA1c measurements underwent 1) predictive time-dependent modeling of type 1 diabetes risk (n = 2776); and 2) baseline comparisons between high-risk mutually exclusive groups: Index60 ≥ 2.04 (n = 268) vs HbA1c ≥ 5.7% (n = 268). The Index60 ≥ 2.04 threshold was commensurate in ordinal ranking with the standard prediabetes threshold of HbA1c ≥ 5.7%. RESULTS In mutually exclusive groups, individuals exceeding Index60 ≥ 2.04 had a higher cumulative incidence of type 1 diabetes than those exceeding HbA1c ≥ 5.7% (P < 0.0001). Appreciably more individuals with Index60 ≥ 2.04 were at stage 2, and among those at stage 2, the cumulative incidence was higher for those with Index60 ≥ 2.04 (P = 0.02). Those with Index60 ≥ 2.04 were younger, with lower BMI, greater autoantibody number, and lower C-peptide than those with HbA1c ≥ 5.7% (P < 0.0001 for all comparisons). CONCLUSION Individuals with Index60 ≥ 2.04 are at greater risk for type 1 diabetes with features more characteristic of the disorder than those with HbA1c ≥ 5.7%. Index60 ≥ 2.04 is superior to the standard HbA1c ≥ 5.7% threshold for identifying prediabetes in autoantibody-positive individuals. These findings appear to justify using Index60 ≥ 2.04 as a prediabetes criterion in this population.
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Affiliation(s)
- Laura M Jacobsen
- Correspondence: Laura M. Jacobsen, MD, Division of Pediatric Endocrinology, University of Florida, 1275 Center Drive, Gainesville, FL 32610, USA.
| | - Brian N Bundy
- Health Informatics Institute, University of South Florida, Tampa, FL 33620, USA
| | - Heba M Ismail
- Department of Pediatrics, Indiana University, Indianapolis, IN 46202, USA
| | - Mark Clements
- Pediatric Endocrinology, Children’s Mercy, Kansas City, MO 64111, USA
| | - Megan Warnock
- Health Informatics Institute, University of South Florida, Tampa, FL 33620, USA
| | - Susan Geyer
- Health Informatics Institute, University of South Florida, Tampa, FL 33620, USA
| | - Desmond A Schatz
- Division of Pediatric Endocrinology, University of Florida, Gainesville, FL 32610, USA
| | - Jay M Sosenko
- Division of Endocrinology, University of Miami, Miami, FL 33136, USA
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10
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Abdallah N, Smith A, Geyer S, Binder M, Greipp P, Kapoor P, Dispenzieri A, Gertz M, Baughn L, Lacy M, Hayman S, Buadi F, Dingli D, Hwa Y, Lin Y, Kourelis T, Warsame R, Kyle R, Rajkumar S, Kumar S. 639P Conditional survival in MM and impact of prognostic factors over time. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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11
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Tetzlaff J, Luy M, Epping J, Geyer S, Beller J, Stahmeyer J, Sperlich S, Tetzlaff F. Estimating trends in working life expectancy based on health insurance data from Germany – Challenges and advantages. SSM Popul Health 2022; 19:101215. [PMID: 36091300 PMCID: PMC9450162 DOI: 10.1016/j.ssmph.2022.101215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 08/17/2022] [Accepted: 08/19/2022] [Indexed: 11/30/2022] Open
Abstract
Against the backdrop of population aging and growing strain on pension systems, monitoring the development of Working Life Expectancy (WLE) is vital to assess whether the policies taken are effective. This is the first study investigating time trends and educational inequalities in WLE based on German health insurance data. The analyses are based on the data of the AOK Lower Saxony (N = 3,347,912) covering three time periods (2006-08, 2011-13, and 2016-18). WLE is defined as years spent in the labor force (i.e. in employment and unemployment) and was calculated for each age between 18 and 69 years for the three periods to depict changes over time using multistate life table analysis. Educational inequalities in 2011-13 are reported for two educational levels (8–11 years and 12–13 years of schooling). WLE increased in both sexes with increases being stronger among women. This holds irrespective of whether WLE at age 18 (35.8–38.3 years in men, 27.5–34.0 years in women) or the older working-age (e.g. at age 50 10.2–11.7 years in men, 7.8–10.5 years in men) is considered. Among women at all ages and men from their mid-20s onwards, WLE was higher among higher-educated individuals. Inequalities were most pronounced among women (e.g. Δ3.1 years in women, Δ1.3 years in men at age 50). The study supports previous research indicating that measures to extend working life are effective, but that noticeable inequalities in WLE exist. Health insurance data represent a valuable source for such research that has so far remained untapped. The data provide a suitable basis to investigate trends and inequalities in WLE. Future research should build on the strengths of the data by broadening the research towards a more comprehensive analysis of the development of WLE from a health perspective. Working Life Expectancy has increased substantially since the mid-2000s. The gender gap narrowed over time, but men still spend considerably more years in the labor force than women. Educational inequalities in WLE exist in both sexes, but are larger in women. Measures to increase labor force participation should focus especially on lower-educated women, as WLE is low in this group. Prevention should be strengthened for vulnerable groups to reduce health inequalities and early labor market exits.
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12
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Tetzlaff J, Epping J, Geyer S, Beller J, Sperlich S, Tetzlaff F. Länger leben, länger arbeiten? Zeittrends und
Bildungsungleichheiten in der Working Life Expectancy auf der Basis von
Krankenkassendaten. Das Gesundheitswesen 2022. [DOI: 10.1055/s-0042-1753711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- J Tetzlaff
- Medizinische Hochschule Hannover, Medizinische Soziologie, Hannover,
Deutschland
| | - J Epping
- Medizinische Hochschule Hannover, Medizinische Soziologie, Hannover,
Deutschland
| | - S Geyer
- Medizinische Hochschule Hannover, Medizinische Soziologie, Hannover,
Deutschland
| | - J Beller
- Medizinische Hochschule Hannover, Medizinische Soziologie, Hannover,
Deutschland
| | - S Sperlich
- Medizinische Hochschule Hannover, Medizinische Soziologie, Hannover,
Deutschland
| | - F Tetzlaff
- Medizinische Hochschule Hannover, Medizinische Soziologie, Hannover,
Deutschland
- Robert Koch-Institut, Fachgebiet Soziale Determinanten der Gesundheit,
Berlin, Deutschland
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13
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Sperlich S, Adler FM, Beller J, Safieddine B, Tetzlaff J, Geyer S. Zeitliche Entwicklung subjektiver Gesundheit von alleinerziehenden
Müttern in Deutschland – eine Dekompositionsanalyse des
Einflusses von Veränderungen der sozioökonomischen
Lebenssituation von 1994 bis 2018. Das Gesundheitswesen 2022. [DOI: 10.1055/s-0042-1753619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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14
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Gagnon MF, Tian S, Geyer S, Sharma N, Vachon CM, Kusne Y, Bergsagel PL, Stewart AK, Rajkumar SV, Kumar S, Ailawadhi S, Baughn LB. Distribution of clonal hematopoiesis of indeterminate potential (CHIP) is not associated with race in patients with plasma cell neoplasms. Blood Cancer J 2022; 12:112. [PMID: 35882836 PMCID: PMC9325693 DOI: 10.1038/s41408-022-00706-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 07/04/2022] [Accepted: 07/08/2022] [Indexed: 11/09/2022] Open
Affiliation(s)
- Marie-France Gagnon
- Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Shulan Tian
- Division of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Susan Geyer
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Neeraj Sharma
- Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Celine M Vachon
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Yael Kusne
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | - P Leif Bergsagel
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | | | - S Vincent Rajkumar
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Shaji Kumar
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Sikander Ailawadhi
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Jacksonville, FL, USA
| | - Linda B Baughn
- Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA. .,Division of Hematopathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
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15
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Baidal DA, Warnock M, Xu P, Geyer S, Marks JB, Moran A, Sosenko J, Evans-Molina C. Oral Glucose Tolerance Test Measures of First-phase Insulin Response and Their Predictive Ability for Type 1 Diabetes. J Clin Endocrinol Metab 2022; 107:e3273-e3280. [PMID: 35524749 PMCID: PMC9282258 DOI: 10.1210/clinem/dgac285] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Decreased first-phase insulin response (FPIR) during intravenous glucose tolerance testing (IVGTT) is an early indicator of β-cell dysfunction and predictor of type 1 diabetes (T1D). OBJECTIVE Assess whether oral glucose tolerance test (OGTT) measures could serve as FPIR alternatives in their ability to predict T1D in autoantibody positive (Aab+) subjects. DESIGN OGTT and IVGTT were performed within 30 days of each other. Eleven OGTT variables were evaluated for (1) correlation with FPIR and (2) T1D prediction. SETTING Type 1 Diabetes TrialNet "Oral Insulin for Prevention of Diabetes in Relatives at Risk for T1D" (TN-07) and Diabetes Prevention Trial-Type 1 Diabetes (DPT-1) studies clinical sites. PATIENTS TN-07 (n = 292; age 9.4 ± 6.1 years) and DPT-1 (n = 194; age 15.1 ± 10.0 years) Aab + relatives of T1D individuals. MAIN OUTCOME MEASURES (1) Correlation coefficients of OGTT measures with FPIR and (2) T1D prediction at 2 years using area under receiver operating characteristic (ROCAUC) curves. RESULTS Index60 showed the strongest correlation in DPT-1 (r = -0.562) but was weaker in TN-07 (r = -0.378). C-peptide index consistently showed good correlation with FPIR across studies (TN-07, r = 0.583; DPT-1, r = 0.544; P < 0.0001). Index60 and C-peptide index had the highest ROCAUCs for T1D prediction (0.778 vs 0.717 in TN-07 and 0.763 vs 0.721 in DPT-1, respectively; P = NS), followed by FPIR (0.707 in TN-07; 0.628 in DPT-1). CONCLUSIONS C-peptide index was the strongest measure to correlate with FPIR in both studies. Index60 and C-peptide index had the highest predictive accuracy for T1D and were comparable. OGTTs could be considered instead of IVGTTs for subject stratification in T1D prevention trials.
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Affiliation(s)
- David A Baidal
- Correspondence: David A. Baidal, MD, Department of Medicine and the Diabetes Research Institute, Leonard Miller School of Medicine, University of Miami, 1450 NW 10th Ave, Miami, FL 33136, USA.
| | - Megan Warnock
- Data Analysis & Research, Office of Data Management & Information Systems, West Virginia Department of Education, Charleston, WV 25305, USA
| | - Ping Xu
- Late Development Statistics, Biostatistics and Research Decision Sciences, Merck Research Laboratories, Rahway, NJ 07065-4607, USA
| | - Susan Geyer
- Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA
| | - Jennifer B Marks
- Department of Medicine and the Diabetes Research Institute, Leonard Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Antoinette Moran
- Department of Pediatrics, University of Minnesota, Minneapolis, MN 55454, USA
| | - Jay Sosenko
- Department of Medicine and the Diabetes Research Institute, Leonard Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Carmella Evans-Molina
- Departments of Medicine and Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202, USA
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16
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Kronsteiner B, Zopf L, Heimel P, Oberoi G, Kramer AM, Slezak P, Reissig L, Geyer S, Weninger WJ, Podesser BK, Kiss A, Moscato F. Topographical Mapping of the cardiac autonomic innervation for selective cardiac neuromodulation in pigs and rabbits using MicroCT. Cardiovasc Res 2022. [DOI: 10.1093/cvr/cvac066.156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Horizon 2020- EU H2020-EU.1.2.2. - FET Proactive
"NeuHeart" Nr. 824071
Background & Introduction
In recent years, Vagus Nerve Stimulation (VNS) has proved to be a potential therapeutic approach for the treatment of cardiovascular diseases, such as Heart Failure or atrial fibrillation [1]. However, the lack of specific anatomical knowledge of the cervical VN [2, 3] and thus, of the cardiac autonomic innervation aggravates the side effects of unselective cervical VNS.
Purpose
The goal of this study was to investigate the cardiac vagus nerve branches for selective cardiac VNS stimulation using micro-computed tomography (µCT) and 3D renderings.
Methods
Vagus nerve specimens (n= 11 pig nerves, n= 5 rabbit nerves) were harvested from the nodose ganglion down to the cardiac branches in domestic pigs and New Zealand White rabbits on both sides, and the cardiac autonomic innervation was mapped µCT and 3D renderings.
Results
Our results provide anatomical and topographical key features on the cervical and cardiac autonomic innervation including course of the cardiac branch, cardiac branching patterns, fascicle number, and size of the autonomic nerves. We also compared these aforementioned anatomical parameters between pigs and rabbits and highlighted key anatomical differences among individuals within pigs. In pigs, the cardiac branches were partly composed of both nerves even when they branched off the VN whereas in rabbits, the two nerves were completely separated and the cardiac branch was solely parasympathetic. Finally, we generated a 3D model of various parts of the VN specimen and compared them to images of the native nerves taken during VN dissection surgery.
Conclusions
Here we present an imaging approach to map the anatomy and topography of the cardiac Vagus Nerve for selective stimulation of cardiac VN branches. We also characterized the morphology of the VN, the sympathetic trunk (ST), and the cardiac branch (CB) at the level of the cardiac branching point to highlight the complex interplay between the nerves. Our data provide one possible reason for unwanted side effects of cervical VNS. However, future studies are required to broaden the knowledge in this specific research field of selective cardiac VNS.
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Affiliation(s)
| | - L Zopf
- Ludwig Boltzmann Cluster for Cardiovascular Research , Vienna , Austria
| | - P Heimel
- Ludwig Boltzmann Cluster for Cardiovascular Research , Vienna , Austria
| | - G Oberoi
- Medical University of Vienna , Vienna , Austria
| | - A-M Kramer
- Medical University of Vienna , Vienna , Austria
| | - P Slezak
- Ludwig Boltzmann Cluster for Cardiovascular Research , Vienna , Austria
| | - L Reissig
- Medical University of Vienna , Vienna , Austria
| | - S Geyer
- Medical University of Vienna , Vienna , Austria
| | - WJ Weninger
- Medical University of Vienna , Vienna , Austria
| | - BK Podesser
- Medical University of Vienna , Vienna , Austria
| | - A Kiss
- Medical University of Vienna , Vienna , Austria
| | - F Moscato
- Medical University of Vienna , Vienna , Austria
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17
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Nathan BM, Redondo MJ, Ismail H, Jacobsen L, Sims EK, Palmer J, Skyler J, Bocchino L, Geyer S, Sosenko JM. Index60 Identifies Individuals at Appreciable Risk for Stage 3 Among an Autoantibody-Positive Population With Normal 2-Hour Glucose Levels: Implications for Current Staging Criteria of Type 1 Diabetes. Diabetes Care 2022; 45:311-318. [PMID: 34853027 PMCID: PMC8914436 DOI: 10.2337/dc21-0944] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 11/08/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We assessed whether Index60, a composite measure of fasting C-peptide, 60-min C-peptide, and 60-min glucose, could improve the metabolic staging of type 1 diabetes for progression to clinical disease (stage 3) among autoantibody-positive (Ab+) individuals with normal 2-h glucose values (<140 mg/dL). RESEARCH DESIGN AND METHODS We analyzed 3,058 Type 1 Diabetes TrialNet Pathway to Prevention participants with 2-h glucose <140 mg/dL and Index60 <1.00 values from baseline oral glucose tolerance tests. Characteristics associated with type 1 diabetes (younger age, greater Ab+, higher HLA DR3-DQ2/DR4-DQ8 prevalence, and lower C-peptide) were compared among four mutually exclusive groups: top 2-h glucose quartile only (HI-2HGLU), top Index60 quartile only (HI-IND60), both top quartiles (HI-BOTH), and neither top quartile (LO-BOTH). Additionally, within the 2-h glucose distribution of <140 mg/dL and separately within the Index60 <1.00 distribution, comparisons were made between those above or below the medians. RESULTS HI-IND60 and HI-BOTH were younger, with greater frequency of more than two Ab+, and lower C-peptide levels, than either HI-2HGLU or LO-BOTH (all P < 0.001). The cumulative incidence for stage 3 was greater for HI-IND60 and HI-BOTH than for either HI-2HGLU or LO-BOTH (all P < 0.001). Those with Index60 values above the median were younger and had higher frequency of two or more Ab+ (P < 0.001) and DR3-DQ2/DR4-DQ8 prevalence (P < 0.001) and lower area under the curve (AUC) C-peptide levels (P < 0.001) than those below. Those above the 2-h glucose median had higher AUC C-peptide levels (P < 0.001), but otherwise did not differ from those below. CONCLUSIONS Index60 identifies individuals with characteristics of type 1 diabetes at appreciable risk for progression who would otherwise be missed by 2-h glucose staging criteria.
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Affiliation(s)
| | - Maria J Redondo
- Baylor College of Medicine, Texas Children's Hospital, Houston, TX
| | - Heba Ismail
- Indiana University School of Medicine, Indianapolis, IN
| | | | - Emily K Sims
- Indiana University School of Medicine, Indianapolis, IN
| | | | | | | | - Susan Geyer
- University of South Florida, Tampa, FL.,Mayo Clinic, Rochester, MN
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18
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Galanis E, Anderson SK, Twohy E, Butowski NA, Hormigo A, Schiff D, Omuro A, Jaeckle KA, Kumar S, Kaufmann TJ, Geyer S, Kumthekar PU, Campian J, Giannini C, Buckner JC, Wen PY. Phase I/randomized phase II trial of TRC105 plus bevacizumab versus bevacizumab in recurrent glioblastoma: North Central Cancer Treatment Group N1174 (Alliance). Neurooncol Adv 2022; 4:vdac041. [PMID: 35664553 PMCID: PMC9154335 DOI: 10.1093/noajnl/vdac041] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Background Patients with glioblastoma (GBM) have a poor prognosis and limited effective treatment options. Bevacizumab has been approved for treatment of recurrent GBM, but there is questionable survival benefit. Based on preclinical and early clinical data indicating that CD105 upregulation may represent a mechanism of resistance to bevacizumab, we hypothesized that combining bevacizumab with the anti-CD105 antibody TRC105 may improve efficacy in recurrent GBM. Methods Phase I dose-escalation/comparative randomized phase II trial in patients with GBM. During phase I, the maximum tolerated dose (MTD) of TRC105 in combination with bevacizumab was determined. In phase II, patients were randomized 1:1 to TRC105 and bevacizumab or bevacizumab monotherapy. Patients received TRC105 (10 mg/kg) weekly and bevacizumab (10 mg/kg) every 2 weeks. Efficacy, as assessed by progression-free survival (PFS), was the primary endpoint; safety, quality of life, and correlative outcomes were also evaluated. Results In total, 15 patients were enrolled in phase I and 101 in phase II; 52 patients were randomized to TRC105 with bevacizumab and 49 to bevacizumab monotherapy. The MTD was determined to be 10 mg/kg TRC105 weekly plus bevacizumab 10 mg/kg every 2 weeks. An increased occurrence of grade ≥3 adverse events was seen in the combination arm, including higher incidences of anemia. Median PFS was similar in both treatment arms: 2.9 months for combination versus 3.2 months for bevacizumab monotherapy (HR = 1.16, 95% CI = 0.75-1.78, P = .51). Quality of life scores were similar for both treatment arms. Conclusions TRC105 in combination with bevacizumab was well tolerated in patients with recurrent GBM, but no difference in efficacy was observed compared to bevacizumab monotherapy.
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Affiliation(s)
- Evanthia Galanis
- Department of Oncology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Pathology, Mayo Clinic, Rochester, Minnesota, USA
- Mayo Clinic, Rochester, Minnesota, USA
| | - S Keith Anderson
- Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, Minnesota, USA
| | - Erin Twohy
- Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, Minnesota, USA
| | - Nicholas A Butowski
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California, USA
| | - Adilia Hormigo
- Department of Neurology, Icahn School of Medicine at Mount Sinai, The Tisch Cancer Institute, New York, New York, USA
| | - David Schiff
- Department of Neurology, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Antonio Omuro
- Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Kurt A Jaeckle
- Department of Neurology, Mayo Clinic Florida, Jacksonville, Florida, USA
| | - Shaji Kumar
- Department of Hematology, Mayo Clinic, Rochester, Minnesota, USA
- Mayo Clinic, Rochester, Minnesota, USA
| | - Timothy J Kaufmann
- Department of Neuroradiology, Mayo Clinic, Rochester, Minnesota, USA
- Mayo Clinic, Rochester, Minnesota, USA
| | - Susan Geyer
- Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, Minnesota, USA
| | - Priya U Kumthekar
- Northwestern Medicine, Lou and Jean Malnati Brain Tumor Institute, Chicago Illinois, USA
| | - Jian Campian
- Washington University School of Medicine, Siteman Cancer Center, St. Louis, Missouri, USA
| | | | - Jan C Buckner
- Department of Oncology, Mayo Clinic, Rochester, Minnesota, USA
- Mayo Clinic, Rochester, Minnesota, USA
| | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber/Partners Cancer Care, Boston, Massachusetts, USA
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19
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Shih H, Tabrizi S, Kabat B, Twohy E, Geyer S, Vora S, Gerstner E, Kaufmann T, Ruff M, Reardon D, Cohen A, Bota D, Agarwalla P, De la Fuente M, Lesser G, Campian J, Kumthekar P, Knopp M, Cahill D, Santagata S, Barker F, Galanis E, Brastianos P, Brown P. CTNI-53. RADIATION TREATMENT VOLUMES BEFORE AND AFTER BRAF/MEK THERAPY IN NEWLY DIAGNOSED PAPILLARY CRANIOPHARYNGIOMAS: A CORRELATIVE ANALYSIS OF THE ALLIANCE A071601 PHASE II TRIAL. Neuro Oncol 2021. [DOI: 10.1093/neuonc/noab196.278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
PURPOSE
Standard of care for craniopharyngiomas is surgery with or without radiotherapy (RT). Cohort A of Alliance A071601 evaluated the efficacy of BRAF/MEK inhibition with vemurafenib/cobimetinib in patients with previously untreated papillary craniopharyngiomas (PCP), which carry the BRAF V600E mutation. Cohort B is currently enrolling patients with recurrence after RT. In a correlative analysis, we examined changes in RT volumes after BRAF/MEK therapy in Cohort A.
METHODS
Previously unirradiated patients with BRAF-mutated PCP were treated with vemurafenib/cobimetinib. Sixteen patients had scans available before starting vemurafenib/cobimetinib (“pre-therapy”) and after completing therapy (“post-therapy”). Two patients went off study treatment after 8 and 9 days due to side-effects and were excluded for this analysis. Gross target volumes (GTV) were contoured on pre-therapy and post-therapy scans. On post-therapy scans, an additional target comprising gross disease and at-risk regions for microscopic residual disease (GTV-micro) was defined and considered the treatment volume. Clinical target volume (CTV) was a 5-mm uniform expansion on pre-therapy GTV and post-therapy GTV-micro. Volumes were independently reviewed by two radiation oncologists. Changes in volumes from pre- versus post-therapy were compared using the Wilcoxon signed rank test.
RESULTS
In 14 patients evaluated, 57% were female and median age at enrollment was 49.5 years (range 33-83). Median time on treatment was 8.9 months (range 4.0-18.0). Median GTV pre-therapy was 3.8 mL (range 0.2-23.4) versus 0.3 mL (range 0.0-3.2) post-therapy (p=0.0001) and 1.7 mL (range 0.1-8.0) post-therapy GTV-micro (p=0.0001). Median CTV pre-therapy was 13.7 mL (range 2.8-51.8) versus 9.1 mL (range 2.2-27.5) post-therapy (p=0.0001). All tumors abutted the optic chiasm pre-therapy, only 6 did post-therapy.
CONCLUSIONS
Vemurafenib/cobimetinib resulted in smaller RT volumes. BRAF/MEK inhibitors could reduce RT volumes and spare dose to surrounding normal structures. Enrollment to Cohort B of Alliance A071601 should be considered for patients with recurrent tumors after RT.
SUPPORT
https://acknowledgments.alliancefound.org
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Affiliation(s)
- Helen Shih
- Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Shervin Tabrizi
- Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | | | | | | | - Shivangi Vora
- Imaging Core Lab at IROC Ohio, The Ohio State University, Columbus, OH, USA
| | | | | | | | - David Reardon
- Dana-Farber Cancer Institute, Boston, MA, USA, Boston, MA, USA
| | - Adam Cohen
- Inova Schar Cancer Institute, Fairfax, VA, USA
| | - Daniela Bota
- Department of Neurology, University of California, Irvine, Irvine, CA, USA
| | | | - Macarena De la Fuente
- Sylvester Comprehensive Cancer Center, University of Miami Hospital and Clinics, Miami, FL, USA
| | - Glen Lesser
- Wake Forest Baptist Health - Comprehensive Cancer Center, Winston-Salem, NC, USA
| | | | - Priya Kumthekar
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | | | | | - Fred Barker
- Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Paul Brown
- Mayo Clinic Rochester, Rockester, MN, USA
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20
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Safieddine B, Sperlich S, Epping J, Lange K, Geyer S. Development of Comorbidities in Type 2 Diabetes: Morbidity Expansion or Dynamic Equilibrium? Eur J Public Health 2021. [DOI: 10.1093/eurpub/ckab164.332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Different hypotheses have been proposed about the future development of morbidity associated with the temporal improvement in life expectancy. However, many studies have focused on general morbidity while testing these hypotheses. In type 2 diabetes (T2D), one of the most prevalent chronic diseases, research points towards an increasing prevalence over time with a simultaneous increase in life expectancy among this population. While morbidity compression in T2D can thus be ruled out, it remains unclear whether morbidity expansion or dynamic equilibrium applies, which could be the case with a decrease in personal disease burden despite increasing prevalence. Against this background, this study aims to examine how the prevalence of T2D-related comorbidities is developing over time.
Methods
Using claims data of a large statutory insurance provider in the state of Lower-Saxony, Germany, the period prevalence of nine T2D-related comorbidities was examined for the time periods 2005-2007, 2010-2012, and 2015-2017 in 240241, 295868, and 308134 individuals with T2D, respectively. The temporal development of comorbidities was examined by logistic regression analysis. The change in the number of comorbidities over time was examined by ordered logistic regression. Analyses were stratified by gender and three age groups.
Results
Over the three time periods, age-adjusted predicted probabilities for more severe cardiovascular diseases (CVDs) decreased in men and women with T2D while those for less severe CVDs and other vascular diseases such as retinopathy, polyneuropathy any nephropathy increased significantly in all subgroups. Among all subgroups, the predicted probability of having more comorbidities over time also increased significantly.
Conclusions
Despite differences in the way CVDs are developing, the results are in favour of the morbidity expansion hypothesis for this population. Further research is needed to examine the reasons behind the observed trends.
Key messages
The developement of comorbidities in individuals with type 2 diabetes points towards morbidity expansion among this population. Future studies should examine whether the change is socioeconomic status, medication use and lifestyle risk factors are contributing to these trends.
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Affiliation(s)
- B Safieddine
- Medical Sociology Unit, Hannover Medical School, Hannover, Germany
| | - S Sperlich
- Medical Sociology Unit, Hannover Medical School, Hannover, Germany
| | - J Epping
- Medical Sociology Unit, Hannover Medical School, Hannover, Germany
| | - K Lange
- Medical Psychology Unit, Hannover Medical School, Hannover, Germany
| | - S Geyer
- Medical Sociology Unit, Hannover Medical School, Hannover, Germany
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21
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Redondo MJ, Warnock MV, Libman IM, Bocchino LE, Cuthbertson D, Geyer S, Pugliese A, Steck AK, Evans-Molina C, Becker D, Sosenko JM, Bacha F. TCF7L2 Genetic Variants Do Not Influence Insulin Sensitivity or Secretion Indices in Autoantibody-Positive Individuals at Risk for Type 1 Diabetes. Diabetes Care 2021; 44:2039-2044. [PMID: 34326068 PMCID: PMC8740915 DOI: 10.2337/dc21-0531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 06/10/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We aimed to test whether type 2 diabetes (T2D)-associated TCF7L2 genetic variants affect insulin sensitivity or secretion in autoantibody-positive relatives at risk for type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS We studied autoantibody-positive TrialNet Pathway to Prevention study participants (N = 1,061) (mean age 16.3 years) with TCF7L2 single nucleotide polymorphism (SNP) information and baseline oral glucose tolerance test (OGTT) to calculate indices of insulin sensitivity and secretion. With Bonferroni correction for multiple comparisons, P values < 0.0086 were considered statistically significant. RESULTS None, one, and two T2D-linked TCF7L2 alleles were present in 48.1%, 43.9%, and 8.0% of the participants, respectively. Insulin sensitivity (as reflected by 1/fasting insulin [1/IF]) decreased with increasing BMI z score and was lower in Hispanics. Insulin secretion (as measured by 30-min C-peptide index) positively correlated with age and BMI z score. Oral disposition index was negatively correlated with age, BMI z score, and Hispanic ethnicity. None of the indices were associated with TCF7L2 SNPs. In multivariable analysis models with age, BMI z score, ethnicity, sex, and TCF7L2 alleles as independent variables, C-peptide index increased with age, while BMI z score was associated with higher insulin secretion (C-peptide index), lower insulin sensitivity (1/IF), and lower disposition index; there was no significant effect of TCF7L2 SNPs on any of these indices. When restricting the analyses to participants with a normal OGTT (n = 743; 70%), the results were similar. CONCLUSIONS In nondiabetic autoantibody-positive individuals, TCF7L2 SNPs were not related to insulin sensitivity or secretion indices after accounting for BMI z score, age, sex, and ethnicity.
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Affiliation(s)
- Maria J Redondo
- Texas Children's Hospital, Baylor College of Medicine, Houston, TX
| | | | | | - Laura E Bocchino
- University of South Florida, Tampa, FL.,Jaeb Center for Health Research, Tampa, FL
| | | | - Susan Geyer
- University of South Florida, Tampa, FL.,Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | | | - Andrea K Steck
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Carmella Evans-Molina
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN
| | | | - Jay M Sosenko
- Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, FL
| | - Fida Bacha
- Texas Children's Hospital, Baylor College of Medicine, Houston, TX.,Children's Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture, Houston, TX
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22
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Horenkamp-Sonntag D, Bitzer EM, Geyer S. Behandlungsfade in GKV-Routinedaten: Status-Quo der Screening-Inanspruchnahme beim Gebärmutterhalskrebs vor Einführung des HPV-Tests. Das Gesundheitswesen 2021. [DOI: 10.1055/s-0041-1732721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
| | - EM Bitzer
- Pädagogische Hochschule Freiburg, Public Health & Health Education
| | - S Geyer
- Medizinische Hochschule Hannover, Medizinische Soziologie
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23
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Larson RA, Mandrekar SJ, Huebner LJ, Sanford BL, Laumann K, Geyer S, Bloomfield CD, Thiede C, Prior TW, Döhner K, Marcucci G, Voso MT, Klisovic RB, Galinsky I, Wei AH, Sierra J, Sanz MA, Brandwein JM, de Witte T, Niederwieser D, Appelbaum FR, Medeiros BC, Tallman MS, Krauter J, Schlenk RF, Ganser A, Serve H, Ehninger G, Amadori S, Gathmann I, Döhner H, Stone RM. Midostaurin reduces relapse in FLT3-mutant acute myeloid leukemia: the Alliance CALGB 10603/RATIFY trial. Leukemia 2021; 35:2539-2551. [PMID: 33654204 PMCID: PMC8591906 DOI: 10.1038/s41375-021-01179-4] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 01/13/2021] [Accepted: 02/01/2021] [Indexed: 01/31/2023]
Abstract
The prospective randomized, placebo-controlled CALGB 10603/RATIFY trial (Alliance) demonstrated a statistically significant overall survival benefit from the addition of midostaurin to standard frontline chemotherapy in a genotypically-defined subgroup of 717 patients with FLT3-mutant acute myeloid leukemia (AML). The risk of death was reduced by 22% on the midostaurin-containing arm. In this post hoc analysis, we analyzed the cumulative incidence of relapse (CIR) on this study and also evaluated the impact of 12 4-week cycles of maintenance therapy. CIR analyses treated relapses and AML deaths as events, deaths from other causes as competing risks, and survivors in remission were censored. CIR was improved on the midostaurin arm (HR = 0.71 (95% CI, 0.54-0.93); p = 0.01), both overall and within European LeukemiaNet 2017 risk classification subsets when post-transplant events were considered in the analysis as events. However, when transplantation was considered as a competing risk, there was overall no significant difference between the risks of relapse on the two randomized arms. Patients still in remission after consolidation with high-dose cytarabine entered the maintenance phase, continuing with either midostaurin or placebo. Analyses were inconclusive in quantifying the impact of the maintenance phase on the overall outcome. In summary, midostaurin reduces the CIR.
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Affiliation(s)
- Richard A Larson
- Department of Medicine and Comprehensive Cancer Center, University of Chicago, Chicago, IL, USA.
| | - Sumithra J Mandrekar
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
- Alliance Statistics and Data Center, Mayo Clinic, Rochester, MN, USA
| | - Lucas J Huebner
- Alliance Statistics and Data Center, Mayo Clinic, Rochester, MN, USA
| | - Ben L Sanford
- Alliance Statistics and Data Center, Duke University, Durham, NC, USA
| | - Kristina Laumann
- Alliance Statistics and Data Center, Mayo Clinic, Rochester, MN, USA
| | - Susan Geyer
- Alliance Statistics and Data Center, Mayo Clinic, Rochester, MN, USA
| | - Clara D Bloomfield
- The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Christian Thiede
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus der TU Dresden, Dresden, Germany
| | - Thomas W Prior
- The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Konstanze Döhner
- Department of Internal Medicine III, University of Ulm, Ulm, Germany
| | - Guido Marcucci
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Maria Teresa Voso
- Department of Biomedicine and Prevention, University Tor Vergata, Rome, Italy
| | | | - Ilene Galinsky
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Andrew H Wei
- Department of Clinical Haematology, The Alfred Hospital and Monash University, Melbourne, Australia
| | - Jorge Sierra
- Hematology Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau and Jose Carreras Leukemia Research Institute, Autonomous University of Barcelona, Barcelona, Spain
| | - Miguel A Sanz
- Department of Hematology, Hospital Universitario y Politécnico La Fe and Department of Medicine, University of Valencia, Valencia, Spain
| | | | - Theo de Witte
- Radboud University Medical Centre, Nijmegen, Netherlands
| | | | - Frederick R Appelbaum
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Bruno C Medeiros
- Division of Hematology, Stanford Comprehensive Cancer Center, Stanford University, Stanford, CA, USA
| | - Martin S Tallman
- Leukemia Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jürgen Krauter
- Department of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany
| | - Richard F Schlenk
- Department of Internal Medicine III, University of Ulm, Ulm, Germany
- NCT Trial Center, National Center of Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany
| | - Arnold Ganser
- Department of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany
| | - Hubert Serve
- Department of Medicine II, Hematology/Oncology, Goethe University Hospital Frankfurt, Frankfurt/Main, Germany
| | - Gerhard Ehninger
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus der TU Dresden, Dresden, Germany
| | - Sergio Amadori
- Department of Biomedicine and Prevention, University Tor Vergata, Rome, Italy
| | | | - Hartmut Döhner
- Department of Internal Medicine III, University of Ulm, Ulm, Germany
| | - Richard M Stone
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
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24
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Redondo MJ, Nathan BM, Jacobsen LM, Sims E, Bocchino LE, Pugliese A, Schatz DA, Atkinson MA, Skyler J, Palmer J, Geyer S, Sosenko JM. Index60 as an additional diagnostic criterion for type 1 diabetes. Diabetologia 2021; 64:836-844. [PMID: 33496819 PMCID: PMC7940596 DOI: 10.1007/s00125-020-05365-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 10/28/2020] [Indexed: 12/12/2022]
Abstract
AIMS/HYPOTHESIS We aimed to compare characteristics of individuals identified in the peri-diagnostic range by Index60 (composite glucose and C-peptide measure) ≥2.00, 2 h OGTT glucose ≥11.1 mmol/l, or both. METHODS We studied autoantibody-positive participants in the Type 1 Diabetes TrialNet Pathway to Prevention study who, at their baseline OGTT, had 2 h blood glucose ≥11.1 mmol/l and/or Index60 ≥2.00 (n = 354, median age = 11.2 years, age range = 1.7-46.6; 49% male, 83% non-Hispanic White). Type 1 diabetes-relevant characteristics (e.g., age, C-peptide, autoantibodies, BMI) were compared among three mutually exclusive groups: 2 h glucose ≥11.1 mmol/l and Index60 <2.00 [Glu(+), n = 76], 2 h glucose <11.1 mmol/l and Index60 ≥2.00 [Ind(+), n = 113], or both 2 h glucose ≥11.1 mmol/l and Index60 ≥2.00 [Glu(+)/Ind(+), n = 165]. RESULTS Participants in Glu(+), vs those in Ind(+) or Glu(+)/Ind(+), were older (mean ages = 22.9, 11.8 and 14.7 years, respectively), had higher early (30-0 min) C-peptide response (1.0, 0.50 and 0.43 nmol/l), higher AUC C-peptide (2.33, 1.13 and 1.10 nmol/l), higher percentage of overweight/obesity (58%, 16% and 30%) (all comparisons, p < 0.0001), and a lower percentage of multiple autoantibody positivity (72%, 92% and 93%) (p < 0.001). OGTT-stimulated C-peptide and glucose patterns of Glu(+) differed appreciably from Ind(+) and Glu(+)/Ind(+). Progression to diabetes occurred in 61% (46/76) of Glu(+) and 63% (71/113) of Ind(+). Even though Index60 ≥2.00 was not a Pathway to Prevention diagnostic criterion, Ind(+) had a 4 year cumulative diabetes incidence of 95% (95% CI 86%, 98%). CONCLUSIONS/INTERPRETATION Participants in the Ind(+) group had more typical characteristics of type 1 diabetes than participants in the Glu(+) did and were as likely to be diagnosed. However, unlike Glu(+) participants, Ind(+) participants were not identified at the baseline OGTT.
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Affiliation(s)
- Maria J Redondo
- Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA.
| | - Brandon M Nathan
- Division of Pediatric Endocrinology, University of Minnesota, Minneapolis, MN, USA
| | | | - Emily Sims
- Indiana University School of Medicine, Indiana University, Indianapolis, IN, USA
| | - Laura E Bocchino
- University of South Florida, Tampa, FL, USA
- Jaeb Center for Health Research, Tampa, FL, USA
| | - Alberto Pugliese
- Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, FL, USA
| | | | - Mark A Atkinson
- University of Florida Diabetes Institute, Gainesville, FL, USA
| | - Jay Skyler
- Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, FL, USA
| | | | - Susan Geyer
- University of South Florida, Tampa, FL, USA
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Jay M Sosenko
- Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, FL, USA
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25
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Sallman DA, McLemore AF, Aldrich AL, Komrokji RS, McGraw KL, Dhawan A, Geyer S, Hou HA, Eksioglu EA, Sullivan A, Warren S, MacBeth KJ, Meggendorfer M, Haferlach T, Boettcher S, Ebert BL, Al Ali NH, Lancet JE, Cleveland JL, Padron E, List AF. TP53 mutations in myelodysplastic syndromes and secondary AML confer an immunosuppressive phenotype. Blood 2020; 136:2812-2823. [PMID: 32730593 PMCID: PMC7731792 DOI: 10.1182/blood.2020006158] [Citation(s) in RCA: 108] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 07/09/2020] [Indexed: 12/12/2022] Open
Abstract
Somatic gene mutations are key determinants of outcome in patients with myelodysplastic syndromes (MDS) and secondary AML (sAML). In particular, patients with TP53 mutations represent a distinct molecular cohort with uniformly poor prognosis. The precise pathogenetic mechanisms underlying these inferior outcomes have not been delineated. In this study, we characterized the immunological features of the malignant clone and alterations in the immune microenvironment in patients with TP53-mutant and wild-type MDS or sAML. Notably, PDL1 expression is significantly increased in hematopoietic stem cells of patients with TP53 mutations, which is associated with MYC upregulation and marked downregulation of MYC's negative regulator miR-34a, a p53 transcription target. Notably, patients with TP53 mutations display significantly reduced numbers of bone marrow-infiltrating OX40+ cytotoxic T cells and helper T cells, as well as decreased ICOS+ and 4-1BB+ natural killer cells. Further, highly immunosuppressive regulatory T cells (Tregs) (ie, ICOShigh/PD-1-) and myeloid-derived suppressor cells (PD-1low) are expanded in cases with TP53 mutations. Finally, a higher proportion of bone marrow-infiltrating ICOShigh/PD-1- Treg cells is a highly significant independent predictor of overall survival. We conclude that the microenvironment of TP53 mutant MDS and sAML has an immune-privileged, evasive phenotype that may be a primary driver of poor outcomes and submit that immunomodulatory therapeutic strategies may offer a benefit for this molecularly defined subpopulation.
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MESH Headings
- Adult
- Aged
- Aged, 80 and over
- Female
- Humans
- Immunosuppression Therapy
- Leukemia, Myeloid, Acute/genetics
- Leukemia, Myeloid, Acute/immunology
- Leukemia, Myeloid, Acute/pathology
- Male
- MicroRNAs/genetics
- MicroRNAs/immunology
- Middle Aged
- Mutation
- Myelodysplastic Syndromes/genetics
- Myelodysplastic Syndromes/immunology
- Myelodysplastic Syndromes/pathology
- Myeloid-Derived Suppressor Cells/immunology
- Myeloid-Derived Suppressor Cells/pathology
- RNA, Neoplasm/genetics
- RNA, Neoplasm/immunology
- T-Lymphocytes, Regulatory/immunology
- T-Lymphocytes, Regulatory/pathology
- Tumor Suppressor Protein p53/immunology
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Affiliation(s)
- David A Sallman
- Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Amy F McLemore
- Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Amy L Aldrich
- Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Rami S Komrokji
- Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Kathy L McGraw
- Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Abhishek Dhawan
- Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Susan Geyer
- Health Informatics Institute, University of South Florida, Tampa, FL
| | - Hsin-An Hou
- Division of Hematology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Erika A Eksioglu
- Department of Immunology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | | | | | | | | | | | - Steffen Boettcher
- Department of Medical Oncology and Hematology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Benjamin L Ebert
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA
- Division of Hematology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and
| | - Najla H Al Ali
- Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Jeffrey E Lancet
- Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - John L Cleveland
- Department of Tumor Biology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Eric Padron
- Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Alan F List
- Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
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Simmons KM, Sosenko JM, Warnock M, Geyer S, Ismail HM, Elding Larsson H, Steck AK. One-Hour Oral Glucose Tolerance Tests for the Prediction and Diagnostic Surveillance of Type 1 Diabetes. J Clin Endocrinol Metab 2020; 105:5897237. [PMID: 32844178 PMCID: PMC7514797 DOI: 10.1210/clinem/dgaa592] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 08/21/2020] [Indexed: 01/13/2023]
Abstract
CONTEXT Once islet autoantibody-positive individuals are identified, predicting which individuals are at highest risk for type 1 diabetes (T1D) is important. A metabolic risk score derived from 2-hour oral glucose tolerance test (OGTT) data, the Diabetes Prevention Trial-Type 1 risk score (DPTRS), can accurately predict T1D. However, 2-hour OGTTs are time-consuming and costly. OBJECTIVE We aimed to determine whether a risk score derived from 1-hour OGTT data can predict T1D as accurately as the DPTRS. Secondarily, we evaluated whether a 1-hour glucose value can be used for diagnostic surveillance. METHODS The DPTRS was modified to derive a 1-hour OGTT risk score (DPTRS60) using fasting C-peptide, 1-hour glucose and C-peptide, age, and body mass index. Areas under receiver operating curves (ROCAUCs) were used to compare prediction accuracies of DPTRS60 with DPTRS in Diabetes Prevention Trial-Type 1 (DPT-1) (n = 654) and TrialNet Pathway to Prevention (TNPTP) (n = 4610) participants. Negative predictive values (NPV) for T1D diagnosis were derived for 1-hour glucose thresholds. RESULTS ROCAUCs for T1D prediction 5 years from baseline were similar between DPTRS60 and DPTRS (DPT-1: 0.805 and 0.794; TNPTP: 0.832 and 0.847, respectively). DPTRS60 predicted T1D significantly better than 2-hour glucose (P < .001 in both cohorts). A 1-hour glucose of less than 180 mg/dL had a similar NPV, positive predictive value, and specificity for T1D development before the next 6-month visit as the standard 2-hour threshold of less than 140 mg/dL (both ≥ 98.5%). CONCLUSION A 1-hour OGTT can predict T1D as accurately as a 2-hour OGTT with minimal risk of missing a T1D diagnosis before the next visit.
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Affiliation(s)
- Kimber M Simmons
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, Colorado, USA
- Correspondence and Reprint Requests: Kimber M. Simmons, MD, Barbara Davis Center for Diabetes, University of Colorado School of Medicine, 1775 Aurora Ct, Mail Stop A140, Aurora, CO 80045, USA. E-mail:
| | - Jay M Sosenko
- Division of Endocrinology, University of Miami, Miami, Florida, USA
| | | | - Susan Geyer
- University of South Florida, Tampa, Florida, USA
| | - Heba M Ismail
- Department of Pediatrics, Indiana University, Indianapolis, Indiana, USA
| | - Helena Elding Larsson
- Department of Clinical Sciences and Department of Pediatrics, Skåne University Hospital, Malmö, Sweden
| | - Andrea K Steck
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, Colorado, USA
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Eisaman D, Geyer S, McFarland J, Fleming C, Suyama J. 60 The Value of an Integrated Sexual Assault Nurse Examiner Program at Trauma Centers: Comparing the Quality of Documentation. Ann Emerg Med 2020. [DOI: 10.1016/j.annemergmed.2020.09.070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Safieddine B, Sperlich S, Beller J, Lange K, Epping J, Tetzlaff J, Tetzlaff F, Geyer S. Socioeconomic inequalities in type 2 diabetes among different population subgroups. Eur J Public Health 2020. [DOI: 10.1093/eurpub/ckaa165.1044] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Type 2 diabetes (T2D) is a rising global epidemic with lower socioeconomic status (SES) groups being more affected. Considering specific population subgroups to examine prevalence and SES inequalities in T2D is rare. In addition, using only one indicator to depict SES inequalities in health has been a common practice despite evidence on differences in what different indicators measure. This study examines the prevalence of and SES (school education, occupation and income) inequalities in T2D in the three population subgroups: employed individuals, nonworking spouses and pensioners. This study also determines the SES indictor with the highest explanatory power.
Methods
This study is based on claims data from a statutory health insurance provider in Lower Saxony, Germany. T2D prevalence in the period between 2013 and 2017 was examined in 1,345,841 employed individuals, 180,949 nonworking spouses and 773,427 pensioners. Multivariate logistic regression analysis was applied to examine SES inequalities in T2D in the three subgroups. Explanatory power of the three SES indicators was compared by deviance analysis.
Results
T2D prevalence was four times higher in male nonworking spouses (24.2%) and 2.6 times higher in female nonworking spouses (12.7%) compared to employed men (6.4%) and women (4.7%) respectively, while it accounted for 40% of men and 36% of women in pensioners. Clear gradients in T2D inequalities emerged for all three SES indicators and were observed in the three population subgroups. School education had the highest explanatory power in employed men and women and male nonworking spouses.
Conclusions
Nonworking spouses are an important target group in T2D prevention interventions. The three SES indicators differ in their explanatory power where low school education appears to be a major risk factor. It can be discussed that health literacy and the associated health behavior play a role in mediating the association between education and T2D.
Key messages
The population subgroup “nonworking spouses” is an important target group for type 2 diabetes prevention interventions. The level of school education is a substantial determinant of socioeconomic inequalities in type 2 diabetes.
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Affiliation(s)
- B Safieddine
- Medical Sociology Unit, Hannover Medical School, Hannover, Germany
| | - S Sperlich
- Medical Sociology Unit, Hannover Medical School, Hannover, Germany
| | - J Beller
- Medical Sociology Unit, Hannover Medical School, Hannover, Germany
| | - K Lange
- Medical Psychology Unit, Hannover Medical School, Hannover, Germany
| | - J Epping
- Medical Sociology Unit, Hannover Medical School, Hannover, Germany
| | - J Tetzlaff
- Medical Sociology Unit, Hannover Medical School, Hannover, Germany
| | - F Tetzlaff
- Institute for General Practice, Hannover Medical School, Hannover, Germany
| | - S Geyer
- Medical Sociology Unit, Hannover Medical School, Hannover, Germany
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29
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Sosenko JM, Skyler JS, Herold KC, Schatz DA, Haller MJ, Pugliese A, Cleves M, Geyer S, Rafkin LE, Matheson D, Palmer JP. Slowed Metabolic Decline After 1 Year of Oral Insulin Treatment Among Individuals at High Risk for Type 1 Diabetes in the Diabetes Prevention Trial-Type 1 (DPT-1) and TrialNet Oral Insulin Prevention Trials. Diabetes 2020; 69:1827-1832. [PMID: 32439823 PMCID: PMC7372067 DOI: 10.2337/db20-0166] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Accepted: 05/18/2020] [Indexed: 12/16/2022]
Abstract
We assessed whether oral insulin slowed metabolic decline after 1 year of treatment in individuals at high risk for type 1 diabetes. Two oral insulin trials that did not show efficacy overall and had type 1 diabetes as the primary end point were analyzed: the Diabetes Prevention Trial-Type 1 (DPT-1) and the TrialNet oral insulin trials. Oral glucose tolerance tests at baseline and after 1 year of treatment were analyzed. Among those at high risk (with a Diabetes Prevention Trial-Type 1 Risk Score [DPTRS] ≥6.75), the area under the curve (AUC) C-peptide increased significantly from baseline to 1 year in each oral insulin group, whereas the AUC glucose increased significantly in each placebo group. At 1 year, the AUC C-peptide/AUC glucose (AUC Ratio) was significantly higher in the oral insulin group than in the placebo group in each trial (P < 0.05; P = 0.057 when adjusted for age in the TrialNet trial) and in both trials combined (P < 0.01 with or without adjustment for age). For a DPTRS <6.75, oral insulin groups did not differ from placebo groups in the AUC Ratio. The findings suggest that 1 year of treatment with oral insulin slows metabolic deterioration in individuals at high risk for type 1 diabetes. Moreover, the findings further suggest that metabolic end points can be useful adjuncts to the diagnostic end point in assessments of preventive treatments for the disorder.
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Affiliation(s)
- Jay M Sosenko
- University of Miami Miller School of Medicine, Miami, FL
| | - Jay S Skyler
- University of Miami Miller School of Medicine, Miami, FL
| | | | | | | | | | | | | | - Lisa E Rafkin
- University of Miami Miller School of Medicine, Miami, FL
| | - Della Matheson
- University of Miami Miller School of Medicine, Miami, FL
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30
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Wesolowski R, Stover DG, Lustberg MB, Shoben A, Zhao M, Mrozek E, Layman RM, Macrae E, Duan W, Zhang J, Hall N, Wright CL, Gillespie S, Berger M, Chalmers JJ, Carey A, Balasubramanian P, Miller BL, Amaya P, Andreopoulou E, Sparano J, Shapiro CL, Villalona‐Calero MA, Geyer S, Chen A, Grever MR, Knopp MV, Ramaswamy B. Phase I Study of Veliparib on an Intermittent and Continuous Schedule in Combination with Carboplatin in Metastatic Breast Cancer: A Safety and [18F]-Fluorothymidine Positron Emission Tomography Biomarker Study. Oncologist 2020; 25:e1158-e1169. [PMID: 32452601 PMCID: PMC7418347 DOI: 10.1634/theoncologist.2020-0039] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 05/14/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Poly(ADP-ribose) polymerase inhibitors (PARPis) are U.S. Food and Drug Administration (FDA) approved for treatment of BRCA-mutated metastatic breast cancer. Furthermore, the BROCADE studies demonstrated benefit of adding an oral PARPi, veliparib, to carboplatin and paclitaxel in patients with metastatic breast cancer harboring BRCA mutation. Given multiple possible dosing schedules and the potential benefit of this regimen for patients with defective DNA repair beyond BRCA, we sought to find the recommended phase II dose (RP2D) and schedule of veliparib in combination with carboplatin in patients with advanced breast cancer, either triple-negative (TNBC) or hormone receptor (HR)-positive, human epidermal growth receptor 2 (HER2) negative with defective Fanconi anemia (FA) DNA-repair pathway based on FA triple staining immunofluorescence assay. MATERIALS AND METHODS Patients received escalating doses of veliparib on a 7-, 14-, or 21-day schedule with carboplatin every 3 weeks. Patients underwent [18]fluoro-3'-deoxythymidine (18 FLT) positron emission tomography (PET) imaging. RESULTS Forty-four patients (39 TNBC, 5 HR positive/HER2 negative with a defective FA pathway) received a median of 5 cycles (range 1-36). Observed dose-limiting toxicities were grade (G) 4 thrombocytopenia (n = 4), G4 neutropenia (n = 1), and G3 akathisia (n = 1). Common grade 3-4 toxicities included thrombocytopenia, lymphopenia, neutropenia, anemia, and fatigue. Of the 43 patients evaluable for response, 18.6% achieved partial response and 48.8% had stable disease. Median progression-free survival was 18.3 weeks. RP2D of veliparib was established at 250 mg twice daily on days 1-21 along with carboplatin at area under the curve 5. Patients with partial response had a significant drop in maximum standard uptake value (SUVmax ) of target lesions between baseline and early in cycle 1 based on 18 FLT-PET (day 7-21; ptrend = .006). CONCLUSION The combination of continuous dosing of veliparib and every-3-week carboplatin demonstrated activity and an acceptable toxicity profile. Decrease in SUVmax on 18 FLT-PET scan during the first cycle of this therapy can identify patients who are likely to have a response. IMPLICATIONS FOR PRACTICE The BROCADE studies suggest that breast cancer patients with BRCA mutation benefit from addition of veliparib to carboplatin plus paclitaxel. This study demonstrates that a higher dose of veliparib is tolerable and active in combination with carboplatin alone. With growing interest in imaging-based early response assessment, the authors demonstrate that decrease in [18]fluoro-3'-deoxythymidine positron emission tomography (FLT-PET) SUVmax during cycle 1 of therapy is associated with response. Collectively, this study established a safety profile of veliparib and carboplatin in advanced breast cancer while also providing additional data on the potential for FLT-PET imaging modality in monitoring therapy response.
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Affiliation(s)
- Robert Wesolowski
- Stefanie Spielman Comprehensive Breast Center, The Ohio State UniversityColumbusOhioUSA
- The Ohio State University Comprehensive Cancer CenterColumbusOhioUSA
| | - Daniel G. Stover
- Stefanie Spielman Comprehensive Breast Center, The Ohio State UniversityColumbusOhioUSA
- The Ohio State University Comprehensive Cancer CenterColumbusOhioUSA
| | - Maryam B. Lustberg
- Stefanie Spielman Comprehensive Breast Center, The Ohio State UniversityColumbusOhioUSA
| | - Abigail Shoben
- The Ohio State University Comprehensive Cancer CenterColumbusOhioUSA
| | - Meng Zhao
- Stefanie Spielman Comprehensive Breast Center, The Ohio State UniversityColumbusOhioUSA
| | - Ewa Mrozek
- Mercy Health – St. Rita's Medical CenterLimaOhioUSA
| | | | | | - Wenrui Duan
- The Ohio State University Comprehensive Cancer CenterColumbusOhioUSA
| | - Jun Zhang
- The Ohio State University Comprehensive Cancer CenterColumbusOhioUSA
| | - Nathan Hall
- The Ohio State University Comprehensive Cancer CenterColumbusOhioUSA
| | | | - Susan Gillespie
- Stefanie Spielman Comprehensive Breast Center, The Ohio State UniversityColumbusOhioUSA
| | - Michael Berger
- Stefanie Spielman Comprehensive Breast Center, The Ohio State UniversityColumbusOhioUSA
| | | | - Alahdra Carey
- The Ohio State University Comprehensive Cancer CenterColumbusOhioUSA
| | | | - Brandon L. Miller
- The Ohio State University Comprehensive Cancer CenterColumbusOhioUSA
| | - Peter Amaya
- The Ohio State University Comprehensive Cancer CenterColumbusOhioUSA
| | | | - Joseph Sparano
- Montefiore Medical Center, Albert Einstein College of MedicineBronxNew YorkUSA
| | | | | | | | - Alice Chen
- National Cancer InstituteBethesdaMarylandUSA
| | - Michael R. Grever
- The Ohio State University Comprehensive Cancer CenterColumbusOhioUSA
| | - Michael V. Knopp
- The Ohio State University Comprehensive Cancer CenterColumbusOhioUSA
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Brastianos PK, Twohy E, Anders CK, Iafrate AJ, Kaufman PA, Cohen JV, Heist RS, Gerstner ER, Kaufmann TJ, Geyer S, Hoffman L, Kumthekar P, Barker FG, Carter SL, Brown PD, Galanis E. Alliance A071701: Genomically guided treatment trial in brain metastases. J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.15_suppl.tps2573] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
TPS2573 Background: Brain metastases, most commonly derived from melanoma, lung and breast cancers, are the most common brain tumor, with approximately 200,000 cases diagnosed annually in the United States. Median survival is on the order of months. For patients with clinically symptomatic brain metastases, approximately half succumb due to intracranial progression. In preclinical work, we demonstrated that brain metastases and primary tumors are often genetically distinct with frequent alterations in the CDK and PI3K pathway (Brastianos, Carter et al. Cancer Discovery 2015). Methods: We are currently accruing to a prospective multi-arm phase II study of CDK, PI3K/mTOR, and NTRK/ROS1 inhibitors in patients with brain metastases harboring alterations associated with sensitivity to these inhibitors (abemaciclib, paxalisib and entrectinib), respectively. Patients with new, recurrent or progressive brain metastases are eligible for this trial. Previously obtained tissue from brain metastases and extracranial sites (primary or extracranial metastases) are screened for the presence of these alterations, and if present in both tumor sites, patients will receive the appropriate corresponding targeted treatment. Screening is carried out with the SNaPshot NGS assay, which is a fully validated clinical test designed and developed at the MGH Center for Integrated Diagnostics. The primary endpoint of response rate (RR) in the central nervous system as per RANO criteria will be evaluated separately for each inhibitor, stratified by histology within each arm. There will be 21 evaluable patients assigned to each of the CDK and PI3K inhibitor and tumor type cohorts (breast, lung and other) and 10 patients assigned to the NTRK/ROS1 inhibitor cohort (lung) for a total of 136 evaluable patients. Although current systemic therapy for brain metastases is often ineffective, we hypothesize that targeted therapies will demonstrate efficacy in patients harboring the appropriate mutations. This study represents a novel individualized therapeutic approach in brain metastases, a disease with a critical need for effective therapy. Support: U10CA180821, U10CA180882, https://acknowledgments.alliancefound.org ; Genentech, Kazia Therapeutics Limited, Eli Lilly; Clinical trial information: NCT03994796 .
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Affiliation(s)
| | - Erin Twohy
- Alliance Statistics and Data Center, Mayo Clinic, Rochester, MN
| | | | | | - Peter A. Kaufman
- University of Vermont Medical Center and UVM Cancer Center, Burlington, VT
| | | | | | | | | | | | | | | | | | | | - Paul D. Brown
- The University of Texas MD Anderson Cancer Center, Houston, TX
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Maus RL, Leontovich A, Moore R, Nevala WK, Flotte TJ, Geyer S, Guo R, Schimke J, Dicke BA, Markovic S. Utilizing quantitative multiplex immunofluorescence to characterize paracrine interactions within the tumor-immune landscape of metastatic melanoma. J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.15_suppl.e15184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e15184 Background: Clinical responses to anti-PD1 immunotherapy in patients with metastatic melanoma (MM) remain challenging to predict. This clinical heterogeneity is also reflected in the tumor-immune microenvironment among patients and within a single tumor lesion. With the emergence of multiplex imaging platforms, defining complex phenotypes at single cell resolution has become possible. Here, we sought to objectively quantify paracrine tumor-immune interactions contributing to the variable clinical responses observed in patients receiving anti-PD1 therapy. Methods: Excisional lymph node (LN) biopsies were obtained from treatment-naïve patients with MM who underwent subsequent anti-PD1 therapy. A single 5µm section of LN tissue was used to assess a 42 analyte panel by multiplex immunofluorescence. From 30 LN samples, 418 fields of view (FOVs) were selected resulting in 14,360 high-resolution images of 4 anatomical subregions: tumor core, tumor-immune interface, tumor infiltrate and adjacent immune stroma. Following image processing, we developed an adaptive classification for tumor-centric cellular neighborhoods (TCCN) to identify and quantify critical paracrine interactions within the tumor-immune microenvironment. Results: Stratification based on responsiveness to anti-PD1 therapy resulted in 4 complete responders (CR) and 12 non-responders (NR) at 12-week follow-up. From 126 FOVs, we defined the cellular composition of 197,865 TCCN across patients based on clinical response and LN subregions. Overall, the percentage of TCCN devoid of any T cells, B cells or macrophages was significantly higher in NR compared to CR irrespective of subregion. However, other markers differentiated TCCN based on subregion. Specifically in CR, tumor core regions were enriched for CD8 T cells, while enrichment for B cells and endothelial cells was demonstrated at the tumor-immune interface. Strikingly, tumor infiltrate regions demonstrate robust immune reactivity with enrichment for M1 polarized macrophages, NK cells and B cells in CR compared to NR. Complete data from the 30 patient cohort across 418 FOVs will be presented. Conclusions: Taken together, this data suggests cellular composition of TCCN across subregions of the LN is dynamic within a single metastatic site. In this small cohort, we introduce a formalized stratification to quantify and classify critical paracrine interactions within the immune-tumor microenvironment with the potential to inform clinical responsiveness to therapy.
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Brastianos PK, Twohy E, Gerstner ER, Kaufmann TJ, Iafrate AJ, Jeyapalan SA, Piccioni DE, Lassman AB, Fadul CE, Schiff D, Taylor JW, Chowdhary SA, Kaley TJ, Morrison T, Kumthekar P, Geyer S, Cahill DP, Santagata S, Barker FG, Galanis E. Alliance A071401: Phase II trial of FAK inhibition in meningiomas with somatic NF2 mutations. J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.15_suppl.2502] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
2502 Background: Patients with progressive or recurrent meningiomas have limited treatment options. Clinical trials of systemic therapies for meningiomas have failed to demonstrate benefit. FAK inhibition has a synthetic lethal relationship with NF2 loss. Given the predominance of NF2 mutations in meningiomas, we evaluated the efficacy of GSK2256098, a FAK inhibitor, as part of the first genomically-driven phase II study in recurrent or progressive grade I-III meningiomas. Methods: Eligible patients (pts) whose tumors screened positively for NF2 mutations were treated with GSK2256098 750mg po bid until progressive disease in 2 separate cohorts: grade I or II/III meningiomas. Two co-primary endpoints were used: progression-free survival at 6 months (PFS6) and response rate (RR) by Macdonald criteria; per study design, the trial would be declared positive if either endpoint was met. RR was evaluated across the overall cohort; PFS6 was evaluated within each subgroup. Historical benchmark data was obtained from Kaley et al. Neuro Oncol 2014. In the grade I group, 12 evaluable pts provided >79% power to detect a PFS6 rate >65% (vs. null hypothesis of 25%; alpha=0.014). In the grade II/III group, 24 evaluable pts provided >85% power to detect a PFS6 >41.5% (vs. null 15%; alpha=0.02). The threshold for promising results for PFS6 was: 7+/12(grade I) and 8+/24(grade II/III) pts. For RR, 36 evaluable pts provided >94% power to detect RR >20% (vs. null 2.5%; alpha= 0.012). Results: Of 322 pts screened for all mutation cohorts of the study, 36 eligible and evaluable pts with NF2 mutations were enrolled. Across all grades, one pt had a partial response and 24 had stable disease as best response to treatment. In Grade I pts, the observed PFS6 rate was 83% (10/12 pts; 95% CI: 52-98%). In Grade II/III pts, the observed PFS6 rate was 33% (8/24 pts; 95% CI: 16-55%). The study met PFS6 efficacy endpoint both for the Grade I and the Grade II/III cohorts. Treatment was well tolerated. Only 7 patients had a maximum grade-3 adverse event that was at least possibly related to treatment; toxicities across these pts included: proteinuria (2), rash (1), pain (1), ALT (1), AST (1), cholecystitis (1), hypertriglyceridemia (1), apraxia (1), and lymphopenia (1) with no grade 4 or 5 events. Conclusions: GSK2256098 had excellent tolerability andresulted in an improved PFS6 rate in pts with recurrent or progressive NF2-mutated meningiomas. Trial endpoint was met. FAK inhibition warrants further evaluation in this patient population. Support: U10CA180821, U10CA180882; https://acknowledgments.alliancefound.org Clinical trial information: NCT02523014 .
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Affiliation(s)
| | - Erin Twohy
- Alliance Statistics and Data Center, Mayo Clinic, Rochester, MN
| | | | | | | | | | - David Eric Piccioni
- Center for Personalized Cancer Therapy and Division of Hematology and Oncology, UCSD Moores Cancer Center, San Diego, CA
| | | | | | | | | | | | | | | | | | | | | | - Sandro Santagata
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
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Redondo MJ, Sosenko J, Libman I, McVean JJF, Tosur M, Atkinson MA, Becker D, Geyer S. Single Islet Autoantibody at Diagnosis of Clinical Type 1 Diabetes is Associated With Older Age and Insulin Resistance. J Clin Endocrinol Metab 2020; 105:dgz296. [PMID: 31867614 PMCID: PMC7089846 DOI: 10.1210/clinem/dgz296] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 12/19/2019] [Indexed: 12/11/2022]
Abstract
CONTEXT Multiple islet autoantibody positivity usually precedes clinical (stage 3) type 1 diabetes (T1D). OBJECTIVE To test the hypothesis that individuals who develop stage 3 T1D with only a single autoantibody have unique metabolic differences. DESIGN Cross-sectional analysis of participants in the T1D TrialNet study. SETTING Autoantibody-positive relatives of individuals with stage 3 T1D. PARTICIPANTS Autoantibody-positive relatives who developed stage 3 T1D (at median age 12.4 years, range = 1.4-58.6) and had autoantibody data close to clinical diagnosis (n = 786, 47.4% male, 79.9% non-Hispanic white). MAIN OUTCOME MEASURES Logistic regression modeling was used to assess relationships between autoantibody status and demographic, clinical, and metabolic characteristics, adjusting for potential confounders and correcting for multiple comparisons. RESULTS At diagnosis of stage 3 T1D, single autoantibody positivity, observed in 119 (15.1%) participants (72% GAD65, 13% microinsulin antibody assay, 11% insulinoma-associated antigen 2, 1% islet cell antibody, 3% autoantibodies to zinc transporter 8 [ZnT8]), was significantly associated with older age, higher C-peptide measures (fasting, area under the curve, 2-hour, and early response in oral glucose tolerance test), higher homeostatic model assessment of insulin resistance, and lower T1D Index60 (all P < 0.03). While with adjustment for age, 2-hour C-peptide remained statistically different, controlling for body mass index (BMI) attenuated the differences. Sex, race, ethnicity, human leukocyte antigen DR3-DQ2, and/or DR4-DQ8, BMI category, and glucose measures were not significantly associated with single autoantibody positivity. CONCLUSIONS Compared with multiple autoantibody positivity, single autoantibody at diagnosis of stage 3 T1D was associated with older age and insulin resistance possibly mediated by elevated BMI, suggesting heterogeneous disease pathogenesis. These differences are potentially relevant for T1D prevention and treatment.
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Affiliation(s)
- Maria J Redondo
- Baylor College of Medicine, Texas Children’s Hospital, Houston, Texas
| | | | | | | | - Mustafa Tosur
- Baylor College of Medicine, Texas Children’s Hospital, Houston, Texas
| | - Mark A Atkinson
- University of Florida Diabetes Institute, Gainesville, Florida
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Geyer S, Imhoff AB, Siebenlist S. Komplikationsmanagement – Ellenbogenarthrolyse. Arthroskopie 2020. [DOI: 10.1007/s00142-020-00371-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Sims EK, Geyer S, Johnson SB, Libman I, Jacobsen LM, Boulware D, Rafkin LE, Matheson D, Atkinson MA, Rodriguez H, Spall M, Larsson HE, Wherrett DK, Greenbaum CJ, Krischer J, DiMeglio LA. Erratum. Who Is Enrolling? The Path to Monitoring in Type 1 Diabetes TrialNet's Pathway to Prevention. Diabetes Care 2019;42:2228-2236. Diabetes Care 2020; 43:934. [PMID: 32132004 PMCID: PMC7301159 DOI: 10.2337/dc20-er04] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
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Jacobsen LM, Bocchino L, Evans-Molina C, DiMeglio L, Goland R, Wilson DM, Atkinson MA, Aye T, Russell WE, Wentworth JM, Boulware D, Geyer S, Sosenko JM. The risk of progression to type 1 diabetes is highly variable in individuals with multiple autoantibodies following screening. Diabetologia 2020; 63:588-596. [PMID: 31768570 PMCID: PMC7229995 DOI: 10.1007/s00125-019-05047-w] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2019] [Accepted: 10/11/2019] [Indexed: 12/30/2022]
Abstract
AIMS/HYPOTHESIS Young children who develop multiple autoantibodies (mAbs) are at very high risk for type 1 diabetes. We assessed whether a population with mAbs detected by screening is also at very high risk, and how risk varies according to age, type of autoantibodies and metabolic status. METHODS Type 1 Diabetes TrialNet Pathway to Prevention participants with mAbs (n = 1815; age, 12.35 ± 9.39 years; range, 1-49 years) were analysed. Type 1 diabetes risk was assessed according to age, autoantibody type/number (insulin autoantibodies [IAA], glutamic acid decarboxylase autoantibodies [GADA], insulinoma-associated antigen-2 autoantibodies [IA-2A] or zinc transporter 8 autoantibodies [ZnT8A]) and Index60 (composite measure of fasting C-peptide, 60 min glucose and 60 min C-peptide). Cox regression and cumulative incidence curves were utilised in this cohort study. RESULTS Age was inversely related to type 1 diabetes risk in those with mAbs (HR 0.97 [95% CI 0.96, 0.99]). Among participants with 2 autoantibodies, those with GADA had less risk (HR 0.35 [95% CI 0.22, 0.57]) and those with IA-2A had higher risk (HR 2.82 [95% CI 1.76, 4.51]) of type 1 diabetes. Those with IAA and GADA had only a 17% 5 year risk of type 1 diabetes. The risk was significantly lower for those with Index60 <1.0 (HR 0.23 [95% CI 0.19, 0.30]) vs those with Index60 values ≥1.0. Among the 12% (225/1815) ≥12.0 years of age with GADA positivity, IA-2A negativity and Index60 <1.0, the 5 year risk of type 1 diabetes was 8%. CONCLUSIONS/INTERPRETATION Type 1 diabetes risk varies substantially according to age, autoantibody type and metabolic status in individuals screened for mAbs. An appreciable proportion of older children and adults with mAbs appear to have a low risk of progressing to type 1 diabetes at 5 years. With this knowledge, clinical trials of type 1 diabetes prevention can better target those most likely to progress.
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Affiliation(s)
- Laura M Jacobsen
- Division of Pediatric Endocrinology, Department of Pediatrics, College of Medicine, University of Florida, 1275 Center Drive, Gainesville, FL, 32610, USA.
| | - Laura Bocchino
- Health Informatics Institute, University of South Florida, Tampa, FL, USA
| | - Carmella Evans-Molina
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Linda DiMeglio
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Robin Goland
- Division of Pediatric Endocrinology, Diabetes, and Metabolism, Columbia University Medical Center, New York, NY, USA
| | - Darrell M Wilson
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Mark A Atkinson
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida College of Medicine, Gainesville, FL, USA
| | - Tandy Aye
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - William E Russell
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John M Wentworth
- Walter and Eliza Hall Institute, Parkville, VIC, Australia
- Department of Diabetes and Endocrinology, Royal Melbourne Hospital, Parkville, VIC, Australia
| | - David Boulware
- Health Informatics Institute, University of South Florida, Tampa, FL, USA
| | - Susan Geyer
- Health Informatics Institute, University of South Florida, Tampa, FL, USA
| | - Jay M Sosenko
- Division of Endocrinology, University of Miami, Miami, FL, USA
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Liva SG, Coss CC, Wang J, Blum W, Klisovic R, Bhatnagar B, Walsh K, Geyer S, Zhao Q, Garzon R, Marcucci G, Phelps MA, Walker AR. Phase I study of AR-42 and decitabine in acute myeloid leukemia. Leuk Lymphoma 2020; 61:1484-1492. [PMID: 32037935 DOI: 10.1080/10428194.2020.1719095] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
This phase I trial sought to determine a biologically safe and effective dose of AR-42, a novel histone deacetylase inhibitor, which would lead to a doubling of miR-29b prior to decitabine administration. Thirteen patients with previously untreated or relapsed/refractory AML were treated at 3 dose levels (DL): AR-42 20 mg qd on d1,3,5 in DL1, 40 mg qd on d1,3,5 in DL2 and 40 mg qd on d1,3,4,5 in DL3. Patients received decitabine 20 mg/m2 on d6-15 of each induction cycle and 20 mg/m2 on d6-10 of each maintenance cycle. One DLT of polymicrobial sepsis and multi-organ failure occurred at DL3. Two patients achieved a CRi and one patient achieved a CR for an ORR of 23.1%. The higher risk features of this patient population and the dosing schedule of AR-42 may have led to the observed clinical response and failure to meet the biologic endpoint.
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Affiliation(s)
- Sophia G Liva
- Division of Pharmaceutics & Pharmacology, College of Pharmacy, The Ohio State University, Columbus, OH, USA
| | - Christopher C Coss
- Division of Pharmaceutics & Pharmacology, College of Pharmacy, The Ohio State University, Columbus, OH, USA
| | - Jiang Wang
- Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - William Blum
- Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Rebecca Klisovic
- Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Bhavana Bhatnagar
- Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Katherine Walsh
- Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA
| | | | - Qiuhong Zhao
- Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Ramiro Garzon
- Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Guido Marcucci
- Department of Hematologic Malignancies Translational Science, City of Hope, Duarte, CA, USA
| | - Mitch A Phelps
- Division of Pharmaceutics & Pharmacology, College of Pharmacy, The Ohio State University, Columbus, OH, USA
| | - Alison R Walker
- Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA
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Sims EK, Geyer S, Johnson SB, Libman I, Jacobsen LM, Boulware D, Rafkin LE, Matheson D, Atkinson MA, Rodriguez H, Spall M, Elding Larsson H, Wherrett DK, Greenbaum CJ, Krischer J, DiMeglio LA. Who Is Enrolling? The Path to Monitoring in Type 1 Diabetes TrialNet's Pathway to Prevention. Diabetes Care 2019; 42:2228-2236. [PMID: 31558546 PMCID: PMC6868467 DOI: 10.2337/dc19-0593] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Accepted: 08/29/2019] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To better understand potential facilitators of individual engagement in type 1 diabetes natural history and prevention studies through analysis of enrollment data in the TrialNet Pathway to Prevention (PTP) study. RESEARCH DESIGN AND METHODS We used multivariable logistic regression models to examine continued engagement of eligible participants at two time points: 1) the return visit after screening to confirm an initial autoantibody-positive (Ab+) test result and 2) the initial oral glucose tolerance test (OGTT) for enrollment into the monitoring protocol. RESULTS Of 5,387 subjects who screened positive for a single autoantibody (Ab), 4,204 (78%) returned for confirmatory Ab testing. Younger age was associated with increased odds of returning for Ab confirmation (age <12 years vs. >18 years: odds ratio [OR] 2.12, P < 0.0001). Racial and ethnic minorities were less likely to return for confirmation, particularly nonwhite non-Hispanic (OR 0.50, P < 0.0001) and Hispanic (OR 0.69, P = 0.0001) relative to non-Hispanic white subjects. Of 8,234 subjects, 5,442 (66%) were identified as eligible to be enrolled in PTP OGTT monitoring. Here, younger age and identification as multiple Ab+ were associated with increased odds of returning for OGTT monitoring (age <12 years vs. >18 years: OR 1.43, P < 0.0001; multiple Ab+: OR 1.36, P < 0.0001). Parents were less likely to enroll into monitoring than other relatives (OR 0.78, P = 0.004). Site-specific factors, including site volume and U.S. site versus international site, were also associated with differences in rates of return for Ab+ confirmation and enrollment into monitoring. CONCLUSIONS These data confirm clear differences between successfully enrolled populations and those lost to follow-up, which can serve to identify strategies to increase ongoing participation.
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Affiliation(s)
- Emily K Sims
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN
| | - Susan Geyer
- Health Informatics Institute, University of South Florida, Tampa, FL
| | | | - Ingrid Libman
- Division of Endocrinology, Diabetes and Metabolism, University of Pittsburgh and UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA
| | - Laura M Jacobsen
- Department of Pediatrics, University of Florida College of Medicine, Gainesville, FL
| | - David Boulware
- Health Informatics Institute, University of South Florida, Tampa, FL
| | - Lisa E Rafkin
- University of Miami Miller School of Medicine Diabetes Research Institute, Miami, FL
| | - Della Matheson
- University of Miami Miller School of Medicine Diabetes Research Institute, Miami, FL
| | - Mark A Atkinson
- Department of Pediatrics, University of Florida College of Medicine, Gainesville, FL
| | - Henry Rodriguez
- University of Miami Miller School of Medicine Diabetes Research Institute, Miami, FL
| | - Maria Spall
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN
| | - Helena Elding Larsson
- Department of Clinical Sciences, Lund University Clinical Research Center, Skåne University Hospital, Malmö, Sweden
| | - Diane K Wherrett
- Department of Paediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Canada
| | | | - Jeffrey Krischer
- Health Informatics Institute, University of South Florida, Tampa, FL
| | - Linda A DiMeglio
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN
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Stock W, Luger SM, Advani AS, Yin J, Harvey RC, Mullighan CG, Willman CL, Fulton N, Laumann KM, Malnassy G, Paietta E, Parker E, Geyer S, Mrózek K, Bloomfield CD, Sanford B, Marcucci G, Liedtke M, Claxton DF, Foster MC, Bogart JA, Grecula JC, Appelbaum FR, Erba H, Litzow MR, Tallman MS, Stone RM, Larson RA. A pediatric regimen for older adolescents and young adults with acute lymphoblastic leukemia: results of CALGB 10403. Blood 2019; 133:1548-1559. [PMID: 30658992 PMCID: PMC6450431 DOI: 10.1182/blood-2018-10-881961] [Citation(s) in RCA: 251] [Impact Index Per Article: 50.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 01/04/2019] [Indexed: 12/13/2022] Open
Abstract
Retrospective studies have suggested that older adolescents and young adults (AYAs) with acute lymphoblastic leukemia (ALL) have better survival rates when treated using a pediatric ALL regimen administered by pediatric treatment teams. To address the feasibility and efficacy of using a pediatric treatment regimen for AYA patients with newly diagnosed ALL administered by adult treatment teams, we performed a prospective study, CALGB 10403, with doses and schedule identical to those in the Children's Oncology Group study AALL0232. From 2007 to 2012, 318 patients were enrolled; 295 were eligible and evaluable for response. Median age was 24 years (range, 17-39 years). Use of the pediatric regimen was safe; overall treatment-related mortality was 3%, and there were only 2 postremission deaths. Median event-free survival (EFS) was 78.1 months (95% confidence interval [CI], 41.8 to not reached), more than double the historical control of 30 months (95% CI, 22-38 months); 3-year EFS was 59% (95% CI, 54%-65%). Median overall survival (OS) was not reached. Estimated 3-year OS was 73% (95% CI, 68%-78%). Pretreatment risk factors associated with worse treatment outcomes included obesity and presence of the Philadelphia-like gene expression signature. Use of a pediatric regimen for AYAs with ALL up to age 40 years was feasible and effective, resulting in improved survival rates compared with historical controls. CALGB 10403 can be considered a new treatment standard upon which to build for improving survival for AYAs with ALL. This trial was registered at www.clinicaltrials.gov as #NCT00558519.
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Affiliation(s)
- Wendy Stock
- University of Chicago Comprehensive Cancer Center, Chicago, IL
| | - Selina M Luger
- Department of Medicine, University of Pennsylvania, Philadelphia, PA
| | | | - Jun Yin
- Alliance Statistical Center, Rochester, MN
| | - Richard C Harvey
- University of New Mexico Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM
| | | | - Cheryl L Willman
- University of New Mexico Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM
| | - Noreen Fulton
- University of Chicago Comprehensive Cancer Center, Chicago, IL
| | | | - Greg Malnassy
- University of Chicago Comprehensive Cancer Center, Chicago, IL
| | | | - Edy Parker
- Statistical Center, Cancer and Leukemia Group B, Duke University, Durham, NC
| | - Susan Geyer
- Health Informatics Institute, University of Southern Florida, Tampa, FL
| | - Krzysztof Mrózek
- James Comprehensive Cancer Center, The Ohio State University, Columbus, OH
| | - Clara D Bloomfield
- James Comprehensive Cancer Center, The Ohio State University, Columbus, OH
| | - Ben Sanford
- Statistical Center, Cancer and Leukemia Group B, Duke University, Durham, NC
| | | | | | - David F Claxton
- Department of Medicine, Penn State University, State College, PA
| | - Matthew C Foster
- Department of Medicine, University of North Carolina, Chapel Hill, NC
| | - Jeffrey A Bogart
- Department of Radiation Oncology, SUNY Upstate Medical University, Syracuse, NY
| | - John C Grecula
- James Comprehensive Cancer Center, The Ohio State University, Columbus, OH
| | | | - Harry Erba
- Department of Medicine, Duke University, Durham, NC
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Kutny MA, Geyer S, Laumann KM, Gregory J, Willman CL, Stock W, Larson RA, Powell BL, Feusner JH. Outcome for pediatric acute promyelocytic leukemia patients at Children's Oncology Group sites on the Leukemia Intergroup Study CALGB 9710 (Alliance). Pediatr Blood Cancer 2019; 66:e27542. [PMID: 30393935 PMCID: PMC6392047 DOI: 10.1002/pbc.27542] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 10/11/2018] [Accepted: 10/12/2018] [Indexed: 12/29/2022]
Abstract
BACKGROUND Acute promyelocytic leukemia (APL) is a unique leukemia subtype requiring specialized treatment including all-trans retinoic acid (ATRA). A prior report demonstrated worse outcome among young children <5 years old compared with older children. METHODS We evaluated outcomes for pediatric patients (<18 years old; N = 83) with APL treated on North American intergroup study CALGB 9710 at Children's Oncology Group sites. Induction and consolidation included ATRA, cytarabine, and anthracyclines. Patients ≥15 years old were randomized to addition of arsenic trioxide (ATO) consolidation. All patients were randomized to ATRA maintenance with versus without oral chemotherapy. RESULTS The estimated 5-year overall survival (OS) rate was 82%, and the event-free survival (EFS) rate was 54%. Seven patients (8.4%) died during induction due to coagulopathy. Maintenance randomization demonstrated that addition of oral chemotherapy to ATRA significantly reduced relapse rate, but difference in EFS did not reach statistical significance (P = 0.12; 5-year rates [95% CI]: 41% [17%-64%] ATRA only vs 72% [56%-88%] ATRA plus chemotherapy). There was no difference (P = 0.93) in EFS for age <5 years versus 5-12.99 years versus 13-17.99 years (5-year rates: 56%, 47%, and 45%, respectively). Among adolescents 15-17.99 years old in the ATO randomization, there was a significantly lower relapse risk at 5 years for those receiving ATO (0% ATO vs 44% no ATO; P = 0.02). CONCLUSION Our data demonstrate that intensified ATRA, cytarabine, and anthracycline chemotherapy is effective for pediatric APL including very young patients, but early deaths and relapses remain barriers to cure. Further improvements are likely with incorporation of ATO into pediatric APL regimens.
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Affiliation(s)
- Matthew A. Kutny
- Department of Pediatrics, Division of Hematology/Oncology, University of Alabama at Birmingham, Birmingham, AL
| | - Susan Geyer
- Health Informatics Institute, University of South Florida, Tampa, FL
| | | | - John Gregory
- Atlantic Health System, Goryeb Children’s Hospital, Morristown, NJ
| | - Cheryl L. Willman
- Department of Pathology, School of Medicine, University of New Mexico Cancer Center, Albuquerque, NM
| | - Wendy Stock
- Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL
| | - Richard A. Larson
- Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL
| | - Bayard L. Powell
- Section on Hematology and Oncology, Comprehensive Cancer Center of Wake Forest University School of Medicine, Winston-Salem, NC
| | - James H. Feusner
- Division of Hematology/Oncology, Children’s Hospital and Research Center Oakland, Oakland, CA
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Triolo TM, Fouts A, Pyle L, Yu L, Gottlieb PA, Steck AK, Greenbaum CJ, Atkinson M, Baidal D, Battaglia M, Becker D, Bingley P, Bosi E, Buckner J, Clements M, Colman P, DiMeglio L, Gitelman S, Goland R, Gottlieb P, Herold K, Knip M, Krischer J, Lernmark A, Moore W, Moran A, Muir A, Palmer J, Peakman M, Philipson L, Raskin P, Redondo M, Rodriguez H, Russell W, Spain L, Schatz D, Sosenko J, Wentworth J, Wherrett D, Wilson D, Winter W, Ziegler A, Anderson M, Antinozzi P, Benoist C, Blum J, Bourcier K, Chase P, Clare-Salzler M, Clynes R, Eisenbarth G, Fathman C, Grave G, Hering B, Insel R, Kaufman F, Kay T, Leschek E, Mahon J, Marks J, Nanto-Salonen K, Nepom G, Orban T, Parkman R, Pescovitz M, Peyman J, Pugliese A, Roep B, Roncarolo M, Savage P, Simell O, Sherwin R, Siegelman M, Skyler J, Steck A, Thomas J, Trucco M, Wagner J, Krischer JP, Leschek E, Rafkin L, Bourcier K, Cowie C, Foulkes M, Insel R, Krause-Steinrauf H, Lachin JM, Malozowski S, Peyman J, Ridge J, Savage P, Skyler JS, Zafonte SJ, Rafkin L, Sosenko JM, Kenyon NS, Santiago I, Krischer JP, Bundy B, Abbondondolo M, Dixit S, Pasha M, King K, Adcock H, Atterberry L, Fox K, Englert N, Mauras J, Permuy K, Sikes T, Adams T, Berhe B, Guendling L, McLennan L, Paganessi C, Murphy M, Draznin M, Kamboj S, Sheppard V, Lewis L, Coates W, Amado D, Moore G, Babar J, Bedard D, Brenson-Hughes J, Cernich M, Clements R, Duprau S, Goodman L, Hester L, Huerta-Saenz A, Asif I, Karmazin T, Letjen S, Raman D, Morin W, Bestermann E, Morawski J, White A, Brockmyer R, Bays S, Campbell A, Boonstra M, Stapleton N, Stone A, Donoho H, Everett H, Hensley M, Johnson C, Marshall N, Skirvin P, Taylor R, Williams L, Burroughs C, Ray C, Wolverton D, Nickels C, Dothard P, Speiser M, Pellizzari L, Bokor K, Izuora S, Abdelnour P, Cummings S, Cuthbertson D, Paynor M, Leahy M, Riedl S, Shockley R, Saad T, Briones S, Casella C, Herz K, Walsh J, Greening F, Deemer M, Hay S, Hunt N, Sikotra L, Simons D, Karounos R, Oremus L, Dye L, Myers D, Ballard W, Miers R, Eberhard C, Sparks K, Thraikill K, Edwards J, Fowlkes S, Kemp A, Morales L, Holland L, Johnson P, Paul A, Ghatak K, Fiske S, Phelen H, Leyland T, Henderson D, Brenner E, Oppenheimer I, Mamkin C, Moniz C, Clarson M, Lovell A, Peters V, Ford J, Ruelas D, Borut D, Burt M, Jordan S, Castilla P, Flores M, Ruiz L, Hanson J, Green-Blair R, Sheridan K, Garmeson J, Wintergerst G, Pierce A, Omoruyi M, Foster S, Kingery A, Lunsford I, Cervantes T, Parker P, Price J, Urben I, Guillette H, Doughty H, Haydock V, Parker P, Bergman S, Duncum C, Rodda A, Perelman R, Calendo C, Barrera E, Arce-Nunez Y, Geyer S, Martinez M, De la Portilla I, Cardenas L, Garrido M, Villar R, Lorini E, Calandra G, D’Annuzio K, Perri N, Minuto C, Hays B, Rebora R, Callegari O, Ali J, Kramer B, Auble S, Cabrera P, Donohoue R, Fiallo-Scharer M, Hessner P, Wolfgram A, Henderson C, Kansra N, Bettin R, McCuller A, Miller S, Accacha J, Corrigan E, Fiore R, Levine T, Mahoney C, Polychronakos V, Henry M, Gagne H, Starkman M, Fox D, Chin F, Melchionne L, Silverman I, Marshall L, Cerracchio J, Cruz A, Viswanathan J, Heyman K, Wilson S, Chalew S, Valley S, Layburn A, Lala P, Clesi M, Genet G, Uwaifo A, Charron T, Allerton W, Hsiao B, Cefalu L, Melendez-Ramirez R, Richards C, Alleyn E, Gustafson M, Lizanna J, Wahlen S, Aleiwe M, Hansen H, Wahlen C, Karges C, Levy A, Bonaccorso R, Rapaport Y, Tomer D, Chia M, Goldis L, Iazzetti M, Klein C, Levister L, Waldman E, Keaton N, Wallach M, Regelmann Z, Antal M, Aranda C, Reynholds A, Vinik P, Barlow M, Bourcier M, Nevoret J, Couper S, Kinderman A, Beresford N, Thalagne H, Roper J, Gibbons J, Hill S, Balleaut C, Brennan J, Ellis-Gage L, Fear T, Gray L, Law P, Jones C, McNerney L, Pointer N, Price K, Few D, Tomlinson N, Leech D, Wake C, Owens M, Burns J, Leinbach A, Wotherspoon A, Murray K, Short G, Curry S, Kelsey J, Lawson J, Porter S, Stevens E, Thomson S, Winship L, Liu S, Wynn E, Wiltshire J, Krebs P, Cresswell H, Faherty C, Ross L, Denvir J, Drew T, 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Manning G, Hendry B, Taylor S, Jones W, Strader M, Bencomo T, Bailey L, Bedolla C, Roldan C, Moudiotis B, Vaidya C, Anning S, Bunce S, Estcourt E, Folland E, Gordon C, Harrill J, Ireland J, Piper L, Scaife K, Sutton S, Wilkins M, Costelloe J, Palmer L, Casas C, Miller M, Burgard C, Erickson J, Hallanger-Johnson P, Clark W, Taylor A, Lafferty S, Gillett C, Nolan M, Pathak L, Sondrol T, Hjelle S, Hafner J, Kotrba R, Hendrickson A, Cemeroglu T, Symington M, Daniel Y, Appiagyei-Dankah D, Postellon M, Racine L, Kleis K, Barnes S, Godwin H, McCullough K, Shaheen G, Buck L, Noel M, Warren S, Weber S, Parker I, Gillespie B, Nelson C, Frost J, Amrhein E, Moreland A, Hayes J, Peggram J, Aisenberg M, Riordan J, Zasa E, Cummings K, Scott T, Pinto A, Mokashi K, McAssey E, Helden P, Hammond L, Dinning S, Rahman S, Ray C, Dimicri S, Guppy H, Nielsen C, Vogel C, Ariza L, Morales Y, Chang R, Gabbay L, Ambrocio L, Manley R, Nemery W, Charlton P, Smith L, Kerr B, Steindel-Kopp M, Alamaguer D, Liljenquist G, Browning T, Coughenour M, Sulk E, Tsalikan M, Tansey J, Cabbage N. Identical and Nonidentical Twins: Risk and Factors Involved in Development of Islet Autoimmunity and Type 1 Diabetes. Diabetes Care 2019; 42:192-199. [PMID: 30061316 PMCID: PMC6341285 DOI: 10.2337/dc18-0288] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 06/28/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE There are variable reports of risk of concordance for progression to islet autoantibodies and type 1 diabetes in identical twins after one twin is diagnosed. We examined development of positive autoantibodies and type 1 diabetes and the effects of genetic factors and common environment on autoantibody positivity in identical twins, nonidentical twins, and full siblings. RESEARCH DESIGN AND METHODS Subjects from the TrialNet Pathway to Prevention Study (N = 48,026) were screened from 2004 to 2015 for islet autoantibodies (GAD antibody [GADA], insulinoma-associated antigen 2 [IA-2A], and autoantibodies against insulin [IAA]). Of these subjects, 17,226 (157 identical twins, 283 nonidentical twins, and 16,786 full siblings) were followed for autoantibody positivity or type 1 diabetes for a median of 2.1 years. RESULTS At screening, identical twins were more likely to have positive GADA, IA-2A, and IAA than nonidentical twins or full siblings (all P < 0.0001). Younger age, male sex, and genetic factors were significant factors for expression of IA-2A, IAA, one or more positive autoantibodies, and two or more positive autoantibodies (all P ≤ 0.03). Initially autoantibody-positive identical twins had a 69% risk of diabetes by 3 years compared with 1.5% for initially autoantibody-negative identical twins. In nonidentical twins, type 1 diabetes risk by 3 years was 72% for initially multiple autoantibody-positive, 13% for single autoantibody-positive, and 0% for initially autoantibody-negative nonidentical twins. Full siblings had a 3-year type 1 diabetes risk of 47% for multiple autoantibody-positive, 12% for single autoantibody-positive, and 0.5% for initially autoantibody-negative subjects. CONCLUSIONS Risk of type 1 diabetes at 3 years is high for initially multiple and single autoantibody-positive identical twins and multiple autoantibody-positive nonidentical twins. Genetic predisposition, age, and male sex are significant risk factors for development of positive autoantibodies in twins.
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Affiliation(s)
- Taylor M. Triolo
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Alexandra Fouts
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Laura Pyle
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Liping Yu
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Peter A. Gottlieb
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Andrea K. Steck
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
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Schindler S, Schmidt L, Stroske M, Storch M, Anwander A, Trampel R, Strauß M, Hegerl U, Geyer S, Schönknecht P. Hypothalamus enlargement in mood disorders. Acta Psychiatr Scand 2019; 139:56-67. [PMID: 30229855 DOI: 10.1111/acps.12958] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/15/2018] [Indexed: 12/24/2022]
Abstract
OBJECTIVE The purpose of this study was to determine, in vivo, whether the hypothalamus volume is reduced in patients with mood disorders. METHODS The cross-sectional study included 20 unmedicated (MDDu) and 20 medicated patients with major depressive disorder, 21 patients with bipolar disorder, and 23 controls. Twenty of the controls were matched to the MDDu. Seven Tesla, T1-weighted magnetic resonance images were acquired and processed using methods specifically developed for high-precision volumetry of the hypothalamus. RESULTS An overall group difference was observed for the left hypothalamus volume corrected for intracranial volume. Planned contrasts identified that the left hypothalamus was approximately 5% larger in each patient group compared with the control group. A paired t-test with the 20 matched pairs of MDDu and controls and without correction for covariates confirmed the larger left hypothalamus volume in MDDu. CONCLUSIONS Contrary to our expectations, the hypothalamus volume was increased in patients with uni- and bipolar affective disorders. The effect was left-sided and independent of medication status or statistical correction for covariates. Supported by emerging evidence that the stress response may be related to structural and functional asymmetry in the brain, our finding suggests a crucial role of the hypothalamus in mood disorders.
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Affiliation(s)
- S Schindler
- Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany.,Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - L Schmidt
- Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany
| | - M Stroske
- Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany
| | - M Storch
- Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany
| | - A Anwander
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - R Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - M Strauß
- Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany
| | - U Hegerl
- Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany
| | - S Geyer
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - P Schönknecht
- Out-patient Department for Sexual-therapeutic Prevention and Forensic Psychiatry, Leipzig, Germany.,Academic State Hospital Arnsdorf, Arnsdorf, Germany
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Wentworth JM, Bediaga NG, Giles LC, Ehlers M, Gitelman SE, Geyer S, Evans-Molina C, Harrison LC. Beta cell function in type 1 diabetes determined from clinical and fasting biochemical variables. Diabetologia 2019; 62:33-40. [PMID: 30167735 PMCID: PMC6518395 DOI: 10.1007/s00125-018-4722-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Accepted: 08/01/2018] [Indexed: 02/07/2023]
Abstract
AIMS/HYPOTHESIS Beta cell function in type 1 diabetes is commonly assessed as the average plasma C-peptide concentration over 2 h following a mixed-meal test (CPAVE). Monitoring of disease progression and response to disease-modifying therapy would benefit from a simpler, more convenient and less costly measure. Therefore, we determined whether CPAVE could be reliably estimated from routine clinical variables. METHODS Clinical and fasting biochemical data from eight randomised therapy trials involving participants with recently diagnosed type 1 diabetes were used to develop and validate linear models to estimate CPAVE and to test their accuracy in estimating loss of beta cell function and response to immune therapy. RESULTS A model based on disease duration, BMI, insulin dose, HbA1c, fasting plasma C-peptide and fasting plasma glucose most accurately estimated loss of beta cell function (area under the receiver operating characteristic curve [AUROC] 0.89 [95% CI 0.87, 0.92]) and was superior to the commonly used insulin-dose-adjusted HbA1c (IDAA1c) measure (AUROC 0.72 [95% CI 0.68, 0.76]). Model-estimated CPAVE (CPEST) reliably identified treatment effects in randomised trials. CPEST, compared with CPAVE, required only a modest (up to 17%) increase in sample size for equivalent statistical power. CONCLUSIONS/INTERPRETATION CPEST, approximated from six variables at a single time point, accurately identifies loss of beta cell function in type 1 diabetes and is comparable to CPAVE for identifying treatment effects. CPEST could serve as a convenient and economical measure of beta cell function in the clinic and as a primary outcome measure in trials of disease-modifying therapy in type 1 diabetes.
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Affiliation(s)
- John M Wentworth
- The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC, 3052, Australia.
- Department of Medical Biology, University of Melbourne, Parkville, VIC, 3010, Australia.
- Department of Diabetes and Endocrinology, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.
| | - Naiara G Bediaga
- The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC, 3052, Australia
- Department of Medical Biology, University of Melbourne, Parkville, VIC, 3010, Australia
| | - Lynne C Giles
- School of Public Health, The University of Adelaide, Adelaide, SA, Australia
| | - Mario Ehlers
- Clinical Trials Group, Immune Tolerance Network, San Francisco, CA, USA
- Eli Lilly and Company, San Diego, CA, USA
| | | | | | | | - Leonard C Harrison
- The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC, 3052, Australia
- Department of Medical Biology, University of Melbourne, Parkville, VIC, 3010, Australia
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Redondo MJ, Steck AK, Sosenko J, Anderson M, Antinozzi P, Michels A, Wentworth JM, Atkinson MA, Pugliese A, Geyer S. Transcription Factor 7-Like 2 ( TCF7L2) Gene Polymorphism and Progression From Single to Multiple Autoantibody Positivity in Individuals at Risk for Type 1 Diabetes. Diabetes Care 2018; 41:2480-2486. [PMID: 30275285 PMCID: PMC6245213 DOI: 10.2337/dc18-0861] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 08/10/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE The type 2 diabetes-associated alleles at the TCF7L2 locus mark a type 1 diabetes phenotype characterized by single islet autoantibody positivity as well as lower glucose and higher C-peptide measures. Here, we studied whether the TCF7L2 locus influences progression of islet autoimmunity, from single to multiple (≥2) autoantibody positivity, in relatives of patients with type 1 diabetes. RESEARCH DESIGN AND METHODS We evaluated 244 participants in the Type 1 Diabetes TrialNet Pathway to Prevention study with confirmed single autoantibody positivity at screening and Immunochip single nucleotide polymorphism data (47.5% male; median age 12.8 years, range 1.2-45.9; 90.2% white). We analyzed risk allele frequency at TCF7L2 rs4506565 (in linkage disequilibrium with rs7903146). Altogether, 62.6% participants carried ≥1 risk allele. Univariate and multivariable Cox proportional hazards models and Kaplan-Meier statistical methods were used. RESULTS During follow-up (median 5.2 years, range 0.2-12.6), 62% of the single autoantibody-positive participants developed multiple autoantibody positivity. In the overall cohort, the TCF7L2 locus did not significantly predict progression to multiple autoantibody positivity. However, among single GAD65 autoantibody-positive participants (n = 158), those who carried ≥1 risk allele had a lower rate of progression to multiple autoantibody positivity (hazard ratio [HR] 0.65, P = 0.033) than those who did not, after adjustment for HLA risk haplotypes and age. Among subjects who were either IA-2 or insulin autoantibody positive only, carrying ≥1 TCF7L2 risk allele was not a significant factor overall, but in overweight or obese participants, it increased the risk of progression to multiple autoantibody positivity (HR 3.02, P = 0.016) even with adjustment for age. CONCLUSIONS The type 2 diabetes-associated TCF7L2 locus influences progression of islet autoimmunity, with differential effects by autoantibody specificity and interaction by obesity/overweight.
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Affiliation(s)
- Maria J Redondo
- Baylor College of Medicine, Texas Children's Hospital, Houston, TX
| | - Andrea K Steck
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | | | - Mark Anderson
- University of California San Francisco, San Francisco, CA
| | | | - Aaron Michels
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - John M Wentworth
- Walter and Eliza Hall Institute and Royal Melbourne Hospital, Parkville, Australia
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Haraldsdottir S, Janku F, Poi M, Timmers C, Geyer S, Schaaf LJ, Sexton J, Wei L, Thurmond J, Velez-Bravo V, Stepanek VM, Bertino EM, Kendra K, Mortazavi A, Subbiah V, Phelps M, Shah MH. Phase I Trial of Dabrafenib and Pazopanib in BRAF Mutated Advanced Malignancies. JCO Precis Oncol 2018; 2:1-19. [DOI: 10.1200/po.17.00247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Purpose Several tumor types carry BRAF mutations and vascular endothelial growth factor pathway upregulation. Resistance mechanisms to BRAF inhibitors can include platelet-derived growth factor-β upregulation. Dabrafenib, a BRAF inhibitor, and pazopanib, a multikinase inhibitor that targets vascular endothelial growth factor and platelet-derived growth factor, have not been combined previously. This phase I study was designed to evaluate the safety, pharmacokinetics, and pharmacodynamics of the combination. Patients and Methods Patients with any advanced BRAF mutated malignancy with adequate organ function were eligible. Prior use of dabrafenib or pazopanib was not allowed. Dosages started at dabrafenib 50 mg twice a day and pazopanib 400 mg daily on dose level (DL) 1, with maximum dosages of 150 mg twice a day and 800 mg daily on DL5. Pharmacokinetics and BRAF V600E plasma clone were measured, and efficacy was evaluated by imaging and tumor markers every 8 weeks. Results Twenty-three patients with 11 different tumor histologies were enrolled in five DLs. Two dose-limiting toxicities were observed—a grade 3 bowel perforation on DL3 and grade 3 arthralgia on DL5. Common drug-related adverse events included nausea (52%), skin papules (43%), diarrhea (39%), hand-foot syndrome (30%), anemia (26%), rash (22%), vomiting (22%), hypophosphatemia (22%), and transaminitis (22%). Five patients (22%) experienced a partial response, including low-grade ovarian serous carcinoma, thyroid cancer, and glioblastoma multiforme, and two patients (appendiceal and thyroid cancer) had stable disease > 6 months. Pharmacokinetic measurements revealed pazopanib levels < 17.5 μg/mL in 80% of treated patients at steady state, particularly at DL5. BRAF V600E plasma copies correlated with response and progression. Conclusion Combination dabrafenib and pazopanib had no unexpected toxicities, and durable partial responses were observed at DL3 or greater. Dose escalation beyond DL5 may be considered as pazopanib levels were suboptimal as a result of drug interaction with dabrafenib.
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Affiliation(s)
- Sigurdis Haraldsdottir
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Filip Janku
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Ming Poi
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Cynthia Timmers
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Susan Geyer
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Larry J. Schaaf
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Jennifer Sexton
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Lai Wei
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Jennifer Thurmond
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Vivianne Velez-Bravo
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Vanda M. Stepanek
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Erin M. Bertino
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Kari Kendra
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Amir Mortazavi
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Vivek Subbiah
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Mitch Phelps
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
| | - Manisha H. Shah
- Sigurdis Haraldsdottir, Ming Poi, Cynthia Timmers, Susan Geyer, Larry J. Schaaf, Jennifer Sexton, Lai Wei, Jennifer Thurmond, Erin M. Bertino, Kari Kendra, Amir Mortazavi, Mitch Phelps, and Manisha H. Shah, Ohio State University Medical Center, Columbus, OH; Sigurdis Haraldsdottir, Stanford University, Stanford, CA; Filip Janku, Vivianne Velez-Bravo, Vanda M. Stepanek, and Vivek Subbiah, University of Texas MD Anderson Cancer Center, Houston, TX; and Susan Geyer, University of South Florida, Tampa, FL
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Vecchio F, Lo Buono N, Stabilini A, Nigi L, Dufort MJ, Geyer S, Rancoita PM, Cugnata F, Mandelli A, Valle A, Leete P, Mancarella F, Linsley PS, Krogvold L, Herold KC, Elding Larsson H, Richardson SJ, Morgan NG, Dahl-Jørgensen K, Sebastiani G, Dotta F, Bosi E, Battaglia M. Abnormal neutrophil signature in the blood and pancreas of presymptomatic and symptomatic type 1 diabetes. JCI Insight 2018; 3:122146. [PMID: 30232284 DOI: 10.1172/jci.insight.122146] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Accepted: 08/03/2018] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Neutrophils and their inflammatory mediators are key pathogenic components in multiple autoimmune diseases, while their role in human type 1 diabetes (T1D), a disease that progresses sequentially through identifiable stages prior to the clinical onset, is not well understood. We previously reported that the number of circulating neutrophils is reduced in patients with T1D and in presymptomatic at-risk subjects. The aim of the present work was to identify possible changes in circulating and pancreas-residing neutrophils throughout the disease course to better elucidate neutrophil involvement in human T1D. METHODS Data collected from 389 subjects at risk of developing T1D, and enrolled in 4 distinct studies performed by TrialNet, were analyzed with comprehensive statistical approaches to determine whether the number of circulating neutrophils correlates with pancreas function. To obtain a broad analysis of pancreas-infiltrating neutrophils throughout all disease stages, pancreas sections collected worldwide from 4 different cohorts (i.e., nPOD, DiViD, Siena, and Exeter) were analyzed by immunohistochemistry and immunofluorescence. Finally, circulating neutrophils were purified from unrelated nondiabetic subjects and donors at various T1D stages and their transcriptomic signature was determined by RNA sequencing. RESULTS Here, we show that the decline in β cell function is greatest in individuals with the lowest peripheral neutrophil numbers. Neutrophils infiltrate the pancreas prior to the onset of symptoms and they continue to do so as the disease progresses. Of interest, a fraction of these pancreas-infiltrating neutrophils also extrudes neutrophil extracellular traps (NETs), suggesting a tissue-specific pathogenic role. Whole-transcriptome analysis of purified blood neutrophils revealed a unique molecular signature that is distinguished by an overabundance of IFN-associated genes; despite being healthy, said signature is already present in T1D-autoantibody-negative at-risk subjects. CONCLUSIONS These results reveal an unexpected abnormality in neutrophil disposition both in the circulation and in the pancreas of presymptomatic and symptomatic T1D subjects, implying that targeting neutrophils might represent a previously unrecognized therapeutic modality. FUNDING Juvenile Diabetes Research Foundation (JDRF), NIH, Diabetes UK.
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Affiliation(s)
- Federica Vecchio
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Nicola Lo Buono
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Angela Stabilini
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Laura Nigi
- Diabetes Unit, Department of Medicine, Surgery and Neuroscience, University of Siena, and Fondazione Umberto Di Mario ONLUS c/o Toscana Life Science, Siena, Italy
| | - Matthew J Dufort
- Systems Immunology Division, Benaroya Research Institute, Seattle, Washington, USA
| | - Susan Geyer
- University of South Florida, TNCC, Tampa, Florida, USA
| | - Paola Maria Rancoita
- Centre of Statistics for Biomedical Sciences (CUSSB), Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Cugnata
- Centre of Statistics for Biomedical Sciences (CUSSB), Vita-Salute San Raffaele University, Milan, Italy
| | - Alessandra Mandelli
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Andrea Valle
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Pia Leete
- Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, RILD Building Barrack Road, Exeter, Devon, United Kingdom
| | - Francesca Mancarella
- Diabetes Unit, Department of Medicine, Surgery and Neuroscience, University of Siena, and Fondazione Umberto Di Mario ONLUS c/o Toscana Life Science, Siena, Italy
| | - Peter S Linsley
- Systems Immunology Division, Benaroya Research Institute, Seattle, Washington, USA
| | - Lars Krogvold
- Pediatric Department, Oslo University Hospital HF, Oslo, Norway; Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Kevan C Herold
- Departments of Immunobiology and Internal Medicine, Yale University, New Haven, Connecticut, USA
| | - Helena Elding Larsson
- Department of Clinical Sciences, Lund University/CRC, Skane University Hospital SUS, Malmo, Sweden
| | - Sarah J Richardson
- Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, RILD Building Barrack Road, Exeter, Devon, United Kingdom
| | - Noel G Morgan
- Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, RILD Building Barrack Road, Exeter, Devon, United Kingdom
| | - Knut Dahl-Jørgensen
- Pediatric Department, Oslo University Hospital HF, Oslo, Norway; Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Guido Sebastiani
- Diabetes Unit, Department of Medicine, Surgery and Neuroscience, University of Siena, and Fondazione Umberto Di Mario ONLUS c/o Toscana Life Science, Siena, Italy
| | - Francesco Dotta
- Diabetes Unit, Department of Medicine, Surgery and Neuroscience, University of Siena, and Fondazione Umberto Di Mario ONLUS c/o Toscana Life Science, Siena, Italy
| | - Emanuele Bosi
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy, and the Department of Internal Medicine, IRCCS San Raffaele Hospital, Milan, Italy.,TrialNet Clinical Center, IRCCS San Raffaele Hospital, Milan, Italy
| | | | | | - Manuela Battaglia
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy.,TrialNet Clinical Center, IRCCS San Raffaele Hospital, Milan, Italy
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Haller MJ, Schatz DA, Skyler JS, Krischer JP, Bundy BN, Miller JL, Atkinson MA, Becker DJ, Baidal D, DiMeglio LA, Gitelman SE, Goland R, Gottlieb PA, Herold KC, Marks JB, Moran A, Rodriguez H, Russell W, Wilson DM, Greenbaum CJ, Greenbaum C, Atkinson M, Baidal D, Battaglia M, Becker D, Bingley P, Bosi E, Buckner J, Clements M, Colman P, DiMeglio L, Evans-Molina C, Gitelman S, Goland R, Gottlieb P, Herold K, Knip M, Krischer J, Lernmark A, Moore W, Moran A, Muir A, Palmer J, Peakman M, Philipson L, Raskin P, Redondo M, Rodriguez H, Russell W, Spain L, Schatz D, Sosenko J, Wherrett D, Wilson D, Winter W, Ziegler A, Anderson M, Antinozzi P, Benoist C, Blum J, Bourcier K, Chase P, Clare-Salzler M, Clynes R, Cowie C, Eisenbarth G, Fathman C, Grave G, Harrison L, Hering B, Insel R, Jordan S, Kaufman F, Kay T, Kenyon N, Klines R, Lachin J, Leschek E, Mahon J, Marks J, Monzavi R, Nanto-Salonen K, Nepom G, Orban T, Parkman R, Pescovitz M, Peyman J, Pugliese A, Ridge J, Roep B, Roncarolo M, Savage P, Simell O, Sherwin R, Siegelman M, Skyler J, Steck A, Thomas J, Trucco M, Wagner J, Bourcier K, Greenbaum CJ, Krischer JP, Leschek E, Rafkin L, Spain L, Cowie C, Foulkes M, Insel R, Krause-Steinrauf H, Lachin JM, Malozowski S, Peyman J, Ridge J, Savage P, Skyler JS, Zafonte SJ, Greenbaum CJ, Rafkin L, Sosenko JM, Skyler JS, Kenyon NS, Santiago I, Krischer JP, Bundy B, Abbondondolo M, Adams T, Amado D, Asif I, Boonstra M, Boulware D, Bundy B, Burroughs C, Cuthbertson D, Eberhard C, Fiske S, Ford J, Garmeson J, Guillette H, Geyer S, Hays B, Henderson C, Henry M, Heyman K, Hsiao B, Karges C, Kinderman A, Lane L, Leinbach A, Liu S, Lloyd J, Malloy J, Maddox K, Martin J, Miller J, Moore M, Muller S, Nguyen T, O’Donnell R, Parker M, Pereyra M, Reed N, Roberts A, Sadler K, Stavros T, Tamura R, Wood K, Xu P, Young K, Alies P, Badias F, Baker A, Bassi M, Beam C, Boulware D, Bounmananh L, Bream S, Deemer M, Freeman D, Gough J, Ginem J, Granger M, Holloway M, Kieffer M, Lane P, Law P, Linton C, Nallamshetty L, Oduah V, Parrimon Y, Paulus K, Pilger J, Ramiro J, Luvon AQ, Ritzie A, Sharma A, Shor X, Song A, Terry J, Weinberger M, Wootten J, Fradkin E, Leschek L, Spain C, Cowie S, Malozowski P, Savage G, Beck E, Blumberg R, Gubitosi-Klug L, Laffel R, Veatch D, Wallace J, Braun D, Brillon A, Lernmark B, Lo H, Mitchell A, Naji J, Nerup T, Orchard M, Steffes A, Tsiatis B, Zinman B, Loechelt L, Baden M, Green A, Weinberg S, Marcovina JP, Palmer A, Weinberg L, Yu W, Winter GS, Eisenbarth A, Shultz E, Batts K, Fitzpatrick M, Ramey R, Guerra C, Webb M, Romasco C, Greenbaum S, Lord D, VanBuecken W, Hao M, McCulloch D, Hefty K, Varner R, Goland E, Greenberg S, Pollack B, Nelson L, Looper L, DiMeglio M, Spall C, Evans-Molina M, Mantravadi J, Sanchez M, Mullen V, Patrick S, Woerner DM, Wilson T, Aye T, Esrey K, Barahona B, Baker H, Bitar C, Ghodrat M, Hamilton SE, Gitelman CT, Ferrara S, Sanda R, Wesch C, Torok P, Gottlieb J, Lykens C, Brill A, Michels A, Schauwecker MJ, Haller DA, Schatz MA, Atkinson LM, Jacobsen M, Cintron TM, Brusko CH, Wasserfall CE, Mathews JS, Skyler JM, Marks D, Baidal C, Blaschke D, Matheson A, Moran B, Nathan A, Street J, Leschyshyn B, Pappenfus B, Nelson N, Flaherty D, Becker K, Delallo D, Groscost K, Riley H, Rodriguez D, Henson E, Eyth W, Russell A, Brown F, Brendall K, Herold, Feldman L. Low-Dose Anti-Thymocyte Globulin (ATG) Preserves β-Cell Function and Improves HbA 1c in New-Onset Type 1 Diabetes. Diabetes Care 2018; 41:1917-1925. [PMID: 30012675 PMCID: PMC6105329 DOI: 10.2337/dc18-0494] [Citation(s) in RCA: 96] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Accepted: 06/12/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE A pilot study suggested that combination therapy with low-dose anti-thymocyte globulin (ATG) and pegylated granulocyte colony-stimulating factor (GCSF) preserves C-peptide in established type 1 diabetes (T1D) (duration 4 months to 2 years). We hypothesized that 1) low-dose ATG/GCSF or 2) low-dose ATG alone would slow the decline of β-cell function in patients with new-onset T1D (duration <100 days). RESEARCH DESIGN AND METHODS A three-arm, randomized, double-masked, placebo-controlled trial was performed by the Type 1 Diabetes TrialNet Study Group in 89 subjects: 29 subjects randomized to ATG (2.5 mg/kg intravenously) followed by pegylated GCSF (6 mg subcutaneously every 2 weeks for 6 doses), 29 to ATG alone (2.5 mg/kg), and 31 to placebo. The primary end point was mean area under the curve (AUC) C-peptide during a 2-h mixed-meal tolerance test 1 year after initiation of therapy. Significance was defined as one-sided P value < 0.025. RESULTS The 1-year mean AUC C-peptide was significantly higher in subjects treated with ATG (0.646 nmol/L) versus placebo (0.406 nmol/L) (P = 0.0003) but not in those treated with ATG/GCSF (0.528 nmol/L) versus placebo (P = 0.031). HbA1c was significantly reduced at 1 year in subjects treated with ATG and ATG/GCSF, P = 0.002 and 0.011, respectively. CONCLUSIONS Low-dose ATG slowed decline of C-peptide and reduced HbA1c in new-onset T1D. Addition of GCSF did not enhance C-peptide preservation afforded by low-dose ATG. Future studies should be considered to determine whether low-dose ATG alone or in combination with other agents may prevent or delay the onset of the disease.
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Affiliation(s)
| | | | - Jay S. Skyler
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL
| | | | | | | | | | | | - David Baidal
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL
| | | | | | | | - Peter A. Gottlieb
- University of Colorado Barbara Davis Center for Childhood Diabetes, Aurora, CO
| | | | - Jennifer B. Marks
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL
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Redondo MJ, Geyer S, Steck AK, Sharp S, Wentworth JM, Weedon MN, Antinozzi P, Sosenko J, Atkinson M, Pugliese A, Oram RA, Antinozzi P, Atkinson M, Battaglia M, Becker D, Bingley P, Bosi E, Buckner J, Colman P, Gottlieb P, Herold K, Insel R, Kay T, Knip M, Marks J, Moran A, Palmer J, Peakman M, Philipson L, Pugliese A, Raskin P, Rodriguez H, Roep B, Russell W, Schatz D, Wherrett D, Wilson D, Winter W, Ziegler A, Benoist C, Blum J, Chase P, Clare-Salzler M, Clynes R, Eisenbarth G, Fathman C, Grave G, Hering B, Kaufman F, Leschek E, Mahon J, Nanto-Salonen K, Nepom G, Orban T, Parkman R, Pescovitz M, Peyman J, Roncarolo M, Simell O, Sherwin R, Siegelman M, Steck A, Thomas J, Trucco M, Wagner J, Greenbaum ,CJ, Bourcier K, Insel R, Krischer JP, Leschek E, Rafkin L, Spain L, Cowie C, Foulkes M, Krause-Steinrauf H, Lachin JM, Malozowski S, Peyman J, Ridge J, Savage P, Skyler JS, Zafonte SJ, Kenyon NS, Santiago I, Sosenko JM, Bundy B, Abbondondolo M, Adams T, Amado D, Asif I, Boonstra M, Bundy B, Burroughs C, Cuthbertson D, Deemer M, Eberhard C, Fiske S, Ford J, Garmeson J, Guillette H, Browning G, Coughenour T, Sulk M, Tsalikan E, Tansey M, Cabbage J, Dixit N, Pasha S, King M, Adcock K, Geyer S, Atterberry H, Fox L, Englert K, Mauras N, Permuy J, Sikes K, Berhe T, Guendling B, McLennan L, Paganessi L, Hays B, Murphy C, Draznin M, Kamboj M, Sheppard S, Lewis V, Coates L, Moore W, Babar G, Bedard J, Brenson-Hughes D, Henderson C, Cernich J, Clements M, Duprau R, Goodman S, Hester L, Huerta-Saenz L, Karmazin A, Letjen T, Raman S, Morin D, Henry M, Bestermann W, Morawski E, White J, Brockmyer A, Bays R, Campbell S, Stapleton A, Stone N, Donoho A, Everett H, Heyman K, Hensley H, Johnson M, Marshall C, Skirvin N, Taylor P, Williams R, Ray L, Wolverton C, Nickels D, Dothard C, Hsiao B, Speiser P, Pellizzari M, Bokor L, Izuora K, Abdelnour S, Cummings P, Paynor S, Leahy M, Riedl M, Shockley S, Karges C, Saad R, Briones T, Casella S, Herz C, Walsh K, Greening J, Hay F, Hunt S, Sikotra N, Simons L, Keaton N, Karounos D, Oremus R, Dye L, Myers L, Ballard D, Miers W, Sparks R, Thraikill K, Edwards K, Fowlkes J, Kinderman A, Kemp S, Morales A, Holland L, Johnson L, Paul P, Ghatak A, Phelen K, Leyland H, Henderson T, Brenner D, Law P, Oppenheimer E, Mamkin I, Moniz C, Clarson C, Lovell M, Peters A, Ruelas V, Borut D, Burt D, Jordan M, Leinbach A, Castilla S, Flores P, Ruiz M, Hanson L, Green-Blair J, Sheridan R, Wintergerst K, Pierce G, Omoruyi A, Foster M, Linton C, Kingery S, Lunsford A, Cervantes I, Parker T, Price P, Urben J, Doughty I, Haydock H, Parker V, Bergman P, Liu S, Duncum S, Rodda C, Thomas A, Ferry R, McCommon D, Cockroft J, Perelman A, Calendo R, Barrera C, Arce-Nunez E, Lloyd J, Martinez Y, De la Portilla M, Cardenas I, Garrido L, Villar M, Lorini R, Calandra E, D’Annuzio G, Perri K, Minuto N, Malloy J, Rebora C, Callegari R, Ali O, Kramer J, Auble B, Cabrera S, Donohoue P, Fiallo-Scharer R, Hessner M, Wolfgram P, Maddox K, Kansra A, Bettin N, McCuller R, Miller A, Accacha S, Corrigan J, Fiore E, Levine R, Mahoney T, Polychronakos C, Martin J, Gagne V, Starkman H, Fox M, Chin D, Melchionne F, Silverman L, Marshall I, Cerracchio L, Cruz J, Viswanathan A, Miller J, Wilson J, Chalew S, Valley S, Layburn S, Lala A, Clesi P, Genet M, Uwaifo G, Charron A, Allerton T, Milliot E, Cefalu W, Melendez-Ramirez L, Richards R, Alleyn C, Gustafson E, Lizanna M, Wahlen J, Aleiwe S, Hansen M, Wahlen H, Moore M, Levy C, Bonaccorso A, Rapaport R, Tomer Y, Chia D, Goldis M, Iazzetti L, Klein M, Levister C, Waldman L, Muller S, Wallach E, Regelmann M, Antal Z, Aranda M, Reynholds C, Leech N, Wake D, Owens C, Burns M, Wotherspoon J, Nguyen T, Murray A, Short K, Curry G, Kelsey S, Lawson J, Porter J, Stevens S, Thomson E, Winship S, Wynn L, O’Donnell R, Wiltshire E, Krebs J, Cresswell P, Faherty H, Ross C, Vinik A, Barlow P, Bourcier M, Nevoret M, Couper J, Oduah V, Beresford S, Thalagne N, Roper H, Gibbons J, Hill J, Balleaut S, Brennan C, 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Trunnel S, Transue D, Surhigh J, Bezzaire D, Moltz K, Zacharski E, Henske J, Desai S, Frizelis K, Khan F, Sjoberg R, Allen K, Manning P, Hendry G, Taylor B, Jones S, Couch R, Danchak R, Lieberman D, Strader W, Bencomo M, Bailey T, Bedolla L, Roldan C, Moudiotis C, Vaidya B, Anning C, Bunce S, Estcourt S, Folland E, Gordon E, Harrill C, Ireland J, Piper J, Scaife L, Sutton K, Wilkins S, Costelloe M, Palmer J, Casas L, Miller C, Burgard M, Erickson C, Hallanger-Johnson J, Clark P, Taylor W, Galgani J, Banerjee S, Banda C, McEowen D, Kinman R, Lafferty A, Gillett S, Nolan C, Pathak M, Sondrol L, Hjelle T, Hafner S, Kotrba J, Hendrickson R, Cemeroglu A, Symington T, Daniel M, Appiagyei-Dankah Y, Postellon D, Racine M, Kleis L, Barnes K, Godwin S, McCullough H, Shaheen K, Buck G, Noel L, Warren M, Weber S, Parker S, Gillespie I, Nelson B, Frost C, Amrhein J, Moreland E, Hayes A, Peggram J, Aisenberg J, Riordan M, Zasa J, Cummings E, Scott K, Pinto T, Mokashi A, McAssey K, Helden E, Hammond P, Dinning L, Rahman S, Ray S, Dimicri C, Guppy S, Nielsen H, Vogel C, Ariza C, Morales L, Chang Y, Gabbay R, Ambrocio L, Manley L, Nemery R, Charlton W, Smith P, Kerr L, Steindel-Kopp B, Alamaguer M, Tabisola-Nuesca E, Pendersen A, Larson N, Cooper-Olviver H, Chan D, Fitz-Patrick D, Carreira T, Park Y, Ruhaak R, Liljenquist D. A Type 1 Diabetes Genetic Risk Score Predicts Progression of Islet Autoimmunity and Development of Type 1 Diabetes in Individuals at Risk. Diabetes Care 2018; 41:1887-1894. [PMID: 30002199 PMCID: PMC6105323 DOI: 10.2337/dc18-0087] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Accepted: 06/06/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals. RESEARCH DESIGN AND METHODS We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients' relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2-51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). Of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. Of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables. RESULTS Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06-1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS >0.295, 95% CI 1.47-3.51; P = 0.0002). CONCLUSIONS The T1D GRS independently predicts progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives.
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Affiliation(s)
- Maria J. Redondo
- Texas Children’s Hospital, Baylor College of Medicine, Houston, TX
| | | | - Andrea K. Steck
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Seth Sharp
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, U.K
| | - John M. Wentworth
- Walter and Eliza Hall Institute of Medical Research and Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Michael N. Weedon
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, U.K
| | | | | | | | | | - Richard A. Oram
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, U.K
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Evans-Molina C, Sims EK, DiMeglio LA, Ismail HM, Steck AK, Palmer JP, Krischer JP, Geyer S, Xu P, Sosenko JM. β Cell dysfunction exists more than 5 years before type 1 diabetes diagnosis. JCI Insight 2018; 3:120877. [PMID: 30089716 DOI: 10.1172/jci.insight.120877] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 06/21/2018] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The duration and patterns of β cell dysfunction during type 1 diabetes (T1D) development have not been fully defined. METHODS Metabolic measures derived from oral glucose tolerance tests (OGTTs) were compared between autoantibody-positive (aAb+) individuals followed in the TrialNet Pathway to Prevention study who developed diabetes after 5 or more years or less than 5 years of longitudinal follow-up (Progressors≥5, n = 75; Progressors<5, n = 474) and 144 aAb-negative (aAb-) relatives. RESULTS Mean age at study entry was 15.0 ± 12.6 years for Progressors≥5; 12.0 ± 9.1 for Progressors<5; and 16.3 ± 10.4 for aAb- relatives. At baseline, Progressors≥5 already exhibited significantly lower fasting C-peptide (P < 0.01), C-peptide AUC (P < 0.001), and early C-peptide responses (30- to 0-minute C-peptide; P < 0.001) compared with aAb- relatives, while 2-hour glucose (P = 0.03), glucose AUC (<0.001), and Index60 (<0.001) were all higher. Despite significant baseline impairment, metabolic measures in Progressors≥5 were relatively stable until 2 years prior to T1D diagnosis, when there was accelerated C-peptide decline and rising glycemia from 2 years until diabetes diagnosis. Remarkably, patterns of progression within 3 years of diagnosis were nearly identical between Progressors≥5 and Progressors<5. CONCLUSION These data provide insight into the chronicity of β cell dysfunction in T1D and indicate that β cell dysfunction may precede diabetes diagnosis by more than 5 years in a subset of aAb+ individuals. Even among individuals with varying lengths of aAb positivity, our findings indicate that patterns of metabolic decline are uniform within the last 3 years of progression to T1D. TRIAL REGISTRATION Clinicaltrials.gov NCT00097292. FUNDING The Type 1 Diabetes TrialNet Study Group is a clinical trials network currently funded by the NIH through the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Allergy and Infectious Diseases, and The Eunice Kennedy Shriver National Institute of Child Health and Human Development and the Juvenile Diabetes Research Foundation.
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Affiliation(s)
- Carmella Evans-Molina
- Departments of Medicine.,Cellular and Integrative Physiology.,Biochemistry and Molecular Biology.,Pediatrics, and the.,Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Roudebush VA Medical Center, Indianapolis, Indiana, USA
| | - Emily K Sims
- Pediatrics, and the.,Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Linda A DiMeglio
- Pediatrics, and the.,Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Heba M Ismail
- Children's Hospital of Pittsburgh of UPMC, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Andrea K Steck
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Denver, Colorado, USA
| | - Jerry P Palmer
- VA Puget Sound Health Care System and the University of Washington, Seattle, Washington, USA
| | - Jeffrey P Krischer
- Health Informatics Institute, University of South Florida, Tampa, Florida, USA
| | - Susan Geyer
- Health Informatics Institute, University of South Florida, Tampa, Florida, USA
| | - Ping Xu
- Health Informatics Institute, University of South Florida, Tampa, Florida, USA
| | - Jay M Sosenko
- Department of Medicine and the Diabetes Research Institute, Leonard Miller School of Medicine, University of Miami, Miami, Florida, USA
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