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Gharzai LA, Morris E, Suresh K, Nguyen-Tân PF, Rosenthal DI, Gillison ML, Harari PM, Garden AS, Koyfman S, Caudell JJ, Jones CU, Mitchell DL, Krempl G, Ridge JA, Gensheimer MF, Bonner JA, Filion E, Dunlap NE, Stokes WA, Le QT, Torres-Saavedra P, Mierzwa M, Schipper MJ. Surrogate endpoints in clinical trials of p16-positive squamous cell carcinoma of the oropharynx: an individual patient data meta-analysis. Lancet Oncol 2024; 25:366-375. [PMID: 38423050 PMCID: PMC10962533 DOI: 10.1016/s1470-2045(24)00016-0] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 12/19/2023] [Accepted: 01/09/2024] [Indexed: 03/02/2024]
Abstract
BACKGROUND The increased incidence of human papillomavirus (HPV)-related cancers has motivated efforts to optimise treatment for these patients with excellent prognosis. Validation of surrogates for overall survival could expedite the investigation of new therapies. We sought to evaluate candidate intermediate clinical endpoints in trials assessing definitive treatment of p16-positive oropharyngeal cancer with chemotherapy or radiotherapy. METHODS We did a retrospective review of five multicentre, randomised trials (NRG/RTOG 9003, 0129, 0234, 0522, and 1016) that tested radiotherapy with or without chemotherapy in patients (aged ≥18 years) with p16-positive localised head or neck squamous-cell carcinomas. Eight intermediate clinical endpoints were considered as potential surrogates for overall survival: freedom from local progression, freedom from regional progression, freedom from distant metastasis, freedom from locoregional progression, freedom from any progression, locoregional progression-free survival, progression-free survival, and distant metastasis-free survival. We used a two-stage meta-analytical framework, which requires high correlation between the intermediate clinical endpoint and overall survival at the patient level (condition 1), and high correlation between the treatment effect on the intermediate clinical endpoint and the treatment effect on overall survival (condition 2). For both, an r2 greater than 0·7 was used as criteria for clinically relevant surrogacy. FINDINGS We analysed 1373 patients with oropharyngeal cancer from May 9, 2020, to Nov 22, 2023. 1231 (90%) of patients were men, 142 (10%) were women, and 1207 (88%) were White, with a median age of 57 years (IQR 51-62). Median follow-up was 4·2 years (3·1-5·1). For the first condition, correlating the intermediate clinical endpoints with overall survival at the individual and trial level, the three composite endpoints of locoregional progression-free survival (Kendall's τ 0·91 and r2 0·72), distant metastasis-free survival (Kendall's τ 0·93 and r2 0·83), and progression-free survival (Kendall's τ 0·88 and r2 0·70) were highly correlated with overall survival at the patient level and at the trial-group level. For the second condition, correlating treatment effects of the intermediate clinical endpoints and overall survival, the composite endpoints of locoregional progression-free survival (r2 0·88), distant metastasis-free survival (r2 0·96), and progression-free survival (r2 0·92) remained strong surrogates. Treatment effects on the remaining intermediate clinical endpoints were less strongly correlated with overall survival. INTERPRETATION We identified locoregional progression-free survival, distant metastasis-free survival, and progression-free survival as surrogates for overall survival in p16-positive oropharyngeal cancers treated with chemotherapy or radiotherapy, which could serve as clinical trial endpoints. FUNDING NRG Oncology Operations, NRG Oncology SDMC, the National Cancer Institute, Eli Lilly, Aventis, and the University of Michigan.
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Affiliation(s)
- Laila A Gharzai
- Department of Radiation Oncology, Northwestern University, Chicago, IL, USA
| | - Emily Morris
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Krithika Suresh
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA; Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Phuc Felix Nguyen-Tân
- Department of Radiation Oncology, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - David I Rosenthal
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Maura L Gillison
- Department of Thoracic and Head/Neck Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Paul M Harari
- Department of Radiation Oncology, University of Wisconsin, Madison, WI, USA
| | - Adam S Garden
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Shlomo Koyfman
- Department of Radiation Oncology, University of Cleveland Medical Center, Cleveland, OH, USA
| | - Jimmy J Caudell
- Department of Radiation Oncology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Christopher U Jones
- Department of Radiation Oncology, Sutter Cancer Research Consortium, Novato, CA, USA
| | - Darrion L Mitchell
- Department of Radiation Oncology, Ohio State University, Columbus, OH, USA
| | - Greg Krempl
- Department of Otolaryngology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - John A Ridge
- Department of Otolaryngology, Fox Chase Cancer Center, Philadelphia, PA, USA
| | | | - James A Bonner
- Department of Radiation Oncology, University of Alabama at Birmingham Medical Center, Birmingham, AL, USA
| | - Edith Filion
- Department of Radiation Oncology, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Neal E Dunlap
- Department of Radiation Oncology, The James Graham Brown Cancer Center at University of Louisville, Louisville, KY, USA
| | - William A Stokes
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA
| | - Quynh-Thu Le
- Department of Radiation Oncology, Stanford University, Stanford, CA, USA
| | | | - Michelle Mierzwa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA; Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
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Rankin J, Bedrava J, Covington E, Johnson JL, Pollard-Larkin J, Schipper MJ, Castillo R, Woodward M, Xing YH, Paradis KC. Women in the Medical Physics Workforce: Insights from Membership Trends of the American Association of Physicists in Medicine, 1993 to 2023. Int J Radiat Oncol Biol Phys 2024:S0360-3016(24)00318-3. [PMID: 38387813 DOI: 10.1016/j.ijrobp.2024.02.013] [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: 08/11/2023] [Revised: 01/15/2024] [Accepted: 02/08/2024] [Indexed: 02/24/2024]
Abstract
PURPOSE Women remain underrepresented in medical physics in the United States, and determinants of persisting disparities remain unclear. Here, we performed a detailed investigation of American Association of Physicists in Medicine (AAPM) membership trajectories to evaluate trends in Full membership with respect to gender, age, and highest degree. METHODS AND MATERIALS Membership data, including gender, date of birth, highest degree, membership type, and years of active membership for 1993 to 2023 were obtained from AAPM. Group 1 included Full members who joined AAPM in 1993 or later. A subset of group 1 including only members who joined and left AAPM since 1993 (former members, group 1F) was used to calculate age at membership cessation and duration. Results were compared by gender and highest degree. A Kaplan-Meier analysis was also used to evaluate membership "survival" by age and highest degree. RESULTS Complete data were available for 6647 current and former Full members (group 1), including 2211 former members (group 1F). On average, women became Full members at a significantly younger age than men (34.6 vs 37.5 years of age, P < .001) and ended their memberships (if applicable) at a significantly younger age than men (46.1 vs 50.1 years of age, P < .001). The Kaplan-Meier "survival" analysis showed that for a given age, women were at a significantly greater risk of membership cessation than men, and women with master's degrees had the lowest membership survival of any gender/degree subgroup. When analyzing by membership duration, there was no difference in survival by gender alone. Still, women with PhDs were found to have the greatest membership survival among gender/degree subgroups. CONCLUSIONS Both gender and degree type influenced AAPM membership trajectories. Although we have offered a discussion of possible explanations, qualitative data collected from both continuing and departing AAPM members will be critical in the ongoing journey toward gender parity in the profession of medical physics.
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Affiliation(s)
| | - Jenna Bedrava
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Elizabeth Covington
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | | | - Julianne Pollard-Larkin
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan; Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Richard Castillo
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia
| | | | - Yan-Hong Xing
- American Association of Physicists in Medicine, Alexandria, VA
| | - Kelly C Paradis
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
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3
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Ramanathan S, Hochstedler KA, Laucis AM, Movsas B, Stevens CW, Kestin LL, Dominello MM, Grills IS, Matuszak M, Hayman J, Paximadis PA, Schipper MJ, Jolly S, Boike TP. Predictors of Early Hospice or Death in Patients With Inoperable Lung Cancer Treated With Curative Intent. Clin Lung Cancer 2023:S1525-7304(23)00283-8. [PMID: 38290875 DOI: 10.1016/j.cllc.2023.12.014] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 12/11/2023] [Accepted: 12/23/2023] [Indexed: 02/01/2024]
Abstract
INTRODUCTION Treatment for inoperable stage II to III non-small cell lung cancer (NSCLC) involves chemo-radiotherapy (CRT). However, some patients transition to hospice or die early during their treatment course. We present a model to prognosticate early poor outcomes in NSCLC patients treated with curative-intent CRT. METHODS AND MATERIALS Across a statewide consortium, data was prospectively collected on stage II to III NSCLC patients who received CRT between 2012 and 2019. Early poor outcomes included hospice enrollment or death within 3 months of completing CRT. Logistic regression models were used to assess predictors in prognostic models. LASSO regression with multiple imputation were used to build a final multivariate model, accounting for missing covariates. RESULTS Of the 2267 included patients, 128 experienced early poor outcomes. Mean age was 71 years and 59% received concurrent chemotherapy. The best predictive model, created parsimoniously from statistically significant univariate predictors, included age, ECOG, planning target volume (PTV), mean heart dose, pretreatment lack of energy, and cough. The estimated area under the ROC curve for this multivariable model was 0.71, with a negative predictive value of 95%, specificity of 97%, positive predictive value of 23%, and sensitivity of 16% at a predicted risk threshold of 20%. CONCLUSIONS This multivariate model identified a combination of clinical variables and patient reported factors that may identify individuals with inoperable NSCLC undergoing curative intent chemo-radiotherapy who are at higher risk for early poor outcomes.
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Affiliation(s)
| | | | - Anna M Laucis
- Department of Radiation Oncology, University of Michigan Health System, Ann Arbor, MI
| | | | | | - Larry L Kestin
- Genesis Care / Michigan Healthcare Professionals, Troy, MI
| | | | | | - Martha Matuszak
- Department of Radiation Oncology, University of Michigan Health System, Ann Arbor, MI
| | - James Hayman
- Department of Radiation Oncology, University of Michigan Health System, Ann Arbor, MI
| | | | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan Health System, Ann Arbor, MI
| | - Shruti Jolly
- Department of Radiation Oncology, University of Michigan Health System, Ann Arbor, MI.
| | - Thomas P Boike
- Genesis Care / Michigan Healthcare Professionals, Troy, MI
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Das R, Abbott MR, Hadley SW, Sahai V, Bednar F, Evans JR, Schipper MJ, Lawrence TS, Cuneo KC. Predictors of Acute and Late Toxicity in Patients Receiving Chemoradiation for Unresectable Pancreatic Cancer. Adv Radiat Oncol 2023; 8:101266. [PMID: 38047228 PMCID: PMC10692286 DOI: 10.1016/j.adro.2023.101266] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 04/28/2023] [Indexed: 12/05/2023] Open
Abstract
Purpose Patients with pancreatic cancer undergoing chemoradiation therapy may experience acute and chronic side effects. We conducted an exploratory analysis of patients with locally advanced pancreatic cancer (LAPC) undergoing definitive chemoradiation to identify factors influencing the occurrence of gastrointestinal (GI) bleeding, short-term radiation side effects, patterns of failure, and survival. Methods and Materials Under an institutional review board-approved protocol, we retrospectively studied patients with LAPC treated with chemoradiation. Statistical models were used to test associations between clinical characteristics and outcomes, including upper GI bleeding, radiation treatment breaks, and weight loss during therapy. Results Between 1999 and 2012, 211 patients were treated with radiation for pancreatic cancer. All patients received concurrent chemotherapy with either gemcitabine (174) or 5-fluorouracil (27), and 67 received intensity modulated radiation therapy (IMRT). Overall, 18 patients experienced an upper GI bleed related to treatment, with 70% of bleeds occurring in the stomach or duodenum, and among those patients, 11 (61%) patients had a pancreatic head tumor and 17 (94%) patients had a metallic biliary stent. IMRT was associated with decreased risk of postradiation nausea (odds ratio, 0.27 [0.11, 0.67], P = .006) compared with 3-dimensional conformal radiation. Regarding long-term toxicities, patients with a metallic biliary stent at the time of radiation therapy were at a significantly higher risk of developing upper GI bleeding (unadjusted hazard ratio [HR], 15.41 [2.02, 117.42], P = .008), even after controlling for radiation treatment modality and prescribed radiation dose (adjusted HR, 17.38 [2.26, 133.58], P = .006). Furthermore, biliary stent placement was associated with a higher risk of death (HR, 1.99 [1.41, 2.83], P < .001) after adjusting for demographic, treatment-related, and patient-related variables. Conclusions Metallic biliary stents may be associated with an increased risk of upper GI bleeding and mortality. Furthermore, IMRT was associated with less nausea and short-term toxicity compared with 3-dimensional conformal therapy.
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Affiliation(s)
- Rishi Das
- Department of Internal Medicine, University of Southern California, Los Angeles, California
| | - Madeline R. Abbott
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Scott W. Hadley
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Vaibhav Sahai
- Department of Internal Medicine, Hematology and Oncology, University of Michigan, Ann Arbor, Michigan
| | - Filip Bednar
- Department of Surgery, University of Michigan, Ann Arbor, Michigan
| | - Joseph R. Evans
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew J. Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | | | - Kyle C. Cuneo
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
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5
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Gharzai LA, Wang C, Tang M, Jackson WC, Maurino C, Cousins MM, Mendiratta-Lala M, Parikh ND, Mayo CS, Haken RKT, Owen D, Cuneo KC, Schipper MJ, Lawrence TS. Efficacy of a Second Course of Radiation for Patients With Metachronous Hepatocellular Carcinoma. Pract Radiat Oncol 2023; 13:e504-e514. [PMID: 37295727 DOI: 10.1016/j.prro.2023.05.008] [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: 01/30/2023] [Revised: 04/17/2023] [Accepted: 05/25/2023] [Indexed: 06/12/2023]
Abstract
PURPOSE Liver-directed radiation therapy is an effective treatment for hepatocellular carcinoma (HCC), but metachronous lesions develop outside the irradiated field in >50% of patients. We hypothesized that irradiation of these new lesions would produce an outcome like that of patients receiving a first course (C1) of treatment. METHODS AND MATERIALS We included patients with HCC who received a second course (C2) of radiation therapy >1 month after C1. Toxicity was defined as Child-Pugh score increase ≥2 within 6 months posttreatment (binary model) and as the change in albumin-bilirubin during the year after treatment (longitudinal model). Overall survival (OS) and local failure (LF) were captured at the patient and lesion level, respectively; both were summarized with Kaplan-Meier estimates. Predictors of toxicity and OS were assessed using generalized linear mixed and Cox regression models, respectively. RESULTS Of 340 patients with HCC, 47 underwent irradiation for metachronous HCC, receiving similar prescription dose in C1/C2. Median follow-up was 17 months after C1 and 15 months after C2. Twenty-two percent of patients experienced toxicity after C1, and 25% experienced toxicity after C2. Worse baseline albumin-bilirubin predicted toxicity in both binary (odds ratio, 2.40; 95% CI, 1.46-3.94; P = .0005) and longitudinal models (P < .005). Two-year LF rate was 11.2% after C1 and 8.3% after C2; tumor dose (hazard ratio [HR], 0.982; 95% CI, 0.969-0.995; P = .007) and tumor size (HR, 1.135; 95% CI, 1.068-1.206; P < .005) predicted LF. Two-year OS was 46.0% after C1 and 42.6% after C2; tumor dose (HR, 0.986; 95% CI, 0.979-0.992; P < .005) and tumor size (HR, 1.049; 95% CI, 1.010-1.088; P = .0124) predicted OS. Reirradiation was not associated with toxicity (P > .7), LF (P = .79), or OS (P = .39). CONCLUSIONS In this largest series in the Western hemisphere, we demonstrate that irradiation for metachronous HCC offers low rates of LF with acceptable toxicity and OS like that of patients receiving a C1. These findings support judicious selection of patients for reirradiation in metachronous HCC.
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Affiliation(s)
- Laila A Gharzai
- Department of Radiation Oncology, Northwestern University, Evanston, Illinois.
| | - Chang Wang
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Ming Tang
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - William C Jackson
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Christopher Maurino
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew M Cousins
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | | | - Neehar D Parikh
- Division of Gastroenterology and Hepatology, University of Michigan, Ann Arbor, Michigan
| | - Charles S Mayo
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Randall K Ten Haken
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Dawn Owen
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Kyle C Cuneo
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Theodore S Lawrence
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
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6
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Allen SG, Dragovic AF, Yin HM, Bryant AK, Paximadis PA, Matuszak MM, Schipper MJ, Dess RT, Hayman JA, Dominello MM, Kestin LL, Movsas B, Jolly S, Bergsma DP. Prospective Evaluation of Limited-Stage Small Cell Lung Cancer Radiotherapy Fractionation Regimen Usage and Acute Toxicity in a Large Statewide Quality Collaborative. Pract Radiat Oncol 2023; 13:444-453. [PMID: 37100388 DOI: 10.1016/j.prro.2023.04.007] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/11/2023] [Accepted: 04/12/2023] [Indexed: 04/28/2023]
Abstract
PURPOSE National guidelines on limited-stage small cell lung cancer (LS-SCLC) treatment give preference to a hyperfractionated regimen of 45 Gy in 30 fractions delivered twice daily; however, use of this regimen is uncommon compared with once-daily regimens. The purpose of this study was to characterize the LS-SCLC fractionation regimens used throughout a statewide collaborative, analyze patient and treatment factors associated with these regimens, and describe real-world acute toxicity profiles of once- and twice-daily radiation therapy (RT) regimens. METHODS AND MATERIALS Demographic, clinical, and treatment data along with physician-assessed toxicity and patient-reported outcomes were prospectively collected by 29 institutions within the Michigan Radiation Oncology Quality Consortium between 2012 and 2021 for patients with LS-SCLC. We modeled the influence of RT fractionation and other patient-level variables clustered by treatment site on the odds of a treatment break specifically due to toxicity with multilevel logistic regression. National Cancer Institute Common Terminology Criteria for Adverse Events, version 4.0, incident grade 2 or worse toxicity was longitudinally compared between regimens. RESULTS There were 78 patients (15.6% overall) treated with twice-daily RT and 421 patients treated with once-daily RT. Patients receiving twice-daily RT were more likely to be married or living with someone (65% vs 51%; P = .019) and to have no major comorbidities (24% vs 10%; P = .017). Once-daily RT fractionation toxicity peaked during RT, and twice-daily toxicity peaked within 1 month after RT. After stratifying by treatment site and adjusting for patient-level variables, once-daily treated patients had 4.11 (95% confidence interval, 1.31-12.87) higher odds of treatment break specifically due to toxicity than twice-daily treated patients. CONCLUSIONS Hyperfractionation for LS-SCLC remains infrequently prescribed despite the lack of evidence demonstrating superior efficacy or lower toxicity of once-daily RT. With peak acute toxicity after RT and lower likelihood of a treatment break with twice-daily fractionation in real-word practice, providers may start using hyperfractionated RT more frequently.
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Affiliation(s)
- Steven G Allen
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | | | - Huiying Maggie Yin
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Alex K Bryant
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Peter A Paximadis
- Department of Radiation Oncology, Spectrum Health Lakeland, St. Joseph, Michigan
| | - Martha M Matuszak
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Robert T Dess
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - James A Hayman
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Michael M Dominello
- Department of Radiation Oncology, Barbara Ann Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, Michigan
| | - Larry L Kestin
- Michigan Healthcare Professionals, 21st Century Oncology, Farmington Hills, Michigan
| | - Benjamin Movsas
- Department of Radiation Oncology, Henry Ford Cancer Institute, Detroit, Michigan
| | - Shruti Jolly
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
| | - Derek P Bergsma
- Department of Radiation Oncology, Mercy Health Saint Mary's, Grand Rapids, Michigan.
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7
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Wang C, Peterson AB, Wong KK, Roseland ME, Schipper MJ, Dewaraja YK. Single-Time-Point Imaging for Dosimetry After [ 177Lu]Lu-DOTATATE: Accuracy of Existing Methods and Novel Data-Driven Models for Reducing Sensitivity to Time-Point Selection. J Nucl Med 2023; 64:1463-1470. [PMID: 37500260 PMCID: PMC10478823 DOI: 10.2967/jnumed.122.265338] [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] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 04/27/2023] [Indexed: 07/29/2023] Open
Abstract
Estimation of the time-integrated activity (TIA) for dosimetry from imaging at a single time point (STP) facilitates the clinical translation of dosimetry-guided radiopharmaceutical therapy. However, the accuracy of the STP methods for TIA estimation varies on the basis of time-point selection. We constructed patient data-driven regression models to reduce the sensitivity to time-point selection and to compare these new models with commonly used STP methods. Methods: SPECT/CT performed at time period (TP) 1 (3-5 h), TP2 (days 1-2), TP3 (days 3-5), and TP4 (days 6-8) after cycle 1 of [177Lu]Lu-DOTATATE therapy involved 27 patients with 100 segmented tumors and 54 kidneys. Influenced by the previous physics-based STP models of Madsen et al. and Hänscheid et al., we constructed an STP prediction expression, TIA = A(t) × g(t), in a SPECT data-driven way (model 1), in which A(t) is the observed activity at imaging time t, and the curve, g(t), is estimated with a nonparametric generalized additive model by minimizing the normalized mean square error relative to the TIA derived from 4-time-point SPECT (reference TIA). Furthermore, we fit a generalized additive model that incorporates baseline biomarkers as auxiliary data in addition to the single activity measurement (model 2). Leave-one-out cross validation was performed to evaluate STP models using mean absolute error (MAE) and mean square error between the predicted and reference TIA. Results: At days 3-5, all evaluated STP methods performed very well, with an MAE of less than 7% (between-patient SD of <10%) for both kidneys and tumors. At other TPs, the Madsen method and data-driven models 1 and 2 performed reasonably well (MAEs < 17% for kidneys and < 32% for tumors), whereas the error with the Hänscheid method was substantially higher. The proof of concept of adding baseline biomarkers to the prediction model was demonstrated and showed a moderate enhancement at TP1, especially for estimating kidney TIA (MAE ± SD from 15.6% ± 1.3% to 11.8% ± 1.0%). Evaluations on 500 virtual patients using clinically relevant time-activity simulations showed a similar performance. Conclusion: The performance of the Madsen method and proposed data-driven models is less sensitive to TP selection than is the Hänscheid method. At the earliest TP, which is the most practical, the model incorporating baseline biomarkers outperforms other methods that rely only on the single activity measurement.
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Affiliation(s)
- Chang Wang
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan;
| | - Avery B Peterson
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
- Department of Radiation Oncology, Wayne State University, Detroit, Michigan; and
| | - Ka Kit Wong
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - Molly E Roseland
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Yuni K Dewaraja
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
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8
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Allen SG, Rosen BS, Aryal M, Cao Y, Schipper MJ, Wong KK, Casper KA, Chinn SB, Malloy KM, Prince ME, Rosko AJ, Shuman AG, Spector ME, Stucken CL, Swiecicki PL, Worden FP, Brenner JC, Schonewolf CA, Elliott DA, Mierzwa ML, Shah JL. Initial Feasibility and Acute Toxicity Outcomes From a Phase 2 Trial of 18F-Fluorodeoxyglucose Positron Emission Tomography Response-Based De-escalated Definitive Chemoradiotherapy for p16+ Oropharynx Cancer: A Planned Interim Analysis. Int J Radiat Oncol Biol Phys 2023; 117:171-180. [PMID: 36931572 DOI: 10.1016/j.ijrobp.2023.03.043] [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: 10/30/2022] [Revised: 03/04/2023] [Accepted: 03/08/2023] [Indexed: 03/17/2023]
Abstract
PURPOSE 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) parameters are prognostic of oncologic outcomes in human papillomavirus-associated oropharyngeal squamous cell carcinoma (OPSCC). We used FDG-PET imaging biomarkers to select patients for de-escalated chemoradiotherapy (CRT), hypothesizing that acute toxicity will be improved with de-escalation. METHODS AND MATERIALS This is a planned interim initial feasibility and acute toxicity report from a phase 2, prospective, nonrandomized study, which enrolled patients with stage I-II p16+ OPSCC. All patients started definitive CRT to 70 Gy in 35 fractions, and those who met de-escalation criteria on midtreatment FDG-PET at fraction 10 completed treatment at 54 Gy in 27 fractions. We report the acute toxicity and patient-reported outcomes for 59 patients with a minimum follow-up of 3 months. RESULTS There were no statistically significant differences between baseline patient characteristics in the standard and de-escalated cohorts. There were 28 of 59 (47.5%) patients who met FDG-PET de-escalation criteria and collectively received 20% to 30% less dose to critical organs at risk known to affect toxicity. At 3 months posttreatment, patients who received de-escalated CRT lost significantly less weight (median, 5.8% vs 13.0%; P < .001), had significantly less change from baseline in penetration-aspiration scale score (median, 0 vs 1; P = .018), and had significantly fewer aspiration events on repeat swallow study (8.0% vs 33.3%, P = .037) compared with patients receiving standard CRT. CONCLUSIONS Approximately half of patients with early-stage p16+ OPSCC are selected for de-escalation of definitive CRT using midtreatment FDG-PET biomarkers, which resulted in significantly improved rates of observed acute toxicity. Further follow-up is ongoing and will be required to determine whether this de-escalation approach preserves the favorable oncologic outcomes for patients with p16+ OPSCC before adoption.
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Affiliation(s)
- Steven G Allen
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Benjamin S Rosen
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Madhava Aryal
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Ka Kit Wong
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - Keith A Casper
- Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, Michigan
| | - Steven B Chinn
- Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, Michigan
| | - Kelly M Malloy
- Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, Michigan
| | - Mark E Prince
- Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, Michigan
| | - Andrew J Rosko
- Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, Michigan
| | - Andrew G Shuman
- Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, Michigan; Surgery Services-ENT Section, VA Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Matthew E Spector
- Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, Michigan
| | - Chaz L Stucken
- Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, Michigan
| | - Paul L Swiecicki
- Department of Internal Medicine, Division of Medical Oncology, University of Michigan, Ann Arbor, Michigan
| | - Francis P Worden
- Department of Internal Medicine, Division of Medical Oncology, University of Michigan, Ann Arbor, Michigan
| | - J Chad Brenner
- Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, Michigan
| | | | - David A Elliott
- Radiation Oncology Service, VA Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Michelle L Mierzwa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Jennifer L Shah
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Radiation Oncology Service, VA Ann Arbor Healthcare System, Ann Arbor, Michigan.
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9
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Peterson AB, Wang C, Wong KK, Frey KA, Muzik O, Schipper MJ, Dewaraja YK. 177Lu-DOTATATE Theranostics: Predicting Renal Dosimetry From Pretherapy 68Ga-DOTATATE PET and Clinical Biomarkers. Clin Nucl Med 2023; 48:393-399. [PMID: 37010563 PMCID: PMC10353839 DOI: 10.1097/rlu.0000000000004599] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
Abstract
PURPOSE Pretreatment predictions of absorbed doses can be especially valuable for patient selection and dosimetry-guided individualization of radiopharmaceutical therapy. Our goal was to build regression models using pretherapy 68Ga-DOTATATE PET uptake data and other baseline clinical factors/biomarkers to predict renal absorbed dose delivered by 177Lu-DOTATATE peptide receptor radionuclide therapy (177Lu-PRRT) for neuroendocrine tumors. We explore the combination of biomarkers and 68Ga PET uptake metrics, hypothesizing that they will improve predictive power over univariable regression. PATIENTS AND METHODS Pretherapy 68Ga-DOTATATE PET/CTs were analyzed for 25 patients (50 kidneys) who also underwent quantitative 177Lu SPECT/CT imaging at approximately 4, 24, 96, and 168 hours after cycle 1 of 177Lu-PRRT. Kidneys were contoured on the CT of the PET/CT and SPECT/CT using validated deep learning-based tools. Dosimetry was performed by coupling the multi-time point SPECT/CT images with an in-house Monte Carlo code. Pretherapy renal PET SUV metrics, activity concentration per injected activity (Bq/mL/MBq), and other baseline clinical factors/biomarkers were investigated as predictors of the 177Lu SPECT/CT-derived mean absorbed dose per injected activity to the kidneys using univariable and bivariable models. Leave-one-out cross-validation (LOOCV) was used to estimate model performance using root mean squared error and absolute percent error in predicted renal absorbed dose including mean absolute percent error (MAPE) and associated standard deviation (SD). RESULTS The median therapy-delivered renal dose was 0.5 Gy/GBq (range, 0.2-1.0 Gy/GBq). In LOOCV of univariable models, PET uptake (Bq/mL/MBq) performs best with MAPE of 18.0% (SD = 13.3%), and estimated glomerular filtration rate (eGFR) gives an MAPE of 28.5% (SD = 19.2%). Bivariable regression with both PET uptake and eGFR gives LOOCV MAPE of 17.3% (SD = 11.8%), indicating minimal improvement over univariable models. CONCLUSIONS Pretherapy 68Ga-DOTATATE PET renal uptake can be used to predict post-177Lu-PRRT SPECT-derived mean absorbed dose to the kidneys with accuracy within 18%, on average. Compared with PET uptake alone, including eGFR in the same model to account for patient-specific kinetics did not improve predictive power. Following further validation of these preliminary findings in an independent cohort, predictions using renal PET uptake can be used in the clinic for patient selection and individualization of treatment before initiating the first cycle of PRRT.
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Affiliation(s)
- Avery B. Peterson
- Department of Radiology, University of Michigan, Ann Arbor
- Department of Radiation Oncology, Wayne State University, Detroit
| | - Chang Wang
- Department of Biostatistics, University of Michigan, Ann Arbor
| | - Ka Kit Wong
- Department of Radiology, University of Michigan, Ann Arbor
| | - Kirk A. Frey
- Department of Radiology, University of Michigan, Ann Arbor
| | - Otto Muzik
- Department of Pediatrics, Wayne State University, Detroit, MI
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10
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Gharzai LA, Jiang R, Jaworski EM, Morales Rivera K, Dess RT, Jackson WC, Hartman HE, Mehra R, Kishan AU, Solanki AA, Schaeffer EM, Feng FY, Zaorsky NG, Berlin A, Ponsky L, Shoag J, Sun Y, Schipper MJ, Garcia J, Spratt DE. Meta-Analysis of Candidate Surrogate End Points in Advanced Prostate Cancer. NEJM Evid 2023; 2:EVIDoa2200195. [PMID: 38320030 DOI: 10.1056/evidoa2200195] [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] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
Meta-Analysis of Surrogate End Points in Prostate CancerGharzai et al. report on the results of a meta-analysis, which concludes that unlike the case in localized prostate cancer, surrogate end points in advanced prostate cancer may not track overall survival.
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Affiliation(s)
- Laila A Gharzai
- Department of Radiation Oncology, Northwestern University, Chicago
| | - Ralph Jiang
- Department of Biostatistics, University of Michigan, Ann Arbor
| | | | | | - Robert T Dess
- Department of Radiation Oncology, University of Michigan, Ann Arbor
| | | | - Holly E Hartman
- Department of Population and Quantitative Health Sciences, Case Western Reserve, Cleveland, OH
| | - Rohit Mehra
- Department of Pathology, University of Michigan, Ann Arbor
| | - Amar U Kishan
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles
| | - Abhishek A Solanki
- Department of Radiation Oncology, Stritch School of Medicine, Cardinal Bernardin Cancer Center, Loyola University Chicago, Maywood, IL
| | | | - Felix Y Feng
- Department of Radiation Oncology, University of California, San Francisco, San Francisco
| | - Nicholas G Zaorsky
- Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve, Cleveland, OH
| | - Alejandro Berlin
- Department of Radiation Oncology, University of Toronto; Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON
| | - Lee Ponsky
- Department of Urology, University Hospitals Cleveland Medical Center, Case Western Reserve, Cleveland, OH
| | - Jonathan Shoag
- Department of Urology, University Hospitals Cleveland Medical Center, Case Western Reserve, Cleveland, OH
| | - Yilun Sun
- Department of Population and Quantitative Health Sciences, Case Western Reserve, Cleveland, OH
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor
- Department of Radiation Oncology, University of Michigan, Ann Arbor
| | - Jorge Garcia
- Department of Medicine, University Hospitals Seidman Cancer Center, Case Western Reserve, Cleveland, OH
| | - Daniel E Spratt
- Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve, Cleveland, OH
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11
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Moss SD, Flicker JD, Munk DJ, Schipper MJ, Smithard J, Jung G, Hills Z, Hou J, Daniels JE, Finkel P. Magnetic prestressing for a d 32-mode single crystal ultrasonic transducer. J Acoust Soc Am 2023; 153:7. [PMID: 36732278 DOI: 10.1121/10.0016754] [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] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 11/14/2022] [Indexed: 06/18/2023]
Abstract
This work describes a 35.9 kHz ultrasonic transducer that incorporates a magnetic arrangement to apply a static-compressive prestress to a d32-mode relaxor ferroelectric single crystal drive-element. The magnetic arrangement produces a 22.5 N static-compressive force, inducing a static compression of ∼630 nm on the drive-element. Operating in air with a continuous-wave 10 V peak drive at ∼35.9 kHz, the measured resonant peak displacement of the transducers head-mass was 127 nm. This is well within the predicted static compression, thus, the drive-element is protected from damaging tensile stress. Under the same drive conditions and at an axial distance of 10 mm from the face of the head-mass, the measured acoustic pressure was ∼12 Pa. Analytical and finite element model predictions and the measured behaviour of a prototype device are presented and show good correlation, demonstrating that magnetic prestressing of the drive-element can be a viable alternative to the traditional bolt-clamp.
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Affiliation(s)
- Scott D Moss
- Platforms Division, Defence Science and Technology Group, Fishermans Bend, Victoria, 3207, Australia
| | - Jess D Flicker
- Platforms Division, Defence Science and Technology Group, Fishermans Bend, Victoria, 3207, Australia
| | - David J Munk
- Platforms Division, Defence Science and Technology Group, Fishermans Bend, Victoria, 3207, Australia
| | - Matthew J Schipper
- Platforms Division, Defence Science and Technology Group, Fishermans Bend, Victoria, 3207, Australia
| | - Joel Smithard
- Platforms Division, Defence Science and Technology Group, Fishermans Bend, Victoria, 3207, Australia
| | - George Jung
- Platforms Division, Defence Science and Technology Group, Fishermans Bend, Victoria, 3207, Australia
| | - Zane Hills
- Platforms Division, Defence Science and Technology Group, Fishermans Bend, Victoria, 3207, Australia
| | - Jianfu Hou
- Platforms Division, Defence Science and Technology Group, Fishermans Bend, Victoria, 3207, Australia
| | - John E Daniels
- School of Materials Science and Engineering, University of New South Wales, Sydney, New South Wales, 2052, Australia
| | - Peter Finkel
- United States Naval Research Laboratory, Washington, DC 20375, USA
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12
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Covert EC, Fitzpatrick K, Mikell J, Kaza RK, Millet JD, Barkmeier D, Gemmete J, Christensen J, Schipper MJ, Dewaraja YK. Intra- and inter-operator variability in MRI-based manual segmentation of HCC lesions and its impact on dosimetry. EJNMMI Phys 2022; 9:90. [PMID: 36542239 PMCID: PMC9772368 DOI: 10.1186/s40658-022-00515-6] [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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 12/02/2022] [Indexed: 12/24/2022] Open
Abstract
PURPOSE The aim was to quantify inter- and intra-observer variability in manually delineated hepatocellular carcinoma (HCC) lesion contours and the resulting impact on radioembolization (RE) dosimetry. METHODS Ten patients with HCC lesions treated with Y-90 RE and imaged with post-therapy Y-90 PET/CT were selected for retrospective analysis. Three radiologists contoured 20 lesions manually on baseline multiphase contrast-enhanced MRIs, and two of the radiologists re-contoured at two additional sessions. Contours were transferred to co-registered PET/CT-based Y-90 dose maps. Volume-dependent recovery coefficients were applied for partial volume correction (PVC) when reporting mean absorbed dose. To understand how uncertainty varies with tumor size, we fit power models regressing relative uncertainty in volume and in mean absorbed dose on contour volume. Finally, we determined effects of segmentation uncertainty on tumor control probability (TCP), as calculated using logistic models developed in a previous RE study. RESULTS The average lesion volume ranged from 1.8 to 194.5 mL, and the mean absorbed dose ranged from 23.4 to 1629.0 Gy. The mean inter-observer Dice coefficient for lesion contours was significantly less than the mean intra-observer Dice coefficient (0.79 vs. 0.85, p < 0.001). Uncertainty in segmented volume, as measured by the Coefficient of Variation (CV), ranged from 4.2 to 34.7% with an average of 17.2%. The CV in mean absorbed dose had an average value of 5.4% (range 1.2-13.1%) without PVC while it was 15.1% (range 1.5-55.2%) with PVC. Using the fitted models for uncertainty as a function of volume on our prior data, the mean change in TCP due to segmentation uncertainty alone was estimated as 16.2% (maximum 48.5%). CONCLUSIONS Though we find relatively high inter- and intra-observer reliability overall, uncertainty in tumor contouring propagates into non-negligible uncertainty in dose metrics and outcome prediction for individual cases that should be considered in dosimetry-guided treatment.
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Affiliation(s)
- Elise C Covert
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Kellen Fitzpatrick
- Department of Radiology, University of Michigan, 1301 Catherine, 2276 Medical Science I/5610, Ann Arbor, MI, 48109, USA
| | - Justin Mikell
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Ravi K Kaza
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - John D Millet
- Department of Radiology, University of Michigan, 1301 Catherine, 2276 Medical Science I/5610, Ann Arbor, MI, 48109, USA
| | - Daniel Barkmeier
- Department of Radiology, University of Michigan, 1301 Catherine, 2276 Medical Science I/5610, Ann Arbor, MI, 48109, USA
| | - Joseph Gemmete
- Department of Radiology, University of Michigan, 1301 Catherine, 2276 Medical Science I/5610, Ann Arbor, MI, 48109, USA
| | - Jared Christensen
- Department of Radiology, University of Michigan, 1301 Catherine, 2276 Medical Science I/5610, Ann Arbor, MI, 48109, USA
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.,Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Yuni K Dewaraja
- Department of Radiology, University of Michigan, 1301 Catherine, 2276 Medical Science I/5610, Ann Arbor, MI, 48109, USA.
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13
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Chase EC, Bryant AK, Sun Y, Jackson WC, Spratt DE, Dess RT, Schipper MJ. Development and validation of a life expectancy calculator for US patients with prostate cancer. BJU Int 2022; 130:496-506. [PMID: 35373440 PMCID: PMC9474626 DOI: 10.1111/bju.15740] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 03/24/2022] [Accepted: 04/01/2022] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To develop and validate an accurate, usable prediction model for other-cause mortality (OCM) in patients with prostate cancer diagnosed in the United States. MATERIALS AND METHODS Model training was performed using the National Health and Nutrition Examination Survey 1999-2010 including men aged >40 years with follow-up to the year 2014. The model was validated in the Prostate, Lung, Colon, and Ovarian Cancer Screening Trial prostate cancer cohort, which enrolled patients between 1993 and 2001 with follow-up to the year 2015. Time-dependent area under the curve (AUC) and calibration were assessed in the validation cohort. Analyses were performed to assess algorithmic bias. RESULTS The 2420 patient training cohort had 459 deaths over a median follow-up of 8.8 years among survivors. The final model included eight predictors: age; education; marital status; diabetes; hypertension; stroke; body mass index; and smoking. It had an AUC of 0.75 at 10 years for predicting OCM in the validation cohort of 8220 patients. The final model significantly outperformed the Social Security Administration life tables and showed adequate predictive performance across race, educational attainment, and marital status subgroups. There is evidence of major variability in life expectancy that is not captured by age, with life expectancy predictions differing by 10 or more years among patients of the same age. CONCLUSION Using two national cohorts, we have developed and validated a simple and useful prediction model for OCM for patients with prostate cancer treated in the United States, which will allow for more personalized treatment in accordance with guidelines.
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Affiliation(s)
| | - Alex K. Bryant
- Department of Radiation OncologyUniversity of MichiganAnn ArborMIUSA
| | - Yilun Sun
- Department of Radiation OncologyUniversity Hospitals/Case Western Reserve UniversityClevelandOHUSA
| | | | - Daniel E. Spratt
- Department of Radiation OncologyUniversity Hospitals/Case Western Reserve UniversityClevelandOHUSA
| | - Robert T. Dess
- Department of Radiation OncologyUniversity of MichiganAnn ArborMIUSA
| | - Matthew J. Schipper
- Department of BiostatisticsUniversity of MichiganAnn ArborMIUSA,Department of Radiation OncologyUniversity of MichiganAnn ArborMIUSA
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14
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Polan DF, Epelman MA, Wu VW, Sun Y, Varsta M, Owen DR, Jarema D, Matrosic CK, Jolly S, Schonewolf CA, Schipper MJ, Matuszak MM. Direct incorporation of patient-specific efficacy and toxicity estimates in radiation therapy plan optimization. Med Phys 2022; 49:6279-6292. [PMID: 35994026 PMCID: PMC9826508 DOI: 10.1002/mp.15940] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 07/25/2022] [Accepted: 08/01/2022] [Indexed: 01/11/2023] Open
Abstract
PURPOSE Current radiation therapy (RT) treatment planning relies mainly on pre-defined dose-based objectives and constraints to develop plans that aim to control disease while limiting damage to normal tissues during treatment. These objectives and constraints are generally population-based, in that they are developed from the aggregate response of a broad patient population to radiation. However, correlations of new biologic markers and patient-specific factors to treatment efficacy and toxicity provide the opportunity to further stratify patient populations and develop a more individualized approach to RT planning. We introduce a novel intensity-modulated radiation therapy (IMRT) optimization strategy that directly incorporates patient-specific dose response models into the planning process. In this strategy, we integrate the concept of utility-based planning where the optimization objective is to maximize the predicted value of overall treatment utility, defined by the probability of efficacy (e.g., local control) minus the weighted sum of toxicity probabilities. To demonstrate the feasibility of the approach, we apply the strategy to treatment planning for non-small cell lung cancer (NSCLC) patients. METHODS AND MATERIALS We developed a prioritized approach to patient-specific IMRT planning. Using a commercial treatment planning system (TPS), we calculate dose based on an influence matrix of beamlet-dose contributions to regions-of-interest. Then, outside of the TPS, we hierarchically solve two optimization problems to generate optimal beamlet weights that can then be imported back to the TPS. The first optimization problem maximizes a patient's overall plan utility subject to typical clinical dose constraints. In this process, we facilitate direct optimization of efficacy and toxicity trade-off based on individualized dose-response models. After optimal utility is determined, we solve a secondary optimization problem that minimizes a conventional dose-based objective subject to the same clinical dose constraints as the first stage but with the addition of a constraint to maintain the optimal utility from the first optimization solution. We tested this method by retrospectively generating plans for five previously treated NSCLC patients and comparing the prioritized utility plans to conventional plans optimized with only dose metric objectives. To define a plan utility function for each patient, we utilized previously published correlations of dose to local control and grade 3-5 toxicities that include patient age, stage, microRNA levels, and cytokine levels, among other clinical factors. RESULTS The proposed optimization approach successfully generated RT plans for five NSCLC patients that improve overall plan utility based on personalized efficacy and toxicity models while accounting for clinical dose constraints. Prioritized utility plans demonstrated the largest average improvement in local control (16.6%) when compared to plans generated with conventional planning objectives. However, for some patients, the utility-based plans resulted in similar local control estimates with decreased estimated toxicity. CONCLUSION The proposed optimization approach, where the maximization of a patient's RT plan utility is prioritized over the minimization of standardized dose metrics, has the potential to improve treatment outcomes by directly accounting for variability within a patient population. The implementation of the utility-based objective function offers an intuitive, humanized approach to biological optimization in which planning trade-offs are explicitly optimized.
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Affiliation(s)
- Daniel F Polan
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
| | - Marina A Epelman
- Department of Industrial and Operations EngineeringUniversity of MichiganAnn ArborMichiganUSA
| | - Victor W Wu
- Department of Industrial and Operations EngineeringUniversity of MichiganAnn ArborMichiganUSA
| | - Yilun Sun
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA,Department of BiostatisticsUniversity of MichiganAnn ArborMichiganUSA
| | | | - Daniel R Owen
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
| | - David Jarema
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
| | - Charles K Matrosic
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
| | - Shruti Jolly
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
| | | | - Matthew J Schipper
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA,Department of BiostatisticsUniversity of MichiganAnn ArborMichiganUSA
| | - Martha M Matuszak
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
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15
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Jackson WC, Tang M, Schipper MJ, Sandler HM, Zumsteg ZS, Efstathiou JA, Shipley WU, Seiferheld W, Lukka HR, Bahary JP, Zietman AL, Pisansky TM, Zeitzer KL, Hall WA, Dess RT, Lovett RD, Balogh AG, Feng FY, Spratt DE. Biochemical Failure Is Not a Surrogate End Point for Overall Survival in Recurrent Prostate Cancer: Analysis of NRG Oncology/RTOG 9601. J Clin Oncol 2022; 40:3172-3179. [PMID: 35737923 PMCID: PMC9514834 DOI: 10.1200/jco.21.02741] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [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: 12/01/2021] [Revised: 04/05/2022] [Accepted: 05/16/2022] [Indexed: 11/20/2022] Open
Abstract
PURPOSE Metastasis-free survival (MFS), but not event-free survival, is a validated surrogate end point for overall survival (OS) in men treated for localized prostate cancer. It remains unknown if this holds true in biochemically recurrent disease after radical prostatectomy. Leveraging NRG/RTOG 9601, we aimed to determine the performance of intermediate clinical end points (ICEs) as surrogate end points for OS in recurrent prostate cancer. MATERIALS AND METHODS NRG/RTOG 9601 randomly assigned 760 men with recurrence after prostatectomy to salvage radiation therapy with 2 years of placebo versus bicalutamide 150 mg daily. ICEs assessed were biochemical failure (BF) per NRG/RTOG 9601 (prostate-specific antigen nadir + 0.3-0.5 ng/mL or initiation of salvage hormone therapy; [BF1]) and NRG/RTOG 0534 (prostate-specific antigen nadir+2 ng/mL; [BF2]), distant metastasis (DM), and MFS (DM or death). Surrogacy was assessed by the Prentice criteria and a two-stage meta-analytic approach (condition one assessed at the patient level with Kendall's τ and condition two assessed by randomly dividing the entire trial cohort into 10 pseudo trial centers and calculating the average R2 between treatment hazard ratios for ICE and OS). RESULTS BF1, BF2, DM, and MFS satisfied the four Prentice criteria. However, with the two-condition meta-analytic approach, there was strong correlation between MFS and OS (τ = 0.86), moderate correlation between DM and OS (τ = 0.66), and weaker correlation between BF1 (τ = 0.25) or BF2 (τ = 0.40) and OS. Similarly, for condition two, the treatment effect of antiandrogen therapy on MFS and OS were correlated (R2 = 0.67), but this was not true for BF1 (R2 = 0.09), BF2 (R2 = 0.12), or DM (R2 = 0.18) and OS. CONCLUSION MFS is also a strong surrogate for OS in men receiving salvage radiation therapy for recurrence after prostatectomy. Caution should be used when inferring survival benefit from effects on BF in biochemically recurrent prostate cancer. Lack of comorbidity data did not allow us to assess whether BF in men with no/minimal comorbidity could serve as a surrogate for OS.
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Affiliation(s)
| | - Ming Tang
- University of Michigan, Ann Arbor, MI
| | | | | | | | - Jason A. Efstathiou
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - William U. Shipley
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | | | | | - Jean-Paul Bahary
- Centre Hospitalier de l'Universite de Montreal, Montreal, QC, Canada
| | - Anthony L. Zietman
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | | | | | - William A. Hall
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - Robert T. Dess
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | | | | | - Felix Y. Feng
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA
| | - Daniel E. Spratt
- Department of Radiation Oncology, University Hospitals, Cleveland, OH
- Department of Radiation Oncology, Case Western Reserve University School of Medicine, Cleveland, OH
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16
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Parikh ND, Mehta N, Hoteit MA, Yang JD, John BV, Moon AM, Salgia RJ, Pillai A, Kassab I, Saeed N, Thyssen E, Nathani P, McKinney J, Chan W, Durkin C, Connor M, Alsudaney M, Konjeti R, Durand B, Nissen NN, Kim HP, Paknikar R, Rich NE, Schipper MJ, Singal AG. Association between sustained virological response and clinical outcomes in patients with hepatitis C infection and hepatocellular carcinoma. Cancer 2022; 128:3470-3478. [PMID: 35796530 PMCID: PMC9545187 DOI: 10.1002/cncr.34378] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 02/05/2022] [Accepted: 03/09/2022] [Indexed: 11/16/2022]
Abstract
Background Sustained viral response (SVR) improves survival for patients with hepatitis C (HCV) and hepatocellular carcinoma (HCC) after curative treatment; however, the benefit of SVR in those with active HCC with a significant competing risk of mortality is unknown. This study aimed to evaluate the association between SVR and outcomes in patients with active HCC. Methods The authors performed a multicenter, retrospective cohort study including consecutive adults with HCV cirrhosis and treatment‐naive HCC diagnosed between 2014 and 2018. Patients were stratified into two groups: active viremia (n = 431) and SVR before HCC diagnosis (n = 135). All patients underwent nonsurgical therapy as their initial treatment and were followed until liver transplantation, last follow‐up, or death. The primary outcome was incident or worsening hepatic decompensation within 6 months and the secondary outcome was overall survival. All analyses used inverse probability of treatment weights (IPTW) to account for differences between the nonrandomized cohorts. Results Post‐SVR patients had significantly lower odds of hepatic decompensation compared to viremic patients (odds ratio [OR], 0.18; 95% confidence interval [CI], 0.06–0.59). Results were consistent among subgroups of patients with Child Pugh A cirrhosis (OR, 0.22; 95% CI, 0.04–0.77), Barcelona Clinic Liver Cancer stage B/C HCC (OR, 0.20; 95% CI, 0.04–0.65), and those receiving nonablative HCC therapies (OR, 0.21; 95% CI, 0.07–0.67). However, in IPTW multivariable Cox regression, SVR was not associated with improved survival (hazard ratio, 0.79; 95% CI, 0.56–1.12). Conclusions Patients with HCV‐related HCC and SVR are less likely to experience hepatic decompensation than viremic patients, suggesting patients with HCC who are undergoing nonsurgical therapies may benefit from DAA treatment. Hepatitis C virus‐related hepatocellular carcinoma remains prevalent in clinical practice, however, whether treatment of hepatitis C improves outcomes is unknown. The authors have shown an association between hepatitis C sustained virological response and decreased risk of hepatic decompensation in patients with hepatocellular carcinoma, across stages of disease and types of therapy received. See also pages 000–000.
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Affiliation(s)
- Neehar D Parikh
- Division of Gastroenterology and Hepatology, University of Michigan, Ann Arbor, Michigan, USA
| | - Neil Mehta
- Division of Gastroenterology, University of California, San Francisco, San Francisco, California, USA
| | - Maarouf A Hoteit
- Division of Gastroenterology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ju Dong Yang
- Division of Gastroenterology, Cedars Sinai, Los Angeles, California, USA
| | - Binu V John
- Division of Gastroenterology, University of Miami, Miami, Florida, USA.,Section of Hepatology, Miami VA Health System, Miami, Florida, USA
| | - Andrew M Moon
- Division of Gastroenterology and Hepatology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Reena J Salgia
- Division of Gastroenterology, Henry Ford Health System, Detroit, Michigan, USA
| | - Anjana Pillai
- Division of Gastroenterology, University of Chicago, Chicago, Illinois, USA
| | - Ihab Kassab
- Division of Gastroenterology and Hepatology, University of Michigan, Ann Arbor, Michigan, USA
| | - Naba Saeed
- Division of Gastroenterology and Hepatology, University of Michigan, Ann Arbor, Michigan, USA
| | - Emil Thyssen
- Division of Digestive and Liver Diseases, University of Texas Southwestern, Dallas, Texas, USA
| | - Piyush Nathani
- Division of Digestive and Liver Diseases, University of Texas Southwestern, Dallas, Texas, USA
| | - Jeffrey McKinney
- Division of Gastroenterology, University of California, San Francisco, San Francisco, California, USA
| | - Wesley Chan
- Division of Gastroenterology, University of California, San Francisco, San Francisco, California, USA
| | - Claire Durkin
- Division of Gastroenterology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Matthew Connor
- Division of Gastroenterology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Manaf Alsudaney
- Division of Gastroenterology, Cedars Sinai, Los Angeles, California, USA
| | - Rajesh Konjeti
- Division of Gastroenterology and Hepatology, University of Kentucky, Lexington, Kentucky, USA
| | - Brenda Durand
- Comprehensive Transplant Center, Cedars Sinai, Los Angeles, California, USA
| | - Nicholas N Nissen
- Comprehensive Transplant Center, Cedars Sinai, Los Angeles, California, USA
| | - Hannah P Kim
- Division of Gastroenterology and Hepatology, University of North Carolina, Chapel Hill, North Carolina, USA
| | | | - Nicole E Rich
- Division of Digestive and Liver Diseases, University of Texas Southwestern, Dallas, Texas, USA
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Amit G Singal
- Division of Digestive and Liver Diseases, University of Texas Southwestern, Dallas, Texas, USA
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17
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Wages NA, Braun TM, Normolle DP, Schipper MJ. Adaptive Phase 1 Design in Radiation Therapy Trials. Int J Radiat Oncol Biol Phys 2022; 113:493-499. [PMID: 35777394 DOI: 10.1016/j.ijrobp.2022.02.031] [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] [Received: 02/08/2022] [Accepted: 02/20/2022] [Indexed: 10/17/2022]
Affiliation(s)
- Nolan A Wages
- Division of Translational Research & Applied Statistics, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia.
| | - Thomas M Braun
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Daniel P Normolle
- Department of Biostatistics, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan; Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
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18
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Hinton T, Karnak D, Tang M, Jiang R, Luo Y, Boonstra P, Sun Y, Nancarrow DJ, Sandford E, Ray P, Maurino C, Matuszak M, Schipper MJ, Green MD, Yanik GA, Tewari M, Naqa IE, Schonewolf CA, Haken RT, Jolly S, Lawrence TS, Ray D. Improved prediction of radiation pneumonitis by combining biological and radiobiological parameters using a data-driven Bayesian network analysis. Transl Oncol 2022; 21:101428. [PMID: 35460942 PMCID: PMC9046881 DOI: 10.1016/j.tranon.2022.101428] [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] [Received: 02/24/2022] [Revised: 03/25/2022] [Accepted: 04/10/2022] [Indexed: 02/07/2023] Open
Abstract
Grade 2 and higher radiation pneumonitis (RP2) is a potentially fatal toxicity that limits efficacy of radiation therapy (RT). We wished to identify a combined biomarker signature of circulating miRNAs and cytokines which, along with radiobiological and clinical parameters, may better predict a targetable RP2 pathway. In a prospective clinical trial of response-adapted RT for patients (n = 39) with locally advanced non-small cell lung cancer, we analyzed patients' plasma, collected pre- and during RT, for microRNAs (miRNAs) and cytokines using array and multiplex enzyme linked immunosorbent assay (ELISA), respectively. Interactions between candidate biomarkers, radiobiological, and clinical parameters were analyzed using data-driven Bayesian network (DD-BN) analysis. We identified alterations in specific miRNAs (miR-532, -99b and -495, let-7c, -451 and -139-3p) correlating with lung toxicity. High levels of soluble tumor necrosis factor alpha receptor 1 (sTNFR1) were detected in a majority of lung cancer patients. However, among RP patients, within 2 weeks of RT initiation, we noted a trend of temporary decline in sTNFR1 (a physiological scavenger of TNFα) and ADAM17 (a shedding protease that cleaves both membrane-bound TNFα and TNFR1) levels. Cytokine signature identified activation of inflammatory pathway. Using DD-BN we combined miRNA and cytokine data along with generalized equivalent uniform dose (gEUD) to identify pathways with better accuracy of predicting RP2 as compared to either miRNA or cytokines alone. This signature suggests that activation of the TNFα-NFκB inflammatory pathway plays a key role in RP which could be specifically ameliorated by etanercept rather than current therapy of non-specific leukotoxic corticosteroids.
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Affiliation(s)
- Tonaye Hinton
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - David Karnak
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - Ming Tang
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA; Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Ralph Jiang
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yi Luo
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - Philip Boonstra
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yilun Sun
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA; Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Derek J Nancarrow
- Department of Surgery, Division of Hematology-Oncology, Department of Internal Medicine, Medical School, University of Michigan, Ann Arbor, MI, USA
| | - Erin Sandford
- Division of Hematology and Oncology, Department of Internal Medicine, Henry Ford Cancer Institute/Henry Ford Hospital, Detroit, MI, USA
| | - Paramita Ray
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - Christopher Maurino
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - Martha Matuszak
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - Matthew J Schipper
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA; Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Michael D Green
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - Gregory A Yanik
- Division of Hematology and Oncology, Department of Internal Medicine, Henry Ford Cancer Institute/Henry Ford Hospital, Detroit, MI, USA
| | - Muneesh Tewari
- Division of Hematology and Oncology, Department of Internal Medicine, Henry Ford Cancer Institute/Henry Ford Hospital, Detroit, MI, USA
| | - Issam El Naqa
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - Caitlin A Schonewolf
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - Randall Ten Haken
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - Shruti Jolly
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - Theodore S Lawrence
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA
| | - Dipankar Ray
- Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109-2026, USA.
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Gharzai LA, Jiang R, Jaworski E, Morales KA, Dess RT, Jackson WC, Hartman H, Mehra R, Kishan AU, Solanki AA, Schaeffer EM, Feng FY, Zaorsky NG, Berlin A, Ponsky LE, Shoag JE, Sun Y, Schipper MJ, Garcia JA, Spratt DE. Candidate surrogate endpoints in advanced prostate cancer: Aggregate meta-analysis of 143 randomized trials. J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.16_suppl.5039] [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
5039 Background: The Intermediate Clinical Endpoints (ICEs) in Cancer of the Prostate (ICECaP) working group identified metastasis-free survival as a valid surrogate endpoint for overall survival (OS) for patients with localized prostate cancer. No comparably validated surrogate endpoints for OS exist in advanced prostate cancer. Methods: In this meta-analysis, PubMed was searched for trials in advanced prostate cancer, defined as node positive (N1M0), metastatic castration-sensitive (mCSPC), non-metastatic (M0CRPC), or metastatic castration-resistant prostate cancer (mCRPC). Eligible randomized trials were required to report OS and ≥1 intermediate clinical endpoint (ICE). ICEs included biochemical-failure (BF), clinical failure (CF), BF-free survival (BFS), progression-free survival (PFS), radiographic PFS (radiographic +/- other study defined endpoints). Candidacy for surrogacy was assessed using the second condition of the meta-analytic approach, correlation of the treatment effect of the ICE and OS, using R2 weighted by the inverse variance of the log ICE hazard ratio and defined as an R2 > 0.70. Results: A total of 143 randomized trials (n = 75,601 patients) were included. No candidate endpoints met criteria for surrogacy; R2 BF (n = 28,922) 0.42 (95%CI 0.18-0.64), BFS (n = 25,741) 0.57 (95%CI 0.37-0.73), CF (n = 22,616) 0.31 (95%CI 0.0075-0.56), PFS (n = 52,639) 0.50 (95%CI 0.35-0.63), and radiographic PFS (n = 52,548) 0.50 (95%CI 0.35-0.63). Within preplanned subgroups by castration sensitive or resistant disease, or by treatment type, neither BFS nor PFS met criteria for surrogacy. When assessing radiographically-defined progression (exclusive or with clinical progression), PFS for the overall group and by castration status did not meet criteria for surrogacy. Sensitivity analyses demonstrated that candidacy for surrogacy of all endpoints tested did not change over time. Conclusions: Our aggregate screening method for surrogate endpoints in advanced prostate cancer demonstrated commonly used clinical endpoints are not valid surrogate endpoints for OS, and further composite endpoint construction is necessary.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Amar Upadhyaya Kishan
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA
| | | | | | - Felix Y Feng
- Department of Urology, University of California, San Francisco, CA
| | | | - Alejandro Berlin
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Lee Evan Ponsky
- University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, OH
| | | | - Yilun Sun
- University of Michigan, Ann Arbor, MI
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20
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Bryant AK, Yin H, Schipper MJ, Paximadis PA, Boike TP, Bergsma DP, Movsas B, Dess RT, Mietzel MA, Kendrick R, Seferi M, Dominello MM, Matuszak MM, Jagsi R, Hayman JA, Pierce LJ, Jolly S. Uptake of Adjuvant Durvalumab After Definitive Concurrent Chemoradiotherapy for Stage III Nonsmall-cell Lung Cancer. Am J Clin Oncol 2022; 45:142-145. [PMID: 35271524 DOI: 10.1097/coc.0000000000000899] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES The addition of adjuvant durvalumab improves overall survival in locally advanced nonsmall-cell lung cancer (NSCLC) patients treated with definitive chemoradiation, but the real-world uptake of adjuvant durvalumab is unknown. MATERIALS AND METHODS We identified patients with stage III NSCLC treated with definitive concurrent chemoradiation from January 2018 to October 2020 from a statewide radiation oncology quality consortium, representing a mix of community (n=22 centers) and academic (n=5) across the state of Michigan. Use of adjuvant durvalumab was ascertained at the time of routine 3-month or 6-month follow-up after completion of chemoradiation. RESULTS Of 421 patients with stage III NSCLC who completed chemoradiation, 322 (76.5%) initiated adjuvant durvalumab. The percentage of patients initiating adjuvant durvalumab increased over time from 66% early in the study period to 92% at the end of the study period. There was substantial heterogeneity by treatment center, ranging from 53% to 90%. In multivariable logistic regression, independent predictors of durvalumab initiation included more recent month (odds ratio [OR]: 1.05 per month, 95% confidence interval [CI]: 1.02-1.08, P=0.003), lower Eastern Cooperative Oncology Group score (OR: 4.02 for ECOG 0 vs. 2+, 95% CI: 1.67-9.64, P=0.002), and a trend toward significance for female sex (OR: 1.66, 95% CI: 0.98-2.82, P=0.06). CONCLUSION Adjuvant durvalumab for stage III NSCLC treated with definitive chemoradiation was rapidly and successfully incorporated into clinical care across a range of community and academic settings in the state of Michigan, with over 90% of potentially eligible patients starting durvalumab in more recent months.
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Affiliation(s)
- Alex K Bryant
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan
| | - Huiying Yin
- Department of Biostatistics, University of Michigan, Ann Arbor
| | - Matthew J Schipper
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan
- Department of Biostatistics, University of Michigan, Ann Arbor
| | | | | | - Derek P Bergsma
- Department of Radiation Oncology, Mercy Health Saint Mary's, Grand Rapids
| | - Benjamin Movsas
- Department of Radiation Oncology, Henry Ford Hospital, Detroit
| | - Robert T Dess
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan
| | - Melissa A Mietzel
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan
| | - Randi Kendrick
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan
| | - Merita Seferi
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan
| | - Michael M Dominello
- Department of Radiation Oncology, Barbara Ann Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI
| | - Martha M Matuszak
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan
| | - Reshma Jagsi
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan
| | - James A Hayman
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan
| | - Lori J Pierce
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan
| | - Shruti Jolly
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan
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21
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Owen DR, Sun Y, Irrer JC, Schipper MJ, Schonewolf CA, Galbán S, Jolly S, Haken RKT, Galbán C, Matuszak M. Investigating the Incidence of Pulmonary Abnormalities as Identified by Parametric Response Mapping in Lung Cancer Patients Prior to Radiation Treatment. Adv Radiat Oncol 2022; 7:100980. [PMID: 35693252 PMCID: PMC9184868 DOI: 10.1016/j.adro.2022.100980] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Accepted: 12/14/2021] [Indexed: 12/02/2022] Open
Abstract
Purpose Parametric response mapping (PRM) of high-resolution, paired inspiration and expiration computed tomography (CT) scans is a promising analytical imaging technique that is currently used in diagnostic applications and offers the ability to characterize and quantify certain pulmonary pathologies on a patient-specific basis. As one of the first studies to implement such a technique in the radiation oncology clinic, the goal of this work was to assess the feasibility for PRM analysis to identify pulmonary abnormalities in patients with lung cancer before radiation therapy (RT). Methods and Materials High-resolution, paired inspiration and expiration CT scans were acquired from 23 patients with lung cancer as part of routine treatment planning CT acquisition. When applied to the paired CT scans, PRM analysis classifies lung parenchyma, on a voxel-wise basis, as normal, small airways disease (SAD), emphysema, or parenchymal disease (PD). PRM classifications were quantified as a percent of total lung volume and were evaluated globally and regionally within the lung. Results PRM analysis of pre-RT CT scans was successfully implemented using a workflow that produced patient-specific maps and quantified specific phenotypes of pulmonary abnormalities. Through this study, a large prevalence of SAD and PD was demonstrated in this lung cancer patient population, with global averages of 10% and 17%, respectively. Moreover, PRM-classified normal and SAD in the region with primary tumor involvement were found to be significantly different from global lung values. When present, elevated levels of PD and SAD abnormalities tended to be pervasive in multiple regions of the lung, indicating a large burden of underlying disease. Conclusions Pulmonary abnormalities, as detected by PRM, were characterized in patients with lung cancer scheduled for RT. Although further study is needed, PRM is a highly accessible CT-based imaging technique that has the potential to identify local lung abnormalities associated with chronic obstructive pulmonary disease and interstitial lung disease. Further investigation in the radiation oncology setting may provide strategies for tailoring RT planning and risk assessment based on pre-existing PRM-based pathology.
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Affiliation(s)
- Daniel R. Owen
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
- Corresponding author: Daniel 'Rocky' Owen, PhD
| | - Yilun Sun
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
- Departments of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Jim C. Irrer
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | | | | | - Stefanie Galbán
- Departments of Radiology, University of Michigan, Ann Arbor, Michigan
| | - Shruti Jolly
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | | | - C.J. Galbán
- Departments of Radiology, University of Michigan, Ann Arbor, Michigan
| | - M.M. Matuszak
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
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22
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Li P, Taylor JMG, Boonstra PS, Lawrence TS, Schipper MJ. Utility based approach in individualized optimal dose selection using machine learning methods. Stat Med 2022; 41:2957-2977. [PMID: 35343595 PMCID: PMC9233043 DOI: 10.1002/sim.9396] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 02/07/2022] [Accepted: 03/11/2022] [Indexed: 11/23/2022]
Abstract
The goal in personalized medicine is to individualize treatment using patient characteristics and improve health outcomes. Selection of optimal dose must balance the effect of dose on both treatment efficacy and toxicity outcomes. We consider a setting with one binary efficacy and one binary toxicity outcome. The goal is to find the optimal dose for each patient using clinical features and biomarkers from available dataset. We propose to use flexible machine learning methods such as random forest and Gaussian process models to build models for efficacy and toxicity depending on dose and biomarkers. A copula is used to model the joint distribution of the two outcomes and the estimates are constrained to have non‐decreasing dose‐efficacy and dose‐toxicity relationships. Numerical utilities are elicited from clinicians for each potential bivariate outcome. For each patient, the optimal dose is chosen to maximize the posterior mean of the utility function. We also propose alternative approaches to optimal dose selection by adding additional toxicity based constraints and an approach taking into account the uncertainty in the estimation of the utility function. The proposed methods are evaluated in a simulation study to compare expected utility outcomes under various estimated optimal dose rules. Gaussian process models tended to have better performance than random forest. Enforcing monotonicity during modeling provided small benefits. Whether and how, correlation between efficacy and toxicity, was modeled, had little effect on performance. The proposed methods are illustrated with a study of patients with liver cancer treated with stereotactic body radiation therapy.
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Affiliation(s)
- Pin Li
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Jeremy M G Taylor
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.,Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Philip S Boonstra
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Theodore S Lawrence
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.,Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
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23
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Laucis AMB, Hochstedler KA, Schipper MJ, Paximadis PA, Boike TP, Bergsma DP, Movsas B, Kretzler A, Spratt DE, Dess RT, Mietzel MA, Dominello MM, Matuszak MM, Jagsi R, Hayman JA, Pierce LJ, Jolly S. Racial Differences in Treatments and Toxicity in Patients With Non-Small-Cell Lung Cancer Treated With Thoracic Radiation Therapy. JCO Oncol Pract 2022; 18:e1034-e1044. [PMID: 35167337 DOI: 10.1200/op.21.00224] [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 Historical racial disparities in lung cancer surgery rates resulted in lower survival in Black patients. Our objective was to examine racial differences in thoracic radiation treatments and toxicities in patients with non-small-cell lung cancer. METHODS AND MATERIALS A large institutional review board-approved statewide patient-level database of patients with stage II-III non-small-cell lung cancer who received definitive thoracic radiation from March 2012 to November 2019 was analyzed to assess associations between race and other variables. Race (White or Black) was defined by patient self-report. Provider-reported toxicity was defined by Common Terminology Criteria for Adverse Events version 4.0. Patient-reported toxicity was determined by the Functional Assessment of Cancer Therapy-Lung quality-of-life instrument. Univariable and multivariable regression models were fitted to assess relationships between race and variables of interest. Spearman rank-correlation coefficients were calculated between provider-reported toxicity and similar patient-reported outcomes. RESULTS One thousand four hundred forty-one patients from 24 institutions with mean age 68 years (range, 38-94 years) were evaluated. Race was not significantly associated with radiation or chemotherapy approach. There was significantly increased patient-reported general pain in Black patients at the preradiation and end-of-radiation time points. Black patients were significantly less likely to have provider-reported grade 2+ pneumonitis (odds ratio 0.36, P = .03), even after controlling for known patient and treatment factors. Correlation coefficients between provider- and patient-reported toxicities were generally similar across race groups except for a stronger correlation between patient- and provider-reported esophagitis in White patients. CONCLUSION In this large multi-institutional study, we found no evidence of racial differences in radiation treatment or chemotherapy approaches. We did, however, unexpectedly find that Black race was associated with lower odds of provider-reported grade 2+ radiation pneumonitis. The stronger correlation between patient- and provider-reported esophagitis and swallowing symptoms for White patients also suggests possible under-recognition of symptoms in Black patients. Further research is needed to study the implications for Black patients.
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Affiliation(s)
- Anna Mary Brown Laucis
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan, Ann Arbor, MI
| | | | - Matthew J Schipper
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan, Ann Arbor, MI.,Department of Biostatistics, University of Michigan, Ann Arbor, MI
| | | | | | - Derek P Bergsma
- Department of Radiation Oncology, Mercy Health Saint Mary's, Grand Rapids, MI
| | - Benjamin Movsas
- Department of Radiation Oncology, Henry Ford Hospital, Detroit, MI
| | - Annette Kretzler
- Department of Radiation Oncology, Henry Ford Allegiance, Jackson, MI
| | - Daniel E Spratt
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan, Ann Arbor, MI
| | - Robert T Dess
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan, Ann Arbor, MI
| | - Melissa A Mietzel
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan, Ann Arbor, MI
| | - Michael M Dominello
- Department of Radiation Oncology, Barbara Ann Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI
| | - Martha M Matuszak
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan, Ann Arbor, MI
| | - Reshma Jagsi
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan, Ann Arbor, MI
| | - James A Hayman
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan, Ann Arbor, MI
| | - Lori J Pierce
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan, Ann Arbor, MI
| | - Shruti Jolly
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan, Ann Arbor, MI
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24
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Speers C, Murthy VL, Walker EM, Glide-Hurst CK, Marsh R, Tang M, Morris EL, Schipper MJ, Weinberg RL, Gits HC, Hayman J, Feng M, Balter J, Moran J, Jagsi R, Pierce LJ. Cardiac Magnetic Resonance Imaging and Blood Biomarkers for Evaluation of Radiation-Induced Cardiotoxicity in Patients With Breast Cancer: Results of a Phase 2 Clinical Trial. Int J Radiat Oncol Biol Phys 2021; 112:417-425. [PMID: 34509552 DOI: 10.1016/j.ijrobp.2021.08.039] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 08/23/2021] [Accepted: 08/27/2021] [Indexed: 12/25/2022]
Abstract
PURPOSE Radiation therapy (RT) can increase the risk of cardiac events in patients with breast cancer (BC), but biomarkers predicting risk for developing RT-induced cardiac disease are currently lacking. We report results from a prospective clinical trial evaluating early magnetic resonance imaging (MRI) and serum biomarker changes as predictors of cardiac injury and risk of subsequent cardiac events after RT for left-sided disease. METHODS Women with node-negative and node-positive (N-/+) left-sided BC were enrolled on 2 institutional review board (IRB)-approved protocols at 2 institutions. MRI was conducted pretreatment (within 1 week of starting radiation), at the end of treatment (last day of treatment ±1 week), and 3 months after the last day of treatment (±2 weeks) to quantify left and right ventricular volumes and function, myocardial fibrosis, and edema. Perfusion changes during regadenoson stress perfusion were also assessed on a subset of patients (n = 28). Serum was collected at the same time points. Whole heart and cardiac substructures were contoured using CT and MRI. Models were constructed using baseline cardiac and clinical risk factors. Associations between MRI-measured changes and dose were evaluated. RESULTS Among 51 women enrolled, mean heart dose ranged from 0.80 to 4.7 Gy and mean left ventricular (LV) dose from 1.1 to 8.2 Gy, with mean heart dose 2.0 Gy. T1 time, a marker of fibrosis, and right ventricular (RV) ejection fraction (EF) significantly changed with treatment; these were not dose dependent. T2 (marker of edema) and LV EF did not significantly change. No risk factors were associated with baseline global perfusion. Prior receipt of doxorubicin was marginally associated with decreased myocardial perfusion after RT (P = .059), and mean MHD was not associated with perfusion changes. A significant correlation between baseline IL-6 and mean heart dose (MHD) at the end of RT (ρ 0.44, P = .007) and a strong trend between troponin I and MHD at 3 months post-treatment (ρ 0.33, P = .07) were observed. No other significant correlations were identified. CONCLUSIONS In this prospective study of women with left-sided breast cancer treated with contemporary treatment planning, cardiac radiation doses were very low relative to historical doses reported by Darby et al. Although we observed significant changes in T1 and RV EF shortly after RT, these changes were not correlated with whole heart or substructure doses. Serum biomarker analysis of cardiac injury demonstrates an interesting trend between markers and MHD that warrants further investigation.
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Affiliation(s)
- Corey Speers
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Comprehensive Cancer Center, University of Michigan, Ann Arbor, Michigan
| | - Venkatesh L Murthy
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan; Frankel Cardiovascular Center, University of Michigan, Ann Arbor, Michigan
| | - Eleanor M Walker
- Department of Radiation Oncology, Henry Ford Cancer Institute, Detroit, Michigan
| | - Carri K Glide-Hurst
- Department of Human Oncology, School of Medicine and Public Heath, University of Wisconsin-Madison, Madison, Wisconsin
| | - Robin Marsh
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Ming Tang
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Emily L Morris
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Richard L Weinberg
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan; Frankel Cardiovascular Center, University of Michigan, Ann Arbor, Michigan
| | - Hunter C Gits
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
| | - James Hayman
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Comprehensive Cancer Center, University of Michigan, Ann Arbor, Michigan
| | - Mary Feng
- Department of Radiation Oncology, University of California San Francisco, San Francisco, California
| | - James Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Jean Moran
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Reshma Jagsi
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Comprehensive Cancer Center, University of Michigan, Ann Arbor, Michigan
| | - Lori J Pierce
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Comprehensive Cancer Center, University of Michigan, Ann Arbor, Michigan.
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25
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Cousins MM, Devasia TP, Maurino CM, Mikell J, Schipper MJ, Kaza RK, Lawrence TS, Cuneo KC, Dewaraja YK. Pre-treatment sTNFR1 and HGF levels predict toxicity and overall survival after 90Y radioembolization: potential novel application of biomarkers for personalized management of hepatotoxicity. J Nucl Med 2021; 63:882-889. [PMID: 34503962 DOI: 10.2967/jnumed.121.262447] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 08/20/2021] [Indexed: 11/16/2022] Open
Abstract
Liver function may be negatively affected by radiation for treatment of hepatic malignancy. Pretreatment blood cytokine levels are biomarkers for prediction of toxicity and survival after external beam radiation therapy. We hypothesized that cytokines may also predict outcomes after radioembolization, enabling a biomarker-driven personalized approach to treatment. Methods: Pre-therapy blood samples from patients enrolled on a prospective protocol evaluating 90Y radioembolization for management of intrahepatic malignancy were analyzed for two cytokines selected based on prior studies in stereotactic body radiotherapy (SBRT), soluble tumor necrosis factor receptor 1 (sTNFR1) and hepatocyte growth factor (HGF), via enzyme-linked immunosorbent assay (ELISA), and key dosimetric parameters were derived from post-treatment 90Y PET/CT imaging. Toxicity was defined as a change in albumin-bilirubin score (ALBI) from baseline to follow up [3-6-month post-treatment (ΔALBI)]. Associations of cytokine levels, dose metrics, and baseline liver function with toxicity and overall survival were assessed. Results: Data from 43 patients treated with 90Y radioembolization for primary [48.8% (21/43)] or secondary [51.2% (22/43)] malignancy were assessed. Examined dose metrics and baseline liver function were not associated with liver toxicity; however, levels of sTNFR1 (P = 0.045) and HGF (P = 0.005) were associated with liver toxicity in univariate models. Cytokines were the only predictors of toxicity in multivariable models including dose metrics and prior liver directed therapy. sTNFR1 (HR 12.3; CI 3.5-42.5, p<0.001) and HGF (HR 7.5; CI 2.4-23.1, p<0.001) predicted overall survival, and findings were similar when models were controlled for absorbed dose and presence of metastatic disease. Conclusion: Pretreatment cytokine levels predict liver toxicity and overall survival. These pathways can be targeted with available drugs, an advantage over previously studied dose metrics and liver function tests. Interventions directed at the TNF alpha axis should be considered in future studies for prevention of liver toxicity, and HGF should be explored further to determine whether its elevation drives toxicity or indicates ongoing liver regeneration after prior injury.
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Affiliation(s)
- Matthew M Cousins
- Department of Radiation Oncology, University of Michigan, United States
| | - Theresa P Devasia
- Department of Radiation Oncology, University of Michigan, United States
| | | | - Justin Mikell
- Department of Radiation Oncology, University of Michigan, United States
| | | | - Ravi K Kaza
- Department of Radiology, University of Michigan
| | | | - Kyle C Cuneo
- Department of Radiation Oncology, University of Michigan, United States
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26
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Devasia TP, Dewaraja YK, Frey KA, Wong KK, Schipper MJ. A Novel Time-Activity Information-Sharing Approach Using Nonlinear Mixed Models for Patient-Specific Dosimetry with Reduced Imaging Time Points: Application in SPECT/CT After 177Lu-DOTATATE. J Nucl Med 2021; 62:1118-1125. [PMID: 33443063 DOI: 10.2967/jnumed.120.256255] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [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: 09/04/2020] [Accepted: 12/01/2020] [Indexed: 11/16/2022] Open
Abstract
Multiple-time-point SPECT/CT imaging for dosimetry is burdensome for patients and lacks statistical efficiency. A novel method for joint kidney time-activity estimation based on a statistical mixed model, a prior cohort of patients with complete time-activity data, and only 1 or 2 imaging points for new patients was compared with previously proposed single-time-point methods in virtual and clinical patient data. Methods: Data were available for 10 patients with neuroendocrine tumors treated with 177Lu-DOTATATE and imaged up to 4 times between days 0 and 7 using SPECT/CT. Mixed models using 1 or 2 time points were evaluated retrospectively in the clinical cohort, using the multiple-time-point fit as the reference. Time-activity data for 250 virtual patients were generated using parameter values from the clinical cohort. Mixed models were fit using 1 (∼96 h) and 2 (4 h, ∼96 h) time points for each virtual patient combined with complete data for the other patients in each dataset. Time-integrated activities (TIAs) calculated from mixed model fits and other reduced-time-point methods were compared with known values. Results: All mixed models and single-time-point methods performed well overall, achieving mean bias < 7% in the virtual cohort. Mixed models exhibited lower bias, greater precision, and substantially fewer outliers than did single-time-point methods. For clinical patients, 1- and 2-time-point mixed models resulted in more accurate TIA estimates for 94% (17/18) and 72% (13/18) of kidneys, respectively. In virtual patients, mixed models resulted in more than a 2-fold reduction in the proportion of kidneys with |bias| > 10% (6% vs. 15%). Conclusion: Mixed models based on a historical cohort of patients with complete time-activity data and new patients with only 1 or 2 SPECT/CT scans demonstrate less bias on average and significantly fewer outliers when estimating kidney TIA, compared with popular reduced-time-point methods. Use of mixed models allows for reduction of the imaging burden while maintaining accuracy, which is crucial for clinical implementation of dosimetry-based treatment.
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Affiliation(s)
- Theresa P Devasia
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan;
| | - Yuni K Dewaraja
- Department of Radiology, University of Michigan, Ann Arbor, Michigan; and
| | - Kirk A Frey
- Department of Radiology, University of Michigan, Ann Arbor, Michigan; and
| | - Ka Kit Wong
- Department of Radiology, University of Michigan, Ann Arbor, Michigan; and
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
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Cousins MM, Lawrence TS, Morris E, Schipper MJ, Cuneo KC. In Regard to Lo et al. Int J Radiat Oncol Biol Phys 2021; 110:1252. [PMID: 34171242 DOI: 10.1016/j.ijrobp.2021.04.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 04/02/2021] [Indexed: 01/28/2023]
Affiliation(s)
- Matthew M Cousins
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Theodore S Lawrence
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Emily Morris
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Kyle C Cuneo
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
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28
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Bridges AJ, Mehta RK, Shukla S, Schipper MJ, Lawrence TS, Nyati MK. Drug-development, dose-selection, rational combinations from bench-to-bedside: are there any lessons worth revisiting? Oncotarget 2021; 12:1032-1036. [PMID: 34084277 PMCID: PMC8169070 DOI: 10.18632/oncotarget.27931] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Indexed: 01/01/2023] Open
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29
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Bryant AK, Yin H, Schipper MJ, Paximadis PA, Boike TP, Bergsma DP, Movsas B, Ajlouni MI, Dess RT, Mietzel MA, Kendrick R, Seferi M, Dominello MM, Matuszak M, Jagsi R, Hayman J, Pierce LJ, Jolly S. Statewide rates of adjuvant checkpoint inhibitor use after definitive chemoradiation for stage III non-small cell lung cancer. J Clin Oncol 2021. [DOI: 10.1200/jco.2021.39.15_suppl.8523] [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
8523 Background: In the landmark PACIFIC trial, adjuvant durvalumab after definitive chemoradiation for unresectable stage III non-small-cell lung cancer (NSCLC) produced a 11% absolute overall survival benefit at two years compared to placebo, and the US Food and Drug Administration approved durvalumab for this indication in February 2018. We investigated the real-world use of adjuvant durvalumab and other immune checkpoint inhibitors (ICI) in a contemporary cohort of patients. Methods: We identified patients with unresectable stage III (AJCC 8th edition) NSCLC treated with definitive chemoradiation from February 2018 to March 2020 from a statewide radiation oncology quality consortium, representing a mix of community (n=22 centers, 336 patients) and academic practice settings (n=5 centers, 64 patients) across the state of Michigan. Use of adjuvant durvalumab or other ICI (atezolizumab, nivolumab, or pembrolizumab) was ascertained at the time of routine three- or six-month follow-up after completion of chemoradiation. Baseline characteristics of patients treated with or without adjuvant ICI were compared with the Chi-squared test for categorical variables and a two-sided t-test for continuous variables. Results: Of 400 patients with unresectable stage III NSCLC treated with definitive chemoradiation, 268 (67%) received adjuvant ICI. Of these, the majority received durvalumab (86%) followed by pembrolizumab (7.5%) and nivolumab (6.0%). The proportion of patients receiving ICI remained stable throughout the study period with no discernable time trends. Eight-five percent of white patients received ICI compared with 77% of black patients (p=0.04), but there were no differences in gender (54.5% male in ICI vs 52.3% no ICI), current smoking (42.2% ICI vs 37.9% no ICI, p=0.68), number of comorbidities (29.5% with 3 or more comorbidities in ICI vs. 26.5% in no ICI, p=0.86), baseline oxygen use (8.9% ICI vs 10.6% no ICI, p=0.59), age (median 66.4 years [IQR 60.3-73.4] for ICI vs. 66.9 years [IQR 61.1-72.2] no ICI, p=0.89), treatment at an academic center (16.0% ICI vs 15.9% no ICI, p=0.97), or ECOG performance status (59.3% ECOG 0 in ICI vs 62.8% no ICI). Conclusions: In a broad range of academic and community-based practices across a state including 27 sites, only two-thirds of potentially eligible stage III NSCLC patients received adjuvant durvalumab or other ICI agents despite a proven overall survival benefit. Receipt of ICI was not strongly associated with baseline demographic or comorbidity variables. Further work will seek to clarify the patient-level reasons behind non-initiation of adjuvant ICI.
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Affiliation(s)
- Alex K. Bryant
- Department of Radiation Oncology, Rogel Cancer Center, University of Michigan, Ann Arbor, MI
| | | | | | | | | | | | | | | | | | - Melissa A. Mietzel
- Department of Radiation Oncology, Rogel Comprehensive Cancer Center at the University of Michigan, Ann Arbor, MI
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30
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Laucis AMB, Hochstedler KA, Boike TP, Movsas B, Stevens CW, Kestin LL, Dominello MM, Wilkie J, Grills IS, Matuszak M, Hayman J, Paximadis PA, Schipper MJ, Jolly S. Predictors of early hospice or death in patients with inoperable lung cancer treated with curative intent. J Clin Oncol 2021. [DOI: 10.1200/jco.2021.39.15_suppl.e20525] [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
e20525 Background: Treatment for inoperable stage II-III non-small cell lung cancer (NSCLC) involves aggressive chemo-radiotherapy (CRT). While outcomes have improved with immunotherapy, some patients transition to hospice or die early in their treatment course. To help identify these patients, we developed a predictive model for early poor outcomes in NSCLC patients treated with curative intent. Methods: In a statewide consortium involving 27 sites, information was collected prospectively on stage II-III NSCLC patients who received curative CRT from April 2012 to November 2019. We defined an early poor outcome as termination of treatment due to hospice enrollment or death within 5 months of initiating radiation therapy. Potential predictors included clinical characteristics and patient reported outcomes (PROs) from validated questionnaires. Logistic regression models were used to assess potential predictors and build predictive models. Multiple imputation was used to handle missing data. We used Lasso regularized logistic regression to build a predictive model with multiple predictor variables. Results: Of the total of 2267 included patients, 128 patients discontinued treatment early due to hospice enrollment or death. The mean age of the 128 patients was 71 years old (range 48-91) and 59% received concurrent chemotherapy. Significant uni-variable predictors of early hospice or death were advanced age, worse ECOG performance status, high PTV volume, short distance to normal tissue critical structures, high mean heart dose, uninsured status, lower scores on the Functional and Physical Well-Being scale and the Lung Cancer Symptoms sub-scale of the FACT-L quality of life instrument, as well as higher levels of patient-reported lack of energy, cough, and shortness of breath. The best predictive model included age, ECOG performance status, PTV volume, mean heart dose, patient insurance status, and patient-reported lack of energy and cough. The pooled estimate of area under the curve (AUC) for this multivariable model was 0.71, with a negative predictive value of 95%, specificity of 97%, positive predictive value of 23%, and sensitivity of 16% at a predicted risk threshold of 20%. Conclusions: Our models identified a combination of clinical variables and PROs that may help identify individuals with inoperable NSCLC undergoing curative intent chemo-radiotherapy who are at a high risk of early hospice enrollment or death. These preliminary results are encouraging and warrant further evaluation in a larger cohort of patients.
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Gharzai LA, Burger N, Li P, Jaworski EM, Henderson C, Spector M, Rosko A, Chen MM, Prince ME, Bradford CR, Malloy KM, Stucken CL, Swiecicki P, Worden F, Schipper MJ, Schonewolf CA, Shah J, Jagsi R, Chinn S, Shuman A, Casper K, Mierzwa ML. Patient Burden with Current Surveillance Paradigm and Factors Associated with Interest in Altered Surveillance for Early Stage HPV-Related Oropharyngeal Cancer. Oncologist 2021; 26:676-684. [PMID: 33823077 DOI: 10.1002/onco.13784] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 03/26/2021] [Indexed: 11/06/2022] Open
Abstract
INTRODUCTION Optimal surveillance paradigms for survivors of early stage human papillomavirus (HPV)-related oropharyngeal cancer are not well defined. This study aimed to characterize patient interest in and factors associated with an altered surveillance paradigm. MATERIALS AND METHODS We surveyed patients with Stage I or II HPV-related oropharyngeal cancer treated at a tertiary care institution from 2016 to 2019. Primary outcomes were descriptive assessment of patient knowledge, interest in altered surveillance, burdens of in-person appointments, and priorities for surveillance visits. Ordinal regression was used to identify correlates of interest in altered surveillance. RESULTS Sixty-seven patients completed surveys from February to April 2020 at a median of 21 months since completing definitive treatment. A majority (61%) of patients were interested in a surveillance approach that decreased in-person clinic visits. Patients who self-identified as medical maximizers, had higher worry of cancer recurrence, or were in long-term relationships were less likely to be interested. Patients reported significant burdens associated with surveillance visits, including driving distance, time off work, and nonmedical costs. Patients were most concerned with discussing cancer recurrence (76%), physical quality of life (70%), mortality (61%), and mental quality of life (52%) with their providers at follow-up visits. CONCLUSION Patients with early stage HPV-related oropharyngeal cancers are interested in altered surveillance approaches, experience significant burdens related to surveillance visits, and have concerns that are not well addressed with current surveillance approaches, including physical and mental quality of life. Optimized surveillance approaches should incorporate patient priorities and minimize associated burdens. IMPLICATIONS FOR PRACTICE The number of patients with HPV-related oropharyngeal cancers is increasing, and numerous clinical trials are investigating novel approaches to treating these good-prognosis patients. There has been limited work assessing optimal surveillance paradigms in these patients. Patients experience significant appointment-related burdens and have concerns such as physical and mental quality of life. Additionally, patients with early stage HPV-related oropharyngeal cancers express interest in altered surveillance approaches that decrease in-person clinic visits. Optimization of surveillance paradigms to promote broader survivorship care in clinical practice is needed.
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Affiliation(s)
- Laila A Gharzai
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.,Center for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Nicholas Burger
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Pin Li
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Elizabeth M Jaworski
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Caitlin Henderson
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew Spector
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Andy Rosko
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Michelle M Chen
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Mark E Prince
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Carol R Bradford
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Kelly M Malloy
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Chaz L Stucken
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Paul Swiecicki
- Department of Medical Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Francis Worden
- Department of Medical Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Caitlin A Schonewolf
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Jennifer Shah
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Reshma Jagsi
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.,Center for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Steve Chinn
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Andrew Shuman
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Keith Casper
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Michelle L Mierzwa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
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Schipper MJ, Yuan Y, Taylor JM, Ten Haken RK, Tsien C, Lawrence TS. A Bayesian dose-finding design for outcomes evaluated with uncertainty. Clin Trials 2021; 18:279-285. [PMID: 33884907 DOI: 10.1177/17407745211001521] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
INTRODUCTION In some phase I trial settings, there is uncertainty in assessing whether a given patient meets the criteria for dose-limiting toxicity. METHODS We present a design which accommodates dose-limiting toxicity outcomes that are assessed with uncertainty for some patients. Our approach could be utilized in many available phase I trial designs, but we focus on the continual reassessment method due to its popularity. We assume that for some patients, instead of the usual binary dose-limiting toxicity outcome, we observe a physician-assessed probability of dose-limiting toxicity specific to a given patient. Data augmentation is used to estimate the posterior probabilities of dose-limiting toxicity at each dose level based on both the fully observed and partially observed patient outcomes. A simulation study is used to assess the performance of the design relative to using the continual reassessment method on the true dose-limiting toxicity outcomes (available in simulation setting only) and relative to simple thresholding approaches. RESULTS Among the designs utilizing the partially observed outcomes, our proposed design has the best overall performance in terms of probability of selecting correct maximum tolerated dose and number of patients treated at the maximum tolerated dose. CONCLUSION Incorporating uncertainty in dose-limiting toxicity assessment can improve the performance of the continual reassessment method design.
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Affiliation(s)
- Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.,Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Ying Yuan
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jeremy Mg Taylor
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.,Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Randall K Ten Haken
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Christina Tsien
- Department of Radiation Oncology, Johns Hopkins Medicine, Baltimore, MD, USA
| | - Theodore S Lawrence
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
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Jackson WC, Hartman HE, Gharzai LA, Maurino C, Karnak DM, Mendiratta-Lala M, Parikh ND, Mayo CS, Haken RKT, Schipper MJ, Cuneo KC, Lawrence TS. The Potential for Midtreatment Albumin-Bilirubin (ALBI) Score to Individualize Liver Stereotactic Body Radiation Therapy. Int J Radiat Oncol Biol Phys 2021; 111:127-134. [PMID: 33878421 DOI: 10.1016/j.ijrobp.2021.04.012] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 03/29/2021] [Accepted: 04/11/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE Our individualized functional response adaptive approach to liver stereotactic body radiation therapy (SBRT) with assessment of indocyanine green (ICG) retention at baseline and midtreatment to detect subclinical changes in liver function, permitting dose adjustment, has decreased toxicity while preserving efficacy. We hypothesized that assessment of the albumin-bilirubin (ALBI) score at baseline and midtreatment would allow for more practical identification of patients at risk for treatment-related toxicity (TRT). METHODS AND MATERIALS Patients with hepatocellular carcinoma were treated on 3 prospective institutional review board-approved trials using baseline and midtreatment ICG to deliver individualized functional response adaptive liver SBRT. Patients received 3 or 5 fractions, with fraction 3 followed by a 1-month treatment break. TRT was a ≥2-point rise in Child-Pugh score within 6 months of SBRT. Logistic regression was used to estimate odds ratios (ORs) and confidence intervals (CIs) for assessment of TRT. Area under the receiver operating curve was used to compare predictive ability across models. RESULTS In total, 151 patients underwent 166 treatments. Baseline Child-Pugh class and ALBI grade were A (66.9%), B (31.3%), or C (1.8%) and 1 (25.9%), 2 (65.7%), or 3 (8.4%), respectively. Thirty-five patients (20.3%) experienced TRT. On univariate analysis, baseline ALBI (OR, 1.8; 95% CI, 1.24-2.62; P = .02), baseline ICG (OR, 1.66; 95% CI, 1.17-2.35; P = .04), and change in ALBI (OR, 3.07; 95% CI, 1.29-7.32; P = .003) were associated with increased odds of TRT. ALBI-centric models performed similarly to ICG-centric models on multivariate analyses predicting toxicity (area under the receiver operating curve of 0.79 for both). In a model incorporating baseline and midtreatment change in ALBI and ICG, both ALBI values were statistically significantly associated with toxicity, whereas ICG values were not. CONCLUSIONS Incorporation of midtreatment change in ALBI in addition to baseline ALBI improves the ability to predict TRT in patients with hepatocellular carcinoma receiving SBRT. Our findings suggest that functional response adaptive treatment could be implemented in a practical manner because the ALBI score is easily obtained from standard laboratory values.
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Affiliation(s)
| | | | | | | | | | | | - Neehar D Parikh
- Gastroenterology, University of Michigan Ann Arbor, Michigan
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Li P, Taylor JMG, Spratt DE, Karnes RJ, Schipper MJ. Evaluation of predictive model performance of an existing model in the presence of missing data. Stat Med 2021; 40:3477-3498. [PMID: 33843085 DOI: 10.1002/sim.8978] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2020] [Revised: 02/13/2021] [Accepted: 03/24/2021] [Indexed: 11/11/2022]
Abstract
In medical research, the Brier score (BS) and the area under the receiver operating characteristic (ROC) curves (AUC) are two common metrics used to evaluate prediction models of a binary outcome, such as using biomarkers to predict the risk of developing a disease in the future. The assessment of an existing prediction models using data with missing covariate values is challenging. In this article, we propose inverse probability weighted (IPW) and augmented inverse probability weighted (AIPW) estimates of AUC and BS to handle the missing data. An alternative approach uses multiple imputation (MI), which requires a model for the distribution of the missing variable. We evaluated the performance of IPW and AIPW in comparison with MI in simulation studies under missing completely at random, missing at random, and missing not at random scenarios. When there are missing observations in the data, MI and IPW can be used to obtain unbiased estimates of BS and AUC if the imputation model for the missing variable or the model for the missingness is correctly specified. MI is more efficient than IPW. Our simulation results suggest that AIPW can be more efficient than IPW, and also achieves double robustness from miss-specification of either the missingness model or the imputation model. The outcome variable should be included in the model for the missing variable under all scenarios, while it only needs to be included in missingness model if the missingness depends on the outcome. We illustrate these methods using an example from prostate cancer.
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Affiliation(s)
- Pin Li
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Jeremy M G Taylor
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.,Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Daniel E Spratt
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.,Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
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Gharzai LA, Jiang R, Wallington D, Jones G, Birer S, Jairath N, Jaworski EM, McFarlane MR, Mahal BA, Nguyen PL, Sandler H, Morgan TM, Reichert ZR, Alumkal JJ, Mehra R, Kishan AU, Fizazi K, Halabi S, Schaeffer EM, Feng FY, Elliott D, Dess RT, Jackson WC, Schipper MJ, Spratt DE. Intermediate clinical endpoints for surrogacy in localised prostate cancer: an aggregate meta-analysis. Lancet Oncol 2021; 22:402-410. [PMID: 33662287 PMCID: PMC10949134 DOI: 10.1016/s1470-2045(20)30730-0] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [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: 08/14/2020] [Revised: 10/23/2020] [Accepted: 11/26/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND The international Intermediate Clinical Endpoints in Cancer of the Prostate working group has established metastasis-free survival as a surrogate for overall survival in localised prostate cancer based on the findings of 19 predominantly radiotherapy-based trials. We sought to comprehensively assess aggregate trial-level performance of commonly reported intermediate clinical endpoints across all randomised trials in localised prostate cancer. METHODS For this meta-analysis, we searched PubMed for all trials in localised or biochemically recurrent prostate cancer published between Jan 1, 1970, and Jan 15, 2020. Eligible trials had to be randomised, therapeutic, reporting overall survival and at least one intermediate clinical endpoint, and with a sample size of at least 70 participants. Trials of metastatic disease were excluded. Intermediate clinical endpoints included biochemical failure, local failure, distant metastases, biochemical failure-free survival, progression-free survival, and metastasis-free survival. Candidacy for surrogacy was assessed using the second condition of the meta-analytical approach (ie, correlation of the treatment effect of the intermediate clinical endpoint and overall survival), using R2 weighted by the inverse variance of the log intermediate clinical endpoint hazard ratio. The intermediate clinical endpoint was deemed to be a surrogate for overall survival if R2 was 0·7 or greater. FINDINGS 75 trials (53 631 patients) were included in our analysis. Median follow-up was 9·1 years (IQR 5·7-10·6). Biochemical failure (R2 0·38 [95% CI 0·11-0·64]), biochemical failure-free survival (R2 0·12 [0·0030-0·33]), biochemical failure and clinical failure (R2 0·28 [0·0045-0·65]), and local failure (R2 0·085 [0·00-0·37]) correlated poorly with overall survival. Progression-free survival (R2 0·46 [95% CI 0·22-0·67]) showed moderate correlation with overall survival, and metastasis-free survival (R2 0·78 [0·59-0·89]) correlated strongly. INTERPRETATION Intermediate clinical endpoints based on biochemical and local failure did not meet the second condition of the meta-analytical approach and are not surrogate endpoints for overall survival in localised prostate cancer. Our findings validate metastasis-free survival as the only identified surrogate endpoint for overall survival to date. FUNDING Prostate Cancer Foundation and National Institutes of Health.
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Affiliation(s)
- Laila A Gharzai
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Ralph Jiang
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - David Wallington
- Department of Radiation Oncology, Western Michigan University, Kalamazoo, MI, USA
| | - Gavin Jones
- Department of Radiation Oncology, University of Kentucky, Lexington, KY, USA
| | - Samuel Birer
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Neil Jairath
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | | | - Matthew R McFarlane
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Brandon A Mahal
- Department of Radiation Oncology, University of Miami, Miami, FL, USA
| | - Paul L Nguyen
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Howard Sandler
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Todd M Morgan
- Department of Urology, University of Michigan, Ann Arbor, MI, USA
| | - Zachery R Reichert
- Department of Medical Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Joshi J Alumkal
- Department of Medical Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Rohit Mehra
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Amar U Kishan
- Department of Radiation Oncology, University of California Los Angeles, Los Angeles, CA, USA
| | - Karim Fizazi
- Department of Cancer Medicine, Institut Gustave-Roussy, Villejuif, France
| | - Susan Halabi
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | | | - Felix Y Feng
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, USA
| | - David Elliott
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Robert T Dess
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - William C Jackson
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Daniel E Spratt
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
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Dess RT, Suresh K, Zelefsky MJ, Freedland SJ, Mahal BA, Cooperberg MR, Davis BJ, Horwitz EM, Terris MK, Amling CL, Aronson WJ, Kane CJ, Jackson WC, Hearn JWD, Deville C, DeWeese TL, Greco S, McNutt TR, Song DY, Sun Y, Mehra R, Kaffenberger SD, Morgan TM, Nguyen PL, Feng FY, Sharma V, Tran PT, Stish BJ, Pisansky TM, Zaorsky NG, Moraes FY, Berlin A, Finelli A, Fossati N, Gandaglia G, Briganti A, Carroll PR, Karnes RJ, Kattan MW, Schipper MJ, Spratt DE. Development and Validation of a Clinical Prognostic Stage Group System for Nonmetastatic Prostate Cancer Using Disease-Specific Mortality Results From the International Staging Collaboration for Cancer of the Prostate. JAMA Oncol 2021; 6:1912-1920. [PMID: 33090219 DOI: 10.1001/jamaoncol.2020.4922] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Importance In 2016, the American Joint Committee on Cancer (AJCC) established criteria to evaluate prediction models for staging. No localized prostate cancer models were endorsed by the Precision Medicine Core committee, and 8th edition staging was based on expert consensus. Objective To develop and validate a pretreatment clinical prognostic stage group system for nonmetastatic prostate cancer. Design, Setting, and Participants This multinational cohort study included 7 centers from the United States, Canada, and Europe, the Shared Equal Access Regional Cancer Hospital (SEARCH) Veterans Affairs Medical Centers collaborative (5 centers), and the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) registry (43 centers) (the STAR-CAP cohort). Patients with cT1-4N0-1M0 prostate adenocarcinoma treated from January 1, 1992, to December 31, 2013 (follow-up completed December 31, 2017). The STAR-CAP cohort was randomly divided into training and validation data sets; statisticians were blinded to the validation data until the model was locked. A Surveillance, Epidemiology, and End Results (SEER) cohort was used as a second validation set. Analysis was performed from January 1, 2018, to November 30, 2019. Exposures Curative intent radical prostatectomy (RP) or radiotherapy with or without androgen deprivation therapy. Main Outcomes and Measures Prostate cancer-specific mortality (PCSM). Based on a competing-risk regression model, a points-based Score staging system was developed. Model discrimination (C index), calibration, and overall performance were assessed in the validation cohorts. Results Of 19 684 patients included in the analysis (median age, 64.0 [interquartile range (IQR), 59.0-70.0] years), 12 421 were treated with RP and 7263 with radiotherapy. Median follow-up was 71.8 (IQR, 34.3-124.3) months; 4078 (20.7%) were followed up for at least 10 years. Age, T category, N category, Gleason grade, pretreatment serum prostate-specific antigen level, and the percentage of positive core biopsy results among biopsies performed were included as variables. In the validation set, predicted 10-year PCSM for the 9 Score groups ranged from 0.3% to 40.0%. The 10-year C index (0.796; 95% CI, 0.760-0.828) exceeded that of the AJCC 8th edition (0.757; 95% CI, 0.719-0.792), which was improved across age, race, and treatment modality and within the SEER validation cohort. The Score system performed similarly to individualized random survival forest and interaction models and outperformed National Comprehensive Cancer Network (NCCN) and Cancer of the Prostate Risk Assessment (CAPRA) risk grouping 3- and 4-tier classification systems (10-year C index for NCCN 3-tier, 0.729; for NCCN 4-tier, 0.746; for Score, 0.794) as well as CAPRA (10-year C index for CAPRA, 0.760; for Score, 0.782). Conclusions and Relevance Using a large, diverse international cohort treated with standard curative treatment options, a proposed AJCC-compliant clinical prognostic stage group system for prostate cancer has been developed. This system may allow consistency of reporting and interpretation of results and clinical trial design.
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Affiliation(s)
- Robert T Dess
- Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor
| | | | - Michael J Zelefsky
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Stephen J Freedland
- Division of Urology, Department of Surgery, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California.,Durham VA Medical Center, Durham, North Carolina
| | - Brandon A Mahal
- Harvard Radiation Oncology Program, Massachusetts General Hospital, Boston
| | - Matthew R Cooperberg
- Department of Urology, University of California, San Francisco, Helen Diller Family Comprehensive Cancer Center
| | - Brian J Davis
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
| | - Eric M Horwitz
- Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, Pennsylvania
| | - Martha K Terris
- Section of Urology, Medical College of Georgia, Augusta, Georgia
| | - Christopher L Amling
- Division of Urology, Department of Surgery, Oregon Health and Science University, Portland
| | - William J Aronson
- Department of Urology, University of California, Los Angeles, School of Medicine
| | - Christopher J Kane
- Department of Urology, University of California, San Diego, Health System
| | - William C Jackson
- Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor
| | - Jason W D Hearn
- Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor
| | - Curtiland Deville
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland
| | - Theodore L DeWeese
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland
| | - Stephen Greco
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland
| | - Todd R McNutt
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland
| | - Daniel Y Song
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland
| | - Yilun Sun
- Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor.,Department of Biostatistics, University of Michigan, Ann Arbor
| | - Rohit Mehra
- Department of Pathology, University of Michigan, Ann Arbor
| | | | - Todd M Morgan
- Department of Urology, University of Michigan, Ann Arbor
| | - Paul L Nguyen
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Felix Y Feng
- Department of Urology, University of California, San Francisco, Helen Diller Family Comprehensive Cancer Center.,Department of Radiation Oncology, University of California, San Francisco.,Department of Medicine, University of California, San Francisco
| | - Vidit Sharma
- Department of Urology, Mayo Clinic, Rochester, Minnesota
| | - Phuoc T Tran
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland
| | - Bradley J Stish
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
| | | | - Nicholas G Zaorsky
- Department of Radiation Oncology, Penn State Cancer Institute, Hershey, Pennsylvania
| | - Fabio Ynoe Moraes
- Department of Oncology, Queen's University, Kingston, Ontario, Canada
| | - Alejandro Berlin
- Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Antonio Finelli
- Department of Surgical Oncology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,Division of Urology, University of Toronto, Toronto, Ontario, Canada
| | - Nicola Fossati
- Department of Urology, Scientific Institute and University Vita-Salute San Raffaele Hospital, Milan, Italy
| | - Giorgio Gandaglia
- Department of Urology, Scientific Institute and University Vita-Salute San Raffaele Hospital, Milan, Italy
| | - Alberto Briganti
- Department of Urology, Scientific Institute and University Vita-Salute San Raffaele Hospital, Milan, Italy
| | - Peter R Carroll
- Department of Urology, University of California, San Francisco, Helen Diller Family Comprehensive Cancer Center
| | | | - Michael W Kattan
- Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, Ohio
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor.,Department of Biostatistics, University of Michigan, Ann Arbor
| | - Daniel E Spratt
- Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor
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Owen DR, Sun Y, Boonstra PS, McFarlane M, Viglianti BL, Balter JM, El Naqa I, Schipper MJ, Schonewolf CA, Ten Haken RK, Kong FMS, Jolly S, Matuszak MM. Investigating the SPECT Dose-Function Metrics Associated With Radiation-Induced Lung Toxicity Risk in Patients With Non-small Cell Lung Cancer Undergoing Radiation Therapy. Adv Radiat Oncol 2021; 6:100666. [PMID: 33817412 PMCID: PMC8010578 DOI: 10.1016/j.adro.2021.100666] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 01/22/2021] [Indexed: 12/14/2022] Open
Abstract
Purpose Dose to normal lung has commonly been linked with radiation-induced lung toxicity (RILT) risk, but incorporating functional lung metrics in treatment planning may help further optimize dose delivery and reduce RILT incidence. The purpose of this study was to investigate the impact of the dose delivered to functional lung regions by analyzing perfusion (Q), ventilation (V), and combined V/Q single-photon-emission computed tomography (SPECT) dose-function metrics with regard to RILT risk in patients with non-small cell lung cancer (NSCLC) patients who received radiation therapy (RT). Methods and Materials SPECT images acquired from 88 patients with locally advanced NSCLC before undergoing conventionally fractionated RT were retrospectively analyzed. Dose was converted to the nominal dose equivalent per 2 Gy fraction, and SPECT intensities were normalized. Regional lung segments were defined, and the average dose delivered to each lung region was quantified. Three functional categorizations were defined to represent low-, normal-, and high-functioning lungs. The percent of functional lung category receiving ≥20 Gy and mean functional intensity receiving ≥20 Gy (iV20) were calculated. RILT was defined as grade 2+ radiation pneumonitis and/or clinical radiation fibrosis. A logistic regression was used to evaluate the association between dose-function metrics and risk of RILT. Results By analyzing V/Q normalized intensities and functional distributions across the population, a wide range in functional capability (especially in the ipsilateral lung) was observed in patients with NSCLC before RT. Through multivariable regression models, global lung average dose to the lower lung was found to be significantly associated with RILT, and Q and V iV20 were correlated with RILT when using ipsilateral lung metrics. Through a receiver operating characteristic analysis, combined V/Q low-function receiving ≥20 Gy (low-functioning V/Q20) in the ipsilateral lung was found to be the best predictor (area under the curce: 0.79) of RILT risk. Conclusions Irradiation of the inferior lung appears to be a locational sensitivity for RILT risk. The multivariable correlation between ipsilateral lung iV20 and RILT, as well as the association of low-functioning V/Q20 and RILT, suggest that irradiating low-functioning regions in the lung may lead to higher toxicity rates.
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Affiliation(s)
- Daniel R Owen
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Yilun Sun
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.,Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Philip S Boonstra
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Matthew McFarlane
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Benjamin L Viglianti
- Department of Radiology, University of Michigan, Ann Arbor, Michigan.,Veterans Administration, Nuclear Medicine Service, Ann Arbor Michigan
| | - James M Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Issam El Naqa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | | | - Randall K Ten Haken
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Feng-Ming S Kong
- Hong Kong University Shenzhen Hospital and Queen Mary Hospital, Hong Kong University Li Ka Shing Medical School, Department of Clinical Oncology, Hong Kong.,Department of Radiation Oncology, Case Western Reserve University, Cleveland, Ohio
| | - Shruti Jolly
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Martha M Matuszak
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
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Mierzwa ML, Gharzai LA, Li P, Wilkie JR, Hawkins PG, Aryal MP, Lee C, Rosen B, Lyden T, Blakely A, Chapman CH, Thamarus J, Schonewolf C, Shah J, Eisbruch A, Schipper MJ, Cao Y. Early MRI Blood Volume Changes in Constrictor Muscles Correlate With Postradiation Dysphagia. Int J Radiat Oncol Biol Phys 2020; 110:566-573. [PMID: 33346093 DOI: 10.1016/j.ijrobp.2020.12.018] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 12/01/2020] [Accepted: 12/13/2020] [Indexed: 12/01/2022]
Abstract
PURPOSE Predicting individual patient sensitivity to radiation therapy (RT) for tumor control or normal tissue toxicity is necessary to individualize treatment planning. In head and neck cancer, radiation doses are limited by many nearby critical structures, including structures involved in swallowing. Previous efforts showed that imaging parameters correlate with RT dose; here, we investigate the role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) blood volume (BV) changes in predicting dysphagia. METHODS AND MATERIALS This study included 32 patients with locally advanced oropharyngeal squamous cell carcinoma treated with definitive chemoradiation on an institutional protocol incorporating baseline and early midtreatment DCE-MRI. BV maps of the pharyngeal constrictor muscles (PCM) were created, and BV increases midtreatment were correlated with the following parameters at 3 and 12 months post-RT: RT dose, Dynamic Imaging Grade of Swallowing Toxicity swallow score, aspiration frequency, European Organisation for Research and Treatment of Cancer HN35 patient-reported outcomes, physician-reported dysphagia, and feeding tube (FT) dependence. RESULTS The mean BV to the PCMs increased from baseline to fraction 10, which was significant for the superior PCM (P = .006) and middle PCM (P < .001), with a trend in the inferior PCM where lower mean doses were seen (P = .077). The factors associated with FT dependence at 3 months included BV increases in the total PCM (correlation, 0.48; P = .006) and middle PCM (correlation, 0.50; P = .004). A post-RT increase in aspiration was associated with a BV increase in the superior PCM (correlation, 0.44; P = .013),and the increase in the total PCMs was marginally significant (correlation, 0.34; P = .06). The best-performing models of FT dependence (area under the receiver operating curve [AUC] = 0.84) and aspiration increases (AUC = 0.78) included BV increases as well as a mean RT dose to middle PCM. CONCLUSIONS Our results suggest that midtreatment BV increases derived from DCE-MRI are an early predictor of dysphagia. Further investigation of these promising imaging markers to assess individual patient sensitivity to treatment and the patient's subsequent risk of toxicities is warranted to improve personalization of RT planning.
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Affiliation(s)
- Michelle L Mierzwa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
| | - Laila A Gharzai
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Pin Li
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Joel R Wilkie
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | | | - Madhava P Aryal
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Choonik Lee
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Benjamin Rosen
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Teresa Lyden
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan
| | - Anna Blakely
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan
| | - Christina H Chapman
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Jennifer Thamarus
- Department of Speech and Language Pathology, Veterans Affairs Hospital, Ann Arbor, Michigan
| | - Caitlin Schonewolf
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Jennifer Shah
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Avraham Eisbruch
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Radiology, University of Michigan, Ann Arbor, Michigan; Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
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39
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Cousins MM, Morris E, Maurino C, Devasia TP, Karnak D, Ray D, Parikh ND, Owen D, Ten Haken RK, Schipper MJ, Lawrence TS, Cuneo KC. TNFR1 and the TNFα axis as a targetable mediator of liver injury from stereotactic body radiation therapy. Transl Oncol 2020; 14:100950. [PMID: 33395747 PMCID: PMC7744766 DOI: 10.1016/j.tranon.2020.100950] [Citation(s) in RCA: 4] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 10/30/2020] [Accepted: 11/05/2020] [Indexed: 02/08/2023] Open
Abstract
Elevated soluble TNFR1 levels are predictive of liver toxicity among patients receiving radiation. Soluble TNFR1 levels do not independently predict liver toxicity when included in models with ALBI and mean liver dose. Data suggest that liver inflammation mediates toxicity after liver irradiation and that the TNFα axis is associated with this inflammation. Future studies of should evaluate approaches that target pre-treatment inflammation to reduce the risk of toxicity.
Introduction Radiation therapy for the management of intrahepatic malignancies can adversely affect liver function. Liver damage has been associated with increased levels of inflammatory cytokines, including tumor necrosis factor alpha (TNFα). We hypothesized that an inflammatory state, characterized by increased soluble TNFα receptor (sTNFR1), mediates sensitivity of the liver to radiation. Materials/Methods Plasma samples collected during 3 trials of liver radiation for liver malignancies were assayed for sTNFR1 level via enzyme-linked immunosorbent assay (ELISA). Univariate and multivariate logistic regression and longitudinal models were used to characterize associations between liver toxicity (defined as a ≥2-point increase in Child-Pugh [CP] score within 6 months of radiation treatment) and sTNFR1 levels, ALBI score, biocorrected mean liver dose (MLD), age, and baseline laboratory values. Results Samples from 78 patients given liver stereotactic body radiation therapy [SBRT] (92%) or hypofractionated radiation were examined. There was a significant association between liver toxicity and sTNFR1 levels, and higher values were associated with increased toxicity over a range of mean liver doses. When ALBI score and biocorrected dose were included in the model with sTNFR1, baseline ALBI score and change in ALBI (ΔALBI) were significantly associated with toxicity, but sTNFR1 was not. Baseline aminotransferase levels also predicted toxicity but not independently of ALBI score. Conclusions Elevated plasma sTNFR1 levels are associated with liver injury after liver radiation, suggesting that elevated inflammatory cytokine activity is a predictor of radiation-induced liver dysfunction. Future studies should determine whether administration of agents that decrease inflammation prior to treatment is warranted.
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Affiliation(s)
- Matthew M Cousins
- Department of Radiation Oncology, University of Michigan, UH B2C490, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5010, USA
| | - Emily Morris
- Department of Radiation Oncology, University of Michigan, UH B2C490, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5010, USA
| | - Christopher Maurino
- Department of Radiation Oncology, University of Michigan, UH B2C490, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5010, USA
| | - Theresa P Devasia
- Department of Radiation Oncology, University of Michigan, UH B2C490, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5010, USA
| | - David Karnak
- Department of Radiation Oncology, University of Michigan, UH B2C490, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5010, USA
| | - Dipankar Ray
- Department of Radiation Oncology, University of Michigan, UH B2C490, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5010, USA
| | - Neehar D Parikh
- Department of Internal Medicine, University of Michigan, 3110 Taubman Center, SPC 5368, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5368, USA
| | - Dawn Owen
- Department of Radiation Oncology, University of Michigan, UH B2C490, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5010, USA
| | - Randall K Ten Haken
- Department of Radiation Oncology, University of Michigan, UH B2C490, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5010, USA
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan, UH B2C490, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5010, USA
| | - Theodore S Lawrence
- Department of Radiation Oncology, University of Michigan, UH B2C490, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5010, USA
| | - Kyle C Cuneo
- Department of Radiation Oncology, University of Michigan, UH B2C490, 1500 E Medical Center Dr, Ann Arbor, MI 48109-5010, USA.
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Hartman HE, Sun Y, Devasia TP, Chase EC, Jairath NK, Dess RT, Jackson WC, Morris E, Li P, Hochstedler KA, Abbott MR, Kidwell KM, Walter V, Wang M, Wang X, Zaorsky NG, Schipper MJ, Spratt DE. Integrated Survival Estimates for Cancer Treatment Delay Among Adults With Cancer During the COVID-19 Pandemic. JAMA Oncol 2020; 6:1881-1889. [PMID: 33119036 PMCID: PMC7596687 DOI: 10.1001/jamaoncol.2020.5403] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [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: 05/20/2020] [Accepted: 08/04/2020] [Indexed: 12/18/2022]
Abstract
Importance Cancer treatment delay has been reported to variably impact cancer-specific survival and coronavirus disease 2019 (COVID-19)-specific mortality during the severe acute respiratory syndrome coronavirus 2 pandemic. During the pandemic, treatment delay is being recommended in a nonquantitative, nonobjective, and nonpersonalized manner, and this approach may be associated with suboptimal outcomes. Quantitative integration of cancer mortality estimates and data on the consequences of treatment delay is needed to aid treatment decisions and improve patient outcomes. Objective To obtain quantitative integration of cancer-specific and COVID-19-specific mortality estimates that can be used to make optimal decisions for individual patients and optimize resource allocation. Design, Setting, and Participants In this decision analytical model, age-specific and stage-specific estimates of overall survival pre-COVID-19 were adjusted by the probability of COVID-19 (individualized by county, treatment-specific variables, hospital exposure frequency, and COVID-19 infectivity estimates), COVID-19 mortality (individualized by age-specific, comorbidity-specific, and treatment-specific variables), and delay of cancer treatment (impact and duration). These model estimates were integrated into a web application (OncCOVID) to calculate estimates of the cumulative overall survival and restricted mean survival time of patients who received immediate vs delayed cancer treatment. Using currently available information about COVID-19, a susceptible-infected-recovered model that accounted for the increased risk among patients at health care treatment centers was developed. This model integrated the data on cancer mortality and the consequences of treatment delay to aid treatment decisions. Age-specific and cancer stage-specific estimates of overall survival pre-COVID-19 were extracted from the Surveillance, Epidemiology, and End Results database for 691 854 individuals with 25 cancer types who received cancer diagnoses in 2005 to 2006. Data from 5 436 896 individuals in the National Cancer Database were used to estimate the independent impact of treatment delay by cancer type and stage. In addition, data from 275 patients in a nested case-control study were used to estimate the COVID-19 mortality rate by age group and number of comorbidities. Data were analyzed from March 17 to May 21, 2020. Exposures COVID-19 and cancer. Main Outcomes and Measures Estimates of restricted mean survival time after the receipt of immediate vs delayed cancer treatment. Results At the time of the study, the OncCOVID web application allowed for the selection of up to 47 individualized variables to assess net survival for an individual patient with cancer. Substantial heterogeneity was found regarding the association between delayed cancer treatment and net survival among patients with a given cancer type and stage, and these 2 variables were insufficient to discriminate the net impact of immediate vs delayed treatment. Individualized overall survival estimates were associated with patient age, number of comorbidities, treatment received, and specific local community estimates of COVID-19 risk. Conclusions and Relevance This decision analytical modeling study found that the OncCOVID web-based application can quantitatively aid in the resource allocation of individualized treatment for patients with cancer during the COVID-19 global pandemic.
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Affiliation(s)
| | - Yilun Sun
- Department of Biostatistics, University of Michigan, Ann Arbor
- Department of Radiation Oncology, University of Michigan, Ann Arbor
| | | | | | - Neil K. Jairath
- Department of Radiation Oncology, University of Michigan, Ann Arbor
| | - Robert T. Dess
- Department of Radiation Oncology, University of Michigan, Ann Arbor
| | | | - Emily Morris
- Department of Biostatistics, University of Michigan, Ann Arbor
| | - Pin Li
- Department of Biostatistics, University of Michigan, Ann Arbor
| | | | | | | | - Vonn Walter
- Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Penn State University College of Medicine, Hershey, Pennsylvania
| | - Ming Wang
- Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Penn State University College of Medicine, Hershey, Pennsylvania
| | - Xi Wang
- Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Penn State University College of Medicine, Hershey, Pennsylvania
| | - Nicholas G. Zaorsky
- Department of Radiation Oncology, Penn State Cancer Institute, Hershey, Pennsylvania
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania
| | - Matthew J. Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor
- Department of Radiation Oncology, University of Michigan, Ann Arbor
| | - Daniel E. Spratt
- Department of Radiation Oncology, University of Michigan, Ann Arbor
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Mendiratta-Lala M, Masch W, Owen D, Aslam A, Maurino C, Devasia T, Schipper MJ, Parikh ND, Cuneo K, Lawrence TS, Davenport MS. Natural history of hepatocellular carcinoma after stereotactic body radiation therapy. Abdom Radiol (NY) 2020; 45:3698-3708. [PMID: 32303772 DOI: 10.1007/s00261-020-02532-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
PURPOSE To determine the long-term natural history of size change in SBRT-treated HCC to identify an imaging biomarker to help assess treatment response. METHODS This was a retrospective cohort study of consecutive HCCs treated with SBRT from January 2008 to December 2016 with either 2 years post-treatment MRI follow-up or post-treatment resection histology. Size, major features for HCC, and mRECIST and LI-RADS v.2018 treatment response criteria were assessed at each post-treatment MRI. Local progression, distant progression, and survival were modeled with Kaplan Meier analyses. RESULTS 56 HCCs met inclusion criteria. Mean baseline HCC diameter was 30 mm (range: 9-105 mm). At 3 months, 76% (N = 43) of treated HCCs decreased in size (mean reduction: 8 mm, range: 5-99 mm) and 0% (N = 0) increased in size. By 24 months, 11% (N = 5) had increased in size and were considered local progression. APHE remained in 77% (43/56) at 3 months, 38% (19/50) at 12 months, and 23% (11/47) at 24 months. mRECIST-defined viable disease was observed in 77% (43/56) at 3 months and 20% (9/47) at 24 months. LI-RADS v.2018 criteria identified viable or equivocal disease in 0% at 3 months and 10% (5/47) at 24 months. CONCLUSION Gradual loss of APHE and slow decrease in size are normal findings in HCCs treated with SBRT, and persistent APHE does not indicate viable disease. mRECIST is not accurate in the assessment of HCC after SBRT due to an overreliance on APHE to define viable disease. Increasing mass size or new nodular APHE at the treatment site may indicate local progression.
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Hartman H, Tamura RN, Schipper MJ, Kidwell KM. Design and analysis considerations for utilizing a mapping function in a small sample, sequential, multiple assignment, randomized trials with continuous outcomes. Stat Med 2020; 40:312-326. [PMID: 33111381 DOI: 10.1002/sim.8776] [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] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 08/11/2020] [Accepted: 09/29/2020] [Indexed: 12/19/2022]
Abstract
Small sample, sequential, multiple assignment, randomized trials (snSMARTs) are multistage trials with the overall goal of determining the best treatment after a fixed amount of time. In snSMART trials, patients are first randomized to one of three treatments and a binary (e.g. response/nonresponse) outcome is measured at the end of the first stage. Responders to first stage treatment continue their treatment. Nonresponders to first stage treatment are rerandomized to one of the remaining treatments. The same binary outcome is measured at the end of the first and second stages, and data from both stages are pooled together to find the best first stage treatment. However, in many settings the primary endpoint may be continuous, and dichotomizing this continuous variable may reduce statistical efficiency. In this article, we extend the snSMART design and methods to allow for continuous outcomes. Instead of requiring a binary outcome at the first stage for rerandomization, the probability of staying on the same treatment or switching treatment is a function of the first stage outcome. Rerandomization based on a mapping function of a continuous outcome allows for snSMART designs without requiring a binary outcome. We perform simulation studies to compare the proposed design with continuous outcomes to standard snSMART designs with binary outcomes. The proposed design results in more efficient treatment effect estimates and similar outcomes for trial patients.
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Affiliation(s)
- Holly Hartman
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Roy N Tamura
- Health Informatics Institute, University of South Florida, Tampa, Florida, USA
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.,Department of Radiation Oncology, University of Michigan
| | - Kelley M Kidwell
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
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Mehta RK, Pal S, Kondapi K, Sitto M, Dewar C, Devasia T, Schipper MJ, Thomas DG, Basrur V, Pai MP, Morishima Y, Osawa Y, Pratt WB, Lawrence TS, Nyati MK. Low-Dose Hsp90 Inhibitor Selectively Radiosensitizes HNSCC and Pancreatic Xenografts. Clin Cancer Res 2020; 26:5246-5257. [PMID: 32718999 PMCID: PMC7541797 DOI: 10.1158/1078-0432.ccr-19-3102] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 04/21/2020] [Accepted: 07/21/2020] [Indexed: 11/16/2022]
Abstract
PURPOSE Treatment approaches using Hsp90 inhibitors at their maximum tolerated doses (MTDs) have not produced selective tumor toxicity. Inhibition of Hsp90 activity causes degradation of client proteins including those involved in recognizing and repairing DNA lesions. We hypothesized that if DNA repair proteins were degraded by concentrations of an Hsp90 inhibitor below those required to cause nonspecific cytotoxicity, significant tumor-selective radiosensitization might be achieved. EXPERIMENTAL DESIGN Tandem mass tagged-mass spectrometry was performed to determine the effect of a subcytotoxic concentration of the Hsp90 inhibitor, AT13387 (onalespib), on global protein abundance. The effect of AT13387 on in vitro radiosensitization was assessed using a clonogenic assay. Pharmacokinetics profiling was performed in mice bearing xenografts. Finally, the effect of low-dose AT13387 on the radiosensitization of three tumor models was assessed. RESULTS A subcytotoxic concentration of AT13387 reduced levels of DNA repair proteins, without affecting the majority of Hsp90 clients. The pharmacokinetics study using one-third of the MTD showed 40-fold higher levels of AT13387 in tumors compared with plasma. This low dose enhanced Hsp70 expression in peripheral blood mononuclear cells (PBMCs), which is a biomarker of Hsp90 inhibition. Low dose monotherapy was ineffective, but when combined with radiotherapy, produced significant tumor growth inhibition. CONCLUSIONS This study shows that a significant therapeutic ratio can be achieved by a low dose of Hsp90 inhibitor in combination with radiotherapy. Hsp90 inhibition, even at a low dose, can be monitored by measuring Hsp70 expression in PBMCs in human studies.
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Affiliation(s)
- Ranjit K Mehta
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Sanjima Pal
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Koushik Kondapi
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Merna Sitto
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Cuyler Dewar
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Theresa Devasia
- School of Public Health, University of Michigan, Ann Arbor, Michigan
| | | | - Dafydd G Thomas
- Department of Pathology, University of Michigan, Ann Arbor, Michigan
| | - Venkatesha Basrur
- Department of Pathology, University of Michigan, Ann Arbor, Michigan
| | - Manjunath P Pai
- Department of Clinical Pharmacy, University of Michigan, Ann Arbor, Michigan
| | | | - Yoichi Osawa
- Department of Pharmacology, University of Michigan, Ann Arbor, Michigan
| | - William B Pratt
- Department of Pharmacology, University of Michigan, Ann Arbor, Michigan
| | - Theodore S Lawrence
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Mukesh K Nyati
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
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Jackson WC, Tang M, Maurino C, Mendiratta-Lala M, Parikh ND, Matuszak MM, Dow JS, Cao Y, Mayo CS, Ten Haken RK, Schipper MJ, Cuneo KC, Owen D, Lawrence TS. Individualized Adaptive Radiation Therapy Allows for Safe Treatment of Hepatocellular Carcinoma in Patients With Child-Turcotte-Pugh B Liver Disease. Int J Radiat Oncol Biol Phys 2020; 109:212-219. [PMID: 32853708 DOI: 10.1016/j.ijrobp.2020.08.046] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 08/03/2020] [Accepted: 08/14/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE Previous reports of stereotactic body radiation therapy (SBRT) for hepatocellular carcinoma (HCC) suggest unacceptably high rates of toxicity in patients with Child-Turcotte-Pugh (CTP) B liver disease. We hypothesized that an individualized adaptive treatment approach based on midtreatment liver function would maintain good local control while limiting toxicity in this population. METHODS AND MATERIALS Patients with CTP-B liver disease and HCC were treated on prospective trials of individualized adaptive SBRT between 2006 and 2018. Patients underwent pre- and midtreatment liver function assessments using indocyanine green. Treatment-related toxicity was defined as a ≥2-point increase in CTP score from pretreatment within 6 months of treatment. In addition, we performed analyses with a longitudinal model to assess changes in CTP score over 12 months after SBRT. RESULTS Eighty patients with CTP-B (median tumor size, 2.5 cm) were treated: 37 patients were CTP-B-7, 28 were CTP-B-8, and 15 were CTP-B-9. The median treatment dose was 36 Gy in 3 fractions. One-year local control was 92%. In a multivariate model controlling for tumor size, treatment dose, and baseline CTP score, higher treatment dose was associated with improved freedom from local progression (hazard ratio: 0.97; 95% confidence interval, 0.94-1.00; P = .04). Eighteen patients (24%) had a ≥2-point increase in CTP score within 6 months of SBRT. In a longitudinal model assessing changes in CTP score over 12 months after SBRT, controlling for baseline CTP and tumor size, increasing mean liver dose was associated with larger increases in CTP score (P = .04). CONCLUSIONS An individualized adaptive treatment approach allows for acceptable toxicity and effective local control in patients with HCC and CTP-B liver disease. Because increasing dose may increase both local control and toxicity, further work is needed to optimize treatment in patients with compromised liver function.
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Affiliation(s)
- William C Jackson
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan.
| | - Ming Tang
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan
| | - Christopher Maurino
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan
| | | | - Neehar D Parikh
- University of Michigan Department of Gastroenterology, Ann Arbor, Michigan
| | - Martha M Matuszak
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan
| | - Janell S Dow
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan
| | - Yue Cao
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan
| | - Charles S Mayo
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan
| | - Randall K Ten Haken
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan
| | - Matthew J Schipper
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan
| | - Kyle C Cuneo
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan
| | - Dawn Owen
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan
| | - Theodore S Lawrence
- University of Michigan Department of Radiation Oncology, Ann Arbor, Michigan
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Gharzai LA, Li P, Schipper MJ, Yao J, Mayo CS, Wilkie JR, Hawkins PG, Lyden T, Blakely A, Ibrahim M, Schonewolf CA, Shah J, Eisbruch A, Casper K, Mierzwa M. Characterization of very late dysphagia after chemoradiation for oropharyngeal squamous cell carcinoma. Oral Oncol 2020; 111:104853. [PMID: 32805634 DOI: 10.1016/j.oraloncology.2020.104853] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 06/03/2020] [Accepted: 06/07/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVES Improved prognosis for p16+ oropharyngeal squamous cell carcinoma (OPSCC) has led to efforts to mitigate long-term complications of treatment, which remains poorly defined in late survivors. Here we characterize very late dysphagia in OPSCC. MATERIALS AND METHODS Long-term review of 93 p16+ OPSCC patients treated with chemoradiation was performed. We scored videofluoroscopic swallow studies (VFSS) according to the Dynamic Imaging Grade of Swallowing Toxicity (DIGEST) scale. Very late dysphagia was defined >2.5 years from end of treatment. Fine-Gray regression models were used to assess dysphagia with competing risk of death. RESULTS Median follow up was 10.5 years. 402 total VFSS were assessed (median 4 per patient, range 0-8). 15.1% of patients had a DIGEST score ≥2 very late after treatment. Very late DIGEST score ≥2 correlated with T-stage (HR 1.7, p = 0.049), second cancer (HR 6.5, p = 0.004), superior pharyngeal constrictor dose (HR 1.11, p = 0.050), total tongue dose (HR 1.07, p = 0.045), but not hypoglossal nerve dose (p > 0.2). Seven patients (7.5%) had late progressive dysphagia, defined as DIGEST score that increased by ≥2 beyond one year after treatment, and this correlated with higher ipsilateral hypoglossal nerve D1cc dose (75 vs 72 Gy, p = 0.037). CONCLUSION In p16+ OPSCC patients treated with definitive chemoradiation, at least 7.5% developed late progressive dysphagia, and 15.1% experienced moderate dysphagia >2.5 years from treatment. Our study suggests that dose to tongue musculature may be associated with very late dysphagia, and hypoglossal nerve dose may be associated with late progressive dysphagia. More intensive long-term dysphagia survivorship monitoring is suggested.
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Affiliation(s)
- Laila A Gharzai
- Department of Radiation Oncology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Pin Li
- Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, USA
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, USA.
| | - John Yao
- Department of Radiation Oncology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Charles S Mayo
- Department of Radiation Oncology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Joel R Wilkie
- Department of Radiation Oncology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Peter G Hawkins
- Department of Radiation Oncology, The Permanente Medical Group, 5900 State Farm Dr, Rohnert Park, CA 94928, USA
| | - Teresa Lyden
- Department of Otolaryngology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Anna Blakely
- Department of Otolaryngology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Mohannad Ibrahim
- Department of Radiology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Caitlin A Schonewolf
- Department of Radiation Oncology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Jennifer Shah
- Department of Radiation Oncology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Avraham Eisbruch
- Department of Radiation Oncology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Keith Casper
- Department of Otolaryngology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Michelle Mierzwa
- Department of Radiation Oncology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA.
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Wilkie JR, Mierzwa ML, Casper KA, Mayo CS, Schipper MJ, Eisbruch A, Worden FP, El Naqa I, Viglianti BL, Rosen BS. Predicting late radiation-induced xerostomia with parotid gland PET biomarkers and dose metrics. Radiother Oncol 2020; 148:30-37. [DOI: 10.1016/j.radonc.2020.03.037] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 01/21/2020] [Accepted: 03/27/2020] [Indexed: 02/06/2023]
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Spratt DE, Malone S, Roy S, Grimes S, Eapen L, Morgan SC, Malone J, Craig J, Dess RT, Jackson W, Schipper MJ, Michalski JM, Lee WR, Pisansky TM, Feng FY, Shipley WU, Sandler HM, Roach M, Sun Y, Lawton CA. Short-term adjuvant versus neoadjuvant hormone therapy in localized prostate cancer: A pooled individual patient analysis of two phase III trials. J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.15_suppl.5584] [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: 11/20/2022] Open
Abstract
5584 Background: The timing of systemic therapy in relation to radiotherapy (RT) is important in most malignancies. In contrast, androgen deprivation therapy (ADT) has largely been investigated in relation to its duration rather than its sequencing with RT. Herein, we conduct the first combined individual patient analysis of two phase III randomized trials to determine the optimal timing of ADT with RT in localized prostate cancer (PCa). Methods: Individual patient data was obtained from the Malone et al trial (JCO 2019), which randomized patients to receive neoadjuvant/concurrent or concurrent/adjuvant ADT for 6 months with prostate only RT. This was combined with the prostate only RT arms of RTOG 9413 that randomized patients to 4 months of neoadjuvant/concurrent or adjuvant ADT. The neoadjuvant/concurrent arms of both trials were combined into the “neoadjuvant” group, and the concurrent/adjuvant (Malone) and adjuvant arm (RTOG 9413) were combined in the “adjuvant” group. The Kaplan-Meier method was used to estimate overall survival (OS) and progression-free survival (PFS). Cumulative incidence of distant metastasis (DM), PCa-specific mortality (PCSM) and biochemical failure (BF) were calculated using the Fine-Gray method with non-PCa deaths as competing events. Late genitourinary (GU) and gastrointestinal (GI) toxicity are also reported. Results: The median follow-up was 14.9 years (yrs) and 1065 patients were included (n=531 neoadjuvant, 534 adjuvant). Groups were well balanced for all baseline characteristics. Adjuvant ADT was superior to neoadjuvant ADT in terms of BF (15yr: 33% vs 43%, HR: 1.37 (95%CI: 1.12-1.68), p=0.002), DM (15yr: 12% vs 18%, HR: 1.40 (95%CI: 1.00-1.95), p=0.04), and PFS (15yr: 36% vs 29%, HR: 1.25 (95%CI: 1.07-1.47), p=0.01). Adjuvant ADT yielded lower PCSM (15yr: 15% vs 20%, HR: 1.29 (95%CI: 0.95-1.75), p=0.10), but did not reach statistical significance. This approached statistical significance in high risk PCa (HR 1.39 (95%CI 1.00-1.93), p=0.053). OS was not significantly different between arms (15yr: 39% vs 34%, HR: 1.11 (95%CI: 0.95-1.30), p=0.20). There was no significant difference in either late grade ≥3 GI (p=0.21) or GU (p=0.98) toxicity. Conclusions: We demonstrate for the first time that sequencing of ADT with RT significantly impacts long-term oncologic outcomes in localized PCa, favoring an adjuvant rather than neoadjuvant approach, without increasing late toxicity. This data has important implications to ongoing and future clinical trial design. Clinical trial information: NCT00769548 .
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Affiliation(s)
| | - Shawn Malone
- The Ottawa Hospital Cancer Center, Ottawa, ON, Canada
| | - Soumyajit Roy
- The Ottawa Hospital Cancer Centre, Ottawa, ON, Canada
| | - Scott Grimes
- The Ottawa Hospital Cancer Centre, Ottawa, ON, Canada
| | - Libni Eapen
- The Ottawa Hospital Cancer Centre, Ottawa, ON, Canada
| | | | | | - Julia Craig
- Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | | | | | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan Health System, Ann Arbor, MI
| | - Jeff M. Michalski
- Washington University in St. Louis School of Medicine, St. Louis, MO
| | | | | | - Felix Y Feng
- Helen Diller Family Comprehensive Cancer Center, San Francisco, CA
| | | | | | - Mack Roach
- University of California San Francisco, San Francisco, CA
| | - Yilun Sun
- University of Michigan, Ann Arbor, MI
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Kim MM, Parmar H, Aryal MP, Caroen S, Devasia T, Schipper MJ, Morikawa A, Spratt DE, Hayman J, Junck L, Lawrence TS, Lao CD, Cao Y. DCE-MRI Evaluation of 10 patients with brain metastases treated with RRx-001, a Myc inhibitor and a CD47 and PD-L1 downregulator, in a phase I/II trial called BRAINSTORM. J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.15_suppl.e14509] [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
e14509 Background: In a Phase 1/2 trial called BRAINSTORM (NCT02215512) for brain metastases from any histology, quantitative changes in perfusion MRI after administration of RRx-001, a mic inhibitor and CD47 and PD-L1 downregulator with vascular normalizing properties, were determined and correlated with response. Methods: Ten patients with 64 total lesions evaluable at baseline, 24 hours, and end of radiotherapy (RT) that participated in BRAINSTORM were subjected to a correlative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) examination four days prior to the start of whole brain radiotherapy (WBRT) that evaluated Ktrans (capillary permeability) and Vp (plasma volume). The treatment comprised RRx-001 on Day -4, pre-WBRT then twice weekly during WBRT. Four dose levels were administered (5 mg/m2, 8.4 mg/m2, 16.5 mg/m2, and 27.5 mg/m2. Results: 10 patients underwent DCE-MRI scans and eight patients with 44 total evaluable lesions had available imaging at 1 month, and 6 patients with 29 total evaluable lesions had imaging at 4 months. On univariate analysis, only a decrease in 24-hour Vp from baseline after a single dose of RRx-001 was marginally associated with absolute tumor volume response 1 month after treatment (p-0.07). In a multivariate model, only Vp prior to therapy and 24-hour change in Vp were retained in the model after stepwise selection. A reduction in Vp 24 hours after RRx-001 (prior to WBRT) was associated with reduced tumor volume at 1 month (Estimate 0.88, 95% CI 0.37-1.40, p = 0.001) and 4 months (Estimate 1.51, 95% CI 0.58-2.43, p = 0.003). Likewise, a lower Vp prior to therapy was associated with reduced tumor volume at 1 month (Estimate 0.73, 95% CI 0.29-1.17, p = 0.002) and 4 months (Estimate 1.8, 95% CI 0.95-2.65, p = 0.0002), suggesting anti-angiogenic activity and early potential vascular normalization after a single dose of RRx-001 predictive of longer-term tumor response. Conclusions: RRx-001 induced a reduction in blood plasma volume, which was associated with tumor response and which suggests a vascular normalizing effect that merits further investigation in future planned studies. Clinical trial information: NCT02215512.
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Affiliation(s)
| | | | | | | | | | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan Health System, Ann Arbor, MI
| | | | | | | | | | | | | | - Yue Cao
- University of Michigan, Ann Arbor, MI
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Jackson WC, Hartman HE, Dess RT, Birer SR, Soni PD, Hearn JWD, Reichert ZR, Kishan AU, Mahal BA, Zumsteg ZS, Efstathiou JA, Kaffenberger S, Morgan TM, Mehra R, Showalter TN, Krauss DA, Nguyen PL, Schipper MJ, Feng FY, Sandler HM, Hoskin PJ, Roach M, Spratt DE. Addition of Androgen-Deprivation Therapy or Brachytherapy Boost to External Beam Radiotherapy for Localized Prostate Cancer: A Network Meta-Analysis of Randomized Trials. J Clin Oncol 2020; 38:3024-3031. [PMID: 32396488 DOI: 10.1200/jco.19.03217] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
PURPOSE In men with localized prostate cancer, the addition of androgen-deprivation therapy (ADT) or a brachytherapy boost (BT) to external beam radiotherapy (EBRT) have been shown to improve various oncologic end points. Practice patterns indicate that those who receive BT are significantly less likely to receive ADT, and thus we sought to perform a network meta-analysis to compare the predicted outcomes of a randomized trial of EBRT plus ADT versus EBRT plus BT. MATERIALS AND METHODS A systematic review identified published randomized trials comparing EBRT with or without ADT, or EBRT (with or without ADT) with or without BT, that reported on overall survival (OS). Standard fixed-effects meta-analyses were performed for each comparison, and a meta-regression was conducted to adjust for use and duration of ADT. Network meta-analyses were performed to compare EBRT plus ADT versus EBRT plus BT. Bayesian analyses were also performed, and a rank was assigned to each treatment after Markov Chain Monte Carlo analyses to create a surface under the cumulative ranking curve. RESULTS Six trials compared EBRT with or without ADT (n = 4,663), and 3 compared EBRT with or without BT (n = 718). The addition of ADT to EBRT improved OS (hazard ratio [HR], 0.71 [95% CI, 0.62 to 0.81]), whereas the addition of BT did not significantly improve OS (HR, 1.03 [95% CI, 0.78 to 1.36]). In a network meta-analysis, EBRT plus ADT had improved OS compared with EBRT plus BT (HR, 0.68 [95% CI, 0.52 to 0.89]). Bayesian modeling demonstrated an 88% probability that EBRT plus ADT resulted in superior OS compared with EBRT plus BT. CONCLUSION Our findings suggest that current practice patterns of omitting ADT with EBRT plus BT may result in inferior OS compared with EBRT plus ADT in men with intermediate- and high-risk prostate cancer. ADT for these men should remain a critical component of treatment regardless of radiotherapy delivery method until randomized evidence demonstrates otherwise.
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Affiliation(s)
- William C Jackson
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - Holly E Hartman
- Department of Biostatistics, University of Michigan, Ann Arbor, MI
| | - Robert T Dess
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - Sam R Birer
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - Payal D Soni
- Department of Radiation Oncology, Hunter Holmes McGuire Veterans Affairs Medical Center, Richmond, VA
| | - Jason W D Hearn
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - Zachary R Reichert
- Department of Hematology/Oncology, University of Michigan, Ann Arbor, MI
| | - Amar U Kishan
- Department of Radiation Oncology, University of California, Los Angeles, CA
| | - Brandon A Mahal
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA
| | | | - Jason A Efstathiou
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA
| | | | - Todd M Morgan
- Department of Urology, University of Michigan, Ann Arbor, MI
| | - Rohit Mehra
- Department of Pathology, University of Michigan, Ann Arbor, MI
| | - Timothy N Showalter
- Department of Radiation Oncology, University of Virginia, Charlottesville, MD
| | - Daniel A Krauss
- Department of Radiation Oncology, Oakland University William Beaumont School of Medicine, Royal Oak, MI
| | - Paul L Nguyen
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI.,Department of Biostatistics, University of Michigan, Ann Arbor, MI
| | - Felix Y Feng
- Department of Radiation Oncology, University of California, San Francisco, CA
| | | | | | - Mack Roach
- Department of Radiation Oncology, University of California, San Francisco, CA
| | - Daniel E Spratt
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
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50
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Dess RT, Sun Y, Jackson WC, Jairath NK, Kishan AU, Wallington DG, Mahal BA, Stish BJ, Zumsteg ZS, Den RB, Hall WA, Gharzai LA, Jaworski EM, Reichert ZR, Morgan TM, Mehra R, Schaeffer EM, Sartor O, Nguyen PL, Lee WR, Rosenthal SA, Michalski JM, Schipper MJ, Dignam JJ, Pisansky TM, Zietman AL, Sandler HM, Efstathiou JA, Feng FY, Shipley WU, Spratt DE. Association of Presalvage Radiotherapy PSA Levels After Prostatectomy With Outcomes of Long-term Antiandrogen Therapy in Men With Prostate Cancer. JAMA Oncol 2020; 6:735-743. [PMID: 32215583 PMCID: PMC7189892 DOI: 10.1001/jamaoncol.2020.0109] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [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] [Indexed: 12/29/2022]
Abstract
Importance In men with recurrent prostate cancer, addition of long-term antiandrogen therapy to salvage radiotherapy (SRT) was associated with overall survival (OS) in the NRG/RTOG 9601 study. However, hormone therapy has associated morbidity, and there are no validated predictive biomarkers to identify which patients derive most benefit from treatment. Objective To examine the role of pre-SRT prostate-specific antigen (PSA) levels to personalize hormone therapy use with SRT. Interventions Men were randomized to SRT plus high-dose nonsteroidal antiandrogen (bicalutamide, 150 mg/d) or placebo for 2 years. Design, Setting, and Participants In this secondary analysis of the multicenter RTOG 9601 double-blind, placebo-controlled randomized clinical trial conducted from 1998 to 2003 by a multinational cooperative group, men with a positive surgical margin or pathologic T3 disease after radical prostatectomy with pre-SRT PSA of 0.2 to 4.0 ng/mL were included. Analysis was performed between March 4, 2019, and December 20, 2019. Main Outcomes and Measures The primary outcome was overall survival (OS). Secondary end points included distant metastasis (DM), other-cause mortality (OCM), and grades 3 to 5 cardiac and neurologic toxic effects. Subgroup analyses were performed using the protocol-specified PSA stratification variable (1.5 ng/mL) and additional PSA cut points, including test for interaction. Competing risk analyses were performed for DM and other-cause mortality (OCM). Results Overall, 760 men with PSA elevation after radical prostatectomy for prostate cancer were included. The median (range) age of particpants was 65 (40-83) years. Antiandrogen assignment was associated with an OS benefit in the PSA stratum greater than 1.5 ng/mL (n = 118) with a 25% 12-year absolute benefit (hazard ratio [HR], 0.45; 95% CI, 0.25-0.81), but not in the PSA of 1.5 ng/mL or less stratum (n = 642) (1% 12-year absolute difference; HR, 0.87; 95% CI, 0.66-1.16). In a subanalysis of men with PSA of 0.61 to 1.5 (n = 253), there was an OS benefit associated with antiandrogen assignment (HR, 0.61; 95% CI, 0.39-0.94). In those receiving early SRT (PSA ≤0.6 ng/mL, n = 389), there was no improvement in OS (HR, 1.16; 95% CI, 0.79-1.70), an increased OCM hazard (subdistribution HR, 1.94; 95% CI, 1.17-3.20; P = .01), and an increased odds of late grades 3 to 5 cardiac and neurologic toxic effects (odds ratio, 3.57; 95% CI, 1.09-15.97; P = .05). Conclusions and Relevance These results suggest that pre-SRT PSA level may be a prognostic biomarker for outcomes of antiandrogen treatment with SRT. In patients receiving late SRT (PSA >0.6 ng/mL, hormone therapy was associated with improved outcomes. In men receiving early SRT (PSA ≤0.6 ng/mL), long-term antiandrogen treatment was not associated with improved OS. Future randomized clinical trials are needed to determine hormonal therapy benefit in this population. Trial Registration ClinicalTrials.gov Identifier: NCT00002874.
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Affiliation(s)
- Robert T Dess
- Department of Radiation Oncology, University of Michigan, Ann Arbor
| | - Yilun Sun
- Department of Radiation Oncology, University of Michigan, Ann Arbor
- Department of Biostatistics, University of Michigan, Ann Arbor
| | | | - Neil K Jairath
- Department of Radiation Oncology, University of Michigan, Ann Arbor
| | - Amar U Kishan
- Department of Radiation Oncology, University of California, Los Angeles
| | | | - Brandon A Mahal
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Bradley J Stish
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
| | - Zachery S Zumsteg
- Department of Radiation Oncology, Cedars-Sinai Medical Center, West Hollywood, California
| | - Robert B Den
- Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - William A Hall
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee
| | - Laila A Gharzai
- Department of Radiation Oncology, University of Michigan, Ann Arbor
| | | | | | - Todd M Morgan
- Department of Urology, University of Michigan, Ann Arbor
| | - Rohit Mehra
- Department of Pathology, University of Michigan, Ann Arbor
| | | | - Oliver Sartor
- Department of Medicine, Tulane Cancer Center, New Orleans, Louisiana
| | - Paul L Nguyen
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | | | - Seth A Rosenthal
- Department of Radiation Oncology, Sutter Medical Group, Sacramento, California
| | - Jeff M Michalski
- Department of Radiation Oncology, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan, Ann Arbor
- Department of Biostatistics, University of Michigan, Ann Arbor
| | - James J Dignam
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois
| | | | - Anthony L Zietman
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Howard M Sandler
- Department of Radiation Oncology, Cedars-Sinai Medical Center, West Hollywood, California
| | - Jason A Efstathiou
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Felix Y Feng
- Department of Radiation Oncology, University of California, San Francisco
- Department of Urology, University of California, San Francisco
- Department of Medicine, University of California, San Francisco
| | - William U Shipley
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Daniel E Spratt
- Department of Radiation Oncology, University of Michigan, Ann Arbor
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