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Lichtenberg JY, Ramamurthy E, Young AD, Redman TP, Leonard CE, Das SK, Fisher PB, Lemmon CA, Hwang PY. Leader cells mechanically respond to aligned collagen architecture to direct collective migration. PLoS One 2024; 19:e0296153. [PMID: 38165954 PMCID: PMC10760762 DOI: 10.1371/journal.pone.0296153] [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: 03/13/2023] [Accepted: 12/06/2023] [Indexed: 01/04/2024] Open
Abstract
Leader cells direct collective migration through sensing cues in their microenvironment to determine migration direction. The mechanism by which leader cells sense the mechanical cue of organized matrix architecture culminating in a mechanical response is not well defined. In this study, we investigated the effect of organized collagen matrix fibers on leader cell mechanics and demonstrate that leader cells protrude along aligned fibers resulting in an elongated phenotype of the entire cluster. Further, leader cells show increased mechanical interactions with their nearby matrix compared to follower cells, as evidenced by increased traction forces, increased and larger focal adhesions, and increased expression of integrin-α2. Together our results demonstrate changes in mechanical matrix cues drives changes in leader cell mechanoresponse that is required for directional collective migration. Our findings provide new insights into two fundamental components of carcinogenesis, namely invasion and metastasis.
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Affiliation(s)
- Jessanne Y. Lichtenberg
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Ella Ramamurthy
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Bioengineering, University of California Berkeley, Berkeley, California, United States of America
| | - Anna D. Young
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Trey P. Redman
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Corinne E. Leonard
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Swadesh K. Das
- Department of Human and Molecular Genetics, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America
- VCU Institute of Molecular Medicine, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America
- VCU Massey Cancer Center, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Paul B. Fisher
- Department of Human and Molecular Genetics, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America
- VCU Institute of Molecular Medicine, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America
- VCU Massey Cancer Center, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Christopher A. Lemmon
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Priscilla Y. Hwang
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, Virginia, United States of America
- VCU Massey Cancer Center, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America
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Leonard CE, Fryman SP, Turner MP, Bennett JP, Carter DL, Sing AP. Abstract P4-15-08: Association of OncotypeDX® DCIS ScoreTM results with local recurrence in patients with DCIS treated on accelerated partial breast radiotherapy (APBI) protocols. Cancer Res 2018. [DOI: 10.1158/1538-7445.sabcs17-p4-15-08] [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: 11/16/2022]
Abstract
Abstract
Background: Ductal carcinoma in situ (DCIS) is a proliferation of malignant epithelial cells of the ducts and terminal lobular units of the breast that do not invade the basement membrane. The incidence of DCIS has increased markedly since the early 1980s, chiefly due to screening mammography. Whole breast radiotherapy has largely been used to treat breast DCIS after lumpectomy. More recently, APBI has increasingly been utilized for breast DCIS. Currently updated American Society of Radiation Oncology (ASTRO) APBI guidelines have included "low risk" DCIS (as defined by RTOG 9804 criteria). The following results further explore clinico-pathologic factors, in addition to the DCIS Score, in order to better define an appropriate DCIS population for APBI.
Methods: An exploratory analysis aimed to retrospectively measure the association between clinico-pathologic factors and the DCIS Score result, an optimized 12-gene expression algorithm, and risk of any local failure (in situ or IBC recurrence) in a cohort of women treated with local excision and APBI on prospective phase II (NCT01185145) and phase III (NCT01185132) clinical trials. Multifocal tumors were described only by local pathology and not determined or defined centrally. The DCIS Score assay was performed by quantitative RT-PCR on formalin-fixed paraffin-embedded DCIS tumor specimens by Genomic Health (Redwood City, CA). Descriptive statistics of the cohort and assay results overall and by clinical trial were derived. Univariable Cox proportional hazards regression was used to determine whether there was an association between local failure and categorized DCIS Score group (≥39 vs <39) or other clinico-pathologic factors on the pooled cohort of clinical trial patients.
Results: This analysis included 104 evaluable patients (N=18 from NCT01185145 and N=86 from NCT01185132). The median age was 60 (range: 41-80), 79% of patients were postmenopausal, and the median span of DCIS was 6 mm (range 2-25 mm). Over two-thirds of the cohort presented with necrosis (71%). The distribution of DCIS Score results ranged from 0 to 82, with 69% of patients having a DCIS Score result <39. The median follow-up time was longer at 8.2 years in NCT01185145 versus 3.0 years in NCT01185132. There was a total of 6 local recurrences. DCIS Score result was significantly associated with local recurrence in univariable modeling (hazard ratio=10.3 for ≥39 vs <39; p=0.0104). None of the other clinico-pathologic characteristics resulted in any significant correlation with locoregional recurrence. All results were highly variable due to the small number of events.
Conclusion: The DCIS Score assay demonstrated risk stratification in this cohort of patients treated with local excision and APBI pooled from two clinical trials. These results are consistent with those recently published by Rakovitch et al (J Natl Cancer Inst 2017). The cohort in this study was dominated by those in the phase III trial. Due to the small number of local recurrence events and limited follow-up time in the phase III trial, caution should be taken when interpreting the results. Further investigations are needed to confirm findings.
Citation Format: Leonard CE, Fryman SP, Turner MP, Bennett JP, Carter DL, Sing AP. Association of OncotypeDX® DCIS ScoreTM results with local recurrence in patients with DCIS treated on accelerated partial breast radiotherapy (APBI) protocols [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-15-08.
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Affiliation(s)
- CE Leonard
- Rocky Mountain Cancer Centers, Littleton, CO; Rocky Mountain Cancer Centers, Aurora, CO; Genomic Health, Inc., Redwood City, CA
| | - SP Fryman
- Rocky Mountain Cancer Centers, Littleton, CO; Rocky Mountain Cancer Centers, Aurora, CO; Genomic Health, Inc., Redwood City, CA
| | - MP Turner
- Rocky Mountain Cancer Centers, Littleton, CO; Rocky Mountain Cancer Centers, Aurora, CO; Genomic Health, Inc., Redwood City, CA
| | - JP Bennett
- Rocky Mountain Cancer Centers, Littleton, CO; Rocky Mountain Cancer Centers, Aurora, CO; Genomic Health, Inc., Redwood City, CA
| | - DL Carter
- Rocky Mountain Cancer Centers, Littleton, CO; Rocky Mountain Cancer Centers, Aurora, CO; Genomic Health, Inc., Redwood City, CA
| | - AP Sing
- Rocky Mountain Cancer Centers, Littleton, CO; Rocky Mountain Cancer Centers, Aurora, CO; Genomic Health, Inc., Redwood City, CA
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Manders JB, Solin LJ, Leonard CE, Mamounas EP, Lu R, Turner M, Baehner FL, White J. Abstract P4-15-09: Refined estimates of local recurrence risk in a clinical utility study: Integrating the DCIS score, patient age and DCIS tumor size. Cancer Res 2018. [DOI: 10.1158/1538-7445.sabcs17-p4-15-09] [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: 11/16/2022]
Abstract
Abstract
Background:Better tools are needed to estimate the risk of local recurrence (LR; DCIS or invasive) after breast-conserving surgery (BCS) for pts with DCIS in order to inform treatment decisions. Traditional clinico-pathologic (CP) factors, e.g., age and tumor size, provide an average LR risk derived from clinical trials and population studies. The Oncotype DX 12-gene DCIS Score assay has been validated to provide individual 10 yr LR risk estimates (Solin JNCI 2013; Rakovitch BCRT 2015). Previously we reported the impact of the DCIS Score result on radiotherapy (RT) recommendations including the pre-assay LR risk and RT recommendation and the change in RT recommendation from pre- to post-assay (Manders Ann Surg Oncol 2016).Recently a patient specific meta-analysis (MA) combined data from E5194 and Ontario DCIS Cohort (ODC) adjusting for pertinent clinico-pathologic factors to provide refined prediction estimates of LR risk after BCS alone (Rakovitch ASCO 2017). Herein we applied these risk estimates integrating DS, tumor size and patient age with adjustment for diagnosis in the year 2000 or later to refine estimates of LR in DCIS patients from the Manders et al study.
Methods: 13 U.S. sites enrolled pts with DCIS treated with BCS alone from 3/2014 to 5/2015. Pts with LCIS but no DCIS, invasive BC, or planned mastectomy were excluded. Data were prospectively collected on CP factors, physician estimates of LR risk, and DCIS Score. Refined estimates of 10-yr risk of LR are presented by DCIS Score result category (0-38; 39-54; 55-100), age group (≥50 vs <50 yr) and tumor size (≤1; >1-2.5; >2.5 cm).
Results: Of the 127 pts enrolled, median age was 60 yr,79.5% were postmenopausal. Median size was 8mm & 39% were ≤5mm. Median margin width was 3.0mm. ER and PR by IHC were positive in 89% and 78% of pts, respectively. For patients ≥50 yr with tumors ≤1 cm and low risk DS, the 10-yr LR risk ranges from 5.3-10.0%. A high DS result is associated with a higher 10-yr median predicted risk of LR in all subsets (table 1). The DCIS Score integrated with tumor size and patient age and the adjustment for diagnosis in 2000 or later provided risk estimates that are often lower than those provided by the DCIS Score alone without adjustment for diagnostic year. Using DS alone the percentage of patients with risk of LR <8% was 0%; however, incorporating patient age and tumor size with the DS and adjusting for diagnosis in 2000 or later, it increased to 30.9% of patients.
Conclusions: Integration of the DCIS Score assay, that provides individual risk estimates of LR, with patient age and DCIS tumor size and adjusting for diagnosis in 2000 or later, provides refined estimates of 10-yr LR risk after BCS alone for DCIS. This integration enhances prognostic LR risk estimates and frequently provides lower risk estimates with which to guide individualized treatment decisions.
Distribution of 10-year risk of local recurrence using DCIS Score (DS), tumor size, and age, adjusting for diagnosis in 2000 or later. Low DS (<39)Inter DS (39-54)High DS (≥55)Tumor Size(cm)Age(Yr)NMedian (Min-Max)%NMedian (Min-Max)%NMedian (Min-Max)%≤1≥50457.0 (5.3-10)810.8 (10.2-11.8)1015.1 (12.9-18.6) <50810.3 (7.4-12.1)414.9 (14.1-15.4)0 >1-2.5≥50249.5 (7.3-12.6)914.2 (12.9-15.6)519.6 (16.5-20.4) < 50216.4 (16.1-16.7)220.4 (19.8-21.1)122.2 (22.2-22.2)>2.5≥50515.7 (14.9-23.7)0 138.4 (38.4-38.4) <500 141.2 (41.2-41.2)149.3 (49.3-49.3)
Citation Format: Manders JB, Solin LJ, Leonard CE, Mamounas EP, Lu R, Turner M, Baehner FL, White J. Refined estimates of local recurrence risk in a clinical utility study: Integrating the DCIS score, patient age and DCIS tumor size [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-15-09.
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Affiliation(s)
- JB Manders
- The Christ Hospital, Cincinnati, OH; Albert Einstein Health Network, Philadelphia, PA; Rocky Mountain Cancer Centers, Denver, CO; UF Health Cancer Center at Orlando Health, Orlando, FL; Genomic Health, Inc., Redwood City, CA; University of California, San Francisco, San Francisco, CA; Duke University Medical Center, Durham, NC
| | - LJ Solin
- The Christ Hospital, Cincinnati, OH; Albert Einstein Health Network, Philadelphia, PA; Rocky Mountain Cancer Centers, Denver, CO; UF Health Cancer Center at Orlando Health, Orlando, FL; Genomic Health, Inc., Redwood City, CA; University of California, San Francisco, San Francisco, CA; Duke University Medical Center, Durham, NC
| | - CE Leonard
- The Christ Hospital, Cincinnati, OH; Albert Einstein Health Network, Philadelphia, PA; Rocky Mountain Cancer Centers, Denver, CO; UF Health Cancer Center at Orlando Health, Orlando, FL; Genomic Health, Inc., Redwood City, CA; University of California, San Francisco, San Francisco, CA; Duke University Medical Center, Durham, NC
| | - EP Mamounas
- The Christ Hospital, Cincinnati, OH; Albert Einstein Health Network, Philadelphia, PA; Rocky Mountain Cancer Centers, Denver, CO; UF Health Cancer Center at Orlando Health, Orlando, FL; Genomic Health, Inc., Redwood City, CA; University of California, San Francisco, San Francisco, CA; Duke University Medical Center, Durham, NC
| | - R Lu
- The Christ Hospital, Cincinnati, OH; Albert Einstein Health Network, Philadelphia, PA; Rocky Mountain Cancer Centers, Denver, CO; UF Health Cancer Center at Orlando Health, Orlando, FL; Genomic Health, Inc., Redwood City, CA; University of California, San Francisco, San Francisco, CA; Duke University Medical Center, Durham, NC
| | - M Turner
- The Christ Hospital, Cincinnati, OH; Albert Einstein Health Network, Philadelphia, PA; Rocky Mountain Cancer Centers, Denver, CO; UF Health Cancer Center at Orlando Health, Orlando, FL; Genomic Health, Inc., Redwood City, CA; University of California, San Francisco, San Francisco, CA; Duke University Medical Center, Durham, NC
| | - FL Baehner
- The Christ Hospital, Cincinnati, OH; Albert Einstein Health Network, Philadelphia, PA; Rocky Mountain Cancer Centers, Denver, CO; UF Health Cancer Center at Orlando Health, Orlando, FL; Genomic Health, Inc., Redwood City, CA; University of California, San Francisco, San Francisco, CA; Duke University Medical Center, Durham, NC
| | - J White
- The Christ Hospital, Cincinnati, OH; Albert Einstein Health Network, Philadelphia, PA; Rocky Mountain Cancer Centers, Denver, CO; UF Health Cancer Center at Orlando Health, Orlando, FL; Genomic Health, Inc., Redwood City, CA; University of California, San Francisco, San Francisco, CA; Duke University Medical Center, Durham, NC
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Leonard CE, Sobus RD, Fryman S, Sedlacek S, Kercher J, Widner J, Asmar L, Wang Y, Howell K, Barke L, Carter D. Abstract P1-10-03: A randomized trial of accelerated breast radiotherapy utilizing either 3-dimensional radiotherapy versus intensity modulated radiotherapy. Cancer Res 2017. [DOI: 10.1158/1538-7445.sabcs16-p1-10-03] [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: 11/16/2022]
Abstract
Abstract
PURPOSE: Primary objective: patient self-assessment of breast pain between 3-dimensional radiotherapy (3D-CRT) versus intensity modulated radiotherapy (IMRT). Secondary objectives: breast cosmesis as well as local-regional recurrence and survival statistics.
METHODS AND MATERIALS: 656 patients (3D-CRT n=325; IMRT n=331) were prospectively randomized to either IMRT or 3D-CRT accelerated partial breast radiotherapy to 38.5 Gy in 10 BID 3.85 Gy fractions. Follow-up was: 1, 4, 8, 12, 16, 20, 24 months then yearly. At follow-up, patients completed a cosmesis/pain self-assessment form and physicians completed a cosmesis and disease-status form.
RESULTS: 636 patients completed treatment (3D-CRT n=316; IMRT n=320). Median age was 62. Mean tumor size was 1.1 cm. Mean margin was 7mm. Histology was: 74.5% IDCA, 7% ILCA, 17% DCIS, 0.5% Tubular, 1% Mucinous. 99% were ER+. HER2/neu status by IHC was 3+ in 16% of patients. Median follow-up is 2 years. Tables 1 and 2 show there is no significant difference in patient-assessed pain and cosmesis between the two treatment arms (p=0.14, =0.68 respectively). Decreasing pain and worsening cosmesis as reported by the patient were significantly related to time (p<0.01, =0.012 respectively). MD assessed cosmesis worsened significantly from baseline in the IMRT compared to 3D-CRT cohort (p=0.045). At 2 years Grade 3 and 4 toxicities were 1.5% and 3.9% respectively for 3D-CRT versus IMRT cohorts. Overall Survival at 2 years were 99.7% for both cohorts. There were 3/319 (0.9%) and 7/328 (2.1%) ipsilateral breast recurrences in the 3D-CRT and IMRT cohorts respectively.
Patient breast pain by follow-up interval12 Months (3D n=167 and IMRT n=163)Rx ModalityNoneMildModerate-Severep value3D50.9%47.3%1.8%0.44IMRT52.1%44.2%3.7% 24 Months (3D n=111 and IMRT n=109)3D52.3%47.7% 0.07IMRT66.1%33.9% 36 Months (3D n=50 and IMRT n=34)3D60.0%40.0% 0.37IMRT58.8%41.2% 48 Months (3D n=12 and IMRT n=123D25.0%75.0% 0.19IMRT58.3%41.7% Results from mixed model for pain gradeEffectEstimateSELowerUpperp value3D vs IMRT0.0810.055-0.0260.1890.14Visit (Baseline, 12, 24, 36, 48 month-0.1010.019-0.137-0.064<0.01Table 1.
Patient breast cosmesis by follow-up interval12 Months (3D n=162 and IMRT n=158)Rx ModalityNo changeSlight changeObvious changeDrastic changep value3D40.1%38.3%19.1%2.5%0.83IMRT41.8%40.5%15.2%2.5% 24 months (3D n=108 and IMRT n=108)3D38.9%40.7%18.5%1.9%0.30IMRT41.7%29.6%26.9%1.9% 36 Months (3D n=50 and IMRT n=34)3D38.0%34.0%28.0%0%0.37IMRT32.4%35.3%26.5%5.9% 48 Months (3D n=10 and IMRT n=12)3D10.0%30.0%60.0% 0.10IMRT50.0%8.3%41.7% Patient breast cosmoses by follow-up intervalEffectEstimateSELowerUpperp value3D vs IMRT0.0260.064-0.1000.1530.68All Visit (Baseline, 12, 24, 36, 48 month)-0.0530.021-0.095-0.0120.01Table 2.
Conclusion: T here were no significant differences in patient-assessed pain and cosmesis between the two treatment arms (p=0.14, =0.68 respectively) and no significant increase in pain over time. However, MD assessed cosmesis showed worsening cosmesis in the IMRT cohort compared to the 3D-CRT cohort wen compared to baseline.
Citation Format: Leonard CE, Sobus RD, Fryman S, Sedlacek S, Kercher J, Widner J, Asmar L, Wang Y, Howell K, Barke L, Carter D. A randomized trial of accelerated breast radiotherapy utilizing either 3-dimensional radiotherapy versus intensity modulated radiotherapy [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-10-03.
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Affiliation(s)
- CE Leonard
- Rocky Mountain Cancer Center, Denver, CO; Rocky Mountain Cancer Center, Aurora, CO; SurgOne, Littleton, CO; Linasmar Consulting, Houston, TX; Invision Sally Jobe Breast Network, Greenwood Village, CO
| | - RD Sobus
- Rocky Mountain Cancer Center, Denver, CO; Rocky Mountain Cancer Center, Aurora, CO; SurgOne, Littleton, CO; Linasmar Consulting, Houston, TX; Invision Sally Jobe Breast Network, Greenwood Village, CO
| | - S Fryman
- Rocky Mountain Cancer Center, Denver, CO; Rocky Mountain Cancer Center, Aurora, CO; SurgOne, Littleton, CO; Linasmar Consulting, Houston, TX; Invision Sally Jobe Breast Network, Greenwood Village, CO
| | - S Sedlacek
- Rocky Mountain Cancer Center, Denver, CO; Rocky Mountain Cancer Center, Aurora, CO; SurgOne, Littleton, CO; Linasmar Consulting, Houston, TX; Invision Sally Jobe Breast Network, Greenwood Village, CO
| | - J Kercher
- Rocky Mountain Cancer Center, Denver, CO; Rocky Mountain Cancer Center, Aurora, CO; SurgOne, Littleton, CO; Linasmar Consulting, Houston, TX; Invision Sally Jobe Breast Network, Greenwood Village, CO
| | - J Widner
- Rocky Mountain Cancer Center, Denver, CO; Rocky Mountain Cancer Center, Aurora, CO; SurgOne, Littleton, CO; Linasmar Consulting, Houston, TX; Invision Sally Jobe Breast Network, Greenwood Village, CO
| | - L Asmar
- Rocky Mountain Cancer Center, Denver, CO; Rocky Mountain Cancer Center, Aurora, CO; SurgOne, Littleton, CO; Linasmar Consulting, Houston, TX; Invision Sally Jobe Breast Network, Greenwood Village, CO
| | - Y Wang
- Rocky Mountain Cancer Center, Denver, CO; Rocky Mountain Cancer Center, Aurora, CO; SurgOne, Littleton, CO; Linasmar Consulting, Houston, TX; Invision Sally Jobe Breast Network, Greenwood Village, CO
| | - K Howell
- Rocky Mountain Cancer Center, Denver, CO; Rocky Mountain Cancer Center, Aurora, CO; SurgOne, Littleton, CO; Linasmar Consulting, Houston, TX; Invision Sally Jobe Breast Network, Greenwood Village, CO
| | - L Barke
- Rocky Mountain Cancer Center, Denver, CO; Rocky Mountain Cancer Center, Aurora, CO; SurgOne, Littleton, CO; Linasmar Consulting, Houston, TX; Invision Sally Jobe Breast Network, Greenwood Village, CO
| | - D Carter
- Rocky Mountain Cancer Center, Denver, CO; Rocky Mountain Cancer Center, Aurora, CO; SurgOne, Littleton, CO; Linasmar Consulting, Houston, TX; Invision Sally Jobe Breast Network, Greenwood Village, CO
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Gagne JJ, Han X, Hennessy S, Leonard CE, Chrischilles EA, Carnahan RM, Wang SV, Fuller C, Iyer A, Katcoff H, Woodworth TS, Archdeacon P, Meyer TE, Schneeweiss S, Toh S. Successful Comparison of US Food and Drug Administration Sentinel Analysis Tools to Traditional Approaches in Quantifying a Known Drug-Adverse Event Association. Clin Pharmacol Ther 2016; 100:558-564. [PMID: 27416001 DOI: 10.1002/cpt.429] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2016] [Revised: 06/07/2016] [Accepted: 07/06/2016] [Indexed: 12/20/2022]
Abstract
The US Food and Drug Administration's Sentinel system has developed the capability to conduct active safety surveillance of marketed medical products in a large network of electronic healthcare databases. We assessed the extent to which the newly developed, semiautomated Sentinel Propensity Score Matching (PSM) tool could produce the same results as a customized protocol-driven assessment, which found an adjusted hazard ratio (HR) of 3.04 (95% confidence interval [CI], 2.81-3.27) comparing angioedema in patients initiating angiotensin-converting enzyme (ACE) inhibitors vs. beta-blockers. Using data from 13 Data Partners between 1 January 2008, and 30 September 2013, the PSM tool identified 2,211,215 eligible ACE inhibitor and 1,673,682 eligible beta-blocker initiators. The tool produced an HR of 3.14 (95% CI, 2.86-3.44). This comparison provides initial evidence that Sentinel analytic tools can produce findings similar to those produced by a highly customized protocol-driven assessment.
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Affiliation(s)
- J J Gagne
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
| | - X Han
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - S Hennessy
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - C E Leonard
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - E A Chrischilles
- Department of Epidemiology, University of Iowa College of Public Health, Iowa City, Iowa, USA
| | - R M Carnahan
- Department of Epidemiology, University of Iowa College of Public Health, Iowa City, Iowa, USA
| | - S V Wang
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - C Fuller
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
| | - A Iyer
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
| | - H Katcoff
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
| | - T S Woodworth
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
| | - P Archdeacon
- Office of Medical Policy, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA
| | - T E Meyer
- Division of Epidemiology, Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA
| | - S Schneeweiss
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - S Toh
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
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Leonard CE, Bilker WB, Brensinger CM, Han X, Flory JH, Flockhart DA, Gagne JJ, Cardillo S, Hennessy S. Severe hypoglycemia in users of sulfonylurea antidiabetic agents and antihyperlipidemics. Clin Pharmacol Ther 2016; 99:538-47. [PMID: 26566262 DOI: 10.1002/cpt.297] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2015] [Accepted: 11/07/2015] [Indexed: 12/15/2022]
Abstract
Drug-drug interactions causing severe hypoglycemia due to antidiabetic drugs is a major clinical and public health problem. We assessed whether sulfonylurea use with a statin or fibrate was associated with severe hypoglycemia. We conducted cohort studies of users of glyburide, glipizide, and glimepiride plus a statin or fibrate within a Medicaid population. The outcome was a validated, diagnosis-based algorithm for severe hypoglycemia. Among 592,872 persons newly exposed to a sulfonylurea+antihyperlipidemic, the incidence of severe hypoglycemia was 5.8/100 person-years. Adjusted hazard ratios (HRs) for sulfonylurea+statins were consistent with no association. Most overall HRs for sulfonylurea+fibrate were elevated, with sulfonylurea-specific adjusted HRs as large as 1.50 (95% confidence interval (CI): 1.24-1.81) for glyburide+gemfibrozil, 1.37 (95% CI: 1.11-1.69) for glipizide+gemfibrozil, and 1.63 (95% CI: 1.29-2.06) for glimepiride+fenofibrate. Concomitant therapy with a sulfonylurea and fibrate is associated with an often delayed increased rate of severe hypoglycemia.
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Affiliation(s)
- C E Leonard
- Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - W B Bilker
- Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - C M Brensinger
- Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - X Han
- Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - J H Flory
- Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Healthcare Policy and Research, Division of Comparative Effectiveness, Weill Cornell Medical College, New York, New York, USA
| | - D A Flockhart
- Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Medicine, Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - J J Gagne
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - S Cardillo
- Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - S Hennessy
- Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Hennessy S, Leonard CE, Gagne JJ, Flory JH, Han X, Brensinger CM, Bilker WB. Pharmacoepidemiologic Methods for Studying the Health Effects of Drug-Drug Interactions. Clin Pharmacol Ther 2015; 99:92-100. [PMID: 26479278 DOI: 10.1002/cpt.277] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [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: 08/06/2015] [Revised: 10/01/2015] [Accepted: 10/14/2015] [Indexed: 12/13/2022]
Abstract
A drug-drug interaction (DDI) occurs when one or more drugs affect the pharmacokinetics (the body's effect on the drug) and/or pharmacodynamics (the drug's effect on the body) of one or more other drugs. Pharmacoepidemiologic studies are the principal way of studying the health effects of potential DDIs. This article discusses aspects of pharmacoepidemiologic research designs that are particularly salient to the design and interpretation of pharmacoepidemiologic studies of DDIs.
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Affiliation(s)
- S Hennessy
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - C E Leonard
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - J J Gagne
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - J H Flory
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Division of Comparative Effectiveness and Outcomes Research, Department of Healthcare Research and Policy, Weill Cornell Medical College, New York, New York, USA
- Endocrinology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - X Han
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - C M Brensinger
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - W B Bilker
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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Leonard CE, Philpott P, Shapiro H, Corkill M, Gonzales C, Ponce J, Howell K, Aarestad N, Sedlacek SM. Clinical observations of axillary involvement for tubular, lobular, and ductal carcinomas of the breast. J Surg Oncol 1999; 70:13-20. [PMID: 9989415 DOI: 10.1002/(sici)1096-9098(199901)70:1<13::aid-jso3>3.0.co;2-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
BACKGROUND AND OBJECTIVES Recently, there has been much interest in identifying primary breast cancer characteristics which have predictive value for axillary metastases. We studied breast cancer patients to determine variables associated with the incidence/extent of axillary involvement and to construct a modeled analysis. METHODS Patients with invasive ductal, lobular, and tubular breast cancer (group 1, n = 15,719) were analyzed by tumor size and histology for the probability/extent of axillary metastases. A subgroup of patients was analyzed separately for any association of axillary involvement and other variables (group 2). RESULTS In group 1, the incidence and extent (number of positive lymph nodes) of axillary metastases correlated significantly with histology and increasing tumor size of ductal and lobular histologies. Significant associations for < or = 10% axillary involvement in group 2 were age and S phase for tubular histology and differentiation for ductal histology. In a multivariate analysis, increasing tumor size was the only statistically significant correlate for axillary involvement (group 2) and for increasing number of positive nodes (group 1). CONCLUSIONS A multivariate model of tumor size and age combined with staging techniques can successfully confirm or assess extent of axillary metastases in breast carcinoma.
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Affiliation(s)
- C E Leonard
- Department of Radiation Oncology, Swedish Medical Center, Englewood, Colorado 80110, USA
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Leonard CE, Chan DC, Chou TC, Kumar R, Bunn PA. Paclitaxel enhances in vitro radiosensitivity of squamous carcinoma cell lines of the head and neck. Cancer Res 1996; 56:5198-204. [PMID: 8912857] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Squamous cell carcinoma of the head and neck is the fourth most common cancer in the United States, and therapy for very advanced cases is relatively ineffective. Paclitaxel has activity against cancers of the breast, lung, prostate, cervix, and ovary. The activity of paclitaxel for squamous cell carcinoma of the head and neck is less certain, and results of its radiosensitization properties have been variable. The radiation responses of two squamous carcinomas, SCC-9 (oropharynx) and HEP-2 (larynx), were examined to determine the radiosensitizing potential of paclitaxel. In vitro exposures for 24 and 48 h with paclitaxel concentrations of 10(-4) to 6 x 10(-2) microg/ml were followed by irradiation of 0.1-10 Gy. Percent survival was calculated by colony count, and the paclitaxel-radiation interaction was quantitated by the median effect principle and the combination index method of Chou and Talalay. The paclitaxel-radiation combination resulted in multiphasic interactions in both 24 and 48 h paclitaxel pretreatment in SCC-9 and HEP-2 cell lines. In general there was slight synergism [combination index (CI) <1] at low dose-low effect levels (e.g., at a paclitaxel concentration of 0.002 microg/ml or lower and radiation of 0.1-0.3 Gy), moderate antagonism (CI >1) at median dose ranges and strong synergism (CI <<1) at high dose ranges (e.g., at a paclitaxel concentration of 0.012-0.06 microg/ml and radiation doses of 3-10 Gy), especially at a surviving fraction of <0.1, which is therapeutically relevant. The median effect principle and combination index method provided a simple way to quantitate the synergism or antagonism of a paclitaxel-radiation interaction under various conditions. This analysis demonstrated that paclitaxel-radiation synergy exists at doses that are readily achievable in the clinical scenario for both agents and that greater synergy occurred at high dose-high effect levels. These results suggest that the combination of both therapies should be explored further in clinical trials assessing the treatment of squamous cell carcinomas of the head and neck.
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Affiliation(s)
- C E Leonard
- Department of Radiation Oncology, Swedish Medical Center, Englewood, Colorado 80110, USA
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10
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Abstract
The dimensionality of the SCL-90-R was investigated in an acute, involuntarily committed adult psychiatric sample (N = 260) using common principal factor extraction and confirmatory factor analytic procedures. The findings show a large primary factor accounting for 42% of the variance. Confirmatory factor analyses failed to replicate the standardization data. These results are consistent with previous research suggesting a primary global distress factor. They raise questions of the validity of the SCL-90-R clinical profile from acute involuntarily hospitalized psychiatric adults.
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Affiliation(s)
- U K Rauter
- Department of Psychology, New Hampshire Hospital, Concord, NH 03301, USA
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11
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Leonard CE, Wood ME, Zhen B, Rankin J, Waitz DA, Norton L, Howell K, Sedlacek S. Does administration of chemotherapy before radiotherapy in breast cancer patients treated with conservative surgery negatively impact local control? J Clin Oncol 1995; 13:2906-15. [PMID: 8523054 DOI: 10.1200/jco.1995.13.12.2906] [Citation(s) in RCA: 57] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
PURPOSE To determine if a delay of irradiation to the intact breast for administration of adjuvant chemotherapy results in increased local recurrence in breast cancer. PATIENTS AND METHODS The records of 262 women with 264 cases of breast cancer were reviewed. Group I contained 105 patients treated with conservative surgery, chemotherapy, and radiotherapy. Group II contained 157 patients (used as a concurrent control) treated with conservative surgery and radiotherapy only. Eighty-nine percent of subjects in group I received all chemotherapy before radiotherapy. Fifty-eight percent of patients received hormone therapy. Seventy-one percent of patients had negative surgical margins, and 74% had negative lymph nodes. For group I, conservative surgery-radiotherapy intervals in months were less than 1 (five, 5%), > or = 1 to less than 3 (10, 9%), > or = 1 to less 6 (48, 46%), and > or = 6 (42, 40%), mean of 5. For group II, the intervals were less than 1 (20, 13%), > or = 1 to less than 3 (123, 79%), > or = 3 to less than 6 (11, 7%), and > or = 6 (two, 1%), mean of 1.5. RESULTS Thirty patients (11.5%) have disease recurrence (19 distant [6%] and 12 local [5%]). There were no significant differences in local recurrence (group I, four [4%]; group II, eight [5%]; difference not significant). There were no significant differences in local recurrence in any surgery-radiotherapy interval within each group. Although we found marginal increases in the percentage of local recurrences in group I patients (with prolonged surgery-radiotherapy intervals) who had positive margins, positive lymph nodes, and tumor size more than 2 cm versus group II (without prolonged surgery-radiotherapy intervals), these results were not significant. CONCLUSION We could not identify any surgery-radiotherapy interval that resulted in increased local recurrence if radiotherapy was delayed for administration of adjuvant chemotherapy in breast cancer patients. Because of the heterogenous population of breast cancer patients, our results also support the need for further study to determine the optimum integration of radiotherapy and chemotherapy in the management of the conservatively treated breast.
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Affiliation(s)
- C E Leonard
- Department of Radiation Oncology, Swedish Medical Center, Englewood, CO 80110, USA
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12
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Leonard CE, Waitz DA. Altered fractionation in radiation therapy for head and neck cancer. West J Med 1994; 160:456. [PMID: 8048234 PMCID: PMC1022494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
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13
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Hazuka MB, Burleson WD, Stroud DN, Leonard CE, Lillehei KO, Kinzie JJ. Multiple brain metastases are associated with poor survival in patients treated with surgery and radiotherapy. J Clin Oncol 1993; 11:369-73. [PMID: 8426215 DOI: 10.1200/jco.1993.11.2.369] [Citation(s) in RCA: 78] [Impact Index Per Article: 2.5] [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: 01/30/2023] Open
Abstract
PURPOSE A retrospective analysis was performed to evaluate the role of surgery in the management of patients with solitary and multiple brain metastases. PATIENTS AND METHODS Between 1980 and 1990, 46 patients underwent surgical resection of brain metastases at the University of Colorado Health Sciences Center. All but two patients received postoperative whole-brain radiotherapy to a median total dose of 30 Gy (range, 11.4 Gy to 50.0 Gy). Lung was the most common (56%) primary site and adenocarcinoma was the most common (46%) tumor histology. Twenty-eight of 46 patients (61%) had solitary metastases, while the remaining 18 patients had two or more foci. RESULTS The median survival of all 46 patients was 11 months, and the 1- and 2-year survival rates were 40% and 12%, respectively. Moderately severe to severe neurologic impairment at the time of diagnosis and the presence of multiple brain metastases were associated with a significantly poorer survival. In patients with solitary metastasis, gross total resection and adenocarcinoma tumor histology significantly prolonged survival, whereas primary tumor site, the presence of active extracranial disease, and radiation dose had no significant effect on survival. CONCLUSION These results are consistent with a recent randomized study supporting the role of surgery and whole-brain radiation therapy in the management of patients with solitary brain metastases. We would caution against the generalization of this concept to patients with two or more brain metastases.
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Affiliation(s)
- M B Hazuka
- Division of Radiation Oncology, University of Colorado Health Sciences Center, Denver
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Abstract
Tumor seeding of the mediastinoscopy tract has been described. Although it is a rare occurrence, it can present the radiation oncologist with a therapeutic dilemma. Two cases of mediastinoscopy scar recurrences are reported. Their response to treatment and a review of previous cases are included.
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Affiliation(s)
- E R Hoyer
- Department of Radiology, University of Colorado Health Sciences Center, Denver 80262
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