Literature DB >> 31158272

Factors Associated With Age Disparities Among Cancer Clinical Trial Participants.

Ethan B Ludmir1, Walker Mainwaring2, Timothy A Lin1,2, Austin B Miller3, Amit Jethanandani1,4, Andres F Espinoza2, Jacob J Mandel2, Steven H Lin1, Benjamin D Smith1, Grace L Smith1, Noam A VanderWalde4, Bruce D Minsky1, Albert C Koong1, Thomas E Stinchcombe5, Reshma Jagsi6, Daniel R Gomez1,7, Charles R Thomas8,9, C David Fuller1.   

Abstract

Importance: Seminal investigation 2 decades ago alerted the oncology community to age disparities in participation in cooperative group trials; less is known about whether these disparities persist in industry-funded research. Objective: To characterize the age disparities among trial enrollees on randomized clinical trials (RCTs) of common cancers in clinical oncology and identify factors associated with wider age imbalances. Data Sources: Phase 3 clinical oncology RCTs were identified through ClinicalTrials.gov. Study Selection: Multiarm RCTs assessing a therapeutic intervention for patients with breast, prostate, colorectal, or lung cancer (the 4 most common cancer disease sites) were included. Data Extraction and Synthesis: Trial data were extracted from ClinicalTrials.gov. Trial screening and parameter identification were independently performed by 2 individuals. Data were analyzed in 2018. Main Outcomes and Measures: The difference in median age (DMA) between the trial participant median age and the population-based disease-site-specific median age was determined for each trial.
Results: Three hundred two trials met inclusion criteria. The trials collectively enrolled 262 354 participants; 249 trials (82.5%) were industry-funded. For all trials, the trial median age of trial participants was a mean of 6.49 years younger than the population median age (95% CI, -7.17 to -5.81 years; P < .001). Age disparities were heightened among industry-funded trials compared with non-industry-funded trials (mean DMA, -6.84 vs -4.72 years; P = .002). Enrollment criteria restrictions based on performance status or age cutoffs were associated with age disparities; however, industry-funded trials were not more likely to use these enrollment restrictions than non-industry-funded trials. Age disparities were also larger among trials that evaluated a targeted systemic therapy and among lung cancer trials. Linear regression modeling revealed a widening gap between trial and population median ages over time at a rate of -0.19 years annually (95% CI, -0.37 to -0.01 years; P = .04). Conclusions and Relevance: Age disparities between trial participants and the incident disease population are pervasive across trials and appear to be increasing over time. Industry sponsorship of trials is associated with heightened age imbalances among trial participants. With an increasing role of industry funding among cancer trials, efforts to understand and address age disparities are necessary to ensure generalizability of trial results as well as equity in trial access.

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Year:  2019        PMID: 31158272      PMCID: PMC6547133          DOI: 10.1001/jamaoncol.2019.2055

Source DB:  PubMed          Journal:  JAMA Oncol        ISSN: 2374-2437            Impact factor:   31.777


  51 in total

1.  Toxicity and outcomes in older versus younger patients treated with trimodality therapy for locally advanced rectal cancer.

Authors:  J Karen Wong; Elizabeth Handorf; Douglas Lee; Rishi Jain; Eddie Zhang; Harry S Cooper; Jeffrey M Farma; Efrat Dotan; Joshua E Meyer
Journal:  J Geriatr Oncol       Date:  2020-05-04       Impact factor: 3.599

2.  Sex-Based Disparities Among Cancer Clinical Trial Participants.

Authors:  Ethan B Ludmir; C David Fuller; Shalini Moningi; Walker Mainwaring; Timothy A Lin; Austin B Miller; Amit Jethanandani; Andres F Espinoza; Vivek Verma; Benjamin D Smith; Grace L Smith; Noam A VanderWalde; Emma B Holliday; B Ashleigh Guadagnolo; Thomas E Stinchcombe; Reshma Jagsi; Daniel R Gomez; Bruce D Minsky; Claus Rödel; Emmanouil Fokas
Journal:  J Natl Cancer Inst       Date:  2020-02-01       Impact factor: 13.506

3.  Age no bar: A CIBMTR analysis of elderly patients undergoing autologous hematopoietic cell transplantation for multiple myeloma.

Authors:  Pashna N Munshi; David Vesole; Artur Jurczyszyn; Jan Maciej Zaucha; Andrew St Martin; Omar Davila; Vaibhav Agrawal; Sherif M Badawy; Minoo Battiwalla; Saurabh Chhabra; Edward Copelan; Mohamed A Kharfan-Dabaja; Nosha Farhadfar; Siddhartha Ganguly; Shahrukh Hashmi; Maxwell M Krem; Hillard M Lazarus; Ehsan Malek; Kenneth Meehan; Hemant S Murthy; Taiga Nishihori; Rebecca L Olin; Richard F Olsson; Jeffrey Schriber; Sachiko Seo; Gunjan Shah; Melhem Solh; Jason Tay; Shaji Kumar; Muzaffar H Qazilbash; Nina Shah; Parameswaran N Hari; Anita D'Souza
Journal:  Cancer       Date:  2020-09-23       Impact factor: 6.860

4.  Tracking the Nonenrolled: Lung Cancer Screening Patterns Among Individuals not Accrued to a Clinical Trial.

Authors:  David E Gerber; Heidi A Hamann; Claudia Chavez; Olivia Dorsey; Noel O Santini; Travis Browning; Cristhiaan D Ochoa; Joyce Adesina; Vijaya Subbu Natchimuthu; Eric Steen; Hong Zhu; Simon J Craddock Lee
Journal:  Clin Lung Cancer       Date:  2020-02-26       Impact factor: 4.785

5.  Decreasing incidence of upper age restriction enrollment criteria among cancer clinical trials.

Authors:  Ethan B Ludmir; Ishwaria M Subbiah; Walker Mainwaring; Austin B Miller; Timothy A Lin; Amit Jethanandani; Andres F Espinoza; Jacob J Mandel; Penny Fang; Benjamin D Smith; Grace L Smith; Chelsea C Pinnix; Mina S Sedrak; Gretchen G Kimmick; Thomas E Stinchcombe; Reshma Jagsi; Charles R Thomas; C David Fuller; Noam A VanderWalde
Journal:  J Geriatr Oncol       Date:  2019-11-08       Impact factor: 3.599

6.  Disparities in older adult accrual to cancer trials: Analysis from the alliance for clinical trials in oncology (A151736).

Authors:  Noam A VanderWalde; Travis Dockter; Daniel V Wakefield; Daniel Satele; Jeff Sloan; Reshma Jagsi; Stuart M Lichtman; Rachel A Freedman; Jacqueline M Lafky; Hyman Muss; Harvey Jay Cohen; Jennifer Le-Rademacher; Aminah Jatoi
Journal:  J Geriatr Oncol       Date:  2021-08-04       Impact factor: 3.599

7.  Real-world evaluation of the impact of radiotherapy and chemotherapy in elderly patients with glioblastoma based on age and performance status.

Authors:  Karine A Al Feghali; Samantha M Buszek; Hesham Elhalawani; Neil Chevli; Pamela K Allen; Caroline Chung
Journal:  Neurooncol Pract       Date:  2020-10-14

8.  Transparency in reporting of phase 3 cancer clinical trial results.

Authors:  Roshal R Patel; Vivek Verma; Clifton D Fuller; Zachary R McCaw; Ethan B Ludmir
Journal:  Acta Oncol       Date:  2020-12-13       Impact factor: 4.089

9.  Apples and Oranges? Considerations for EHR-Based Analyses Aggregating Data From Interventional Clinical Trials and Point-of-Care Encounters in Oncology.

Authors:  Jessica A Lavery; Margaret K Callahan; Katherine S Panageas
Journal:  JCO Clin Cancer Inform       Date:  2021-01

10.  Sponsor-involved statistical analyses in Phase III cancer clinical trials.

Authors:  Joseph Abi Jaoude; Ramez Kouzy; Bruce D Minsky; Clifton David Fuller; Ying Yuan; Kim-Anh Do; Cullen M Taniguchi; Ethan B Ludmir
Journal:  Int J Cancer       Date:  2020-07-09       Impact factor: 7.396

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