Medidata Blog
Accelerating Generalizability of Cancer Clinical Trial Results
Substantial research suggests that patients participating in cancer clinical trials of new therapies are a small and largely unrepresentative subset of the United States (US) population with cancer. Compared to the underlying US population with cancer, patients who enroll in cancer clinical trials are younger, otherwise healthier, wealthier, more often White, and less likely to live in rural regions.[[1],[2],[3],[4]] It’s estimated that results from ~5% of patients treated in US cancer clinical trials are extrapolated with little or no evidence to the remaining 95% of patients in the US.[[5],[6]] These findings beg the question: how generalizable to the population are the results of the pivotal clinical trials that inform care standards? And are these standards of care really the best therapies for all Americans with cancer?
For potentially life-saving therapies which also themselves pose a risk to life—like chemotherapy—generalizability of both patient attributes and their context of care is as important. Therapies like chemotherapy often have narrow therapeutic windows and defined cadence of administration. For this reason, treating patients who are known to metabolize drugs differently (related to age, comorbid illness, and concomitant medications), who have less socioeconomic reserve, and/or who live long distances from their healthcare providers (putting them at risk for missed doses) may also put them at risk for divergent outcomes, including toxicity without benefit.
The concern regarding clinical trial generalizability continues to be a focus of US healthcare policy and initiatives. As part of both Project Equity and the Cancer Moonshot initiative, the Food and Drug Administration have reiterated their interest in increasing the generalizability of clinical trials in an April 2022 draft guidance to industry.[[7]] The American Society of Clinical Oncology and the Association of Community Cancer Centers have collaborated to release a joint research statement outlining measures intended to increase the diversity of trial enrollees.[[8]] Some healthcare policy leaders have encouraged a common clinical trial taxonomy for race and ethnicity to facilitate nimble data transformations and comparisons; others have encouraged study of the resources needed to conduct trials among non-high income populations.[[9],[10]]
Research presented at ASCO in 2022 suggests that diversity in oncology clinical trial design may be sensitive to Medicaid coverage. A team from Cornell University and the University of Pennsylvania studied secular changes in enrollment of Black patients in Eastern Cooperative Oncology Group trials within 17 states before and after state-mandated clinical trial coverage over 2000-2019—relative to changes in other states. They found state-mandated Medicaid coverage of the routine costs of trial participation was associated with a short-term increase in the proportion of Black trial participants.[[11]] In an ecological study, a second research group found that as the numbers of Americans with Medicaid increased, so too did enrollment of Black patients in oncology trials. Studying patient enrollment in the Southwest Oncology Group (SWOG) clinical trial network, Unger and colleagues found that the Affordable Care Act Medicaid expansion was associated with a threefold increase in enrollment of black patients on SWOG trials.[[12]] These findings suggest that the federal Clinical Treatment Act mandating Medicaid to reimburse costs associated with clinical trial enrollment may be successful.
In addition to robust policy levers and recommendations to guide new efforts to increase cancer clinical trial success rate, perhaps something may also be learned from investigators and sites who have been successful in recruiting and retaining more representative patients. In prior research of >2,700 trial patients treated in one of 10 multi-site Cancer and Leukemia Group B cooperative group lung cancer clinical trials between 1990-2003, patient demographics varied according to attributes of the sites where patients enrolled.[[13]] Investigators categorized the 272 distinct accrual sites according to one of three mutually exclusive categories: academic, community, and Veteran Administration Hospital (VAH) and found that patients enrolled at VAHs were less likely to be White and more likely to live in neighborhoods with higher amounts of poverty.
More recent research presented at the 2022 ASCO Quality of Care Symposium supports the importance of trial accrual and treatment sites to the racial composition of cancer clinical trials.[[14]] Through secondary analysis of over 400,000 patients enrolled on nearly 3,000 clinical trials over 12 years and across multiple therapeutic areas, researchers found that participation by Black patients in trials varied by accrual and treatment sites. Taken together, these findings suggest further study of sites accruing and treating high numbers of traditionally under-represented patients may be informative in identifying explanatory factors like processes of care, catchment population, or combinations of both.
There is widespread agreement across federal agencies and national organizations that for cancer clinical trial results to be generalizable to the US population, trial participants’ attributes and treatment contexts need to mirror those of the country. A multifaceted approach including health policy experiments, infrastructure harmonization, and empirical research holds promise for improving the generalizability of cancer clinical trials and moving towards equitable cancer care in the US.
Learn more about Medidata's Intelligent Trials Diversity Module.
[1] Institute of Medicine. Delivering High-Quality Cancer Care: Charting a New Course for a System in Crisis. Washington, DC: The National Academies Press; 2013.
[2] Satariano WA, Silliman RA. Comorbidity: implications for research and practice in geriatric oncology. Crit Rev Oncol Hematol. 2003 Nov;48(2):239-48. doi: 10.1016/j.critrevonc.2003.08.002. PMID: 14607386.
[3] Unger JM, Barlow WE, Martin DP, et al. Comparison of survival outcomes among cancer patients treated in and out of clinical trials. J Natl Cancer Inst. 2014 Mar;106(3):dju002. doi: 10.1093/jnci/dju002. Epub 2014 Mar 13. PMID: 24627276; PMCID: PMC3982777.
[4] Sateren WB, Trimble EL, Abrams J et al. How sociodemographics, presence of oncology specialists, and hospital cancer programs affect accrual to cancer treatment trials. J Clin Oncol. 2002 Apr 15;20(8):2109-17. doi: 10.1200/JCO.2002.08.056. PMID: 11956272.
[5] Murthy VH, Krumholz HM, Gross CP. Participation in cancer clinical trials: race-, sex-, and age-based disparities. JAMA. 2004 Jun 9;291(22):2720-6. doi: 10.1001/jama.291.22.2720. PMID: 15187053.
[6] Tejeda HA, Green SB, Trimble EL, et al. Representation of African-Americans, Hispanics, and whites in National Cancer Institute cancer treatment trials. J Natl Cancer Inst. 1996 Jun 19;88(12):812-6. doi: 10.1093/jnci/88.12.812. PMID: 8637047.
[7]https://www.fda.gov/regulatory-information/search-fda-guidance-documents/diversity-plans-improve-enrollment-participants-underrepresented-racial-and-ethnic-populations, accessed 10/25/2022.
[8]Oyer RA, Hurley P, Boehmer L, et al. Increasing racial and ethnic diversity in cancer clinical trials: An American Society of Clinical Oncology and Association of Community Cancer Centers joint research statement. Journal of Clinical Oncology 2022 40:19, 2163-2171.
[9]Blumenthal D, James CV. A data infrastructure for clinical trial diversity. N Engl J Med 2022; 386:2355-2356. DOI: 10.1056/NEJMp2201433
[10] Armstrong K, Ritchie C. Research participation in marginalized communities - overcoming barriers. N Engl J Med 2022; 386:203-205. DOI: 10.1056/NEJMp2115621
[11] Takvorian SU, Chatterjee P, Mamtani R et al. Association between state Medicaid policies and accrual of Black participants to cancer clinical trials. J Clin Oncol 40, 2022 (suppl 16; abstr 1501)
[12] Unger JM, Xiao H, Vaidya R.The Medicaid expansion of the Affordable Care Act and participation of patients with Medicaid in cancer clinical trials. J Clin Oncol 40, 2022 (suppl 16; abstr 6505).
[13] Lamont EB, Landrum MB, Keating NL et al. Differences in clinical trial patient attributes and outcomes according to enrollment setting. J Clin Oncol, 2009; 28:215-221.
[14] Bebi T, Horovitz R, Blum K, et al. How granularity of data matters in understanding and accelerating racial diversity in U.S. clinical trials. Journal of Clinical Oncology 40, 2022 (suppl 28; abstr 88).