Are Pivotal Clinical Trials for Drugs Approved for Leukemias and Multiple Myeloma Representative of the Population at Risk?. Issue 32 (10th November 2022) - Casey, Mycal; Odhiambo, Lorriane; Aggarwal, Nidhi; Shoukier, Mahran; Garner, Jamani; Islam, K.M.; Cortes, Jorge E.
Abstract : PURPOSE: There are significant disparities in care and outcomes for patients with leukemias and multiple myeloma (MM). To evaluate the extent to which clinical trials (CTs) match the demographic and geographic diversity of populations affected by leukemias and MM. METHODS: CTs leading to drug approval were identified from the US Food and Drug Administration databases. Demographic and geographic data were collected from ClinicalTrials.gov and primary manuscripts. Standard descriptive statistics were used to summarize the data in frequencies and proportions, including 95% CIs, by race, ethnicity, sex, and malignancy subtypes. RESULTS: A total of 41 (67.2%) trials leading to drug approval reported data on race and 20 (48.8%) on ethnicity. These trials included 13, 731 patients, of whom 11, 209 (81.6%) were White. Among minorities, Asian-Pacific Islanders and Blacks had the highest representation in chronic myeloid leukemia, 147 (12.7%) and 61 (5.3%), and lowest in chronic lymphocytic leukemia, 55 (3%) and 20 (1.1%), respectively. Proportions for Blacks, Native Americans, and Hispanics were significantly low, reflecting under-representation in trials compared with the proportion in the general population. Females were also under-represented in acute myeloid leukemia (44.7% v 60.5%, P < .0001), and males in MM (55.3% v 60.2%, P < .0001) and chronic myeloid leukemia (55.2% v 62.9%, P < .0001). The geographic distribution of trials showed inadequate regional and state participation compared with mortality for all malignancies except MM. CONCLUSION: There are significant demographic and geographic under-representation and imbalances in pivotal CTs leading to drug approvals for leukemias and MM compared with the population affected. These disparities need to be addressed to make results applicable to all relevant populations.