BACKGROUND/AIMS Determining whether clinical trial findings are applicable to diverse, real-world patient populations can be challenging when the full demographic characteristics of enrolled patients are not consistently reported. Here, we present the results of a descriptive analysis of racial and ethnic demographic information for patients in Bristol Myers Squibb (BMS)-sponsored oncology trials in the United States (US) and describe factors associated with increased patient diversity. METHODS BMS-sponsored oncology trials conducted at US sites with study enrollment dates between 1 January 2013 and 31 May 2021 were analyzed. Patient race/ethnicity information was self-reported in case report forms. As principal investigators (PIs) did not report their own race/ethnicity, a deep-learning algorithm (ethnicolr) was used to predict PI race/ethnicity. Trial sites were linked to counties to understand the role of county-level demographics. The impact of working with patient advocacy and community-based organizations to increase diversity in prostate cancer trials was analyzed. The magnitude of associations between patient diversity and PI diversity, US county demographics, and recruitment interventions in prostate cancer trials were assessed by bootstrapping. RESULTS A total of 108 trials for solid tumors were analyzed, including 15,763 patients with race/ethnicity information and 834 unique PIs. Of the 15,763 patients, 13,968 (89%) self-reported as White, 956 (6%) Black, 466 (3%) Asian, and 373 (2%) Hispanic. Among 834 PIs, 607 (73%) were predicted to be White, 17 (2%) Black, 161 (19%) Asian, and 49 (6%) Hispanic. A positive concordance was observed between Hispanic patients and PIs (mean = 5.9%; 95% confidence interval (CI) = 2.4, 8.9), a less positive concordance between Black patients and PIs (mean = 1.0%; 95% CI = -2.7, 5.5), and no concordance between Asian patients and PIs. Geographic analyses showed that more non-White patients enrolled in study sites in counties with higher proportions of non-White residents (e.g. a county population that was 5%-30% Black had 7%-14% more Black patients enrolled in study sites). Following purposeful recruitment efforts in prostate cancer trials, 11% (95% CI = 7.7, 15.3) more Black men enrolled in prostate cancer trials. CONCLUSION Most patients in these clinical trials were White. PI diversity, geographic diversity, and recruitment efforts were related to greater patient diversity. This report constitutes an essential step in benchmarking patient diversity in BMS US oncology trials and enables BMS to understand which initiatives may increase patient diversity. While complete reporting of patient characteristics such as race/ethnicity is critical, identifying diversity improvement tactics with the highest impact is essential. Strategies with the greatest concordance to clinical trial patient diversity should be implemented to make meaningful improvements to the diversity of clinical trial populations.

中文翻译：

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在百时美施贵宝赞助的美国肿瘤临床试验中增加患者多样性的数据驱动策略。

背景/目的 当入组患者的完整人口统计特征未得到一致报告时，确定临床试验结果是否适用于多样化的现实世界患者群体可能具有挑战性。在此，我们介绍了对百时美施贵宝 (BMS) 在美国 (US) 赞助的肿瘤学试验中患者的种族和民族人口统计信息进行描述性分析的结果，并描述了与患者多样性增加相关的因素。方法 对 BMS 赞助的在美国站点进行的肿瘤学试验进行了分析，研究入组日期为 2013 年 1 月 1 日至 2021 年 5 月 31 日。患者种族/民族信息在病例报告表中自我报告。由于主要研究者 (PI) 没有报告自己的种族/民族，因此使用深度学习算法 (ethnicolr) 来预测 PI 种族/民族。试验地点与县相关联，以了解县级人口统计数据的作用。分析了与患者倡导者和社区组织合作增加前列腺癌试验多样性的影响。通过引导法评估了患者多样性和 PI 多样性、美国县人口统计数据以及前列腺癌试验中的招募干预措施之间的关联程度。结果 总共分析了 108 项实体瘤试验，包括 15,763 名具有种族/民族信息的患者和 834 名独特的 PI。在 15,763 名患者中，13,968 名 (89%) 自称是白人，956 名 (6%) 是黑人，466 名 (3%) 亚裔和 373 名 (2%) 西班牙裔。在 834 名 PI 中，607 名 (73%) 预计为白人，17 名 (2%) 为黑人，161 名 (19%) 为亚裔，49 名 (6%) 为西班牙裔。西班牙裔患者和 PI 之间存在正一致性（平均值 = 5.9%；95% 置信区间 (CI) = 2.4、8.9），黑人患者和 PI 之间的正一致性较差（平均值 = 1.0%；95% CI = -2.7） ，5.5），并且亚洲患者和 PI 之间没有一致性。地理分析显示，在非白人居民比例较高的县，注册研究中心的非白人患者较多（例如，黑人占 5%-30% 的县，注册研究中心的黑人患者要多 7%-14%） 。在前列腺癌试验中进行有目的的招募工作后，参加前列腺癌试验的黑人男性增加了 11% (95% CI = 7.7, 15.3)。结论 这些临床试验中的大多数患者是白人。PI 多样性、地域多样性和招募工作与更大的患者多样性相关。该报告是在 BMS 美国肿瘤学试验中对患者多样性进行基准测试的重要一步，并使 BMS 能够了解哪些举措可以增加患者多样性。虽然完整报告种族/民族等患者特征至关重要，但确定影响最大的多样性改进策略也至关重要。应实施与临床试验患者多样性最一致的策略，以对临床试验人群的多样性做出有意义的改进。