Perez Edith A, Jaffee Elizabeth M, Whyte John, Boyce Cheryl A, Carpten John D, Lozano Guillermina, Williams Raymond M, Winkfield Karen M, Bernstein David, Poblete Sung
Division of Hematology and Oncology, Mayo Clinic, Jacksonville, FL, United States.
Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, United States.
JMIR Cancer. 2021 Sep 23;7(3):e25621. doi: 10.2196/25621.
Racial and ethnic diversity in clinical trials for cancer treatment is essential for the development of treatments that are effective for all patients and for identifying potential differences in toxicity between different demographics. Mining of social media discussions about clinical trials has been used previously to identify patient barriers to enrollment in clinical trials; however, a comprehensive breakdown of sentiments and barriers by various racial and ethnic groups is lacking.
The aim of this study is to use an innovative methodology to analyze web-based conversations about cancer clinical trials and to identify and compare conversation topics, barriers, and sentiments between different racial and ethnic populations.
We analyzed 372,283 web-based conversations about cancer clinical trials, of which 179,339 (48.17%) of the discussions had identifiable race information about the individual posting the conversations. Using sophisticated machine learning software and analyses, we were able to identify key sentiments and feelings, topics of interest, and barriers to clinical trials across racial groups. The stage of treatment could also be identified in many of the discussions, allowing for a unique insight into how the sentiments and challenges of patients change throughout the treatment process for each racial group.
We observed that only 4.01% (372,283/9,284,284) of cancer-related discussions referenced clinical trials. Within these discussions, topics of interest and identified clinical trial barriers discussed by all racial and ethnic groups throughout the treatment process included health care professional interactions, cost of care, fear, anxiety and lack of awareness, risks, treatment experiences, and the clinical trial enrollment process. Health care professional interactions, cost of care, and enrollment processes were notably discussed more frequently in minority populations. Other minor variations in the frequency of discussion topics between ethnic and racial groups throughout the treatment process were identified.
This study demonstrates the power of digital search technology in health care research. The results are also valuable for identifying the ideal content and timing for the delivery of clinical trial information and resources for different racial and ethnic groups.
癌症治疗临床试验中的种族和民族多样性对于开发对所有患者都有效的治疗方法以及识别不同人口统计学群体之间潜在的毒性差异至关重要。此前，挖掘社交媒体上关于临床试验的讨论已被用于识别患者参与临床试验的障碍；然而，目前缺乏按不同种族和民族群体对情绪和障碍进行的全面分类。
本研究的目的是使用一种创新方法来分析基于网络的关于癌症临床试验的对话，并识别和比较不同种族和民族人群之间的对话主题、障碍和情绪。
我们分析了372,283条基于网络的关于癌症临床试验的对话，其中179,339条（48.17%）讨论包含了发布对话者的可识别种族信息。通过使用先进的机器学习软件和分析方法，我们能够识别不同种族群体的关键情绪和感受、感兴趣的主题以及临床试验的障碍。在许多讨论中还能确定治疗阶段，从而对每个种族群体在整个治疗过程中患者的情绪和挑战如何变化有独特的见解。
我们观察到，与癌症相关的讨论中只有4.01%（372,283/9,284,284）提及了临床试验。在这些讨论中，所有种族和民族群体在整个治疗过程中感兴趣的主题和确定的临床试验障碍包括与医护人员的互动、护理费用、恐惧、焦虑和缺乏认知、风险、治疗经历以及临床试验入组过程。少数族裔人群对与医护人员的互动、护理费用和入组过程的讨论明显更为频繁。在整个治疗过程中，我们还发现了不同种族和民族群体在讨论主题频率上的其他细微差异。
本研究证明了数字搜索技术在医疗保健研究中的作用。研究结果对于为不同种族和民族群体确定临床试验信息和资源的理想内容及提供时机也具有重要价值。
