{"title":"社会经济弱势患者参与癌症临床试验帮助进行有针对性干预的风险模型。","authors":"Joseph M. Unger , Katherine Szarama","doi":"10.1016/j.cct.2024.107803","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>In patients with cancer, those with lower incomes are less likely to participate in clinical trials. A broad-based evaluation of variables that could contribute to this disparity has not been conducted.</div></div><div><h3>Methods</h3><div>We used data from Health Information National Trends Survey (HINTS) databases for survey years 2014, 2017, and 2020, the survey years that included questions about whether patients with cancer participated in a clinical trial. We examined 21 demographic, socioeconomic, behavioral, geographic, and health information questions. We derived a risk model to predict clinical trial participation using a training/validation approach with best subset selection and k-fold cross-validation. Logistic regression was used.</div></div><div><h3>Results</h3><div>We examined <em>N</em> = 1023 participants with household income <$75,000 (the U.S. median). In the training dataset (<em>n</em> = 614), a 5-variable model was identified including race/ethnicity, education, trust, anxiety/depression, and geographic locale. A quartile-level risk score was constructed based on the sum of adverse risk factors. In the validation cohort (<em>n</em> = 409), each increase in quartile level was associated with a 73 % increase in the odds of trial nonparticipation (OR = 1.73, 95 %-CI, 1.19–2.53, <em>p</em> = 0.004), indicating successful model validation. Among all individuals, trial participation rates decreased from 18.6 % to 7.5 % to 4.6 % to 2.8 %, respectively, as the number of adverse risk factors increased from 0 to 1 to 2 to 3 to 4–5.</div></div><div><h3>Conclusions</h3><div>We developed and validated a 5-variable risk model that identified a large set of lower-income individuals at lower risk of trial participation. These findings could aid in identification of patients who may benefit from additional support to navigate the treatment trial decision-making process.</div></div>","PeriodicalId":10636,"journal":{"name":"Contemporary clinical trials","volume":"149 ","pages":"Article 107803"},"PeriodicalIF":2.0000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cancer clinical trial participation in socioeconomically vulnerable patients; A risk model to aid in targeted interventions\",\"authors\":\"Joseph M. Unger , Katherine Szarama\",\"doi\":\"10.1016/j.cct.2024.107803\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>In patients with cancer, those with lower incomes are less likely to participate in clinical trials. A broad-based evaluation of variables that could contribute to this disparity has not been conducted.</div></div><div><h3>Methods</h3><div>We used data from Health Information National Trends Survey (HINTS) databases for survey years 2014, 2017, and 2020, the survey years that included questions about whether patients with cancer participated in a clinical trial. We examined 21 demographic, socioeconomic, behavioral, geographic, and health information questions. We derived a risk model to predict clinical trial participation using a training/validation approach with best subset selection and k-fold cross-validation. Logistic regression was used.</div></div><div><h3>Results</h3><div>We examined <em>N</em> = 1023 participants with household income <$75,000 (the U.S. median). In the training dataset (<em>n</em> = 614), a 5-variable model was identified including race/ethnicity, education, trust, anxiety/depression, and geographic locale. A quartile-level risk score was constructed based on the sum of adverse risk factors. In the validation cohort (<em>n</em> = 409), each increase in quartile level was associated with a 73 % increase in the odds of trial nonparticipation (OR = 1.73, 95 %-CI, 1.19–2.53, <em>p</em> = 0.004), indicating successful model validation. Among all individuals, trial participation rates decreased from 18.6 % to 7.5 % to 4.6 % to 2.8 %, respectively, as the number of adverse risk factors increased from 0 to 1 to 2 to 3 to 4–5.</div></div><div><h3>Conclusions</h3><div>We developed and validated a 5-variable risk model that identified a large set of lower-income individuals at lower risk of trial participation. These findings could aid in identification of patients who may benefit from additional support to navigate the treatment trial decision-making process.</div></div>\",\"PeriodicalId\":10636,\"journal\":{\"name\":\"Contemporary clinical trials\",\"volume\":\"149 \",\"pages\":\"Article 107803\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contemporary clinical trials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1551714424003860\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contemporary clinical trials","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1551714424003860","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Cancer clinical trial participation in socioeconomically vulnerable patients; A risk model to aid in targeted interventions
Background
In patients with cancer, those with lower incomes are less likely to participate in clinical trials. A broad-based evaluation of variables that could contribute to this disparity has not been conducted.
Methods
We used data from Health Information National Trends Survey (HINTS) databases for survey years 2014, 2017, and 2020, the survey years that included questions about whether patients with cancer participated in a clinical trial. We examined 21 demographic, socioeconomic, behavioral, geographic, and health information questions. We derived a risk model to predict clinical trial participation using a training/validation approach with best subset selection and k-fold cross-validation. Logistic regression was used.
Results
We examined N = 1023 participants with household income <$75,000 (the U.S. median). In the training dataset (n = 614), a 5-variable model was identified including race/ethnicity, education, trust, anxiety/depression, and geographic locale. A quartile-level risk score was constructed based on the sum of adverse risk factors. In the validation cohort (n = 409), each increase in quartile level was associated with a 73 % increase in the odds of trial nonparticipation (OR = 1.73, 95 %-CI, 1.19–2.53, p = 0.004), indicating successful model validation. Among all individuals, trial participation rates decreased from 18.6 % to 7.5 % to 4.6 % to 2.8 %, respectively, as the number of adverse risk factors increased from 0 to 1 to 2 to 3 to 4–5.
Conclusions
We developed and validated a 5-variable risk model that identified a large set of lower-income individuals at lower risk of trial participation. These findings could aid in identification of patients who may benefit from additional support to navigate the treatment trial decision-making process.
期刊介绍:
Contemporary Clinical Trials is an international peer reviewed journal that publishes manuscripts pertaining to all aspects of clinical trials, including, but not limited to, design, conduct, analysis, regulation and ethics. Manuscripts submitted should appeal to a readership drawn from disciplines including medicine, biostatistics, epidemiology, computer science, management science, behavioural science, pharmaceutical science, and bioethics. Full-length papers and short communications not exceeding 1,500 words, as well as systemic reviews of clinical trials and methodologies will be published. Perspectives/commentaries on current issues and the impact of clinical trials on the practice of medicine and health policy are also welcome.