Community Oncology and Prevention Trials Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland.
Cancer. 2021 May 15;127(10):1630-1637. doi: 10.1002/cncr.33399. Epub 2021 Feb 19.
Clinical trial patient accrual continues to be challenging despite the identification of multiple physician, patient, and system barriers. Expanded collection of demographic data, including socioeconomic status (employment, income, education) and comorbidities, can enhance our understanding of the identified barriers, inform the development of interventions to overcome these barriers, and recognize their impact on treatment outcomes. A clinical trials screening tool was developed to collect expanded demographic data and barriers to trial enrollment; it has been implemented in the National Cancer Institute Clinical Oncology Research Program. The purpose of this article is to describe the development and implementation of the tool and to share information obtained during the first 43 months of its use.
There were 19,373 entries collected; 74% of those screened enrolled in a clinical trial. Demographic characteristics were compared between those screened and those enrolled. They varied significantly between the groups.
Reasons for nonenrollment included ineligibility (50%), eligible but declined (47%), eligible but physician declined to offer participation (2%), and eligible but the study was suspended (1%). The most common reasons for ineligibility were failure to meet the protocol-specific stage of cancer, the presence of comorbidities, and the symptom-eligibility score was not met. The most common reason for eligible patients declining participation was that they had no desire to participate in research.
The tool provides valuable information about the characteristics of individuals who are screened and enrolled in National Cancer Institute-sponsored trials, as well as about barriers to enrollment in trials. The data also inform protocol development and interventions at the patient, provider, and institutional level.
尽管已经确定了多种医生、患者和系统障碍，但临床试验患者的入组仍然具有挑战性。扩展收集人口统计学数据，包括社会经济地位（就业、收入、教育）和合并症，可以增强我们对已确定障碍的理解，为克服这些障碍的干预措施的制定提供信息，并认识到它们对治疗结果的影响。已经开发了一种临床试验筛选工具来收集扩展的人口统计学数据和试验入组障碍；它已在国家癌症研究所临床肿瘤学研究计划中实施。本文的目的是描述该工具的开发和实施，并分享其使用的头 43 个月中获得的信息。
共收集了 19373 条记录；74%的筛选者入组了临床试验。对筛选者和入组者的人口统计学特征进行了比较。两组之间存在显著差异。
未入组的原因包括不符合条件（50%）、符合条件但拒绝（47%）、符合条件但医生拒绝提供参与（2%）以及符合条件但研究暂停（1%）。不符合条件的最常见原因是不符合方案特定的癌症分期、存在合并症以及症状合格评分未达到要求。符合条件的患者拒绝参与的最常见原因是他们没有参与研究的愿望。
该工具提供了有关在国家癌症研究所资助的试验中筛选和入组的个体特征以及试验入组障碍的有价值的信息。该数据还为患者、提供者和机构层面的方案制定和干预措施提供了信息。
