Analysis of ECOG-ACRIN adverse event data to optimize strategies for the longitudinal assessment of tolerability in the context of evolving cancer treatment paradigms (EVOLV)

项目摘要 EVOLV提出提供先进的标准化方法，用于评估、监测、分析和 报告接受癌症治疗的个体经历的不良事件（AE）。这些方法将 利用NCI通用术语标准的患者报告结局版本的潜力， 不良事件（PRO-CTCAETM），以提供先前无法获得的患者对以下药物耐受性的观点 治疗（包括靶向药物、免疫治疗，以及其他正在发展的治疗， 不良事件的严重程度、时间和轨迹鲜为人知）。这些信息将帮助供应商更好地 识别并支持存在治疗中止、剂量减少和治疗延迟风险的患者。 具体而言，本研究旨在：1）对试验中的CTCAE和PRO-CTCAE数据进行纵向分析 在ECOG-ACRIN癌症研究小组内进行，使用传统和创新策略， 检查AE轨迹，并制定新的报告标准，以反映 时间; 2）检查治疗依从性和中止的PRO-CTCAE和CTCAE预测因子;以及3） 验证GP 5的更广泛的预测价值，这是癌症治疗功能评估中的一个单项， 一般（FACT-G）显示可预测接受乳腺癌治疗的女性的早期治疗中止 芳香酶抑制剂。本研究还将探索PRO-CTCAE评分的两种新测量模型， CTCAE分级：包括症状共现和累积负荷指数的表型模型 (CBI)用于表征患者随时间累积的负担量。分析将包括 人口因素和保险状况，以确定潜在的差距。

Project Summary EVOLV proposes to deliver sophisticated and standardized methods for assessing, monitoring, analyzing, and reporting adverse events (AEs) experienced by individuals undergoing cancer treatment. These methods will harness the potential of the patient-reported outcomes version of the NCI Common Terminology Criteria for Adverse Events (PRO-CTCAETM) to provide previously unavailable patient perspectives on the tolerability of treatments (including targeted agents, immunotherapies, and other evolving treatments for which the type, severity, timing, and trajectory of adverse events is less known). Such information will help providers better identify and support patients at risk for treatment discontinuation, dose reductions, and treatment delays. Specifically, this study aims to: 1) perform longitudinal analyses of CTCAE and PRO-CTCAE data from trials conducted within the ECOG-ACRIN Cancer Research Group, using traditional and innovative strategies to examine AE trajectories and to produce a new reporting standard that reflects severity and fluctuations over time; 2) examine PRO-CTCAE and CTCAE predictors of treatment adherence and discontinuation; and 3) validate the broader predictive value of GP5, a single item from the Functional Assessment of Cancer Therapy- General (FACT-G) shown to predict early treatment discontinuation among women with breast cancer taking aromatase inhibitors. The study will also explore two novel measurement models for PRO-CTCAE scores and CTCAE grades: a phenotypic model including co-occurrence of symptoms and a cumulative burden index (CBI) for characterizing the quantity of burden accumulated by patients over time. Analyses will include demographic factors and insurance status to identify potential disparities.