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.
/ Public Health Relevance Improved methods for analyzing and interpreting adverse event data would lead to a more accurate and precise understanding of patients' experiences with cancer treatment, including newly emerging treatment regimens. The development of an effective approach to identifying patients who are experiencing (or who are at risk of experiencing) treatment tolerability issues could trigger improved AE management and maximize treatment outcomes.
