Program Official

Principal Investigator

Robert J
Gray
Awardee Organization

Dana-Farber Cancer Inst
United States

Fiscal Year
2023
Activity Code
U01
Early Stage Investigator Grants (ESI)
Not Applicable
Project End Date

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)

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 TherapyGeneral (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.

Publications

  • Peipert JD, Hays RD, Cella D. Likely change indexes improve estimates of individual change on patient-reported outcomes. Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation. 2023 May;32(5):1341-1352. Epub 2022 Aug 3. PMID: 35921034
  • Obeng-Gyasi S, Graham N, Kumar S, Lee JW, Jacobus S, Weiss M, Cella D, Zhao F, Ip EH, O'Connell N, Hong F, Peipert DJ, Gareen IF, Timsina LR, Gray R, Wagner LI, Carlos RC. Examining allostatic load, neighborhood socioeconomic status, symptom burden and mortality in multiple myeloma patients. Blood cancer journal. 2022 Apr 1;12(4):53. PMID: 35365604