Advancing Analysis and Interpretation of Adverse Events and PROs in Cancer Clinical Trials

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ABSTRACT In this application and program of research, we will collaborate with the NRG Oncology Statistical Center to develop analytic and graphical strategies to investigate novel methods for assessing treatment tolerability, as well as to model new approaches for data presentation using data from randomized NSABP trials that contain both Common Terminology Criteria for Adverse Events (CTCAE) data and high-quality patient reported outcomes (PRO) data. We have applied these new analytic approaches and other methods to NSABP and NRG Oncology phase III clinical trials that include PRO-CTCAE items to assess treatment toxicity associated with immunotherapy and other treatments. During the first four years of the funding period, we developed a novel summary measure, the toxicity index (TI), to discriminate patients based on their overall toxicity experiences as assessed by AE grades according to CTCAE and PRO-CTCAE. TI accounts for all observed toxicity grades rather than only the most severe one, as is conventionally done. Because of its sensitivity to differences in the overall toxicity, we showed that the TI can identify predictors of treatment-related toxicity better than conventional summary scores such as max grade and average grade. In this program of research, we plan to (1) apply our methods for evaluation of endocrine therapy toxicity by use of PRO data to associations between CYP2D6 genotype and tamoxifen discontinuation in the NSABP P-1 clinical trial using plasma samples for CYP2D6 genotyping that are expected within the next six months, (2) continue our analysis of the feasibility of frequent assessment of ePRO data test the added value of weekly measurements of ePROs relative to data collection of ePROs every cycle using clinician’s CTCAE assessment as a benchmark, (3) further evaluate and disseminate the Breast Cancer Symptom Explorer visualization online tool by updating the content, functionality, technical features by returning to original focus groups and recruiting additional focus groups for further qualitative evaluation, (4) continue our analysis of symptom trajectories among postmenopausal women by exploring patient host factors associated with membership in the individual trajectories and how these impact treatment discontinuation and other outcomes, (5) continue our work on developing and building dynamic risk prediction models for treatment discontinuation and efficacy using longitudinal PROs, clinician’s assessed CTCAE, and baseline clinical and demographic data from the NSABP B-35 phase III clinical trial. We will test the added value of including longitudinal clinician’s assessed CTCAE data in addition to longitudinal PROs in the predictive performance of the dynamic model, assess and compare the predictive performance when CTCAE are summarized with our novel TI relative to average grade, and max grade, and build real-time calculators based on these new predictive models in Shiny app to aid healthcare professionals in decision making.