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

> **NIH NIH U01** · CEDARS-SINAI MEDICAL CENTER · 2023 · $350,000

## Abstract

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 de...

## Key facts

- **NIH application ID:** 10884827
- **Project number:** 3U01CA232859-05S1
- **Recipient organization:** CEDARS-SINAI MEDICAL CENTER
- **Principal Investigator:** PATRICIA A. GANZ
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $350,000
- **Award type:** 3
- **Project period:** 2023-07-08 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10884827

## Citation

> US National Institutes of Health, RePORTER application 10884827, Advancing Analysis and Interpretation of Adverse Events and PROs in Cancer Clinical Trials (3U01CA232859-05S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10884827. Licensed CC0.

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