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

推进癌症临床试验中不良事件和 PRO 的分析和解释

• 批准号: 10884827
• 负责人: PATRICIA A. GANZ
• 金额: $ 35万
• 依托单位: CEDARS-SINAI MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-08 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10884827
• 关键词: Adverse event; Advocate; Benchmarking; CYP2D6 gene; Clinical; Clinical Trials; Collaborations; Common Terminology Criteria for Adverse Events; Data; Data Collection; Decision Making; Evaluation; Focus Groups; Funding; Future; Genotype; Health Professional; Immunotherapy; Individual; Integration Host Factors; Measurement; Measures; Methods; Modeling; National Surgical Adjuvant Breast and Bowel Project; Oncology; Outcome; Patient Outcomes Assessments; Patients; Performance; Phase III Clinical Trials; Plasma; Postmenopause; Prediction of Response to Therapy; Qualitative Evaluations; Randomized; Reporting; Research; Sampling; Symptoms; Tamoxifen; Testing; Time; Toxic effect; Treatment-related toxicity; Update; Visualization; Voice; Woman; Work; cancer clinical trial; cancer therapy; experience; hormone therapy; indexing; malignant breast neoplasm; multidisciplinary; novel; novel strategies; predictive modeling; programs; recruit; risk prediction model; statistical center; tool; treatment trial

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.

摘要

项目成果

Applying the Toxicity Index to Patient-Reported Symptom Data: An Example Using the European Organization for Research and Treatment of Cancer Colorectal Cancer-Specific Quality of Life Questionnaire.

将毒性指数应用于患者报告的症状数据：使用欧洲癌症研究和治疗组织结直肠癌特定生活质量调查问卷的示例。

• DOI: 10.1016/j.clinthera.2021.05.011
• 发表时间: 2021
• 期刊: Clinical therapeutics
• 影响因子: 3.2
• 作者: Hays,RonD;Ganz,PatriciaA;Spritzer,KarenL;Rogatko,André
• 通讯作者: Rogatko,André

Evaluating the Association of Adverse Events and Patient-Reported Symptoms to Endocrine Therapy Tolerability.

评估不良事件和患者报告的症状与内分泌治疗耐受性的关联。

• DOI: 10.1200/jco.21.02387
• 发表时间: 2022
• 期刊: Journal of clinical oncology : official journal of the American Society of Clinical Oncology
• 作者: Henry,NLynn;Rogatko,André;Ganz,PatriciaA
• 通讯作者: Ganz,PatriciaA