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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)

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)
分析 ECOG-ACRIN 不良事件数据,以优化在不断发展的癌症治疗范式 (EVOLV) 背景下纵向耐受性评估的策略
批准号:
10884567
负责人:
ROBERT J GRAY
金额:
$35.0万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-07-10 至 2024-08-31

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Project Summary 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.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1007/s00520-022-07484-7
发表时间: 2022-12-16
期刊: Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
影响因子: --
作者: []
通讯作者:
DOI: 10.1002/cncr.33992
发表时间: 2021-12-15
期刊: Cancer
影响因子: 6.2
作者: [Ip EH, Saldana S, Miller KD, Carlos RC, Gareen IF, Sparano JA, Graham N, Zhao F, Lee JW, O'Connell NS, Cella D, Peipert JD, Gray RJ, Wagner LI]
通讯作者: Wagner LI
DOI: 10.1007/s00520-021-06700-0
发表时间: 2022-05
期刊: SUPPORTIVE CARE IN CANCER
影响因子: 3.1
作者: [Peipert, John Devin, Smith, Mary Lou]
通讯作者: Smith, Mary Lou
Statistics Core
  • 批准号:
    10116337
  • 项目类别:
  • 资助金额:
    $339.98万
  • 财政年份:
    2014
  • 负责人:
    ROBERT J GRAY
  • 依托单位:
Administrative Core
  • 批准号:
    10359065
  • 项目类别:
  • 资助金额:
    $115.18万
  • 财政年份:
    2014
  • 负责人:
    ROBERT J GRAY
  • 依托单位:
海外基金