A practical toolkit with recommendations for analysing and visualising patient-reported outcomes in early phase dose-finding oncology trials (OPTIMISE-AR)

Emily Alger, Antoine Regnault, Amylou C Dueck, Madeline Pe, Michael J Grayling, Melanie J Calvert, Aaron R Hansen, Olga Kholmanskikh, Julia Lai-Kwon, J Jack Lee, Anna Minchom, Yu Qiao, Khadija Rerhou Rantell, Jessica Roydhouse, Claire Snyder, Stefan N Symeonides, Nolan A Wages, Roger Wilson, Christina Yap
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Abstract

Patient-reported outcomes (PROs) are increasingly recognised for their role in assessing tolerability in dose-finding oncology trials (DFOTs). However, analysis and reporting of PRO data within DFOTs are often unclear and inconsistent. OPTIMISE-AR (Incorporating Patient-Reported Outcomes in Dose-Finding Trials–Analysis Recommendations) establishes a practical toolkit supporting the statistical analysis, visualisation, and reporting of PRO data within DFOT publications. International, multidisciplinary, cross-sector statistical analysis and data visualisation working groups identified analytical and visualisation approaches for PROs data, addressing key DFOT PRO research objectives. Informed by existing literature, case studies and recommendations are provided in this Policy Review for analysing binary, ordinal, and continuous PRO data to assess tolerability across doses and timepoints, and to integrate PROs into interim and final dose-decision processes. The OPTIMISE-AR toolkit is structured around four methodological domains aligned with key DFOT PRO research objectives, providing statistical analysis and data visualisation recommendations for (1) PRO endpoints across timepoints, (2) PRO endpoints between timepoints, (3) time-to-event PRO endpoints, and (4) PRO endpoints for formal dose-decision making in model-based dose-finding designs. As PROs have an increasing role in tolerability assessment, this Policy Review promotes analysis and data visualisation of PRO data, facilitating robust, patient-centred tolerability conclusions and supporting the broader development of tolerable and effective treatments.
一个实用的工具包,用于分析和可视化早期剂量发现肿瘤学试验中患者报告的结果(optimize - ar)
在剂量寻找肿瘤试验(DFOTs)中,患者报告结果(PROs)在评估耐受性方面的作用日益得到认可。然而,DFOTs中PRO数据的分析和报告往往不明确和不一致。optimize - ar(将患者报告的结果纳入剂量寻找试验分析建议)建立了一个实用的工具包,支持DFOT出版物中PRO数据的统计分析、可视化和报告。国际、多学科、跨部门的统计分析和数据可视化工作组确定了PRO数据的分析和可视化方法,解决了DFOT PRO研究的关键目标。根据现有文献,本政策审查提供了案例研究和建议,用于分析二元、有序和连续的PRO数据,以评估跨剂量和时间点的耐受性,并将PRO纳入中期和最终剂量决策过程。优化- ar工具包围绕四个方法领域构建,与关键的DFOT PRO研究目标一致,为(1)跨时间点的PRO端点,(2)时间点之间的PRO端点,(3)时间到事件的PRO端点,以及(4)基于模型的剂量发现设计中的正式剂量决策的PRO端点提供统计分析和数据可视化建议。由于PRO在耐受性评估中的作用越来越大,本政策审查促进了PRO数据的分析和数据可视化,促进了强有力的、以患者为中心的耐受性结论,并支持更广泛的耐受性和有效治疗的开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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