Missing tumor measurement (TM) data in the search for alternative TM-based endpoints in cancer clinical trials
Missing tumor measurement (TM) data in the search for alternative TM-based endpoints in cancer clinical trials
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DOI：
10.1016/j.conctc.2019.100492
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发表时间：
2020-03-01
影响因子：
1.5
通讯作者：
Mandrekar, Sumithra J.
中科院分区：
文献类型：
--
作者：
An, Ming-Wen;Tang, Jun;Mandrekar, Sumithra J.
目的：癌症临床试验 (CCT) 中经常出现数据缺失，可能会阻碍寻找替代试验终点。我们考虑 CCT 中缺失肿瘤测量 (TM) 数据的原因以及通常如何处理缺失的 TM 数据。我们探讨了缺失 TM 数据对一组基于 TM 的端点的预测能力的潜在影响。方法：文献综述确定了处理缺失 TM 数据的原因和方法。使用3个实际临床试验的数据进行说明。通过使用观察数据和估算数据比较替代终点的总生存 (OS) 预测能力，对缺失 TM 数据的潜在影响进行了敏感性分析。 结果：根据文献综述和三项试验，提出了 CCT 中缺失 TM 数据的原因。尽管缺失 TM 数据会影响个体客观状态（例如，一组插补组中 53% 的患者的 12 周状态发生变化），但令人惊讶的是，它对终点预测能力的影响极小（例如，500 个插补数据集的中位 c 指数范围为：N9741 的 0.566 至 0.570，N9841 的 0.592-0.616，以及N0026 为 0.542-0.624)。结论：通过了解缺失的原因，我们可以更好地预测它们并最大限度地减少它们的发生。我们的初步分析表明，缺失 TM 数据可能不会影响终点预测能力，但可能会影响客观反应状态分类；然而这些发现需要进一步验证。随着缓解状态被认为是新癌症疗法（包括免疫疗法）开发中重要的 II 期终点，我们敦促在 CCT 中，完整的 TM 数据收集和尽可能严格遵守方案定义的疾病评估成为优先事项。
Purpose: Missing data commonly occur in cancer clinical trials (CCT) and may hinder the search for alternative trial endpoints. We consider reasons for missing tumor measurement (TM) data in CCT and how missing TM data are typically handled. We explore the potential impact of missing TM data on predictive ability of a set of TM - based endpoints.Methods: Literature review identifies reasons for and approaches to handling missing TM data. Data from 3 actual clinical trials were used for illustration. A sensitivity analysis of the potential impact of missing TM data was performed by comparing overall survival (OS) predictive ability of alternative endpoints using observed and imputed data.Results: Reasons for missing TM data in CCT are presented, based on the literature review and the three trials. Although missing TM data impacted individual objective status (e.g. 12-week status changed for 53% of patients in one imputation set), it surprisingly only minimally impacted endpoint predictive ability (e.g. median c-indices of 500 imputed datasets ranged from 0.566 to 0.570 for N9741, 0.592-0.616 for N9841, and 0.542-0.624 for N0026).Conclusion: By understanding the reasons for missingness, we can better anticipate them and minimize their occurrence. Our preliminary analysis suggests missing TM data may not impact endpoint predictive ability, but could impact objective response status classification; however these findings require further validation. With response status accepted as an important phase II endpoint in the development of new cancer therapies (including immunotherapy), we urge that in CCT complete TM data collection and adherence to protocol-defined disease evaluation as closely as possible be a priority.