Rogula Basia, Lozano-Ortega Greta, Johnston Karissa M
Broadstreet Health Economics & Outcomes Research, Vancouver, British Columbia, Canada.
MDM Policy Pract. 2022 Jan 31;7(1):23814683221077643. doi: 10.1177/23814683221077643. eCollection 2022 Jan-Jun.
Access to individual patient data (IPD) can be advantageous when conducting cost-effectiveness analyses or indirect treatment comparisons. While exact times of censoring are often marked on published Kaplan-Meier (KM) curves, an algorithm for reconstructing IPD from such curves that allows for their incorporation is presently unavailable. An algorithm capable of incorporating marked censoring times was developed to reconstruct IPD from KM curves, taking as additional inputs the total patient count and coordinates of the drops in survival. The reliability of the algorithm was evaluated via a simulation exercise, in which survival curves were simulated, digitized, and then reconstructed. To assess the reliability of the reconstructed curves, hazard ratios (HRs) and quantiles of survival were compared between the original and reconstructed curves, and the reconstructed curves were visually inspected. No systematic differences were found in HRs and quantiles in the original versus reconstructed curves. Upon visual inspection, the reconstructed IPD provided a close fit to the digitized data from the published KM curves. Inherent to the algorithm, censoring times were incorporated into the reconstructed data exactly as specified. This new algorithm can reliably be used to reconstruct IPD from reported KM survival curves in the presence of extractable censoring times. Use of the algorithm will allow health researchers to reconstruct IPD more closely by incorporating censoring times exactly as marked, requiring as additional inputs the total patient count and coordinates of the drops in survival.
在进行成本效益分析或间接治疗比较时,获取个体患者数据(IPD)可能具有优势。虽然在已发表的 Kaplan-Meier(KM)曲线上通常会标记确切的删失时间,但目前还没有一种能从此类曲线重建IPD并纳入这些时间的算法。我们开发了一种能够纳入标记删失时间的算法,用于从KM曲线重建IPD,将患者总数和生存下降点的坐标作为额外输入。通过模拟练习评估了该算法的可靠性,在模拟中对生存曲线进行模拟、数字化,然后进行重建。为了评估重建曲线的可靠性,比较了原始曲线和重建曲线之间的风险比(HRs)和生存分位数,并对重建曲线进行了目视检查。在原始曲线和重建曲线的HRs和分位数方面未发现系统差异。目视检查时,重建的IPD与已发表KM曲线的数字化数据拟合良好。该算法的固有特性是,删失时间被准确地按规定纳入重建数据。这种新算法可可靠地用于在存在可提取删失时间的情况下从报告的KM生存曲线重建IPD。使用该算法将使健康研究人员能够通过准确纳入标记的删失时间更精确地重建IPD,只需将患者总数和生存下降点的坐标作为额外输入。