A Method for Reconstructing Individual Patient Data From Kaplan-Meier Survival Curves That Incorporate Marked Censoring Times.

IF 1.7
MDM policy & practice Pub Date : 2022-01-31 eCollection Date: 2022-01-01 DOI:10.1177/23814683221077643
Basia Rogula, Greta Lozano-Ortega, Karissa M Johnston
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引用次数: 3

Abstract

Introduction. 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. Methods. 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. Results. 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. Conclusion. 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. Graphical Abstract This is a visual representation of the abstract.

Abstract Image

Abstract Image

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一种从Kaplan-Meier生存曲线重构个体患者数据的方法。
介绍。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)可能是有利的。虽然在公布的Kaplan-Meier (KM)曲线上经常标记出精确的审查时间,但目前还没有一种算法可以从这些曲线中重建IPD,从而允许它们的合并。方法。开发了一种能够结合标记审查时间的算法,将患者总数和生存下降坐标作为附加输入,从KM曲线重建IPD。该算法的可靠性通过模拟演习进行评估,其中生存曲线进行模拟,数字化,然后重建。为了评估重建曲线的可靠性,比较原始曲线和重建曲线的风险比(hr)和生存分位数,并对重建曲线进行目测检查。结果。原始曲线和重建曲线的hr和分位数没有系统差异。经目测,重建的IPD与已发表的KM曲线的数字化数据非常接近。该算法固有的特点是,在重构数据中精确地加入了审查时间。结论。该算法可以可靠地从报道的KM存活曲线中重建IPD,存在可提取的审查时间。该算法的使用将允许卫生研究人员更紧密地重建IPD,通过将检查时间精确地纳入标记,需要额外的输入患者总数和生存率下降的坐标。
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