{"title":"根据已发表的Kaplan-Meier曲线重建患者水平的生存数据","authors":"Jaromme Kim, Prabhakar Chalise, Jianghua He","doi":"10.1016/j.conctc.2025.101542","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction</h3><div>Individual-level patient data (IPD) are helpful for designing clinical trials, conducting meta-analyses, or methodology research. However, such patient level data are not readily available. Multiple methods have been developed for reconstructing survival data using published Kaplan-Meier (KM) survival curves. There has been no practical guidance on an optimal approach or extensive evaluation of the performance of the approach.</div></div><div><h3>Methods</h3><div>We reviewed several methods of extracting the coordinates of KM survival curves and reconstructing individual-level survival data. Then, we reproduced data from 46 published KM curves. The accuracy of reconstructed data is quantified by comparing hazard ratios (HRs) and their confidence intervals (CIs) estimated from the reproduced data with those reported in the original papers.</div></div><div><h3>Results</h3><div>The comparison showed a high degree of similarity between the reproduced and original HRs and CIs. In most cases, the differences were less than 5 %. The mean and median absolute percentage differences of 58 reconstructed HRs were 2.85 % and 2.14 %, respectively. These results suggest the reconstruction method reliably reconstructs survival data from KM survival curves.</div></div><div><h3>Conclusions</h3><div>Based on an extensive number of reconstructions, we demonstrated that reconstructed data provided similar estimates overall to those from published papers. The quality of the reproduced data depends on the presence of noise in the published curves and whether the preprocessing step is properly done.</div></div>","PeriodicalId":37937,"journal":{"name":"Contemporary Clinical Trials Communications","volume":"47 ","pages":"Article 101542"},"PeriodicalIF":1.4000,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reconstructing patient level survival data from published Kaplan-Meier curves\",\"authors\":\"Jaromme Kim, Prabhakar Chalise, Jianghua He\",\"doi\":\"10.1016/j.conctc.2025.101542\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Introduction</h3><div>Individual-level patient data (IPD) are helpful for designing clinical trials, conducting meta-analyses, or methodology research. However, such patient level data are not readily available. Multiple methods have been developed for reconstructing survival data using published Kaplan-Meier (KM) survival curves. There has been no practical guidance on an optimal approach or extensive evaluation of the performance of the approach.</div></div><div><h3>Methods</h3><div>We reviewed several methods of extracting the coordinates of KM survival curves and reconstructing individual-level survival data. Then, we reproduced data from 46 published KM curves. The accuracy of reconstructed data is quantified by comparing hazard ratios (HRs) and their confidence intervals (CIs) estimated from the reproduced data with those reported in the original papers.</div></div><div><h3>Results</h3><div>The comparison showed a high degree of similarity between the reproduced and original HRs and CIs. In most cases, the differences were less than 5 %. The mean and median absolute percentage differences of 58 reconstructed HRs were 2.85 % and 2.14 %, respectively. These results suggest the reconstruction method reliably reconstructs survival data from KM survival curves.</div></div><div><h3>Conclusions</h3><div>Based on an extensive number of reconstructions, we demonstrated that reconstructed data provided similar estimates overall to those from published papers. The quality of the reproduced data depends on the presence of noise in the published curves and whether the preprocessing step is properly done.</div></div>\",\"PeriodicalId\":37937,\"journal\":{\"name\":\"Contemporary Clinical Trials Communications\",\"volume\":\"47 \",\"pages\":\"Article 101542\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2025-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contemporary Clinical Trials Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2451865425001164\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contemporary Clinical Trials Communications","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2451865425001164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Reconstructing patient level survival data from published Kaplan-Meier curves
Introduction
Individual-level patient data (IPD) are helpful for designing clinical trials, conducting meta-analyses, or methodology research. However, such patient level data are not readily available. Multiple methods have been developed for reconstructing survival data using published Kaplan-Meier (KM) survival curves. There has been no practical guidance on an optimal approach or extensive evaluation of the performance of the approach.
Methods
We reviewed several methods of extracting the coordinates of KM survival curves and reconstructing individual-level survival data. Then, we reproduced data from 46 published KM curves. The accuracy of reconstructed data is quantified by comparing hazard ratios (HRs) and their confidence intervals (CIs) estimated from the reproduced data with those reported in the original papers.
Results
The comparison showed a high degree of similarity between the reproduced and original HRs and CIs. In most cases, the differences were less than 5 %. The mean and median absolute percentage differences of 58 reconstructed HRs were 2.85 % and 2.14 %, respectively. These results suggest the reconstruction method reliably reconstructs survival data from KM survival curves.
Conclusions
Based on an extensive number of reconstructions, we demonstrated that reconstructed data provided similar estimates overall to those from published papers. The quality of the reproduced data depends on the presence of noise in the published curves and whether the preprocessing step is properly done.
期刊介绍:
Contemporary Clinical Trials Communications is an international peer reviewed open access journal that publishes articles pertaining to all aspects of clinical trials, including, but not limited to, design, conduct, analysis, regulation and ethics. Manuscripts submitted should appeal to a readership drawn from a wide range of disciplines including medicine, life science, pharmaceutical science, biostatistics, epidemiology, computer science, management science, behavioral science, and bioethics. Contemporary Clinical Trials Communications is unique in that it is outside the confines of disease specifications, and it strives to increase the transparency of medical research and reduce publication bias by publishing scientifically valid original research findings irrespective of their perceived importance, significance or impact. Both randomized and non-randomized trials are within the scope of the Journal. Some common topics include trial design rationale and methods, operational methodologies and challenges, and positive and negative trial results. In addition to original research, the Journal also welcomes other types of communications including, but are not limited to, methodology reviews, perspectives and discussions. Through timely dissemination of advances in clinical trials, the goal of Contemporary Clinical Trials Communications is to serve as a platform to enhance the communication and collaboration within the global clinical trials community that ultimately advances this field of research for the benefit of patients.