{"title":"改进中点推算法,以估算间隔删失的事件发生时间数据的中位生存时间","authors":"Yuki Nakagawa, Takashi Sozu","doi":"10.1007/s43441-024-00640-7","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>Progression-free survival (PFS) is used to evaluate treatment effects in cancer clinical trials. Disease progression (DP) in patients is typically determined by radiological testing at several scheduled tumor-assessment time points. This produces a discrepancy between the true progression time and the observed progression time. When the observed progression time is considered as the true progression time, a positively biased PFS is obtained for some patients, and the estimated survival function derived by the Kaplan–Meier method is also biased.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>While the midpoint imputation method is available and replaces interval-censored data with midpoint data, it unrealistically assumes that several DPs occur at the same time point when several DPs are observed within the same tumor-assessment interval. We enhanced the midpoint imputation method by replacing interval-censored data with equally spaced timepoint data based on the number of observed interval-censored data within the same tumor-assessment interval.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>The root mean square error of the median of the enhanced method is almost always smaller than that of the midpoint imputation regardless of the tumor-assessment frequency. The coverage probability of the enhanced method is close to the nominal confidence level of 95% in most scenarios.</p><h3 data-test=\"abstract-sub-heading\">Conclusion</h3><p>We believe that the enhanced method, which builds upon the midpoint imputation method, is more effective than the midpoint imputation method itself.</p>","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improvement of Midpoint Imputation for Estimation of Median Survival Time for Interval-Censored Time-to-Event Data\",\"authors\":\"Yuki Nakagawa, Takashi Sozu\",\"doi\":\"10.1007/s43441-024-00640-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3 data-test=\\\"abstract-sub-heading\\\">Background</h3><p>Progression-free survival (PFS) is used to evaluate treatment effects in cancer clinical trials. Disease progression (DP) in patients is typically determined by radiological testing at several scheduled tumor-assessment time points. This produces a discrepancy between the true progression time and the observed progression time. When the observed progression time is considered as the true progression time, a positively biased PFS is obtained for some patients, and the estimated survival function derived by the Kaplan–Meier method is also biased.</p><h3 data-test=\\\"abstract-sub-heading\\\">Methods</h3><p>While the midpoint imputation method is available and replaces interval-censored data with midpoint data, it unrealistically assumes that several DPs occur at the same time point when several DPs are observed within the same tumor-assessment interval. We enhanced the midpoint imputation method by replacing interval-censored data with equally spaced timepoint data based on the number of observed interval-censored data within the same tumor-assessment interval.</p><h3 data-test=\\\"abstract-sub-heading\\\">Results</h3><p>The root mean square error of the median of the enhanced method is almost always smaller than that of the midpoint imputation regardless of the tumor-assessment frequency. The coverage probability of the enhanced method is close to the nominal confidence level of 95% in most scenarios.</p><h3 data-test=\\\"abstract-sub-heading\\\">Conclusion</h3><p>We believe that the enhanced method, which builds upon the midpoint imputation method, is more effective than the midpoint imputation method itself.</p>\",\"PeriodicalId\":23084,\"journal\":{\"name\":\"Therapeutic innovation & regulatory science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Therapeutic innovation & regulatory science\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s43441-024-00640-7\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MEDICAL INFORMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Therapeutic innovation & regulatory science","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s43441-024-00640-7","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
Improvement of Midpoint Imputation for Estimation of Median Survival Time for Interval-Censored Time-to-Event Data
Background
Progression-free survival (PFS) is used to evaluate treatment effects in cancer clinical trials. Disease progression (DP) in patients is typically determined by radiological testing at several scheduled tumor-assessment time points. This produces a discrepancy between the true progression time and the observed progression time. When the observed progression time is considered as the true progression time, a positively biased PFS is obtained for some patients, and the estimated survival function derived by the Kaplan–Meier method is also biased.
Methods
While the midpoint imputation method is available and replaces interval-censored data with midpoint data, it unrealistically assumes that several DPs occur at the same time point when several DPs are observed within the same tumor-assessment interval. We enhanced the midpoint imputation method by replacing interval-censored data with equally spaced timepoint data based on the number of observed interval-censored data within the same tumor-assessment interval.
Results
The root mean square error of the median of the enhanced method is almost always smaller than that of the midpoint imputation regardless of the tumor-assessment frequency. The coverage probability of the enhanced method is close to the nominal confidence level of 95% in most scenarios.
Conclusion
We believe that the enhanced method, which builds upon the midpoint imputation method, is more effective than the midpoint imputation method itself.
期刊介绍:
Therapeutic Innovation & Regulatory Science (TIRS) is the official scientific journal of DIA that strives to advance medical product discovery, development, regulation, and use through the publication of peer-reviewed original and review articles, commentaries, and letters to the editor across the spectrum of converting biomedical science into practical solutions to advance human health.
The focus areas of the journal are as follows:
Biostatistics
Clinical Trials
Product Development and Innovation
Global Perspectives
Policy
Regulatory Science
Product Safety
Special Populations