Improvement of Midpoint Imputation for Estimation of Median Survival Time for Interval-Censored Time-to-Event Data

IF 2 4区 医学 Q4 MEDICAL INFORMATICS
Yuki Nakagawa, Takashi Sozu
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Abstract

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.

Abstract Image

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
背景无进展生存期(PFS)用于评估癌症临床试验中的治疗效果。患者的疾病进展(DP)通常是通过在几个预定的肿瘤评估时间点进行放射学检测来确定的。这就造成了真实进展时间与观察到的进展时间之间的差异。方法虽然中点估算法可以用中点数据替代间隔删失数据,但当在同一肿瘤评估间隔内观察到多个DP时,该方法不切实际地假定多个DP发生在同一时间点。结果无论肿瘤评估频率如何,增强方法的中位数均方根误差几乎总是小于中点估算法。在大多数情况下,增强型方法的覆盖概率接近 95% 的名义置信水平。结论我们认为,在中点估算法基础上发展起来的增强型方法比中点估算法本身更有效。
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来源期刊
Therapeutic innovation & regulatory science
Therapeutic innovation & regulatory science MEDICAL INFORMATICS-PHARMACOLOGY & PHARMACY
CiteScore
3.40
自引率
13.30%
发文量
127
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
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