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Improvement of Midpoint Imputation for Estimation of Median Survival Time for Interval-Censored Time-to-Event Data
Yuki Nakagawa1,2, Takashi Sozu3
1Biometrics Department, Chugai Pharmaceutical Co., Ltd., 2-1-1 Nihonbashi-Muromachi, Chuo-Ku, Tokyo, 103-8324, Japan. nakagawa.yuki99@chugai-pharm.co.jp.
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.
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