著者

篠崎 智大 横田 勲 大庭 幸治 上妻 佳代子 坂巻 顕太郎

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.41, no.1, pp.1-35, 2020 (Released:2020-12-04)

参考文献数

65

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Prediction models are usually developed through model-construction and validation. Especially for binary or time-to-event outcomes, the risk prediction models should be evaluated through several aspects of the accuracy of prediction. With unified algebraic notation, we present such evaluation measures for model validation from five statistical viewpoints that are frequently reported in medical literature: 1) Brier score for prediction error; 2) sensitivity, specificity, and C-index for discrimination; 3) calibration-in-the-large, calibration slope, and Hosmer-Lemeshow statistic for calibration; 4) net reclassification and integrated discrimination improvement indexes for reclassification; and 5) net benefit for clinical usefulness. Graphical representation such as a receiver operating characteristic curve, a calibration plot, or a decision curve helps researchers interpret these evaluation measures. The interrelationship between them is discussed, and their definitions and estimators are extended to time-to-event data suffering from outcome-censoring. We illustrate their calculation through example datasets with the SAS codes provided in the web appendix.

著者

田中 司朗 大庭 幸治 吉村 健一 手良向 聡

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.31, no.1, pp.23-48, 2010-07-31 (Released:2010-12-14)

参考文献数

71

被引用文献数

1 1

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Surrogate endpoints, which represent a compromise in the conflict between measurability and clinical relevance of endpoints, have considerable advantage in rapid drug approvals compared to true endpoints in confirmatory clinical trials dealing with life-threatening diseases, such as cancer or AIDS. However, past experiences have shown the risk of relying too heavily on surrogate endpoints. In this paper, we review statistical criteria for evaluating surrogate endpoints and the past examples properly evaluated the surrogacy, taking into consideration relevant clinical and statistical issues.