Statistical Models for Patient-Centered Outcomes in Clinical Studies

被引:0
|
作者
Heller, Gillian [1 ]
Forbes, Andrew [2 ]
Heritier, Stephane [2 ]
机构
[1] Univ Sydney, NHMRC Clin Trials Ctr, Sydney, NSW, Australia
[2] Monash Univ, Sch Publ Hlth & Prevent Med, Melbourne, Vic, Australia
关键词
distributional regression; censoring; hospital length of stay; GAMLSS; patient-centered outcomes;
D O I
10.1007/978-3-031-65723-8_8
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Days alive and out of hospital is recommended as a patient-centered outcome in perioperative clinical studies. It is defined as the number of days, out of the first M postoperative days, that the patient has been discharged from hospital, or zero if the patient dies within M days of surgery. This composite measure presents statistical challenges in its unusual distributional shape, and its inability to distinguish between the qualitatively different outcomes of death, and a hospital stay longer than M days. We propose a mixed binary-continuous model that over-comes these difficulties, and illustrate its use on a clinical trial of a drug administered in cardiac surgery.
引用
收藏
页码:48 / 54
页数:7
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