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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
来源:
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.
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页码:48 / 54
页数:7
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