Estimating effects of time-varying exposures on mortality risk

被引:0
作者
Thomson, Trevor J. [1 ,2 ]
Hu, X. Joan [1 ]
Nosyk, Bohdan [3 ,4 ]
机构
[1] Simon Fraser Univ, Dept Stat & Actuarial Sci, 8888 Univ Dr, Burnaby, BC V5A 1S6, Canada
[2] Fred Hutchinson Canc Res Ctr, Biostat Bioinformat & Epidemiol Program, Seattle, WA USA
[3] Simon Fraser Univ, Fac Hlth Sci, Burnaby, BC, Canada
[4] St Pauls Hosp, Ctr Hlth Evaluat & Outcome Sci, Vancouver, BC, Canada
基金
加拿大自然科学与工程研究理事会; 美国国家卫生研究院;
关键词
Estimating equation; internal covariate; risk assessment; semiparametric regression; time-dependent stratification; DYNAMIC PREDICTION; REGRESSION; LANDMARKING; MODELS; DEATH;
D O I
10.1080/02664763.2024.2313459
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
Administrative databases have become an increasingly popular data source for population-based health research. We explore how mortality risk is associated with some health service utilization process via linked administrative data. A generalized Cox regression model is proposed using a time-dependent stratification variable to summarize lifetime service utilization. Recognizing the service utilization over time as an internal covariate in the survival analysis, conventional likelihood methods are inapplicable. We present an estimating function based procedure for estimating model parameters, and provide a testing procedure for updating the stratification levels. The proposed approach is examined both asymptotically and numerically via simulation. We motivate and illustrate the proposed approach using an on-going program pertaining to opioid agonist treatment (OAT) management for individuals identified with opioid use disorders. Our analysis of the OAT data indicates that the OAT effect on mortality risk decreases in successive OAT attempts, in which two risk classes based on an individual's treatment episode number are established: one with 1-3 OAT episodes, and the other with 4+ OAT episodes.
引用
收藏
页码:2652 / 2671
页数:20
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