Measurement error and precision medicine: Error-prone tailoring covariates in dynamic treatment regimes

被引：6

作者：

Spicker, Dylan ^{[1
]}

Wallace, Michael P. ^{[1
]}

机构：

[1] Univ Waterloo, Stat & Actuarial Sci, Waterloo, ON N2L 3G1, Canada

来源：

STATISTICS IN MEDICINE | 2020年 / 39卷 / 26期

基金：

加拿大自然科学与工程研究理事会;

关键词：

precision medicine; measurement error; personalized medicine; dynamic treatment regimes; adaptive treatment strategies; SEQUENCED TREATMENT ALTERNATIVES; MODELS; REGRESSION; RATIONALE; INFERENCE; SCORE;

D O I：

10.1002/sim.8690

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Precision medicine incorporates patient-level covariates to tailor treatment decisions, seeking to improve outcomes. In longitudinal studies with time-varying covariates and sequential treatment decisions, precision medicine can be formalized with dynamic treatment regimes (DTRs): sequences of covariate-dependent treatment rules. To date, the precision medicine literature has not addressed a ubiquitous concern in health research-measurement error-where observed data deviate from the truth. We discuss the consequences of ignoring measurement error in the context of DTRs, focusing on challenges unique to precision medicine. We show-through simulation and theoretical results-that relatively simple measurement error correction techniques can lead to substantial improvements over uncorrected analyses, and apply these findings to the sequenced treatment alternatives to relieve depression study.

引用

页码：3732 / 3755

页数：24

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