医学
边际结构模型
危险系数
混淆
比例危险模型
队列
扩大残疾状况量表
观察研究
队列研究
多发性硬化
工具变量
内科学
置信区间
统计
精神科
数学
作者
Nils Koch‐Henriksen,Lau Caspar Thygesen,Per Soelberg Sørensen,Melinda Magyari
标识
DOI:10.1177/13524585231201423
摘要
Background: Estimating the effect of disease-modifying treatment of MS in observational studies is impaired by bias from unmeasured confounders, in particular indication bias. Objective: To show how instrumental variables (IVs) reduce bias. Methods: All patients with relapsing onset of MS 1996–2010, identified by the nationwide Danish Multiple Sclerosis Registry, were followed from onset. Exposure was treatment index throughout the first 12 years from onset, defined as a cumulative function of months without and with medium- or high-efficacy treatment, and outcomes were hazard ratios (HRs) per unit treatment index for sustained Expanded Disability Scale Score (EDSS) 4 and 6 adjusted for age at onset and sex, without and with an IV. We used the onset cohort (1996–2000; 2001–2005; 2006–2010) as an IV because treatment index increased across the cohorts. Results: We included 6014 patients. With conventional Cox regression, HRs for EDSS 4 and 6 were 1.15 [95% CI: 1.13–1.18] and 1.17 [1.13–1.20] per unit treatment index. Only with IVs, we confirmed a beneficial effect of treatment with HRs of 0.86 [0.81–0.91] and 0.82 [0.74–0.90]. Conclusion: The use of IVs eliminates indication bias and confirms that treatment is effective in delaying disability. IVs could, under some circumstances, be an alternative to marginal structural models.
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