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应用 G 估计法评估改良肌酐指数对终末期肾病患者全因死亡率的纵向因果效应:考虑时变混杂因素。

Longitudinal causal effect of modified creatinine index on all-cause mortality in patients with end-stage renal disease: Accounting for time-varying confounders using G-estimation.

机构信息

Department of Epidemiology, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran.

HIV/STI Surveillance Research Center, and WHO Collaborating Centre for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.

出版信息

PLoS One. 2022 Aug 19;17(8):e0272212. doi: 10.1371/journal.pone.0272212. eCollection 2022.

Abstract

BACKGROUND

Standard regression modeling may cause biased effect estimates in the presence of time-varying confounders affected by prior exposure. This study aimed to quantify the relationship between declining in modified creatinine index (MCI), as a surrogate marker of lean body mass, and mortality among end stage renal disease (ESRD) patients using G-estimation accounting appropriately for time-varying confounders.

METHODS

A retrospective cohort of all registered ESRD patients (n = 553) was constructed over 8 years from 2011 to 2019, from 3 hemodialysis centers at Kerman, southeast of Iran. According to changes in MCI, patients were dichotomized to either the decline group or no-decline group. Subsequently the effect of interest was estimated using G-estimation and compared with accelerated failure time (AFT) Weibull models using two modelling strategies.

RESULTS

Standard models demonstrated survival time ratios of 0.91 (95% confidence interval [95% CI]: 0.64 to 1.28) and 0.84 (95% CI: 0.58 to 1.23) in patients in the decline MCI group compared to those in no-decline MCI group. This effect was demonstrated to be 0.57 (-95% CI: 0.21 to 0.81) using G-estimation.

CONCLUSION

Declining in MCI increases mortality in patients with ESRD using G-estimation, while the AFT standard models yield biased effect estimate toward the null.

摘要

背景

在存在受先前暴露影响的时变混杂因素的情况下,标准回归模型可能会导致偏倚的效应估计。本研究旨在使用适当考虑时变混杂因素的 G 估计来量化改良肌酐指数(MCI)下降与终末期肾病(ESRD)患者死亡率之间的关系,MCI 是瘦体重的替代标志物。

方法

从 2011 年至 2019 年,在伊朗东南部克尔曼的 3 个血液透析中心,构建了一个包含 553 名 ESRD 患者的回顾性队列,随访 8 年。根据 MCI 的变化,患者被分为下降组或无下降组。随后,使用 G 估计来估计感兴趣的效应,并使用两种建模策略与加速失效时间(AFT)Weibull 模型进行比较。

结果

标准模型显示,与无 MCI 下降组相比,MCI 下降组的患者生存时间比值分别为 0.91(95%置信区间[95%CI]:0.64 至 1.28)和 0.84(95%CI:0.58 至 1.23)。使用 G 估计,该效应被证明为 0.57(95%CI:0.21 至 0.81)。

结论

使用 G 估计,MCI 的下降会增加 ESRD 患者的死亡率,而 AFT 标准模型会导致效应估计向零偏倚。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d003/9390931/722746a594dd/pone.0272212.g001.jpg

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