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Dose of hemodialysis and survival: A marginal structural model analysis

机译:血液透析剂量和生存率:边缘结构模型分析

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Background: Observational studies have consistently demonstrated the survival benefits of a greater dialysis dose in maintenance hemodialysis (MHD) patients, whereas randomized controlled trials have shown conflicting results. The possible causal impact of dialysis dose on mortality needs to be investigated using rich cohort data analyzed with novel statistical methods such as marginal structural models (MSMs) that account for time-varying confounding and exposure. Methods: We quantified the effect of delivered dose of hemodialysis (HD) [single-pool Kt/V (spKt/V)] on mortality risk in a contemporary cohort of 68,110 patients undergoing HD 3 times weekly (7/2001-9/2005). We compared conventional Cox proportional hazard and MSM survival analyses, accounting for time-varying confounding by applying longitudinally modeled inverse-probability-of-dialysis-dose weights to each observation. Results: In conventional Cox models, baseline spKt/V showed a weak negative association with mortality, while higher time-averaged spKt/V was strongly associated with lower mortality risk. In MSM analyses, compared to a spKt/V range of 1.2-<1.4, a spKt/V range of <1.2 was associated with a higher risk of mortality [HR (95% CI) 1.67 (1.54-1.80)], whereas mortality risks were significantly lower with higher spKt/V [HRs (95% CI): 0.74 (0.70-0.78), 0.63 (0.59-0.66), 0.56 (0.52-0.60), and 0.56 (0.52-0.61) for spKt/V ranges of 1.4-<1.6, 1.6-<1.8, 1.8-<2.0, and ≥2.0, respectively]. Thus, MSM analyses showed that the greatest survival advantage of a higher dialysis dose was observed for a spKt/V range of 1.8-<2.0, and the dialysis dose-mortality relationship was robust in almost all subgroups of patients. Conclusions: Higher HD doses were robustly associated with greater survival in MSM analyses that more fully and appropriately accounted for time-varying confounding.
机译:背景:观察性研究一贯表明,在维持性血液透析(MHD)患者中使用更大剂量的透析可提高生存率,而随机对照试验则显示出相互矛盾的结果。透析剂量对死亡率的可能因果关系需要使用丰富的队列数据进行调查,这些数据采用新颖的统计方法进行分析,例如边际结构模型(MSM),这些因素说明了时变的混杂和暴露。方法:我们量化了在当代队列中每周进行3次HD治疗的68,110名患者的血液透析剂量(HD)[单池Kt / V(spKt / V)]对死亡风险的影响(7 / 2001-9 / 2005 )。我们比较了传统的Cox比例风险分析和MSM生存分析,通过对每个观察结果应用纵向建模的透析剂量的反向概率权重来解释随时间变化造成的混淆。结果:在传统的Cox模型中,基线spKt / V与死亡率呈弱的负相关性,而较高的时间平均spKt / V与较低的死亡率风险有很强的相关性。在MSM分析中,与spKt / V范围小于1.2- <1.4相比,spKt / V范围小于1.2与较高的死亡风险相关[HR(95%CI)1.67(1.54-1.80)],而死亡率spKt / V较高时,风险显着降低[HRs(95%CI):spKt / V范围为0.74(0.70-0.78),0.63(0.59-0.66),0.56(0.52-0.60)和0.56(0.52-0.61)分别为1.4- <1.6、1.6- <1.8、1.8- <2.0和≥2.0]。因此,MSM分析显示,在spKt / V范围为1.8- <2.0的情况下,观察到较高的透析剂量具有最大的生存优势,并且在几乎所有患者亚组中,透析剂量与死亡率的关系均很强。结论:在MSM分析中,较高的HD剂量与更高的生存率密切相关,而MSM分析则更充分,更适当地说明了时变混杂因素。

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