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.
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.
Authors: Trinh B Pifer; Keith P McCullough; Friedrich K Port; David A Goodkin; Bradley J Maroni; Philip J Held; Eric W Young Journal: Kidney Int Date: 2002-12 Impact factor: 10.612
Authors: Frank Fung; Donald J Sherrard; Daniel L Gillen; Craig Wong; Bryan Kestenbaum; Steven Seliger; Adrianne Ball; Catherine Stehman-Breen Journal: Am J Kidney Dis Date: 2002-08 Impact factor: 8.860
Authors: Garabed Eknoyan; Gerald J Beck; Alfred K Cheung; John T Daugirdas; Tom Greene; John W Kusek; Michael Allon; James Bailey; James A Delmez; Thomas A Depner; Johanna T Dwyer; Andrew S Levey; Nathan W Levin; Edgar Milford; Daniel B Ornt; Michael V Rocco; Gerald Schulman; Steve J Schwab; Brendan P Teehan; Robert Toto Journal: N Engl J Med Date: 2002-12-19 Impact factor: 91.245
Authors: Friedrich K Port; Robert A Wolfe; Tempie E Hulbert-Shearon; Keith P McCullough; Valarie B Ashby; Philip J Held Journal: Am J Kidney Dis Date: 2004-06 Impact factor: 8.860
Authors: Kamyar Kalantar-Zadeh; Connie M Rhee; Jason Chou; S Foad Ahmadi; Jongha Park; Joline Lt Chen; Alpesh N Amin Journal: Kidney Int Rep Date: 2017-02-01
Authors: Emilio Sánchez-Álvarez; Minerva Rodríguez-García; Francesco Locatelli; Carmine Zoccali; Alejandro Martín-Malo; Jürgen Floege; Markus Ketteler; Gerard London; José L Górriz; Boleslaw Rutkowski; Anibal Ferreira; Drasko Pavlovic; Jorge B Cannata-Andía; José L Fernández-Martín Journal: Clin Kidney J Date: 2020-12-26