Association of Achieved Dialysis Dose with Mortality in the Hemodialysis Study

Abstract

In the intention-to-treat analysis of the Hemodialysis Study, all-cause mortality did not differ significantly between the high versus standard hemodialysis dose groups. The association of mortality with delivered dose within each of the two randomized treatment groups was examined, and implications for observational studies were considered. Time-dependent Cox regression was used to relate the relative risk (RR) for mortality to the running mean of the achieved equilibrated Kt/V (eKt/V) over the preceding 4 mo. eKt/V was categorized by quintiles within each dose group. Analyses were controlled for case-mix factors and baseline anthropometric volume. Within each randomized dose group, mortality was elevated markedly when achieved eKt/V was in the lowest quintile (RR, 1.93; 95% confidence interval [CI], 1.40 to 2.66; P < 0.0001 in the standard-dose group; RR, 2.04; 95% CI, 1.50 to 2.76; P < 0.0001 in the high-dose group; RR relative to the middle quintiles). The mortality rate in the lowest eKt/V quintile of the high-dose group was higher than in the full standard-dose group (RR, 1.59; 95% CI, 1.29 to 1.96; P < 0.0001). Each 0.1 eKt/V unit below the group median was associated with a 58% higher mortality in the standard-dose group (P < 0.001) and a 37% higher mortality in the high-dose group (P < 0.001). The magnitude of these dose-mortality effects was seven-to 12-fold higher than the upper limit of the 95% CI from the intention-to-treat analysis. The effects were attenuated in lagged analyses but did not disappear. When dialysis dose is targeted closely, as under the controlled conditions of the Hemodialysis Study, patients with the lowest achieved dose relative to their target dose experience markedly increased mortality, to a degree that is not compatible with a biologic effect of dose. The possibility of similar (albeit smaller) biases should be considered when analyzing observational data sets relating mortality to achieved dose of dialysis.

Modeled Urea Distribution Volume and Mortality in the HEMO Study

“…These results contrast markedly with observational studies that have consistently shown associations between higher dialysis dose and survival (3)(4)(5). In a previous analysis of HEMO Study data, we found strong associations between the achieved dose and survival within each of the two randomized dose groups (6). The magnitude of the association greatly exceeded the 95% confidence limits of the dose-survival relationship indicated by the intention-to-treat analysis.…”

Dialysis Dose Scaled to Body Surface Area and Size-Adjusted, Sex-Specific Patient Mortality

“…First, we used an observational dataset in which dose of dialysis and mortality may be confounded by dose-targeting bias (32,33). This bias suggests that delivered dose of dialysis may be linked to mortality by factors other than the biologic effect of increased solute removal.…”

Test of the recommended dialysis dose on one-year mortality of nondiabetic maintenance hemodialysis patients; observations from a single dialysis unit

“…The HEMO study, a randomized controlled trial (RCT), and the subsequent reanalysis of the same data require a particular attention at this point. 11,12 The mortality outcome was investigated using the intention-to-treat analysis in the original HEMO study, and there were no statistically significant difference between low and high dialysis doses for a mean difference in eKt/V (spKt/V -0.6K/Vþ 0.03) of 0.37.…”

“…12 An additional detail from the second analysis of the HEMO cohort was that, although patients with the lowest quintile of achieved eKt/V in the high-dose group had an average eKt/V greater than the entire standard dose group; their mortality rate was still 59% higher. These findings suggest that the association between increased mortality and low eKt/V may not be explained solely by Kt/V itself.…”

“…This reduces the predictability of initial Kt/V sampling, such as the baseline eKt/V was predictive of mortality for no more than one year in the reanalysis of the HEMO study. 12 The variables related to mortality and Kt/V that can change over time are collectively called time-varying confounders, and it is claimed that they may not be sufficiently controlled in longitudinal studies with the conventional Cox regression models. 18 In a recent report with a large cohort of MHD patients, Lertdumrongluk et al used a marginal structural model analysis model to overcome the time-varying confounders influence, and they found that there was a robust inverse relationship between mortality and spKt/V up until 1.8 2.0 units of spKt/V, above which the mortality benefit showed a plateau.…”