Survival comparisons between haemodialysis and peritoneal dialysis

Dialysis modality selection for end-stage renal disease patients should not solely be dictated by survival comparisons but also take into account patient preference. Nevertheless, potential mortality differences between dialysis modalities in (subgroups of ) patients may contribute to modality choice. Survival comparisons have therefore frequently been made. With one exception, the investigators used an observational study design to study this issue. Observational studies fulfil a valuable role in nephrology research, but their most important drawback is that selection bias by the clinician may occur [1]. Even after adjustment for potential confounders in the statistical analysis, there is usually at least some amount of residual confounding due to unmeasured variables. This may prevent a fair comparison of outcomes between patient groups, something that is usually feasible from well-conducted randomized controlled trials. Almost a decade ago, such a trial with random allocation of dialysis modality was unsuccessful because patient and physician preference turned out to play a crucial role in modality choice [2]. Despite this unsuccessful attempt, a new trial has started in China (trial registration NCT01413074 at clinicaltrials.gov). However, until the results of this trial are presented, mortality in haemodialysis and peritoneal dialysis patients can only be compared based on large-scale observational studies. Even though there is some heterogeneity in the results, these observational studies usually indicated that the mortality risk on haemodialysis treatment compared with that on peritoneal dialysis treatment changes over time, with the lowest relative risk for patients on peritoneal dialysis in the first 2 years of therapy. After these first 2 years, mortality risk increases for those who started on peritoneal dialysis and patient survival becomes similar for haemodialysis and peritoneal dialysis patients, or even somewhat better for patients on haemodialysis [3–5]. This finding could be attributable to residual confounding. For example, it has been postulated that patients who start dialysis urgently are at high risk of death and as they are treated predominantly with haemodialysis. This could induce selection bias in the comparison of mortality between haemodialysis and peritoneal dialysis patients. Couchoud et al. [6] showed in 2007 that mortality risk was significantly increased with 50% among elderly patients (75 years or older) with an ‘unplanned’ start of haemodialysis when compared to patients with a ‘planned’ start suggesting that a comparison between both dialysis modalities would be more balanced after removing the unplanned haemodialysis starts. Quinn et al. [7] recently confirmed the findings of Couchoud et al. by showing that haemodialysis and peritoneal dialysis were associated with similar survival in incident patients starting dialysis electively as outpatients. A planned start is usually not taken into account in survival comparisons of haemodialysis and peritoneal dialysis. Another point frequently not taken into account is whether haemodialysis and peritoneal dialysis are provided in a state-of-the-art manner. For example, in many survival comparisons, the type of vascular access used for haemodialysis is not included in the analyses, whereas Perl et al. [8] recently showed that type of vascular access plays an important role in the relationship between dialysis modality and mortality. They found in a Canadian cohort that starting haemodialysis with a central venous catheter largely explained the higher early mortality risk of haemodialysis. In order to reduce the influence of selection bias and confounding, research groups started to re-assess the associations between dialysis modality and mortality risk in large cohort studies using more advanced statistical methods, in addition to the conventional methods of survival analysis, i.e. Kaplan–Meier and Cox proportional hazards models. Examples of such methods are the use of time-dependent covariates in survival analysis [4], marginal structural models [9, 10] and the use of treatment propensity scores in statistical models by means of adjustment, stratification or matching [4, 11, 12]. In the current issue of Nephrology Dialysis Transplantation, Yeates et al. [13] applied different statistical methods to compare the survival of haemodialysis and peritoneal dialysis patients using data on >35 000 incident dialysis patients from the Canadian Organ Replacement Register. They performed both a standard intention-totreat analysis and a time-dependent as-treated analysis for which proportional and non-proportional hazards models were built to compare mortality risks between both groups. For the non-proportional hazards analyses, they used a piecewise exponential survival model, using successive 6-month intervals in the first 5 years of dialysis

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