Dialysis Modality After Renal Transplant Failure

Advising individual patients about the dialysis treatment that offers the best outcomes in terms of mortality, morbidity, and quality of life is complex. The evidence base for that advice remains incomplete, given that survival comparisons between dialysis modalities are fraught with methodologic difficulties. A randomized controlled trial has so far proved impossible to conduct; an attempt by a Dutch group failed to recruit sufficient patients (1), and an older attempt by an American group used an outdated form of peritoneal dialysis (PD) therapy (intermittent PD) in a highly selected group of patients (2). Another attempt is underway in China [mentioned in Noordzij and Jager (3)], but the findings are not yet reported. Studies comparing dialysis treatments have therefore largely been observational, leading to difficulties in interpreting their conclusions. The nonrandom decision by participants to undertake PD or hemodialysis (HD) results in differences between the groups of patients that may or may not be measured by researchers and therefore may or may not be accounted for. Observational studies like the one by Perl and colleagues (4) in this issue of Peritoneal Dialysis International have attempted to overcome those difficulties by using sophisticated statistical techniques such as propensity score matching, inverse probability weighting, and marginal structural modeling (5,6), but it is unclear whether they have solved the fundamental problem of confounding by indication bias. In an effort to compare the effect of treatment type alone, propensity score matching accounts for differences in the characteristics of patients that affect their likelihood of choosing to receive one form of treatment over another. In the Perl analysis, propensity score matching and the more standard multivariate technique yielded different results: survival is lower on PD beyond year 2 in the multivariate analysis, but it is not significantly different once patients are matched by propensity score. However, whatever the statistical approach, groups can be matched only on the covariates that are known to affect the outcome and that have been measured by investigators; the inability to recognize and measure all confounders in a study is known as residual confounding. Perl and colleagues report better 1-year survival for patients with a failed graft who chose to receive PD rather than HD, but both treatments resulted in similar survival beyond year 2. The demonstrated early benefit of PD is similar to that reported in well-designed observational studies, such as one study using the ANZDATA registry (7) and another from the Netherlands Cooperative Study on the Adequacy of Dialysis (8). However, those studies also identified worse survival after 1 – 2 years for patients on PD, similar to the multivariate results in the current Perl analysis, but at odds with the propensity-matched results. However, studies using more recent cohorts from the Canadian Organ Replacement Register (9) and the US Renal Data System (6) found no difference in survival between dialysis modalities after 1 – 2 years, and a study by Quinn et al. (10) demonstrated that the increase in the risk of death over time on PD disappeared once patients starting dialysis urgently were excluded. The consistency of those findings across various health care settings is perhaps surprising, given the vastly different survival rates in the comparator group (patients on HD) in various countries (11). Differences in treatment adherence (12) and background atherosclerotic disease (13) have been postulated as determinants of survival and would likely affect patients whether they chose HD or PD. However, shorter treatment times and faster ultrafiltration rates, which are more prevalent in the United States (14), would affect the HD group only. The fact that the results presented here are so similar to those from other studies comparing HD and PD patients around the world reassures us that any differences in survival between the United States, Europe, and Australia–New Zealand are not materially affecting the patterns seen. Geographic access to treatment is an important factor that Perl and colleagues have not addressed in their comparison of PD and HD, and yet access has been shown to influence modality choice and outcomes. O’Hare et al. (15) showed that patients living in small rural or remote small rural areas in the Unites States are more likely than those living in urban settings to receive PD (17% and 15% vs 11% respectively). It has also been shown that, compared with patients living close to their treatment center, remote dialysis patients in North America have fewer comorbid conditions (16), higher transplantation rates (17), and yet higher mortality (18,19). Distance