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NDT Advance Access originally published online on June 2, 2007
Nephrology Dialysis Transplantation 2007 22(10):3005-3012; doi:10.1093/ndt/gfm324
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© The Author [2007]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org


High membrane transport status on peritoneal dialysis is not associated with reduced survival following transfer to haemodialysis

Kathryn J. Wiggins1,2, Stephen P. McDonald1,3, Fiona G. Brown1,4, Johan B. Rosman1,5 and David W. Johnson1,6

1Australia and New Zealand Dialysis and Transplant Registry, Adelaide, 2Department of Renal Medicine, St. Vincent's Hospital, Melbourne, 3Department of Nephrology, Queen Elizabeth Hospital, Adelaide, Australia, 4Department of Nephrology, Monash Medical Centre, Clayton, Victoria, Australia, 5Renal Department, Middlemore Hospital, Otahuhu, Auckland, New Zealand and 6Department of Renal Medicine, University of Queensland at Princess Alexandra Hospital, Brisbane, Australia

Correspondence and offprint requests to: Kate Wiggins, Department of Renal Medicine, St. Vincent's Hospital, PO Box 2900 Fitzroy VIC 3065, Australia. Email: kate.wiggins{at}svhm.org.au



   Abstract
Top
 Abstract
Introduction
 Results
 Discussion
 Acknowledgements
 References
 
Background. High transporter status is associated with reduced survival of patients receiving peritoneal dialysis (PD). This may be due primarily to the development of complications related to the PD process, in which case the survival disadvantage may not persist following transfer to haemodialysis (HD). In this study, we aimed to assess the impact of peritoneal membrane transporter status on patient survival and the likelihood of return to PD following transfer from PD to HD.

Methods. The Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry was searched to identify all patients between 1 April 1999 and 31 March 2004 who had received PD and subsequently transferred to HD, in whom an incident 4 h dialysate: plasma creatinine ratio was recorded. A Cox proportional hazards model was used to identify factors significantly associated with patient and technique survival after commencement of HD.

Results. A total of 918 patients were included in the analysis. On multivariate Cox regression analysis there was no difference in survival between transport groups relative to the reference group of low average transporters (adjusted hazard ratio (HR) 0.71, 95% CI 0.42–1.19, P = 0.19, HR 0.94, 95% CI 0.63–1.38, P = 0.73 and HR 0.24, 95% CI 0.06–1.01, P = 0.051 for high, high average and low transporter groups, respectively). Significant predictors of mortality were duration of PD more than 22 months (HR 2.32, 95% CI 1.24–4.33, P = 0.01), increasing age, late referral to a nephrologist and a history of diabetes mellitus. The likelihood of returning to PD was increased if initial PD technique failure was due to mechanical complications compared with all other causes of failure [HR 3.65 (95% CI 2.78–4.79) P < 0.001] and decreased with higher body mass index [HR 0.97 per kg/m2 (95% CI 0.94–0.99), P = 0.01] and the 4 h dialysate: plasma creatinine ratio considered as a continuous variable [4 h D:P Cr; HR 0.32 per unit (95% CI 0.12–0.89), P = 0.03].

Conclusions. The survival disadvantage associated with high peritoneal membrane transport status during PD treatment does not persist following transfer to HD. Early transfer to HD may be beneficial in this patient group.

Keywords: haemodialysis; peritoneal dialysis; peritoneal membrane; survival; transporter



   Introduction
Top
 Abstract
 Introduction
Results
 Discussion
 Acknowledgements
 References
 
The relationship between peritoneal membrane transport characteristics and the outcomes of patients receiving peritoneal dialysis (PD) has been the subject of several studies. Churchill et al. [1] found that, in the CANUSA study population, high transport status was associated with mortality risk; a finding that has been substantiated by several other researchers [2–8]. However, these observations have been offset by several studies, many of which are large multicentre trials, such as ADEMEX and EAPOS, which have found peritoneal membrane properties are not associated with patient survival [9–13]. A common limitation of many of these studies has been small patient numbers, an issue that was addressed in a recent analysis of a very large cohort based on the Australian and New Zealand Dialysis and Transplant (ANZDATA) registry. In this analysis the authors found that high and high average transporters did face an increased mortality risk [14]. Technique failure also occurs more commonly in high transporters and sooner after the commencement of PD [14].

High transporter status has been associated with several parameters that in themselves are associated with poor outcomes on PD, for example, hypoalbuminaemia [15,16] poor nutritional status [17], hypertension and left ventricular hypertrophy [18] and elevated inflammatory markers [19]. Cardiovascular disease is also more common in high transporters than other transport groups [19]. Factors such as these may play a role in the higher rate of adverse outcomes observed in high transporters.

It is unclear whether the poor outcome of high transporters is due solely to the development of adverse events related to the interaction between membrane characteristics and PD, such as hypoalbuminaemia and ultrafiltration failure (UFF). If this is the case, the subsequent survival disadvantage should be ameliorated by transfer to haemodialysis (HD). Alternatively the poor outcome associated with increasing transporter status may reflect an increased burden from comorbidities, including cardiovascular disease. In this latter case, it would be expected that initial transport properties would continue to influence outcomes despite change in dialysis modality.

The aim of the present study was to ascertain whether peritoneal membrane transporter status predicted patient and technique survival among patients who have ceased PD and transferred to HD.

Methods
The ANZDATA database was searched to identify all incident PD patients who subsequently transferred to HD for 1 month or longer between 1 April 1999 and 31 March 2004 and who had a 4 h dialysate: plasma creatinine (4 h D:P Cr) recorded within the first 6 months of commencing PD. Demographic data (age, gender, racial origin), comorbidities (diabetes mellitus (DM), coronary artery disease (CAD), cerebrovascular disease (CVD), peripheral vascular disease (PVD), pulmonary disease, hypertension, cigarette smoking), cause of end-stage renal disease (ESRD), serum creatinine immediately prior to commencement of renal replacement therapy (RRT) and initial modality of RRT were recorded. Estimation of glomerular filtration rate (eGFR) at commencement of RRT was performed using the abbreviated MDRD formula [20]. Transporter status was categorized according to the four groupings of 4 h D: P Cr values defined by Twardowski [21]. (low <0.50, low-average 0.50 – 0.64, high-average 0.65–0.80 and high ≥0.81.)

The primary outcomes of the study were patient survival after commencement of HD and HD technique failure (return to PD for a period of one month or longer). Patient survival data following transfer to HD were censored for transplantation and return to PD. Data for return to PD were censored for death and transplantation. Deaths occurring within two months of change in dialysis modality were included as death attributable to the first modality, as this was considered likely to reflect comorbid conditions prompting transfer rather than the modality itself.

Statistical analysis
Results are expressed as mean ± standard deviation (SD) for continuous parametric data, median (interquartile range) for continuous non-parametric data and frequencies and percentages for categorical data. Differences between groups were assessed by one way analysis of variance and the {chi}2test. Low average transport group was used as the reference group for transporter status. Duration of time on PD was divided into quartiles and analysed as an ordinal categorical variable. Univariate Cox regression analysis was performed to identify factors significantly associated with patient and HD technique survival. Factors with a P- value of <0.05 were considered to be significant.

Factors that were significant on univariate analysis, or that differed significantly between transport groups and parameters previously reported to influence survival, were included in a multivariate Cox proportional hazards model to determine factors significantly associated with survival. To account for possible lead time bias, a history of HD prior to commencing PD and duration of prior HD were included as variables. The final model thus included demographic factors (age, gender, race), comorbid conditions (DM, CAD, PVD, CVD, cigarette smoking), body mass index (BMI), serum creatinine and GFR at commencement of RRT, peritoneal membrane transporter group, a history of HD prior to commencing PD, late referral to a nephrologist, cause of PD technique failure and duration of time on PD. A backward step-wise elimination procedure based on the likelihood ratio was carried out to remove superfluous variables from the model until the most parsimonious model was identified. Adjusted survival times were estimated using the Cox average covariate method, which calculates predicted survival probabilities at the mean levels of the covariates. Proportional hazards assumptions were checked by Schoenfeld residuals and scaled Schoenfeld residuals, examined by formal hypothesis test and graphically. First-order interaction terms between the significant covariates were examined for all models. Finally, to further explore the issue of possible lead time bias, an additional multivariate analysis was performed in which each HD episode was treated as a time-dependent covariate. Additional subgroup survival analyses were performed for people on continuous automated PD (CAPD) and automated PD (APD). In these analyses patients were categorized according to the final PD modality received. Statistical analysis was performed using the statistical software package, SPSS for Windows release 14.0.0 (SPSS Inc. North Sydney, Australia) except for the time-dependent analyses for which Stata version 9.2 was used (College Station, TX, USA). P-values <0.05 were considered statistically significant; no adjustments were made for multiple comparisons.



   Results
Top
 Abstract
 Introduction
 Results
Discussion
 Acknowledgements
 References
 
Patient Characteristics
Total of 1396 patients commenced PD and subsequently transferred to HD between 1st April 1999 and 31st March 2004. A 4 h D:P Cr recorded within the first 6 months of commencing PD was available in 918 (65.8%). The baseline characteristics of the study population are shown in Table 1. A total of 365 patients (39.8%) received a mean period of 1.1 ± 3.1 months of HD before starting PD. The average duration of PD treatment was 16.1 ± 11.3 months.


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  		Table 1. Baseline characteristics of 918 incident peritoneal dialysis patients subsequently transferred to haemodialysis; results are expressed as mean ± SD, median (interquartile range), or frequencies (percentages), depending on data type

 
The mean D:P Cr 4 h was 0.70 ± 0.12. One hundred and fifty three (16.7%) patients were high transporters (H), 472 (51.4%) high average transporters (HA), 257 (28.0%) low average transporters (LA) and 36 (3.9%) low transporters (L). There were no significant differences in demographics, causes of ESRD, comorbid conditions, initial dialysis modality, duration of PD and reason for PD technique failure, between each transporter group. However, BMI and GFR at PD commencement differed significantly between groups.

Patient Survival
In total 138 patients (15.0%) died within the study period. The median survival time on HD, following transfer from PD, was 37.7 months. The median survival time from commencement of first renal replacement therapy was 50.6 months. Kaplan–Meier survival curves for patient survival on HD following transfer from PD and patient survival from commencement of RRT are shown in Figures 1 and 2, respectively. Factors significantly associated with mortality on univariate analysis were increasing age, Caucasian race, lower GFR at commencement of dialysis, higher serum creatinine at commencement of dialysis, late referral to a nephrologist, CAD, PVD, CVD and cigarette smoking. Transporter status was not a significant predictor of survival on univariate analysis (log rank test, P = 0.3). Despite this, it was included in the final multivariate analysis as it has been shown to influence survival in studies of PD outcomes.


Figure 1
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  		Fig. 1. Kaplan–Meier survival curve showing patient survival from commencement of haemodialysis in patients who received peritoneal dialysis and subsequently transferred to haemodialysis.

 

Figure 2
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  		Fig. 2. Kaplan–Meier survival curve showing patient survival from the commencement of renal replacement therapy (RRT) in patients who received peritoneal dialysis and subsequently transferred to haemodialysis.

 
On multivariate Cox regression analysis, there was no difference in survival between high and high average transporters relative to the low average group [hazard ratio (HR) 0.70, 95% CI 0.41–1.19, P = 0.18 and HR 0.96, 95% CI 0.65–1.40, P = 0.82, respectively]. Low transporter status was associated with a trend towards better survival (HR 0.24, 95% CI 0.06–1.01, P = 0.051) relative to low average transporters (Figure 3). The overall P-value for variation among transporter categories was 0.14. When an analysis was performed using time on HD as a time-dependent covariate the HR (95% CI) for survival was 0.85 (0.49–1.48), 0.99 (0.66–1.49) and 0.35 (0.08–1.49) for H, HA and L groups respectively. The P value for overall variation between groups was P = 0.37. When PD modality (CAPD or APD) was added as a covariate in the multivariate Cox regression analysis the predictors of mortality remained unchanged. Similarly when the model used for the survival analysis was repeated for the subgroups of APD and CAPD; transporter status was not a significant predictor of survival.


Figure 3
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  		Fig. 3. Multivariate Cox-adjusted survival curves for each of the four peritoneal transport groups following transfer to haemodialysis. There was no significant difference in survival amongst transport groups compared with the reference group of low average transporter group. Abbreviations: H, high transporter; HA, high average transporter; LA, low average transporter; L, low transporter.

 
Patients in the upper quartile for duration of PD (more than 22 months) had an increased mortality risk (HR 1.85, 95% CI 1.11–3.09, P = 0.02 relative to the lowest quartile). There was a gradient of increased mortality across the intermediate quartiles however, the HRs for these groups were not statistically significant. Other significant predictors of mortality were increasing age, late referral to a nephrologist and a history of DM. A history of treated hypertension at commencement of RRT was associated with a survival advantage. Although late referral was predictive of mortality neither duration of initial RRT nor a history of HD prior to commencing PD (both of which were associated with late referral) were significant in the multivariate analysis. Race, serum creatinine, BMI, calculated GFR, CAD, PVD, CVD and cigarette smoking did not influence survival rates. Details of the final model used in the multivariate analysis are summarized in Table 2.


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  		Table 2. Predictors of mortality on haemodialysis following transfer from peritoneal dialysis in 918 patients according to final multivariate Cox proportional hazards model analysis; results are expressed as adjusted hazard ratio (HR) and 95% confidence interval (CI)

 
Return to peritoneal dialysis
Of the study population, 628 patients (68.4%) remained on HD until study completion or until death; 47 patients (5.1%) received renal transplants and 243 (26.5%) returned to PD. The strongest predictor of a higher likelihood of a return to PD, on multivariate Cox regression analysis, was initial PD technique failure due to mechanical complications [HR 2.37 (95% CI 1.50–3.74 -3) P = 0.03]. Other categories of techniques failure (inadequate solute clearance, infection, ultrafiltration failure, social and other reasons) were not predictive of a return to PD. Recommencement of PD was less likely with increasing BMI [HR 0.97 per kg/m2 (95% CI 0.94–0.99), P = 0.01] and increasing 4 h D:P Cr at PD commencement [HR 0.32 (95% CI 0.12–0.89), P = 0.03].



   Discussion
Top
 Abstract
 Introduction
 Results
 Discussion
Acknowledgements
 References
 
The results of this study demonstrated that baseline peritoneal membrane transport properties at the commencement of PD were not associated with patient survival following subsequent transfer to HD. Specifically, patients with a high average transporter status were not at increased risk of death when compared with the reference group of low average transporters. A further finding in this study was that PD failure due to mechanical complications, (when compared with infection, inadequate solute clearance and ultrafiltration failure) was associated with an increased likelihood of subsequent return to PD following a period of HD.

To our knowledge, this is the first published study to assess the impact of peritoneal membrane transport characteristics on patient outcomes following transfer to HD. In contrast the relationship between transporter status and patient and technique survival in PD has been the subject of several studies, with some conflicting results. In the CANUSA study, Churchill et al. [1] prospectively assessed the influence of peritoneal membrane transport on patient and technique survival in 606 patients. They observed a significant increase in the 2-year probability of both technique and patient survival with decreasing transporter status. The relative risk of either technique failure or death increased with each transporter group, namely 2.54 for LA, 3.39 for HA and 4.00 for H compared with L. Increasing transport status was also associated with reduced drain volumes, decreased serum albumin and increased peritoneal protein losses. Several other studies have found a similar impact of transport status on patient outcomes in patients receiving both CAPD and APD [3–8,22]. There have, however, been a number of studies failing to find a relationship between survival and transport properties. In the ADEMEX trial, a prospective study of 965 patients, baseline peritoneal transport properties (determined by the dialysis adequacy and transport test) did not influence survival [11]. Similarly, in the EAPOS study of patients receiving APD, transport status had no bearing on outcomes [9]. The largest and most recent investigation of this subject was an analysis of 3702 patients using ANZDATA Registry data, which found that the risk of death was significantly, increased by 34% in H transporters and 21% in HA transporters [14].

The relationship between reduced survival on PD and high transporter status may relate to properties of the peritoneal membrane that predispose to the development of conditions associated with a poor prognosis. For example, left ventricular hypertrophy and hypertension are more common in high transporters [18], and are both interrelated with intravascular volume overload [23,24]. This in turn is more common in high transporters [25], as rapid solute transport leads to early dissipation of the osmotic gradient for fluid removal [26] hence, reduced drain volumes [1]. Other markers of a poor prognosis such as hypoalbuminaemia [27] are also more common with higher transport groups. In a cross-sectional study of 106 patients receiving (CAPD), Han et al. [15] found that serum albumin was affected by 24 h D:P Cr, age, C reactive protein (CRP) and Subjective Global Assessment (SGA) score. Similarly Margetts and coworkers [16] found that in 67 incident PD patients the serum albumin had a significant negative correlation with the 4 h D:P Cr. A further example lies with markers of systemic inflammation such as CRP, total white cell count and TGF-β1, which are also associated with all-cause mortality [28–32] and are more common in high transporters [19,33]. The mechanism by which pro-inflammatory states increase mortality on PD is thought to be at least in part by the development of cardiovascular disease [19]. Genetic factors may also play a role in determining baseline transport characteristics, hence patient outcomes. Gillerot et al. [34] showed that the –174G/C polymorphism of the IL-6 gene is an independent predictor of solute transport. The C allele of this polymorphism acts to increase dialysate and plasma IL-6 levels, which in turn lead to increased permeability of the peritoneal membrane.

The absence of a difference in survival between transport groups following transfer to HD may be due to amelioration of the influence peritoneal membrane transport properties have on the prognostic factors discussed above, as the peritoneal membrane is no longer involved in solute transfer. An alternative, yet complementary, explanation is that some complications that develop in high transporters are better managed by HD. For example, as discussed above, volume overload is more common in high transporters and overall total body water volume is lower in patients on HD than CAPD [35] suggesting that management of volume overload is more efficient in HD.

Rumpsfeld et al. [14] found that in a subgroup analysis of a previous ANZDATA analysis high transporter status was predictive of mortality in patients receiving CAPD but not APD (HR 1.44, 95% CI 1.08–1.93, P = 0.01 and HR 1.39, 95% CI 0.87–2.21, P = 0.16 for CAPD and APD respectively). Of note, the confidence intervals for these results were wide, with those for the APD group easily overlapping the effect seem among CAPD patients and in fact there was no significant difference between patients treated with CAPD and APD in the relationship between transporter status and outcome. Nevertheless in light of the fact that APD may achieve better fluid removal in high transporters [36], this result in combination with the present study allows consideration of the possibility that dialysis modalities facilitating improved control of intravascular volume may mitigate the adverse prognosis of high transporters. As such, these results suggest that the poor prognosis associated with high transport status may relate more to use of a therapy that is disadvantageous in this particular group rather than to comorbidities and genetic factors. Information about dialysate strength, particularly the use of icodextrin, would be beneficial in exploring this issue further. Unfortunately, such data is not collected in ANZDATA.

Of note, we did find a trend towards improved survival among the low transporter group compared with the reference group of low average transporters (adjusted HR 0.24, 95% CI 0.06–1.01, P = 0.051). There were, however, only 36 patients in this group, raising the possibility that the study was underpowered to adequately evaluate whether low transporter status truly confers a survival advantage.

An additional finding in this study was that patients who received 22 months or longer of PD had reduced HD survival time. This may be due to lead time bias. However, it could reflect a true effect of later transfer from PD on mortality. In the Netherlands Co-operative Study on the Adequacy of Dialysis, adjusted mortality rates between PD and HD patients were similar for the first two years of dialysis [37]. Beyond this time point, the relative risk of death for patients on HD compared with those on PD decreased progressively. This effect was most prominent in patients more than 60 years of age, which is in keeping with the results of our study, given that increasing age was associated with an increased mortality risk. Vonesh et al. [38] reached a similar conclusion in a study of United States Medicare patients initiating dialysis.

In this study, those patients referred to a nephrologist within 3 months of commencing renal replacement therapy had a poorer prognosis, which is consistent with previous reports [39–41]. Sixty one percent of such patients required HD prior to PD in contrast to 33% of patients referred earlier (data not shown). Intuitively one may think therefore, that a history of HD therapy before PD would also confer a poorer prognosis. However, the predictive value of initial HD was not independent of late referral. A possible explanation is that the poor prognosis associated with late referral to a nephrologist relates to factors other than a higher likelihood of initial HD, such as a higher burden of comorbidities and over-representation of indigenous race [42]. In support of this, in our cohort Aboriginal and Torres Strait Islanders represented 13.2% of people referred late, compared with 6.2% of people referred earlier.

While this study has yielded useful results, there are limitations, some of which have already been discussed. The retrospective nature of the data collection method exposes the information to recall and ascertainment bias. Periods of time on HD prior to commencing PD may introduce lead time bias. This was addressed by including time on HD as a covariate in the Cox regression analysis and by performing an analysis with time on HD entered as a time-dependent covariate. Despite these measures, some lead time bias may still exist. It is also possible that higher rates of technical failure and preferential earlier transfer to HD in high transporters by some clinicians may introduce selection bias and reduce the validity of the results. While we did not detect a difference in HD survival between incident PD transporter groups in this study, the confidence intervals were quite wide and the study population may have been of insufficient size to detect a true difference hence introducing a type II statistical error.

In conclusion, the results of this study demonstrate that the survival disadvantage conferred by high baseline peritoneal membrane transport properties during PD treatment does not continue to play a role following transfer to HD. This finding suggests that dialysis modality may influence the impact of high transporter status on patient outcomes.



   Acknowledgements
Top
 Abstract
 Introduction
 Results
 Discussion
 Acknowledgements
References
 
The authors gratefully acknowledge the substantial contributions of the entire Australia and New Zealand nephrology community (physicians, surgeons, database managers, nurses, renal operators and patients) in providing information for and maintaining the ANZDATA Registry database.

Conflicts of interest statement. None declared.



   References
Top
 Abstract
 Introduction
 Results
 Discussion
 Acknowledgements
 References
 

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Received for publication: 8.10.06
Accepted in revised form: 2. 5.07


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