Clinical Outcomes of PD and HD

For a detailed and updated report on US clinical outcomes for end-stage renal disease patients, see the United States Renal Data System (USRDS) Annual Report.

The mortality rate associated with PD and HD has slowly but definitely improved during the past two decades despite an increase in comorbidity.  In the United States, the adjusted five-year survival by first modality has shown positive trends since 1988 for transplantation, PD and hemodialysis¹. 

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This trend for PD has been maintained for all age groups and major comorbid conditions.  Similarly, a progressive fall in mortality among PD patients between 1981 and 1997 has been reported in Canada, albeit an increasingly aged population and a higher proportion of diabetic patients².

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The relative survival of PD and HD patients has been somewhat difficult to evaluate because of the diversity of data and analyses and the inherent selection bias.  Factors that should theoretically favor HD are peritoneal membrane failure, large body mass and patient burn out.  Preservation of renal function, maintenance of euvolemia and quality of life should favor PD.  A review of the literature on the outcomes between HD and PD reveals marked discrepancies³.  Many of these differences can be easily explained by the type of statistical analysis applied⁴.  In 1995, Bloembergen et al. found that, on average, patients treated with PD had a 19% higher adjusted mortality rate than patients treated with HD based on a prevalent cohort of US patients covering a three year period and 170,700 patient years at risk [the USRDS data system]⁵.  This 19% survival disadvantage was highly significant (p < 0.001).  Fenton et al. analyzed an incident cohort of 11,970 Canadian patients and demonstrated a 27% lower adjusted mortality rate among patients treated with PD versus HD [RR of 0.73; 95% CI 0.68-0.78]⁴.  When Fenton et al. used the methodology of Bloembergen et al. they found no difference in mortality between HD and PD.  The determinants of mortality in PD and HD are quite similar and probably more influential than the modality of renal replacement therapy per se.

Determinants of Mortality in HD and PD

Patient selection (age, sex, education, compliance, etc.)

Dose

Background mortality

Rate of transplantation

Comorbid conditions (DM, malnutrition, CVD)

Quality of general care

Pre-dialysis nephrology care

Center experience

Vintage

Body size

Sequence of modality

Patient selection.  Patient selection introduces one of the major biases evaluating the relative outcomes of HD and PD.  The mere fact that patients elect self therapy suggests that they are more confident, better motivated and possibly better informed than those receiving fully assisted therapy.  The statistics are further confounded by the fact that practically all patients on PD are self care while HD are mostly center patients.  The outcomes would probably be quite different is PD patients were compared to home HD patients.  In addition, differences in age, gender, education and socioeconomic status can markedly affect outcomes.  Thus, every attempt should be made to adjust for these variables. 

Dose of therapy.  It is remarkable that so few comparisons of clinical outcomes between HD and PD have taken into consideration the delivered dose when adjusting results.  Keshaviah et al. compared survival rates of diabetic and non-diabetic PD and HD patients stratified by dose according to the Peak Concentration Hypothesis^6,7.  They observed comparable survival in HD and PD as long as therapy dose was matched.  More recently Gotch introduced the standard Kt/V (stdKt/V) concept to measure the relative efficiency of the whole spectrum of dialytic therapies whether intermittent, continuous or mixed⁸.  The stdKt/V is a method to measure the clearance efficiency of HD of variable frequency, continuous PD, intermittent PD, slow continuous renal replacement therapies (CRRT), residual renal function (RRF) and all situations involving the use of clearance from various methods⁹.  This method could be used to adjust for therapy dose when reporting outcomes with various modalities of therapy.

Background mortality.  The prevalent background mortality of the general population is an important factor to consider in the statistical analysis of survival data since there is such marked variation in survival among ethnic groups. 

Rate of transplantation.  The rate of transplantation will definitely affect the remaining population at risk undergoing dialysis.  Since younger and healthier patients are more likely to be transplanted, censorship for transplantation will influence the results.

Comorbid conditions.  Several studies have concluded that the main differences in survival observed between HD and PD, the variable survival rates observed in specific countries and the differences in survival between nations and series are highly dependent on the frequency and severity of comorbid factors.   

One of the most ominous predictors of death among dialysis patients is hypoalbuminemia and malnutrition.  PD patients are often severely hypoalbuminemic and malnourished at the initiation of dialysis due to diabetes and uremia.  In addition, PD patients are at higher risk of malnutrition due to constant protein losses in the effluent that are significantly higher among high peritoneal transporters and during episodes of peritonitis.  It is imperative to screen for malnutrition and to take it into serious consideration during the dialytic selection process.  If PD is selected, the nutritional status must be closely monitored and proper nutritional supplements are recommended. 

Quality of general care, pre-dialysis nephrology care and center experience.  The quality of general and nephrological care will logically affect the outcomes of dialysis by delivering a healthier patient for renal substitution therapy.  Nephrological training and the interest and experience of the team should further enhance the quality of care.  Schaubel et al. identified center activity in PD as having a significant impact on relative risk of death and of technique failure¹⁰. Centers with the largest cumulative experience of PD and those where a majority of patients were initiated with PD had lower relative risk of death and technique failure.  Comparing centers with the most and the least cumulative experience of PD, patients treated at more experienced centers had a 30% reduction in risk of death. Risk of technique failure was also diminished by PD experience [17% reduction for most versus least experienced].

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Early nephrology referral of patients with chronic kidney disease (CKD) has been suggested to reduce mortality after initiation of dialysis.  Kahn et al. performed a retrospective cohort study of incident dialysis patients between 1995 and 1998 to address the association between frequency of nephrology care during the 24 months before initiation of dialysis and first-year mortality after initiation of dialysis¹¹. Nephrology care before dialysis was shown to be important and consistency of care in the immediate six months before dialysis was a predictor of mortality. Consistent nephrology care may be more important than previously thought, particularly because the frequency and severity of CKD complications increase as patients approach dialysis.  Similarly, Schwenger et al. reported significantly better survival among patients referred more than 17 weeks before the start of dialysis as compared to those with shorter pre-dialysis care¹².

Early referral probably improves outcomes by allowing early interventions which may delay the progression of renal disease, by providing additional time for patient education that may facilitate informed consent and improve compliance.  Less urgent starts will also improve peritoneal access and could influence the rate of renal transplantation. 

Body size.  Obesity is often cited as a risk factor for vascular disease and a relative contraindication for PD.  Interestingly, increased body weight and body mass index (BMI) have been identified as potentially protective factors in improving survival for both HD¹³ and PD.  This reverse epidemiology has been further studied by Kalantar-Zadeh et al. by examining the changes in weight over time and prospective mortality using time-dependent Cox models and adjusting for changes in laboratory values over time and BMI with mortality in a prospective study¹⁴.  Weight gain and both baseline and time-varying obesity was associated with reduced cardiovascular mortality in HD patients independent of laboratory findings and nutritional status.  In fact, morbidly obese patients had the lowest mortality. 

Snyder et al. performed a prospective cohort study of US Medicare PD patients initiating dialysis between 1995 and 2000 to evaluate the effect of body size on outcomes¹⁵.  They showed that overweight and obese patients, although less likely to initiate PD, have longer survival than those with lower BMI.  These observations were not explained by their lower transplantation and technique survival rates.

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Ramkumar et al. using creatinine excretion as a measure of muscle mass and BMI concluded that both body size and composition influenced survival of incident PD patients¹⁶.  They recommended a gain in muscle mass rather than fat mass among patients undergoing PD.

Sequence of modality.    It is possible that the initial modality of therapy may influence outcomes.  Van Biesen et al. showed a survival advantage for integrative care in a matched-pair analysis of patients who started on PD and were transferred to HD (integrative care patients) and patients who started and remained on HD¹⁷.  A retrospective analysis of data from China on incident patients initially treated with either PD or HD also found that initial treatment with PD was associated with a higher survival rate¹⁸.  Potential factors to explain the benefits of PD as first therapy include selection bias (better motivated and healthier patients undergoing PD first), better preservation of renal function among PD patients (see How RRF Influences Survival) and the opportunity to create an adequate AV fistula before a possible transfer to HD. 

The initial modality of therapy and switches in therapy also have an impact on cost.  Shih et al. examined the impact of initial dialysis modality choice and subsequent modality switches on Medicare expenditures over a three year period¹⁹.  After adjusting for patient characteristics, the annual expenditure was significantly lower for PD as the initial modality.  The PD group no-switch and one-switch had a significantly lower total expenditure than the respective HD subgroups.

References:

1. U.S. Renal Data System, Excerpts from the USRDS 2004 Annual Data Report.  Am J Kidney Dis 45 (Suppl 1):S1-S280, 2005
2. Schaubel DE, Fenton SSA. Trends in mortality rates on peritoneal dialysis: Canada 1981 – 1997.  J Am Soc Nephrol 11:126-133, 2000
3. Schaubel DE, Morrison HI, Fenton SSA. Comparing mortality rates on CAPD/CCPD and hemodialysis.  The Canadian experience: Fact or fiction? Perit Dial Int 18:478-484, 1998
4. Fenton SSA, Schaubel DE, Desmeules M, Morrison HI, Mao Y, Copleston P, et al. Am J Kidney Dis 30:334-342, 1997
5. Bloembergen WE, Port FK, Mauger EA, Wolfe RA. A comparison of mortality between patients treated with hemodialysis and peritoneal dialysis. J Am Soc Nephrol 6:177-183, 1995
6. Keshaviah PR, Nolph KD, Van Stone JC. The peak concentration hypothesis: A urea kinetic approach to comparing the adequacy of continuous ambulatory peritoneal dialysis (CAPD) and hemodialysis. Perit Dial Int 9:257-260, 1989
7. Keshaviah P, Ma J, Thorpe K, Churchill D, Collins A. Comparison of 2 year survival on hemodialysis (HD) and peritoneal dialysis (PD) with dose of dialysis matched using the Peak Concentration Hypothesis. J Am Soc Nephrol 6:540, 1995
8. Gotch FA. The current place of urea kinetic modeling with respect to different dialysis modalities. Nephrol Dial Transplant 13:10-14, 1998
9. Diaz-Buxo JA, Loredo JP. Standard kt/v: comparison of calculation methods. Artif Organs 30:178-185, 2006
10. Schaubel DE, Blake PG, Fenton SS.  Effect of renal centre characteristics on mortality and technique failure on peritoneal dialysis.  Kidney Int 60:1517-1524, 2001
11. Khan SS, Xue JL, Kazmi WH, Gilbertson DT, Obrador GT, Pereira BJ, Collins AJ. Does predialysis nephrology care influence patient survival after initiation of dialysis? Kidney Int 67:1038-1046, 2005
12. Schwenger V, Hofmann A, Khalifeh N, Meyer T, Zeier M, Horl WH, Ritz E. [Uremic patients--late referral, early death]. Dtsch Med Wochenschr 128:1216-1220, 2003
13. Lowrie EG, Chertow GM, Lew NL, Lazarus JM, Owen WF. The urea [clearance x dialysis time] product (Kt) as an outcome-based measure of hemodialysis dose. Kidney Int 56:729-737, 1999
14. Kalantar-Zadeh K, Kopple JD, Kilpatrick RD, McAllister CJ, Shinaberger CS, Gjertson DW, Greenland S. Association of morbid obesity and weight change over time with cardiovascular survival in hemodialysis population. Am J Kidney Dis 46:489-500, 2005
15. Snyder JJ, Foley RN, Gilbertson DT, Vonesh EF, Collins AJ. Body size and outcomes on peritoneal dialysis in the United States. Kidney Int 64:1838-1844, 2003
16. Ramkumar N, Pappas LM, Beddhu S. Effect of body size and body composition on survival in peritoneal dialysis patients. Perit Dial Int 25:461-469, 2005
17. Van Biesen W, Vanholder RC, Veys N, Dhondt A, Lameire NH. An evaluation of an integrative care approach for end-stage renal disease patients. J Am Soc Nephrol 11:116-125, 2000
18. Lin TC, Kao MT, Lai MN, Huang CC. Mortality difference by dialysis modality among new ESRD patients with and without diabetes mellitus. Dial & Transplant 35:234-244. 2006
19. Shih TY-C, Guo A, Just PM, Mujais S. Impact of initial dialysis modality and modality switches on Medicare expenditures of end-stage renal disease patients. Kidney Int 68:319-329, 2005