Variation in Peritoneal Dialysis Time on Therapy by Country: Results from the Peritoneal Dialysis Outcomes and Practice Patterns Study

Abstract

Background and objectives: Quantifying contemporary peritoneal dialysis time on therapy is important for patients and providers. We describe time on peritoneal dialysis in the context of outcomes of hemodialysis transfer, death, and kidney transplantation on the basis of the multinational, observational Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS) from 2014 to 2017.

Design, setting, participants, & measurements: Among 218 randomly selected peritoneal dialysis facilities (7121 patients) in the PDOPPS from Australia/New Zealand, Canada, Japan, Thailand, the United Kingdom, and the United States, we calculated the cumulative incidence from peritoneal dialysis start to hemodialysis transfer, death, or kidney transplantation over 5 years and adjusted hazard ratios for patient and facility factors associated with death and hemodialysis transfer.

Results: Median time on peritoneal dialysis ranged from 1.7 (interquartile range, 0.8-2.9; the United Kingdom) to 3.2 (interquartile range, 1.5-6.0; Japan) years and was longer with lower kidney transplantation rates (range: 32% [the United Kingdom] to 2% [Japan and Thailand] over 3 years). Adjusted hemodialysis transfer risk was lowest in Thailand, but death risk was higher in Thailand and the United States compared with most countries. Infection was the leading cause of hemodialysis transfer, with higher hemodialysis transfer risks seen in patients having psychiatric disorder history or elevated body mass index. The proportion of patients with total weekly Kt/V ≥1.7 at a facility was not associated with death or hemodialysis transfer.

Conclusions: Countries in the PDOPPS with higher rates of kidney transplantation tended to have shorter median times on peritoneal dialysis. Identification of infection as a leading cause of hemodialysis transfer and patient and facility factors associated with the risk of hemodialysis transfer can facilitate interventions to reduce these events.

Podcast: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_05_31_CJN16341221.mp3.

Keywords: hemodialysis; kidney transplantation; peritoneal dialysis.

Graphical abstract

Figure 1.

Unadjusted outcomes of peritoneal dialysis (PD) therapy vary by country and by time period after start of PD. Cumulative incidence curve of death, hemodialysis (HD) transfer, and transplant in (A) Australia/New Zealand; (B) Canada; (C) Japan; (D) Thailand; (E) the United Kingdom; and (F) the United States.

Figure 2.

Adjusted and unadjusted outcomes of PD are associated with country. Hazard ratios of PD discontinuation due to death/hemodialysis transfer (HDT), death, HDT, or transplant by country compared with the United States. Hazard ratios were estimated separately for each outcome using Cox models left truncated on the basis of PD vintage. Models were adjusted for patient age, sex, body mass index, Black race, heart disease, diabetes, psychiatric disorder, prior HD experience, urine volume, albumin, caregiver involvement, transplant waiting list referred, and accounting for facility clustering. Transplant waiting list referred was excluded as an adjustment from the model for transplant outcome. A/NZ, Australia/New Zealand; 95% CI, 95% confidence interval; ref, reference; UK, United Kingdom; US, United States.

Figure 3.

Primary and secondary reasons patients switch to HD vary by country and by time period after start of PD. (A) By country and (B) by PD vintage at the time of modality switch, excluding EHR data where no reason was reported, with 287 events. Another 196 events were excluded due to missing reason. EPS, encapsulating peritoneal sclerosis; Jpn, Japan; Thai, Thailand; EHR, electronic health record.

Figure 4.

Patient and facility characteristics are associated with PD outcomes. (A) Hazard ratios for patient characteristics. Hazard ratios were estimated using the left truncated Cox model on the basis of PD vintage. The model was adjusted for patient age, sex, body mass index (BMI), Black race, heart disease, diabetes, psychiatric disorder, prior HD experience, urine volume, albumin, caregiver involvement, transplant waiting list referred, and accounting for facility clustering. There are separate models for each outcome. (B) Adjusted hazard ratios of facility factors. Hazard ratios were estimated using the left truncated Cox model on the basis of PD vintage. The model was adjusted for patient age, sex, BMI, Black race, heart disease, diabetes, psychiatric disorder, prior HD experience, urine volume, albumin, caregiver involvement, transplant waiting list referred, and accounting for facility clustering. There are separate models for each outcome. For facility size and patient-nurse ratio, small ≤quartile 1, large ≥quartile 3, and medium =quartile 1–quartile 3 within the country. Median interquartile ranges are listed in Table 2.