3. Kidney Transplantation and Wait-Listing Rates from the International Dialysis Outcomes and Practice Patterns Study (DOPPS)

4. Introduction

5. DOPPS Background
DOPPS refers to the Dialysis Outcomes and Practice Patterns Study
DOPPS is a large international study to identify dialysis unit practices associated with the best outcomes for chronic hemodialysis patients
Major outcomes studied are: mortality, hospitalization, vascular access and QoL
DOPPS is sponsored by an unrestricted scientific/educational grant from the Kirin and Amgen companies

6. Methods: Time-To-Transplant
Time-to-transplant analyses used a Cox model left-truncated to account for the time since the patient started ESRD. The analyses were adjusted as indicated.

7. Methods: Probability of Being On the Waitlist
The probability of being on the kidney transplant waitlist was analysed using a logistic model for a prevalent cohort of hemodialysis patients at the time of study entry. Analysis was restricted to patients yrs of age, and who had been on dialysis at least 90 days as of June 1, The analyses were adjusted as indicated.

8. Unadjusted Transplant Rate versus Years on Dialysis
The longer a candidate is on hemodialysis, the lower the transplant rate. This could be due to differences in the ability to get good HLA matches for certain patients. The patients who have waited the longest will have a higher percentage of these rarer antigen patterns and would correspondingly have low transplant rates.

9. Crude Kidney Transplant Rate By Country: DOPPS I (1996-2001)
The rate for year-olds varies by a factor of more than 50 to 1 across countries. All countries transplant 65+ year-olds at a lower rate than younger patients.

10. Patient Factors Predicting Transplant: Demographics
Younger, White, and male patients are transplanted more often, especially if they have been on dialysis for less time. These results are from DOPPS I, adjusted as indicated, including adjustment for country.

11. Patient Factors Predicting Transplant: Comorbidities
With the exception of hypertension (which, unlike the other factors, has a positive relationship overall with survival), sicker patients are transplanted less often.

12. Patient Factors Predicting Transplant: Income, Education, Nursing Home
Wealthier patients with high-school or better education are transplanted more often. Sicker patients in a nursing home are transplanted less often; a pattern that is similar to that found among the comorbidities.

13. Adjusted Relative Rates of Kidney Transplantation for HD Patients, by Country
Adjusting for demographics, comorbidities, and socio-economic factors does not explain the extremely large difference (here > 70:1) in transplantation rates across countries.

14. US Regional Differences in Relative Rates of Kidney Transplantation in HD Patients
Transplantation rates vary widely (by more than 2:1) across regions within the US.

15. Percent of Prevalent HD Patients on Transplant Waitlist, by Country DOPPS II (2002-2003)
Japan has the lowest percentage of patients on a kidney transplant waitlist. Spain displays one of the highest percentage of patients on the waitlist. (Note: these also correspond with the earlier slides on transplantation rates which indicated Japan having the lowest transplant rate and Spain the highest transplant rate).

16. Transplant Waitlisting of HD Patients According to Type of US Dialysis Facility
There is no significant difference between the proportion of patients waitlisted in the US among for-profit and not-for-profit facilities.

17. US Regional Differences in Transplant Waitlisting of HD Patients
There are wide differences in kidney transplant waitlisting across nine US regions, varying by almost 3:1.

18. Patient Factors Associated with Lower Odds of Transplant Waitlisting in HD Patients
In the US, Black patients have lower access to the waitlist and, once on it, a lower rate of transplant. This is not explained by region, comorbid factors, age, or time on dialysis.

19. Conclusions

20. Acknowledgements

21. States in United States geographic regions based on United States census divisions