Kidney Allocation- Will it ever be fair? Peter G Stock MD, PhD UCSF Department of Surgery. Would you accept this offer?

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1 Kidney Allocation- Will it ever be fair? Peter G Stock MD, PhD UCSF Department of Surgery Question 1: A 19 y/o deceased donor kidney (O mismatch) from NYC is allocated to a 72 y/o highly sensitized caucasian woman (blood Type O) who has just been listed in SF Would you accept this offer? A) YES B) NO Question 2: A 9 y/o blood type AB kidney is allocated to a 21 y/o unsensitized man Would you accept this offer? A) YES B) NO Three Sides to Allocation Justice Utility Efficiency 1

2 KARS formed in o review of allocation Models proposed KPSAM modeling Process to date Investigation of additional concepts Public Forum #1 Feb 2007 KARS merged with Kidney Committee Review and discussion Public Forum #2 Jan 2009 Consideration of feedback KPSAM modeling Part 1 of New Allocation Proposal Common Sense Clinical Sense Flexibility Addressing Current System Limitations mismatch between potential survival of the kidney and the recipient which increases the need for retransplant and results in hundreds of potential life years not being realized variability in access to transplantation by blood group and geographic location high discard rates of kidneys (especially ECD) that could benefit candidates on the waiting list Major Goals for Kidney Allocation Better match graft longevity and recipient longevity within biological reason and acceptable levels of accessibility Decrease return to wait list Minimize loss of potential graft function Improve system efficiency and organ utilization Make comprehensive data better available to patients and transplant programs Address differences in accessibility for populations described in the National Organ Transplant Act A plan for reaching these goals Utilize a kidney donor profile index () to better characterize donor kidneys and to provide additional clinical information for patients and providers to consider during the transplant evaluation process and organ offer process. Allocate the majority of organs (8) by age matching so that candidates within 1 years (older and younger) of the donor are prioritized. Allocate some kidneys (2) by a kidney donor profile index (KPDI) and estimated recipient posttransplant survival. Longest lived recipients receiving kidney with longest potential function 2

3 Factors used to determine groups Donor age Race/ethnicity Hypertension Diabetes Serum creatinine COD CVA Height Weight DCD HCV Candidate Estimated Post-Transplant Survival (EPTS) Candidate Age Candidate Diabetes Prior transplant ESRD time Kidney allocation based on donor characteristics Currently SCD ECD Proposed <= 2 > 2 * is a formula that summarizes the risk of graft failure into the average patient following kidney transplant by combining a variety of donor factors into a single number *A lower number is lower risk for failure. In three steps: How does this system work? In three steps: How does this system work? 1 Estimate longevity of donor kidney () 2 Divide candidates into broad groups (Group A & B) 3 Rank order candidates within each group (Points) It all starts with the estimated potential function of the kidney that is available for allocation is the kidney one of the 2 longest potential functioning or not? <=2 OR >2 The concept document covers Steps 1 and 2. Step 3 (rank ordering) will be addressed in the future. 3

4 TWO Pathways make up ONE Allocation System TWO Pathways make up ONE Allocation System survival matching age matching survival matching age matching Longest --- Estimated Time to Function --- Shortest Longest --- Estimated Time to Function --- Shortest We determine the pathway based on the DONOR S CHARACTERISTICS (as measured by ) TWO Pathways make up ONE Allocation System Example: = 6 survival matching 2 10 age matching 2 of kidneys 8 of kidneys The majority of kidneys (approximately 8) are allocated by broad age matching 2 year old donor 6 10 GROUP A: 40 to 70 survival matching All candidates year old age matching 2 of kidneys +/- 1 years of candidates 8 of kidneys donor s age <40 and >70 year old candidates GROUP B: Everyone else (older and younger) 4

5 Example: = 1 Distribution of Estimated Median Post-Transplant Survival GROUP A: survival matching All candidates age matching 2 of kidneys EPTS Longest 2 8 of kidneys GROUP B: Everyone else Median PT Lifespan Median life span for recipients is markedly different at Percentile Among Recipients Uses patient factors only Distribution of Relative Risks for Donor Kidneys: RR Graft Failure (DPI eqn) Relative Risk for graft failure is not markedly different for top 2 of kidneys Percentile Among Donor Kidneys Why was +/- 1 years chosen? Considered 10, 1, and 20 year ranges Donor distribution is younger than candidate distribution +/- 10 resulted in fewer donors available to the youngest candidates +/- 20 resulted in fewer donors available to older candidates +/- 1 resulted in a compromise with a more even number of donors available to all candidates Uses donor factors only

6 Candidates With Priority if Age Within X Years of Donor Age Shifts Kidneys Away From Oldest Candidates Donor Age v. Restrictions to Access to Donors by Candidate Age and Rule (Candidate within X years of Donor Age) % Donors Available to Candidates Candidate Age # Newly listed at each year of age Within 10 Within 1 Within 20 Distribution among newly listed in 2008 overlaps substantially for donors from most age categories Slide 22 Summary RESULTS No changes observed to proportion of transplants by Race/ethnicity ABO Blood Types HLA mismatch Changes observed to proportion of transplants by Primary Diagnosis Recipient age (compared to last few yrs) 6

7 System Metrics Baseline (current 2009 rules + extras) Proposed (Top 2, then within 1) : Kidneys used or discarded by donor age Number of transplant recipients 10,974* 10,930* Total lifespan after transplant 12, ,686 Total graft years of life 92,199 97,04 Total extra years* 4,197 9,309 Change in lifespan after transplant (ref) 1,223 Change in graft years of life (ref) 4,847 Change in extra years* (ref),112 Lifespan benefit per transplant Age correlation N u m b e r o f K id n e y s R e m o v e d for Transplant Use d Discarde d Donor age Slide 16 *Difference is not statistically significant Donor-Recipient Age Matching KPSAM Results: Baseline (Current + Extras) Age Correlation = Donor Recipient Age Age < All <18 1.2% 2.1% 3.% 3.4% 0.9% % 4.% 8.7% 10.2% 3.1% 29.9% % 3.4% % 4.1% 29.8% %. 11.7% 6.1% 23.9% % 0.8% 2.7% 1.8%.% All. 11.2% % 16.1% % of transplants have close age match (green cells). 27.7% have large age differential (grey cells). Donor-Recipient Age Matching KPSAM Results: Proposed System Age Correlation = Donor Age < Recipient Age All <18 1.3% 3.% 3.3% 2.4% 0.7% 11.1% % 10.% 9.8% 4.4% 1.4% 29.6% % 3.9% 12.9% 11.4% 1.3% 29.7% % 4.8% 13.6%.3% 24.1% % 0.4% 2.7% 2.3%.4% All.1% 18.4% % % of transplants have close age match (green cells). 14.6% have large age differential (grey cells). Based on SRTR KPSAM Results, Jan 27, Based on SRTR KPSAM Results, Jan 27,

8 Kidney-alone recipient age Recipient Ages % Kidney-alone Recipients Baseline ( extras) Proposed (top 2, then within 1) < Recipient Age Recipient Ages 0 Kidney-alone Recipient Diagnosis 4 40 Baseline Proposed % Kidney-alone Recipients Baseline ( extras) Proposed (top 2, then within 1) Glomerular Hypertension Polycystic Diabetes Other/Missing Recipient Primary Diagsnosis 8

9 High-level timeline PATH FORWARD Spring 2010 Summer/Fall 2010 Fall 2010 Winter/Spring 2011 June 2011 Concept document released *Concepts Proposal revised/details finalized based on PC feedback Public Comment Proposal *Policy details/language Proposal revised based on PC feedback Proposal sent to Board for consideration ENOUGH DEBATES TIME TO MOVE FORWARD SUMMARY Specific pathway defined most consistent with goals of NOTA/HHS/Final Rule AND public comments from stakeholders Backbone of DT, use of DPI, and better matching of donor longevity with projected recipient longevity STOP the transplantation of donor kidneys with long projected survival into recipients with shorter projected post-tx survival times THIS BENEFITS NO ONE Serve as a starting point already broad consensus for better matching donor longevity with recipient longevity 9

10 SUMMARY PROPSOSED PATH FORWARD ALLOWS FOR A SMOOTH TRANSITION PROVIDES A BACKBONE WHICH ACCOMODATES FURTHER MODIFICATIONS BASED ON BETTER DATA (i.e. cardiovascular risk factors) SINGLE NATIONAL SYSTEM WITHOUT VARIANCES To Improve Patient Survival, Allocation is One Strategy Other strategies need to be considered in tandem with the allocation system Removing/re-defining geographic barriers Improving immunosuppression coverage The Future How to Deal With Geographic Disparity Issue which must be secondarily addressed requires a single national allocation system Geographic disparity complex requires objective medical criteria to describe kidney transplant recipients (based on projected survival times) and donors (DPI) utilized in each region Geographic Disparity Wider sharing of organs will require a clear assessment of types of patients being transplant in various regions AND types of donors being utilized Objective data used to facilitate the development of sharing arrangements Analogous to MELD broader sharing arrangements based on geographical differences in the severity of illness 10

11 Backup Slides Three major concepts working together DPI LYFT Donor Profile Index Life Years from Transplant Life Years from Transplant (LYFT) The difference between a candidate s median projected lifespan after transplant minus projected median survival without a transplant DT KAS Dialysis Time Kidney Allocation Score (KAS is calculated each time a donor becomes available) Time without a transplant is adjusted for quality of life 11

12 LYFT Example Example: Based on patient and donor characteristics the remaining lifetime might be estimated as: 1 years with this transplant and years without transplant. LYFT = 1 = Ten extra years of life Weight for Kidney Allocation Score Differential Emphasis for DT and LYFT in the KAS Calculation 10 7% 64% 36% 2% DPI Percentile DT LYFT In the starred example, a donor from the 20 th percentile is available. Candidate KAS scores would be comprised of 64% LYFT and 36% DT. If this candidate is sensitized, sensitization points would be determined and added to the KAS. 12