Presentation on theme: "Ken Andreoni, MD Chair UNOS Kidney Comm The Ohio State University"— Presentation transcript:
1Ken Andreoni, MD Chair UNOS Kidney Comm The Ohio State University UNOS Kidney Committee Allocation Concepts: Not As Different As Some Want You to Believe…Ken Andreoni, MDChair UNOS Kidney CommThe Ohio State UniversityWelcome to the Spring UNOS Regional Meeting Presentation by the Kidney Committee. We would like to review the first set of concepts which we hope to develop into a new kidney allocation policy. We are presenting this information to you in hope of receiving constructive feedback.
2DD Kidney Allocation Concepts We are ONLY talking about standard ADULT Kidney only allocation today. We are NOT talking about:Kidney with extra-renal organ (LK, HK, KP, etc.)Pediatric – no change (except KDPI, not age)Prior Living Donor categoryO-MM National Sharing (CPRA >20)Geography: being thoroughly investigated by other UNOS committees; complex issue
3DD Kidney Allocation Concepts Though we think of allocating 10,000 deceased donor kidneys a year in the US, allocation is one kidney at a time…This is why many theoretical allocation concepts do not work in reality!
4DD Kidney Allocation: Recent Change 0 mm ABDR is local by category of CPRA, then regional or national for CPRA >20 onlyThis change has decreased the share of unsensitized 0 mm, and allowed more highly sensitized candidates to be transplanted nationally with less overall shipping of kidneys
5DD Kidney Allocation: TODAY Estimation of DD kidney graft potential function: ECD or SCDIf ECD: goes to those on the local ECD list (by wait time)If not accepted, then regional, then national ECD listsIf SCD: then all candidates locally by “points”Wait time, HLA-DR matching (2 pts max), CPRA (>80 = 4 pts)Then regional, then national by pts
6DD Kidney Allocation: TODAY Most candidates at the top of list mostly by Wait Time“If I just wait another week/month, could I get a much better kidney?”Makes very inefficient use of very useable kidneysPatients and Transplant Professionals need better educational tools to decide about the trade-off: time to transplant vs. quality of organ
7DD Kidney New Allocation: Concepts (not policy) Estimation of DD kidney graft potential function: ECD or SCD “KDPI”: < or > 20%If KDPI is 21 to 100%, first offered to all within 15 years of donor age (30 yr span)This large group rank ordered (WT, CPRA, HLA)If not accepted, then to those outside of 15 yrs local, then regional, then nationalIf KDPI <=20%; then first to candidates with Est Post-Tx Survival longest 20%If not accepted, then to all local, then regional, then national
8SCD vs ECD: Overlap Too many candidates are listed for ECD Waiting for the ‘Good ECD’Despite this survival overlap, the current system leads to higher discard rates for potential well functioning kidneys that are labeled ECD8
9KDPI vs ECD KDPI ECD Donor age (c) Race/ethnicity Hypertension DiabetesSerum creatinine (c)COD CVAHeightWeightDCDHCVECDDonor Age>60 alone>50 with two below:Cr >1.5HTNCVARR of graft failure >1.7 compared to the ‘ideal’ donor (16 – 17%)The Kidney Donor Profile Index is calculated from DONOR characteristics only. These donor characteristics are listed on the left of this slide and are already collected by OPOs. The KPDI is based on the actual outcome of kidney grafts from donors in the UNOS database over the last several years. The KPDI is an estimate of how well kidneys from donors will function if transplanted in the average recipient.The Estimated Candidate Post-Transplant Survival is based only on Candidate characteristics if they were to receive the average transplant graft. Candidate Age, the presence of diabetes, prior transplant and time with ESRD go into this calculation. Candidates who are estimated to have the potential to live the longest after transplant are considered to be in the “Top 20%” for estimated post-transplant survival.
10KDPI overlaps substantially for donors from most age categories Donor Age v. KDPIKDPI overlaps substantially for donors from most age categoriesThis is a box and whisker plot that shows the wide range of Kidney graft quality across donor ages. The age range of the donors are across the bottom on the X axis and the KPDI is vertically on the Y axis. The lower the KPDI, the longer the likely function of the kidney graft. As you can see, the average or 50th% kidney can come from a donor ranging from 5 years old to 54 years old. So all candidates can have access to kidney grafts of reasonable function.Slide 1010
11Donor Age by Recipient Age ###SAS code in:T:\Data Requests\Kidney-Pancreas\2009\99999\karswork\dpi by donor age.sasSlide 1111
12Distribution of Relative Risks for Donor Kidneys: 2004-2007 Relative Risk for graft failure is not markedly different for top 20% of kidneysUses donor factors only12
13+- 15 years: mostly what we already do… Median age difference is 14 years in the US25% of DD txs <6 yrs apart75% < 26 yrs apartDonors <35 yo are 41% of donorsDonors <=35, mean recipient age is 49Recip >65 more than half of donors >50yoSegev DL. Evaluating Options… AJT 2009; 9:
14DD Kidney UtilizationEstimation of DD kidney graft potential function:ECD/SCD vs KDPIEducation of potential benefit to recipients (and transplant professionals)Quality of organ vs. prolonged wait time for better organ
15Median Expected Survival by Age for Active Kidney Candidates, 1/1/2004 Wolfe et al, SRTRsimulation models
16Median Expected Survival by Age Active Kidney Candidates, 1/1/2004 ###SAS code inT:\Data Requests\Kidney-Pancreas\2007\4783\KARS Exploration\Avg survival by age wl pt gen pop.sasWolfe et al, SRTR Simulation Models16
17Recipient Survival by Recipient Age and Donor DPI ###SAS code in:T:\Data Requests\Kidney-Pancreas\2009\99999\karswork\pt surv by dpi by rec age.sasT:\Data Requests\Kidney-Pancreas\2009\99999\karswork\Donor age by DPI v2.xlsSlide 17transplants17
18Candidate of X yrs old, with Y, Z co-morbidities, living in a DSA C Hypothetical Output from an Educational Tool to help Candidates and Transplant Professionals Make More Informed Decisions on Organ Acceptance:Candidate of X yrs old, with Y, Z co-morbidities, living in a DSA C54321
19The easy potential increase in kidney utilization 19
20DD Kidney UtilizationEstimation of DD kidney graft potential function:ECD/SCD vs KDPIEducation of potential benefit to recipientsTransplant Center Outcome reports
21% Deaths by Year by DPI among candidates >50 by decade of age
22Big Picture Slide: Most with ESRD do not live to avg Big Picture Slide: Most with ESRD do not live to avg. pop lifetime, Transplantation is good for most candidates, young w ESRD lose more years from their expected lifetime.22
23Who is the Sickest? Die first? Like MELD for liverThen we transplant all sicker and older ptsWho loses the most years from their disease?25yo on HD:13 yrs, w Tx:34 yrs60yo on HD: 5 yrs, w Tx:12 yrs25yo unlikely to reach age 60 w Tx25yo will die at <40 yrs of age on HD25yo gains 21 yrs of survival, 60yo gains 7 yrs of survival w Tx25yo lives 13 yrs on HD, 60yo lives 12 yrs w Tx
24‘A Kidney That Looks Like You’ All candidates of all ages have accessAccess for most candidates does NOT changeThe average candidate will receive the SAME quality kidneyWill only prevent transplantation across many decades of age differencesAll candidates may benefit…why?Improvement of utilization of kidneys by KDPI and understanding of age ranges should increase transplantation of appropriate kidneys, especially to older candidatesPublic understanding of system to increase donation
25‘A Kidney That Looks Like You’ Living Donation should not be influenced in the negative: No one goes to the front of the lineWhether within 30 year age group, or “top 20%” everyone within that group is then equal and put in order by variables such as: Wait time, CPRA, HLA, etc., so everyone will wait for their DD offerNOT similar to the Pediatric Share 35 situation that occurred in some DSAs
26Is the Data Good Enough?80% of organs first to candidate group within 15 years (30 yr range)Rank-ordered by variables similar to today such as Wait Time, CPRA, HLA match, etc.Clinical common senseAlignment of potential function of organ to post-transplant potential survival20% DPI and EPTSPredictive models are reasonably good to predict the longest potential functioning organs and longest surviving recipient
27C StatisticMeasure of “goodness of fit”, or how accurately does this tool tell two people apart everywhere on the listIt gives the same weight to tell number 1 from number 10,000, as it does from telling number 5,000 from number 5,001The first is important in allocation, the later is not!