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HLA Matching Trumps Donor Age: Donor-Recipient Pairing Characteristics That Impact Long-Term Success in Living Donor Kidney Tran

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HLA Matching Trumps Donor Age: Donor-Recipient Pairing Characteristics That Impact Long-Term Success in Living Donor Kidney Tran KidneyTransplantation HLA Matching Trumps Donor Age: Donor-Recipient Pairing Characteristics That Impact Long-Term Success in Living Donor Kidney Transplantation in the Era of Paired Kidney Exchange John Milner, MD, FRCSC1,MarcL.Melcher,MD,PhD2, Brian Lee, MD3, Jeff Veale, MD, FRCSC4,MatthewRonin5, Tom D'Alessandro5, Garet Hil5, Phillip C. Fry, PhD6, Patrick W. Shannon, PhD6 Background. We sought to identify donor characteristics influencing long-term graft survival, expressed by a novel mea- sure, kidney life years (KLYs), in living donor kidney transplantation (LDKT). Methods. Cox and multiple regression analyses were applied to data from the Scientific Registry for Transplant Research from 1987 to 2015. Dependent variable was KLYs. Results. Living donor kidney transplantation (129 273) were performed from 1987 to 2013 in the United States. To allow suf- ficient time to assess long-term results, outcomes of LDKTs between 1987 and 2001 were analyzed. After excluding cases where a patient died with a functioning graft (8301) or those missing HLA data (9), 40 371 cases were analyzed. Of 18 indepen- dent variables, the focus became the 4 variables that were the most statistically and clinically significant in that they are poten- tially modifiable in donor selection (P <0.0001; ie, HLA match points, donor sex, donor biological sibling and donor age). HLA match points had the strongest relationship with KLYs, was associated with the greatest tendency toward graft longevity on Cox regression, and had the largest increase in KLYs (2.0 year increase per 50 antigen Match Points) based on multiple regression. Conclusions. In cases when a patient has multiple potential donors, such as through paired exchange, graft life might be ex- tended when a donor with favorable matching characteristics is selected. (Transplantation Direct 2016;2: e85; doi: 10.1097/TXD.0000000000000597. Published online 6 June 2016.) ith increasing numbers of patients awaiting kidney For practical purposes, it is difficult to conceptualize how Wtransplant, many consider living donor kidney trans- indices such as those above translate into measurable long- plantation (LDKT) as an option. Patients rely on transplant term graft survival. We address “longevity matching” within centers for direction, but centers lack information on which LDKT, using a novel measure, kidney life years (KLYs), that living donor characteristics predict the best long-term re- is easier to conceptualize with respect to the added benefit 1 sults. Introduction of an allocation system for deceased do- kidney may have over another. Kidney life years are defined nation is an attempt at “longevity matching” using the as the number of years a graft has or is expected to function. Kidney Donor Profile Index, though it is not directly appli- For example, if graft “A” survives 7 years and graft “B” sur- cable to LDKT.1 More recently, a Living Kidney Donor Risk vives 9 years, then graft “B” has a +2 KLYs advantage over Index was published.2 “A.” This information is important to patients with multiple direct donors and easy to match patient-donor pairs that are Received 31 December 2015. Revision received 8 April 2016. performance of the research and data analysis. T.D.A. participated in performance Accepted 22 April 2016. of the research and data analysis. G.H. participated in research design, writing of 1 Northshore University Health System, Chicago, IL. the article, performance of the research, and data analysis. P.C.F. participated in 2 Department of Surgery, Stanford University, Stanford, CA. research design, writing of the article, performance of the research, and data 3 analysis. P.W.S. participated in research design, writing of the article, performance Department of Medicine, University of California, San Francisco, San Francisco, CA. of the research, and data analysis. 4 Department of Urology, University of California, Los Angeles, Los Angeles, CA. Correspondence: John Milner, MD, FRCSC, 757 Park Ave West, 3800 Highland 5 The National Kidney Registry, Babylon, NY. Park, IL 60035 ([email protected]; [email protected]). 6 College of Business and Economics, Boise State University, Boise, ID. Copyright © 2016 The Authors. Transplantation Direct. Published by Wolters Kluwer The authors declare no funding or conflicts of interest. Health, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), J.M. participated in research design, writing of the article, performance of the where it is permissible to download and share the work provided it is properly cited. research, and data analysis. M.L.M. participated in research design, writing of the The work cannot be changed in any way or used commercially article, performance of the research, and data analysis. B.L. participated in research design, writing of the article, and data analysis. J.V. participated in ISSN: 2373-8731/16/0000-00 research design, writing of the article, and data analysis. M.R. participated in DOI: 10.1097/TXD.0000000000000597 Transplantation DIRECT ■ Month 2016 www.transplantationdirect.com 1 2 Transplantation DIRECT ■ Month 2016 www.transplantationdirect.com participating in kidney paired donation (KPD) (hereafter de- regression to compute hazard ratios (HRs) for the inde- fined as “participants”) who may have more than 1 potential pendent variables affecting graft longevity (KLYs). A total exchange donor to choose from.3,4 Therefore, we sought to of 40371 transplants were performed between 1987 and identify characteristics that influence long-term LDKT graft 2001 and were followed through March 31, 2013. Of these, survival and examine KLYsas it pertains to optimizing donor 15 821 were no longer functioning, and the exact KLYscould selection. Although KLYs is a novel concept, it is important be computed, whereas 24 550 were “still-functioning” and because participants will understand this metric more easily exact KLYs could not be computed. Cox regression is de- compared with other models. signed to handle this issue of “still-functioning” grafts, using truncated KLYs (graft survival abridged at end of the study interval and recorded as such for matters of data inclusion) MATERIALS AND METHODS to compute HRs. We accessed the Scientific Registry for Transplant Re- The second approach to answer the “which kidney lasts search (SRTR) which includes data on all donors, waitlisted ” 5 longest question applied multiple regression to determine candidates, and transplant recipients in the United States. the expected difference in KLYs for alternative donors. For Records from the standard analysis file (March 31, 2015) this analysis, the dependent variable, KLYs, was determined were analyzed. Events were excluded after December 31, using 1 of 2 ways depending on whether the transplanted 2013, to maximize accuracy due to a lag in SRTR data up- kidney had already failed or was “still functioning.” For dates via the United States Renal Data System and Social Se- failed kidneys, actual KLYs were used. For those cases with curity Master Death Files. “still functioning” kidneys, the KLYs were calculated by The focus was LDKTs occurring from 1987 to 2001 to al- adding the estimated T1/2 life to the known graft life, drawing low sufficient time to assess long-term effects of independent from work done in other studies.6,7 For example, for kidneys variables on the dependent variable (KLYs), especially those that were still functioning after 20 years, 50% are expected that might be modified in donor selection such as would be to still be functioning 17 years later based on the estimated available through KPD, or when more than 1 living donor T1/2, thus the KLYs would be recorded as 37 years. Although is available. Several variables were excluded due to missing we recognize that using the T1/2 estimates has the downside data: donor height, weight, body surface area, and kidney of using extrapolated values for the dependent variable, we size, leaving 18 for analysis (Table 1). Type of immunosup- believe that the resulting regression coefficients more accu- pression and presence of donor-specific antibody (DSA) are rately reflect the impact that the donor characteristics have absent in the SRTR data and could not be assessed. on KLYsand is a superior approach as compared with not in- Graft failure was defined as a patient who returned to cluding the information associated with the nearly 26 000 permanent dialysis or waitlisting and those who received a transplant cases with “still-functioning” grafts. As will be repeat transplant. Patients dying with a functioning graft shown, both the Cox and multiple regression models pointed were censored. Dates of graft failure were used to calculate to the same results internally validating this approach. graft survival. We decided against reporting 5- or 10-year HLA Match Points were calculated using the formula survival because patients are most interested in how long used by the National Kidney Registry. A single “A” antigen the transplanted kidney will last. match, 10 points; “B” match, 15 points; and “DR” match, The first approach we took in answering the question, 25 points. Matches on all 6 loci is equal to 100 points. The “ ” Which LDKT kidney lasts the longest? applied Cox calculation is based on studies reporting HLA-matching af- fecting recipient graft outcome, with variable weighting TABLE 1. assigned to the different HLA loci.8 Independent variables Statistical Methods Qualitative Cox proportional hazards were calculated to demonstrate Donor age > 10 y older than the recipient the degree to which each variable affected the chance for graft Donor age > 55 y failure (event of interest). An HR greater than 1 denotes an Donor age > 60 y increased likelihood of graft loss, whereas a value less than Donor age > Recipient Age 1 denotes a reduced likelihood for graft loss. Multiple linear Donor age > 5 y older than the recipient regression was used to estimate the impact each of the statis- Donor sex: 1 = male 0 = female tically significant independent variables had on KLYs.
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