The Risk of Transplant Failure With HLA Mismatch in First Adult Kidney Allografts 2: Living Donors, Summary, Guide

Abstract

Background: Allografts from living donors survive longer than those from deceased donors but the role of HLA mismatching in living kidney donation is still in question. We examined the effect of HLA compatibility on kidney allograft survival from living donors by studying all first adult kidney transplants performed in the United States over 25 years.

Methods: Using the United Network for Organ Sharing data, we identified first kidney transplants between October 1, 1987, and December 31, 2013. Recipients were classified by their number of HLA mismatches and stratified by donor origin. Cox multivariate regression analyses adjusting for recipient and donor transplant characteristics were performed to determine impact of HLA compatibility on kidney allograft survival for all living donors and for living related and living unrelated subsets.

Results: There were 66 596 first adult transplants from living donors with 348 960 years of follow-up. We found a linear relationship between HLA mismatch and allograft survival. In adjusted analyses, among all living donors, 1 mismatch conferred a 44% higher risk, whereas 6 mismatches conferred a twofold higher risk of allograft failure. When using 0-mismatched full siblings as a reference, living-donor kidneys reduce the hazard of failure by approximately 34% when compared with deceased donors. Twenty-five years of transplant experience, stratified by donor source, was summarized and presented as a guide for allocation.

Conclusions: These data reinforce the importance of optimizing HLA matching to further improve survival in first adult kidney allografts in the future, especially in living unrelated donations, when possible.

FIGURE 1

Cox multivariate regressions were performed with the survival time of kidney allografts from living donors as the dependent variable and HLA mismatch as the primary explanatory variable with 0 mismatch as the reference. Blue diamonds represent the observed HRs for HLA mismatch for a reduced model with age, sex, and transplant era as covariates (Table S5, SDC, http://links.lww.com/TXD/A36), whereas the red squares represent the observed HR values for the full model as presented in Table 2. The solid blue line is the fitted line for the reduced model with an intercept of 1.31 (0.92-1.70; P = 0.0003) and a slope of 0.15 (0.04-0.26; P = 0.0161), whereas the red line is fitted to the full model observed values with an intercept of 1.28 (0.94-1.61; P = 0.0002) and a slope of 0.15 (0.05-0.24; P = 0.0096). Error bars are the 95% CI for the respective points on the fitted lines.

FIGURE 2

Cox multivariate regressions were performed with the survival time of kidney allografts from LR donors as the dependent variable and HLA mismatch as the primary explanatory variable with 0 mismatch as the reference. Blue diamonds represent the observed HRs for HLA mismatch for a reduced model with age, sex, and transplant era as covariates (Table S5, SDC, http://links.lww.com/TXD/A36), whereas the red squares represent the observed HR values for the full model (Table 2). The solid blue line is the fitted line for the reduced model with an intercept of 1.21 (0.91-1.51; P = 0.0002) and a slope of 0.21 (0.10-0.31; P = 0.0037), whereas the red line is fitted to the full model observed values with an intercept of 1.20 (0.92-1.48; P = 0.0001) and a slope of 0.19 (0.09-0.29; P = 0.0043). Error bars are the 95% CI for the respective points on the fitted lines.

FIGURE 3

Cox multivariate regressions were performed with the survival time of kidney allografts from LU donors as the dependent variable and HLA mismatch as the primary explanatory variable with 0 mismatch as the reference. Blue diamonds represent the observed HRs for HLA mismatch for a reduced model with age, sex, and transplant era as covariates (Table S5, SDC, http://links.lww.com/TXD/A36), whereas the red squares represent the observed HR values for the full model (Table 2). The solid blue line is the fitted line for the reduced model with an intercept of 1.41 (0.84-1.98; P = 0.0014) and a slope of 0.16 (0.04-0.28; P = 0.0213), whereas the red line is fitted to the full model observed values with an intercept of 1.47 (0.90-2.03; P = 0.0011) and a slope of 0.16 (0.04-0.29; P = 0.0194). Error bars are the 95% CI for the respective points on the fitted lines.

FIGURE 4

Fully adjusted Cox multivariate regressions for kidney allograft failure time were performed when stratified by kidney allograft origin: deceased (green), LR (red), and LU (blue). HLA mismatch is the primary explanatory variable with 0 mismatch as the reference (Table 2). The solid line of the respective color is fitted to the observed points weighted by the number in each mismatch category for that stratum. Although kidneys from living donors survive longer than do those from deceased donors, the LU donor HRs for HLA mismatches are greatest, which suggests that there is a greater penalty in survival for mismatching a LU donor kidney when compared with a LR donor, and that the survival mismatch penalty is greater for living donors when compared with deceased ones.

FIGURE 5

A weighted regression line (red) was fitted to the HRs (red squares) in Table 4, a categorical variable that was constructed to combine the relatedness strata with HLA mismatch. The predicted line has an intercept of 1.27 (1.07-1.47; P <0.0001) and a slope of 0.14 (0.09-0.20; P < 0.0001). This slope is similar to the fully adjusted line of Figure 1 for all living donors and lies above the line for deceased donors, as previously described. Therefore, there is a higher penalty in kidney failure time for each HLA mismatch for a living donor as opposed to an organ from a deceased donor.

FIGURE 6

The distribution of HLA mismatches stratified by relatedness of the donor, for all living donors, is skewed to the right for the LU stratum because there are relatively small numbers of living donors in categories 0 to 2 (Table 1). Given that the LU 0 and 1 mismatch categories were not significantly different from the LR 0-mismatch category in the full Cox regression, improving the numbers of persons in these categories could potentially increase overall survival in the unrelated sample.

FIGURE 7

To parse the “living component” for increased kidney survival a new categorical variable with 7 values was created (Table 5). With 0-mismatched full sibling transplants as a reference the magnitudes of the HRs in a full Cox multivariate regression allowed us to estimate a reduction of approximately 34% in the risk of kidney failure for living donations with more than 1 mismatch. This is illustrated by the higher green bars for the deceased donor strata. See text for details.

FIGURE 8

Cox multivariate regressions were performed with the survival time of kidney allografts as the dependent variable and HLA mismatch as the primary explanatory variable with 0 mismatch as the reference. Blue diamonds represent the observed HRs for HLA mismatch for a reduced model with age, sex, and transplant era as covariates, while the red squares represent the observed HR values for the full model (Table 6). The solid blue line is the fitted line for the reduced model with an intercept of 1.01 (0.94-1.07; P < 0.0001) and a slope of 0.19 (0.17-0.21; P < 0.0001), whereas the red line is fitted to the full model observed values with an intercept of 1.08 (0.98-1.18; P < 0.0001) and slope of 0.12 (0.10-0.15; P < 0.0001). Error bars are the 95% CI for the respective points on the fitted lines.

FIGURE 9

Full model Cox multivariate regressions were performed within each 5-year period with HLA mismatch as the primary explanatory variable: 1987-1993, blue line; 1994-1998, green; 1999-2003, gray; 2004-2008, orange; and 2009-2013, red. The fitted lines are from a weighted regression within each period. The dashed black line is the weighted regression line over all 35 HRs. Each line has a statistically significant intercept and slope (Table 8). The HRs for the latest period are less than for the earlier ones in mismatch categories 4 to 6 and might reflect the combination of better immunosuppression and the use of living donor organs. However, because of the limited sample size and much smaller follow-up time per person for this interval, this result should be viewed with caution. See Figure 10.

FIGURE 10

The follow-up years per person was calculated for each of the 5-year periods in our time covariate and plotted against the slopes of the weighted fitted regression lines on the HRs within each period. Although the slope of the latest period, 2009-2013, is least, and might suggest that the effect of HLA matching is becoming less important, this is also the period in which the follow-up time is least, 1.87 years per person. The accuracy of the HRs for HLA matching, as all covariates in a Cox multivariate regression, are sensitive to sample size and follow-up time. Therefore, the stronger effect of HLA, which is apparent in the earlier periods, might very well be present with a higher slope when more data are available.