Nonimmunologic Donor-Recipient Pairing, HLA Matching, and Graft Loss in Deceased Donor Kidney Transplantation

Predicting graft and patient outcomes following kidney transplantation using interpretable machine learning models

The decision to accept a deceased donor organ offer for transplant, or wait for something potentially better in the future, can be challenging. Clinical decision support tools predicting transplant outcomes are lacking. This project uses interpretable methods to predict both graft failure and patient death using data from previously accepted kidney transplant offers. Using more than 25 years of transplant outcome data, we train and compare several survival analysis models in single risk settings. In addition, we use post hoc interpretability techniques to clinically validate these models. Neural networks show comparable performance to the Cox proportional hazard model, with concordance of 0.63 and 0.79 for prediction of graft failure and patient death, respectively. Donor and recipient ages, the number of mismatches at DR locus, dialysis type, and primary renal disease appear to be important features for transplant outcome prediction. Owing to their good predictive performance and the clinical relevance of their post hoc interpretation, neural networks represent a promising core component in the construction of future decision support systems for transplant offering.

Role of Complement-dependent Cytotoxicity Crossmatch and HLA Typing in Solid Organ Transplant

BACKGROUND

Solid organ transplantation is a life-saving medical operation that has progressed greatly because of developments in diagnostic tools and histocompatibility tests. Crossmatching for complement-dependent cytotoxicity (CDC) and human leukocyte antigen (HLA) typing are two important methods for checking graft compatibility and reducing the risk of graft rejection. HLA typing and CDC crossmatching are critical in kidney, heart, lung, liver, pancreas, intestine, and multi-organ transplantation.

METHODS

A systematic literature search was conducted on the internet, using PubMed, Scopus, and Google Scholar databases, to identify peer-reviewed publications about solid organ transplants, HLA typing, and CDC crossmatching.

CONCLUSION

Recent advances in HLA typing have allowed for high-resolution evaluation, epitope matching, and personalized therapy methods. Genomic profiling, next-generation sequencing, and artificial intelligence have improved HLA typing precision, resulting in better patient outcomes. Artificial intelligence (AI) driven virtual crossmatching and predictive algorithms have eliminated the requirement for physical crossmatching in the context of CDC crossmatching, boosting organ allocation and transplant efficiency. This review elaborates on the importance of HLA typing and CDC crossmatching in solid organ transplantation.

Recipient race modifies the association between obesity and long-term graft outcomes after kidney transplantation

Donor and recipient obesity (defined using body mass index [BMI]) are associated with worse outcomes after kidney transplant (KT). In adult KT recipients identified using the Scientific Registry of Transplant Recipients (2000-2017), we examined the modifying effect of recipient race on recipient obesity (BMI > 30 kg/m2) and combined donor and recipient (DR) obesity pairing, with death-censored graft loss (DCGL), all-cause graft loss (ACGL), and short-term graft outcomes using multivariable Cox proportional hazards models and logistic regression. Obesity was associated with a higher risk of DCGL in White (adjusted hazard ratio [aHR], 1.29; 95% CI, 1.25-1.35) than Black (aHR, 1.13; 95% CI, 1.08-1.19) recipients. White, but not Black, recipients with obesity were at higher risk for ACGL (aHR, 1.08; 95% CI, 1.05-1.11, for White recipients; aHR, 0.99; 95% CI, 0.95-1.02, for Black recipients). Relative to nonobese DR, White recipients with combined DR obesity experienced more DCGL (aHR, 1.38; 95% CI, 1.29-1.47 for White; aHR, 1.19; 95% CI, 1.10-1.29 for Black) and ACGL (aHR, 1.12; 95% CI, 1.07-1.17 for White; aHR, 1.00; 95% CI, 0.94-1.07 for Black) than Black recipients. Short-term obesity risk was similar irrespective of race. An elevated BMI differentially affects long-term outcomes in Black and White KT recipients; uniform BMI thresholds to define transplant eligibility are likely inappropriate.

Reciprocal Donor-Recipient Strain Combinations Present Different Vascularized Composite Allotransplantation Outcomes in Rodent Models

BACKGROUND

Although vascularized composite allotransplantation (VCA) has been the focus of many animal studies, further research is needed to determine the potential for a generalized model and immunosuppression regimen that applies across different donor-recipient combinations. In this study, the authors evaluated the outcome of VCAs performed on reciprocal rodent donor-recipient combinations.

METHODS

VCA was performed in rats using Lewis and Brown Norway (BN) donor-recipient pairs, under the previously reported antilymphocyte serum/cyclosporine/adipose-derived stem cell regimen. Similarly, a published co-stimulatory blockade/rapamycin regimen was performed on the mouse VCA model between Balb/C and C57BL/6 strains.

RESULTS

To accommodate the active behaviors of BN recipients, the allograft had to be modified and inset to the neck instead of to the groin. The tolerogenic regimen did not provide the same benefits for BN rats as it did for Lewis recipients. Increasing antilymphocyte serum dose and extending the duration of cyclosporine administration from 10 to 21 days significantly prolonged allograft survival and induced donor-specific tolerance. In mice, the co-stimulatory blockade/rapamycin regimen produced inferior VCA outcomes in BALB/c recipients than in C57BL/6 recipients. In both rats and mice, the authors identified an association between the tolerance outcome and the peripheral chimerism measured on postoperative day 30.

CONCLUSIONS

Reciprocal donor-recipient combinations led to different responses toward the immunosuppression regimen and varied VCA outcomes. Sustained donor chimerism that remained in circulation for 1 month after surgery supported long-term VCA survival. Modification of the model and immunosuppression regimen accordingly is recommended.

CLINICAL RELEVANCE STATEMENT

Various donor-recipient combinations respond differently to the immunosuppression regimens. Maintaining donor chimerism for 30 days after surgery improves VCA survival. It is recommended to tailor the immunosuppression regimen based on the recipient's background to optimize outcomes.

Seeking Standardized Definitions for HLA-incompatible Kidney Transplants: A Systematic Review

BACKGROUND

There is no standard definition for "HLA incompatible" transplants. For the first time, we systematically assessed how HLA incompatibility was defined in contemporary peer-reviewed publications and its prognostic implication to transplant outcomes.

METHODS

We combined 2 independent searches of MEDLINE, EMBASE, and the Cochrane Library from 2015 to 2019. Content-expert reviewers screened for original research on outcomes of HLA-incompatible transplants (defined as allele or molecular mismatch and solid-phase or cell-based assays). We ascertained the completeness of reporting on a predefined set of variables assessing HLA incompatibility, therapies, and outcomes. Given significant heterogeneity, we conducted narrative synthesis and assessed risk of bias in studies examining the association between death-censored graft failure and HLA incompatibility.

RESULTS

Of 6656 screened articles, 163 evaluated transplant outcomes by HLA incompatibility. Most articles reported on cytotoxic/flow T-cell crossmatches (n = 98). Molecular genotypes were reported for selected loci at the allele-group level. Sixteen articles reported on epitope compatibility. Pretransplant donor-specific HLA antibodies were often considered (n = 143); yet there was heterogeneity in sample handling, assay procedure, and incomplete reporting on donor-specific HLA antibodies assignment. Induction (n = 129) and maintenance immunosuppression (n = 140) were frequently mentioned but less so rejection treatment (n = 72) and desensitization (n = 70). Studies assessing death-censored graft failure risk by HLA incompatibility were vulnerable to bias in the participant, predictor, and analysis domains.

CONCLUSIONS

Optimization of transplant outcomes and personalized care depends on accurate HLA compatibility assessment. Reporting on a standard set of variables will help assess generalizability of research, allow knowledge synthesis, and facilitate international collaboration in clinical trials.

Combined Donor-Recipient Obesity and the Risk of Graft Loss After Kidney Transplantation

Background: As the prevalence of obesity increases globally, appreciating the effect of donor and recipient (DR) obesity on graft outcomes is of increasing importance.

Methods: In a cohort of adult, kidney transplant recipients (2000–2017) identified using the SRTR, we used Cox proportional hazards models to examine the association between DR obesity pairing (body mass index (BMI) >30 kg/m2), and death-censored graft loss (DCGL) or all-cause graft loss, and logistic regression to examine risk of delayed graft function (DGF) and ≤30 days graft loss. We also explored the association of DR weight mismatch (>30 kg, 10-30 kg (D>R; D<R) and <10 kg (D = R)) with each outcome, stratifying by DR obesity pairing.

Results: Relative to non-obese DR, obese DR were highest risk for all outcomes (DCGL: HR 1.26, 95% CI 1.22–1.32; all-cause graft loss: HR 1.09, 95% CI 1.06–1.12; DGF: OR 1.98, 95% CI 1.89–2.08; early graft loss: OR 1.34, 95% CI 1.19–1.51). Donor obesity modified the risk of recipient obesity and DCGL [p = 0.001] and all-cause graft loss [p < 0.001] but not DGF or early graft loss. The known association of DR weight mismatch with DCGL was attenuated when either the donor or recipient was obese.

Conclusion: DR obesity status impacts early and late post-transplant outcomes.

Impact of Size Matching Based on Donor-Recipient Height on Kidney Transplant Outcomes

Transplantation of kidneys from shorter donors into taller recipients may lead to suboptimal allograft survival. The effect of discrepancy in donor and recipient heights (ΔHeight) on long term transplant outcomes is not known. Adult patients ≥18 years undergoing living or deceased donor (LD or DD) kidney transplants alone from donors ≥18 years between 2000 and 2016 in the United States were included in this observational study. The cohort was divided into three groups based on ΔHeight of 5 inches as 1) Recipient < Donor (DD: 31,688, LD: 12,384), 2) Recipient = Donor (DD: 84,711, LD: 54,709), and 3) Recipient > Donor (DD: 21,741, LD: 18,753). Univariate analysis showed a higher risk of DCGL and mortality in both DD and LD (p < 0.001 for both). The absolute difference in graft and patient survival between the two extremes of ΔHeight was 5.7% and 5.7% for DD, and 0.4% and 1.4% for LD. On multivariate analysis, the HR of DCGL for Recipient < Donor and Recipient > Donor was 0.95 (p = 0.05) and 1.07 (p = 0.01) in DD and 0.98 (p = 0.55) and 1.14 (p < 0.001) in LD. Similarly, the corresponding HR of mortality were 0.97 (p = 0.07) and 1.07 (p = 0.003) for DD and 1.01 (p < 0.001) and 1.05 (p = 0.13) for LD. For DGF, the HR were 1.04 (p = 0.1) and 1.01 (p = 0.7) for DD and 1.07 (p = 0.45) and 0.89 (p = 0.13) for LD. Height mismatch between the donor and recipient influences kidney transplant outcomes.

Time to Move on: HLA Matching Should Be Reconsidered in Modern Deceased Donor Kidney Allocation

HLA matching has been the cornerstone of deceased donor kidney allocation policies worldwide but can lead to racial inequity. Although HLA matching has been shown to improve clinical outcomes, the long-term impacts of nonallogenic factors are being increasingly recognized. This has led some transplant programs to include points for nonallogenic factors, for example, age. Our study looks at long-term graft and patient outcomes based on allocation cohorts rather than individual number of HLA mismatches.

Donor selection for multiorgan transplantation

PURPOSE OF REVIEW

There is limited data and guidance on donor selection for multiorgan transplantation. In this article, we review the current Organ Procurement and Transplantation Network policy on multiorgan allocation and the ideal donor criteria for each specific organ, in order to provide a framework to guide donor selection for various scenarios of multiorgan transplantation, including heart-kidney, heart-lung, heart-liver and heart-kidney-liver transplant procedures.

RECENT FINDINGS

Combined heart-kidney transplantation is the most common multiorgan transplant procedure and requires the most stringent HLA matching to ensure optimal graft survival. Using the virtual crossmatch and desensitization therapies can shorten waitlist times without increasing posttransplant rejection or mortality rates. The ideal heart-lung donor tends to be younger than other multiorgan transplants, and more tolerant to HLA mismatch, but ideally requires donors with no prior history of smoking, a short period of time on mechanical ventilation, adequate oxygenation and absence of pulmonary infection. The ideal heart-liver donor is often driven by criteria specific to the donor heart. Finally, several observational studies suggest that livers are more tolerant to HLA mismatch than other organs, and offer some degree of immune protection in combined organ transplants.

SUMMARY

Multiorgan transplantation is a steadily growing field. The required short ischemic time for the donor heart is often the limiting factor, as well as the scarcity of appropriate donors available within geographical confines. In general, as with single organ transplantation, younger age, size matching, few medical comorbidities and HLA compatibility confer the best posttransplant outcomes.

Predicting Kidney Graft Survival Using Machine Learning Methods: Prediction Model Development and Feature Significance Analysis Study

BACKGROUND

Kidney transplantation is the optimal treatment for patients with end-stage renal disease. Short- and long-term kidney graft survival is influenced by a number of donor and recipient factors. Predicting the success of kidney transplantation is important for optimizing kidney allocation.

OBJECTIVE

The aim of this study was to predict the risk of kidney graft failure across three temporal cohorts (within 1 year, within 5 years, and after 5 years following a transplant) based on donor and recipient characteristics. We analyzed a large data set comprising over 50,000 kidney transplants covering an approximate 20-year period.

METHODS

We applied machine learning-based classification algorithms to develop prediction models for the risk of graft failure for three different temporal cohorts. Deep learning-based autoencoders were applied for data dimensionality reduction, which improved the prediction performance. The influence of features on graft survival for each cohort was studied by investigating a new nonoverlapping patient stratification approach.

RESULTS

Our models predicted graft survival with area under the curve scores of 82% within 1 year, 69% within 5 years, and 81% within 17 years. The feature importance analysis elucidated the varying influence of clinical features on graft survival across the three different temporal cohorts.

CONCLUSIONS

In this study, we applied machine learning to develop risk prediction models for graft failure that demonstrated a high level of prediction performance. Acknowledging that these models performed better than those reported in the literature for existing risk prediction tools, future studies will focus on how best to incorporate these prediction models into clinical care algorithms to optimize the long-term health of kidney recipients.

Donor-Recipient Matching in Kidney Transplant: We're Not There Yet

BACKGROUND

Strategic organ allocation is expected to prolong patient and graft survival after transplant. This study explored differences in graft survival when kidneys are allocated based on strategic donor-recipient (D-R) pairing vs with the existing Kidney Allocation System (KAS).

METHODS

Using the Scientific Registry of Transplant Recipients from 2000 to 2014, we used a multivariable Cox model to assess the hazard ratios (HRs) for death or graft failure among 3 hypothetical donor kidneys transplanted into 3 hypothetical recipients, relative to an ideally matched D-R pair. Median predicted survival for each of the 9 possible D-R pairing combinations was determined, and outcomes for strategic D-R pairing were compared with those obtained using the KAS for allocation.

RESULTS

A total of 31,607 patients (29.7%) died or developed graft loss over the study period. Strategic allocation of kidneys resulted in HRs for graft loss of 1.74 (95% confidence interval [CI], 1.41-2.14), 1.82 (95% CI, 1.46-2.26), and 1.74 (95% CI 1.38-2.19) for recipients 1, 2 and 3 respectively, whereas by following the KAS, HRs were 1.93 (95%, CI 1.63-2.28), 2.06 (95% CI, 1.74-2.44), and 1.93 (95% CI, 1.58-2.37); corresponding to 3.84, 11.39, and 7.40 months longer predicted patient or graft survival for recipients 1, 2 and 3 with strategic D-R pairing compared with the KAS.

CONCLUSIONS

Allocation of kidneys by strategic D-R pairing may improve graft survival relative to allocation using the KAS.

The differential impact of size mismatch in live versus deceased donor kidney transplant

BACKGROUND

The impact of weight mismatch between donors and recipients (D-R) undergoing living-donor kidney transplant (LDKT) versus weight-matched deceased donor kidney transplant (DDKT) is not established.

AIM

To determine whether absolute weight mismatch between D-R affects graft survival following LDKT and how this relates to graft outcomes with DDKT when D-R are weight matched.

MATERIALS & METHODS

We used multivariable Cox proportional hazards models and the Scientific Registry of Transplant Recipients to determine the association of weight-mismatched D-R (>50 kg, 30-50 kg or 10-30 kg ((D < R); (D > R) and <10 kg (D = R)) with death-censored graft failure in US LDKT recipients from 2006 to 2017. We also explored outcomes relative to weight-matched DDKT and finally, the impact of combined D-R weight-sex mismatch.

RESULTS

In LDKT, the risk of graft loss was highest in the setting of D < R (HR 1.28, 95% CI 1.05-1.56 for >50 kg difference relative to D = R); however, this was still lower risk than weight-matched DDKT. D-R sex and combined weight-sex mismatch were only important for male recipients (HR 1.47, 95% CI 1.27-1.71 for a male recipient >30 kg larger than their female donor, relative to weight-matched male donor-male recipient). This remained superior to weight-sex-matched DDKT however.

CONCLUSION

D-R weight-sex mismatch is important in LDKT; however, graft survival remains superior to proceeding with matched DDKT. Optimizing D-R matching in LDKT could be facilitated through a national kidney-paired donation registry. LDKT weight-sex mismatch should not be deferred in favor of DDKT.

Development and external validation study combining existing models and recent data into an up-to-date prediction model for evaluating kidneys from older deceased donors for transplantation

With a rising demand for kidney transplantation, reliable pre-transplant assessment of organ quality becomes top priority. In clinical practice, physicians are regularly in doubt whether suboptimal kidney offers from older donors should be accepted. Here, we externally validate existing prediction models in a European population of older deceased donors, and subsequently developed and externally validated an adverse outcome prediction tool. Recipients of kidney grafts from deceased donors 50 years of age and older were included from the Netherlands Organ Transplant Registry (NOTR) and United States organ transplant registry from 2006-2018. The predicted adverse outcome was a composite of graft failure, death or chronic kidney disease stage 4 plus within one year after transplantation, modelled using logistic regression. Discrimination and calibration were assessed in internal, temporal and external validation. Seven existing models were validated with the same cohorts. The NOTR development cohort contained 2510 patients and 823 events. The temporal validation within NOTR had 837 patients and the external validation used 31987 patients in the United States organ transplant registry. Discrimination of our full adverse outcome model was moderate in external validation (C-statistic 0.63), though somewhat better than discrimination of the seven existing prediction models (average C-statistic 0.57). The model's calibration was highly accurate. Thus, since existing adverse outcome kidney graft survival models performed poorly in a population of older deceased donors, novel models were developed and externally validated, with maximum achievable performance in a population of older deceased kidney donors. These models could assist transplant clinicians in deciding whether to accept a kidney from an older donor.

Prolonged Cold Ischemia Time Offsets the Benefit of Human Leukocyte Antigen Matching in Deceased Donor Kidney Transplant

BACKGROUND

The consequences of prolonging cold ischemia time (CIT) to facilitate HLA matching in kidney transplantation are not known.

METHODS

Patients with a history of kidney transplant in the United States (2000-2016) with 0 HLA mismatch (MM) were categorized based on CIT (< 10; 10 to < 15; 15 to < 20; 20 to < 25; 25 to < 30; and ≥ 30 hours). Time to graft loss was compared for each CIT category to a reference group of individuals with > 0 HLA MM and short CIT (< 10 hours) using a multivariable Cox proportional hazards model.

RESULTS

The adjusted risk of graft failure was significantly lower for 0 HLA MM with the shortest CIT compared to the reference group (hazard ratio, 0.82; 95% confidence interval, 0.72-0.94), and this survival advantage persisted to a threshold of < 20 hours of CIT. No survival advantage was observed for the 0 HLA MM group once CIT was > 20 hours. This trend persisted after excluding highly sensitized recipients (panel reactive antibody > 98%) where shipping of organs occurs to achieve more equitable access to organs rather than optimize HLA match.

CONCLUSIONS

CIT > 20 hours offsets the benefit of 0 HLA MM in kidney transplantation. This may have implications in organ shipping to facilitate immunologic match.