Assessment of Spanish Panel Reactive Antibody Calculator and Potential Usefulness

Anti-Human Leukocyte Antigen Antibody Detection from Terasaki's Humoral Theory to Delisting Strategies in 2024

The human leukocyte antigen (HLA) system plays a critical role in transplant immunology, influencing outcomes through various immune-mediated rejection mechanisms. Hyperacute rejection is driven by preformed donor-specific antibodies (DSAs) targeting HLAs, leading to complement activation and graft loss within hours to days. Acute rejection typically occurs within six months post-transplantation, involving cellular and humoral responses, including the formation of de novo DSAs. Chronic rejection, a key factor in long-term graft failure, often involves class II DSAs and complex interactions between the innate and adaptive immune systems. Advancements in HLA antibody detection, particularly single antigen bead (SAB) assays, have improved the sensitivity and characterization of DSAs. However, these assays face challenges like false positives from denatured antigens and false negatives due to low antibody titers or complement competition. Furthermore, molecular mismatch (MM) analysis has emerged as a potential tool for refining donor-recipient compatibility but faces some issues such as a lack of standardization. Highly sensitized patients with calculated panel-reactive antibodies (cPRA) of 100% face barriers to transplantation. Strategies like serum dilution, novel therapies (e.g., Imlifidase), and delisting approaches could refine immunological risk assessment and delisting strategies are essential to expand transplant opportunities for these patients.

Improving the Access of Highly Sensitized Patients to Kidney Transplantation From Deceased Donors: The Spanish PATHI Program With Allocation Based on the Virtual Crossmatch

BACKGROUND

In 2015, the Spanish National Transplant Organization developed a prioritization system (Program for Access to Transplantation for Highly Sensitized Patients [PATHI]) to increase transplant options for patients with calculated panel-reactive antibodies (cPRAs) ≥98%, based on virtual crossmatch. We describe the experience with the implementation of PATHI and assess its efficacy.

METHODS

PATHI registry was used to collect characteristics of donors and patients between June 15, 2015, and March 1, 2018. One-year graft and patient survival and acute rejection were also measured. A Cox model was used to identify factors related to patient death and graft loss and logistical regression for those associated with rejection.

RESULTS

One thousand eighty-nine patients were included, and 272 (25%) were transplanted. Transplant rate by cPRA was 54.9%, 40.5%, and 12.8% in patients with cPRA98%, cPRA99%, and cPRA100%, respectively. One-year patient survival was 92.5%. Recipient age ≥60, time under dialysis >7 y, and delayed graft function were mortality risk factors. One-year graft survival was 88.7%. The factor related to graft loss was delayed graft function. The rejection rate was 22%. Factors related to rejection were sex, older recipients, and posttransplant donor-specific antibodies.

CONCLUSIONS

A prioritization approach increases transplant options for highly sensitized patients with appropriate short-term postransplant outcomes. Along with other programs, PATHI may inspire other countries to adopt strategies to meet transplant needs of these patients.

Development of a calculated panel reactive antibody calculator for the United Arab Emirates: a proof of concept study

Calculated panel reactive antibody (CPRA) is used to help increase sensitized patient's access to transplantation. United Arab Emirates (UAE) has a diverse resident population hence we developed a UAE-CPRA calculator based on HLA antigen frequencies of the different ethnic groups that represent the UAE population. HLA antigen frequencies at serological split antigen level for HLA-A, -B, -C, -DRB1 and -DQB1 of 1002 healthy unrelated donors were performed. We subsequently compared the performance of the UAE CPRA calculator with the Organ Procurement and Transplantation Network (OPTN) and the Canadian CPRA calculators in 110 Kidney Transplant waitlist patients from January 2016 to December 2018. Lin's concordance correlation coefficient showed a moderate agreement between the UAE and OPTN calculator (Rc = 0.949, 95% CI 0.929-0.963) and the UAE and Canadian calculators (Rc = 0.952, 95% CI 0.932-0.965). While there continued to be a moderate agreement (Rc = 0.937, UAE versus OPTN calculator) in the lower sensitized group, a poor agreement (Rc = 0.555, UAE versus OPTN calculator) was observed in the higher sensitized group. In this study, we provide a template for countries to develop their own population-specific CPRA calculator. Implementation of the CPRA algorithm based on HLA frequencies of the multi-ethnic UAE population will be more fitting to increase access to transplantation and improve transplant outcomes. Our study demonstrates that the CPRA calculators developed using the data from the western population had poor correlation in our higher sensitized patients disadvantaging them in potential organ allocations systems. We plan to further refine this calculator by using high resolution HLA typing to address the problem of a genetically diverse population.

Evaluation of the Iranian panel reactive antibody calculator and potential usefulness: A retrospective study

BACKGROUND AND OBJECTIVES

There are several cPRA websites based on large enough samples in Eurotransplant, the United Network for Organ Sharing (UNOS), and the Canadian Transplant Registry (CTR). On the other hand, those calculators can differ based on the ethnicity to which they are applied. We developed the Iranian PRA calculator and compared it with UNOS and CTR calculators.

METHODS

The allele and haplotype frequencies of the Iranian donor pool were estimated using the HLA typing of 523 deceased Iranian kidney donors. The Organ Procurement and Transplantation Network formula was used to generate cPRA (cPRA frequency). We also used a computer script to compare the undesirable antigens of patients with the human leukocyte antigen (HLA) phenotype of donors (cPRA filtering). A total of 100 anti-HLA antibody profiles were determined in 100 sensitized individuals on the waiting list, and cPRA was estimated using various PRA calculators.

RESULTS

Variable allelic frequencies were obtained from population heterogeneity in each calculator's donor panel. However, no significant changes in cPRA were identified between the Iranian calculator, UNOS, and the Canadian online calculators. Lin's concordance correlation coefficient of .98 showed that cPRA (freq) and cPRA (filter) values had almost perfect agreement.

INTERPRETATION AND CONCLUSION

The cPRA values from the Iranian calculator are comparable to those from UNOS and CTR calculators. The donor filtering method was more useful because of factors like cost and flexibility. It also makes it easier to update cPRA on a regular basis.

Development of a Calculated Panel Reactive Antibody Web Service with Local Frequencies for Platelet Transfusion Refractoriness Risk Stratification

BACKGROUND

Calculated panel reactive antibody (cPRA) scoring is used to assess whether platelet refractoriness is mediated by human leukocyte antigen (HLA) antibodies in the recipient. cPRA testing uses a national sample of US kidney donors to estimate the population frequency of HLA antigens, which may be different than HLA frequencies within local platelet inventories. We aimed to determine the impact on patient cPRA scores of using HLA frequencies derived from typing local platelet donations rather than national HLA frequencies.

METHODS

We built an open-source web service to calculate cPRA scores based on national frequencies or custom-derived frequencies. We calculated cPRA scores for every hematopoietic stem cell transplantation (HSCT) patient at our institution based on the United Network for Organ Sharing (UNOS) frequencies and local frequencies. We compared frequencies and correlations between the calculators, segmented by gender. Finally, we put all scores into three buckets (mild, moderate, and high sensitizations) and looked at intergroup movement.

RESULTS

2531 patients that underwent HSCT at our institution had at least 1 antibody and were included in the analysis. Overall, the difference in medians between each group's UNOS cPRA and local cPRA was statistically significant, but highly correlated (UNOS vs. local total: 0.249 and 0.243, ρ = 0.994; UNOS vs. local female: 0.474 and 0.463, ρ = 0.987, UNOS vs. local male: 0.165 and 0.141, ρ = 0.996; P < 0.001 for all comparisons). The median difference between UNOS and cPRA scores for all patients was low (male: 0.014, interquartile range [IQR]: 0.004-0.029; female: 0.0013, IQR: 0.003-0.028). Placement of patients into three groups revealed little intergroup movement, with 2.96% (75/2531) of patients differentially classified.

CONCLUSIONS

cPRA scores using local frequencies were modestly but significantly different than those obtained using national HLA frequencies. We released our software as open source, so other groups can calculate cPRA scores from national or custom-derived frequencies. Further investigation is needed to determine whether a local-HLA frequency approach can improve outcomes in patients who are immune-refractory to platelets.

Portuguese calculated panel reactive antibodies online estimator

Calculated panel reactive antibodies (CPRA) is a sensitization measure used to classify and prioritize transplant candidates in different kidney transplant allocation systems. CPRA is based on identification of HLA unacceptable on potential organ donors making a transplant candidate ineligible for transplantation. Here, we present a CPRA online estimator based on HLA allelic and haplotypic frequencies from Portuguese donors. We also compare the values we obtained from our CPRA estimator (Portuguese [PT]-CPRA) against CPRA values obtained from: Eurotransplant virtual PRA calculator (ET-CPRA); Canadian CPRA calculator (Canadian [CN]-CPRA) and Organ Procurement and Transplantation Network CPRA calculator (United States [US]-CPRA). When we analyzed correlations between CPRA values obtained from pairs of calculators, we observed that they are significantly and highly correlated. Bland-Altman plots for the comparison between PT-CPRA calculator against the other calculators, show higher differences between PT and CN than between PT and ET and PT and US. Also, the lowest value for Lin's concordance coefficient was obtained for the comparison between PT and CN calculators. CPRA values reliability depend on donors' pool from which it is calculated and it is crucial for classify correctly highly sensitized patients. A CPRA calculator must use donors' HLA frequencies similar from those who would be actual organ donors.