Paul Keown’s research while affiliated with University of British Columbia and other places

The optimal immunosuppression management in patients with a failed kidney transplant remains uncertain. This study analyzed the association of class II HLA eplet mismatches and maintenance immunosuppression with allosensitization after graft failure in a well characterized cohort of 21 patients who failed a first kidney transplant. A clinically meaningful increase in cPRA in this study was defined as the cPRA that resulted in 50% reduction in the compatible donor pool measured from the time of transplant failure until the time of repeat transplantation, death, or end of study. The median cPRA at the time of failure was 12.13% (interquartile ranges = 0.00%, 83.72%) which increased to 62.76% (IQR = 4.34%, 99.18%) during the median follow-up of 27 (IQR = 18, 39) months. High HLA-DQ eplet mismatches were significantly associated with an increased risk of developing a clinically meaningful increase in cPRA (p = 0.02) and de novo DQ donor-specific antibody against the failed allograft (p = 0.02). We did not observe these associations in patients with high HLA-DR eplet mismatches. Most of the patients (88%) with a clinically meaningful increase in cPRA had both a high DQ eplet mismatch and a reduction in their immunosuppression, suggesting the association is modified by immunosuppression. The findings suggest HLA-DQ eplet mismatch analysis may serve as a useful tool to guide future clinical studies and trials which assess the management of immunosuppression in transplant failure patients who are repeat transplant candidates.

The optimal immunosuppression management in patients with a failed kidney transplant remains uncertain. This study analyzed the association of class II HLA eplet mismatches and maintenance immunosuppression with allosensitization after graft failure in a well characterized cohort of 21 patients who failed a first kidney transplant. A clinically meaningful increase in cPRA in this study was defined as the cPRA that resulted in 50% reduction in the compatible donor pool measured from the time of transplant failure until the time of repeat transplantation, death, or end of study. The median cPRA at the time of failure was 12.13% (interquartile ranges = 0.00%, 83.72%) which increased to 62.76% (IQR = 4.34%, 99.18%) during the median follow-up of 27 (IQR = 18, 39) months. High HLA-DQ eplet mismatches were significantly associated with an increased risk of developing a clinically meaningful increase in cPRA (p = 0.02) and de novo DQ donor-specific antibody against the failed allograft (p = 0.02). We did not observe these associations in patients with high HLA-DR eplet mismatches. Most of the patients (88%) with a clinically meaningful increase in cPRA had both a high DQ eplet mismatch and a reduction in their immunosuppression, suggesting the association is modified by immunosuppression. The findings suggest HLA-DQ eplet mismatch analysis may serve as a useful tool to guide future clinical studies and trials which assess the management of immunosuppression in transplant failure patients who are repeat transplant candidates.

Background Despite advances in clinical management, cytomegalovirus (CMV) infection remains a serious complication and an important cause of morbidity and mortality following kidney transplantation. Here, we explore the importance of viral load kinetics as predictors of risk and potential guides to therapy to reduce transplant failure in a large longitudinal Genome Canada Transplant Consortium (GCTC) kidney transplant cohort. Methods We examined the relationship between CMV infection rates and clinical characteristics, CMV viral load kinetics, and graft and patient outcomes in 2510 sequential kidney transplant recipients in the British Columbia Transplant Program. Transplants were performed between January 1, 2008, and December 31, 2018, were managed according to a standard protocol, and were followed until December 31, 2019, representing over 3.4 million days of care. Results Longitudinal CMV testing was performed in 2464 patients, of whom 434 (17.6%) developed a first episode of CMV viremia at a median of 120 (range: 9–3906) days post-transplant. Of these patients, 93 (21.4%) had CMV viremia only and 341 (78.6%) had CMV viremia with clinical complications, of whom 21 (4.8%) had resulting hospitalization. A total of 279 (11.3%) patients died and 177 (7.2%) patients lost their graft during the 12 years of follow-up. Patients with CMV infection were at significantly greater risk of graft loss (p=0.0041) and death (p=0.0056) than those without. Peak viral load ranged from 2.9 to 7.0 (median: 3.5) log10 IU/mL, the duration of viremia from 2 to 100 (15) days, and the viral load area under the curve from 9.4 to 579.8 (59.7) log10 IU/mL × days. All three parameters were closely inter-related and were significantly increased in patients with more severe clinical disease or with graft loss (p=0.001). Duration of the first CMV viremic episode greater than 15 days or a peak viral load ≥4.0 log10 IU/mL offered simple predictors of clinical risk with a 3-fold risk of transplant failure. Conclusion Viral load kinetics are closely related to CMV severity and to graft loss following kidney transplantation and provide a simple index of risk which may be valuable in guiding trials and treatment to prevent transplant failure.

Background Recent advances in hardware and software enabled the use of artificial intelligence (AI) algorithms for analysis of complex data in a wide range of daily-life use cases. We aim to explore the benefits of applying AI to a specific use case in transplant nephrology: risk prediction for severe posttransplant events. For the first time, we combine multinational real-world transplant data, which require specific legal and technical protection measures. Objective The German-Canadian NephroCAGE consortium aims to develop and evaluate specific processes, software tools, and methods to (1) combine transplant data of more than 8000 cases over the past decades from leading transplant centers in Germany and Canada, (2) implement specific measures to protect sensitive transplant data, and (3) use multinational data as a foundation for developing high-quality prognostic AI models. Methods To protect sensitive transplant data addressing the first and second objectives, we aim to implement a decentralized NephroCAGE federated learning infrastructure upon a private blockchain. Our NephroCAGE federated learning infrastructure enables a switch of paradigms: instead of pooling sensitive data into a central database for analysis, it enables the transfer of clinical prediction models (CPMs) to clinical sites for local data analyses. Thus, sensitive transplant data reside protected in their original sites while the comparable small algorithms are exchanged instead. For our third objective, we will compare the performance of selected AI algorithms, for example, random forest and extreme gradient boosting, as foundation for CPMs to predict severe short- and long-term posttransplant risks, for example, graft failure or mortality. The CPMs will be trained on donor and recipient data from retrospective cohorts of kidney transplant patients. Results We have received initial funding for NephroCAGE in February 2021. All clinical partners have applied for and received ethics approval as of 2022. The process of exploration of clinical transplant database for variable extraction has started at all the centers in 2022. In total, 8120 patient records have been retrieved as of August 2023. The development and validation of CPMs is ongoing as of 2023. Conclusions For the first time, we will (1) combine kidney transplant data from nephrology centers in Germany and Canada, (2) implement federated learning as a foundation to use such real-world transplant data as a basis for the training of CPMs in a privacy-preserving way, and (3) develop a learning software system to investigate population specifics, for example, to understand population heterogeneity, treatment specificities, and individual impact on selected posttransplant outcomes. International Registered Report Identifier (IRRID) DERR1-10.2196/48892

Background Antibody-mediated rejection is an important cause of kidney transplant loss. A new strategy requiring application of precision medicine tools in transplantation considers molecular compatibility between donors and recipients and holds the promise of improved immunologic risk, preventing rejection and premature graft loss. The objective of this study was to gather Canadian transplant professionals’ perspectives on molecular compatibility in kidney transplantation. Methods Seventeen Canadian transplant professionals (14 nephrologists, 2 nurses, and 1 surgeon) participated in semistructured interviews in 2021. The interviews were digitally recorded, transcribed, and analyzed using the qualitative description approach. Results Participants identified fair access to transplantation as the most important principle in kidney allocation. Molecular compatibility was viewed as a promising innovation. However, participants were concerned about increased waiting times, negative impact on some patients, and potential problems related to the adequacy of information explaining this new technology. To mitigate the challenges associated with molecular matching, participants suggested integrating a maximum waiting time for molecular-matched kidneys and expanding the program nationally/internationally. Conclusions Molecular matching in kidney transplantation is viewed as a promising technology for decreasing the incidence of antibody-mediated rejection and improving graft survival. Further studies are needed to determine how to ethically integrate this technology into the kidney allocation algorithm.

Over the past decade, several observational studies and case series have provided evidence suggesting a connection between glomerular diseases (GN) and the development of malignancies, with an estimated risk ranging from 5%-11%. These malignancies include solid organ tumors as well as hematologic malignancies such as lymphoma and leukemia. However, these risk estimates are subject to several sources of bias, including unmeasured confounding from inadequate exploration of risk factors, inclusion of GN cases that were potentially secondary to an underlying malignancy, misclassification of GN type, and ascertainment bias arising from an increased likelihood of physician encounters compared to the general population. Consequently, population-based studies that accurately evaluate the cancer risk in GN populations are lacking. While it is speculated that long-term use of immunosuppressive medications and GN disease activity measured by proteinuria and estimated glomerular filtration rate may be associated with cancer risk in patients with GN, the independent role of these risk factors remains largely unknown. The presence of these knowledge gaps could lead to (i) lack of awareness of cancer as a potential chronic complication of GN, (ii) under-utilization of routine screening practices in clinical care that allow early diagnosis and treatment of malignancies, and (iii) under-recognition of modifiable risk factors to decrease the risk of de novo malignancies over time. This review summarizes the current evidence on the risk of cancer in patients with GN, explores the limitations of prior studies, and discusses methodological challenges and potential solutions for obtaining accurate estimates of cancer risk and identifying modifiable risk factors unique to GN populations.