Naesens, Maarten

Importance Accurate prediction of patient mortality after kidney transplant is an unmet need. Objective To develop and validate an integrative prediction model that predicts short- and long-term patient mortality for kidney recipients. Design, Setting, and Participants This international cohort study included patients who underwent transplants between 2004 and 2023 from 14 academic medical centers from Europe and the US. The derivation cohort consisted of 1566 consecutive adult kidney recipients in a deeply phenotyped cohort prospectively recruited in 1 French center between 2004 and 2014. External validation cohorts consisted of 10 951 kidney recipients from 7 centers in France, 3 centers in Europe, and 3 centers in North America who underwent kidney transplants between 2006 and 2023. Data were analyzed from January 2023 to June 2025. Main Outcome and Measures All-cause mortality was assessed, and 121 candidate prognostic factors, comprising demographics and clinical, biological, imaging, and immunological parameters, were collected. Results Among 12 517 kidney transplant recipients, including 1566 in the derivation cohort (mean [SD] age, 50.05 [14.31] years; 942 male [60.15%]) and 10 951 in validation cohorts (mean [SD] age, 53.32 [13.97] years; 6766 male [61.78%]), 2486 patients (19.9%) died after a median (IQR) follow-up of 5.08 (2.97-7.00) years. Fourteen prognostic factors (including clinical, biological, and imaging risk factors) were independently associated with patient death (eg, patient age: hazard ratio per 1-year increase in age, 1.07 [95% CI, 1.06-1.08]; P < .001) and were combined into a risk prediction model (mBox). The model exhibited accurate calibration and discrimination in the derivation cohort, with C statistics of 0.82 (95% CI, 0.77-0.87) and 0.80 (95% CI, 0.78-0.82) at 1 and 10 years, respectively, after the transplant. Abbreviated models were developed and validated to ensure model generalizability. Performance of abbreviated models was confirmed in external validation cohorts from France (C statistic, 0.76 [95% CI, 0.73-0.78]), Europe (C statistic, 0.74 [95% CI, 0.72-0.76]), the US (C statistic, 0.74 [95% CI, 0.70-0.78]), the Greater Paris University Hospital database (C statistic, 0.79 [95% CI, 0.77-0.81]), and the University of California at San Francisco database (C statistic, 0.70 [95% CI, 0.65-0.74]). The model was also validated in a series of subpopulations (eg, women vs men: C statistic, 0.81 [95% CI, 0.77-0.84] vs 0.79 [95% CI, 0.77-0.82]) and clinical scenarios (eg, before COVID-19 era: C statistic, 0.79 [95% CI, 0.77-0.81]) with good and stable performance. Conclusions and Relevance In this study, an accurate prediction model for mortality among kidney recipients, computable at the time of transplant, was developed and externally validated. Results suggest that this model may help stratify patient risk of death, allowing for improved medical decisions.

ABSTRACTIntroductionThe diagnosis of antibody‐mediated rejection (AMR) requires input from several transplant professionals. Bringing clinical and laboratory experts together may help standardize care. Yet, little is known about current global practices of multidisciplinary meetings for AMR management.MethodsThe Banff Antibody‐Mediated Injury Working Group approached professional societies worldwide to distribute a survey on the availability, content, participants, perceived value, and barriers to the implementation of multidisciplinary meetings.ResultsFour hundred two transplant professionals from six continents caring for kidney (90.55%), liver (21.14%), pancreas (20.65%), heart (15.17%), and lung (14.18%) transplant recipients participated in the survey, and 302 (75.12%) reported attending multidisciplinary meetings. Multidisciplinary meetings were more prevalent in academic centers, in high‐ versus low‐to‐middle‐income regions (81.03% and 65.99%, respectively; p < 0.001), and in mid‐to‐large size transplant programs compared to smaller programs. Perceived value included continued professional development (97.68%) and trainee education (95.70%). AMR was reported to be discussed at these meetings by 217 respondents with case presentations reviewing patient characteristics, histology, and HLA antibody data. A third of the respondents reviewed non‐HLA/pathogenic autoantibodies and/or molecular diagnostics, with the latter being more frequently applied in high‐ versus low‐to‐middle‐income regions (46.71% and 12.31%, respectively; p < 0.001). AMR case presentations allowed diagnosis revision, actionable management plans and were perceived as improving care. The primary barrier to the implementation of multidisciplinary meetings (63.27%) was the unavailability of transplant professionals (e.g., transplant immunologists).ConclusionFacilitating multidisciplinary meetings through the remote participation of pertinent experts and incentivizing participation through remuneration, protected time, or continued medical education may help standardize AMR diagnosis and harmonize its management.

Significance Statement Why are there so few biomarkers accepted by health authorities and implemented in clinical practice, despite the high and growing number of biomaker studies in medical research ? In this meta-epidemiological study, including 804 studies that were critically appraised by expert reviewers, the authors have identified all prognostic kidney transplant biomarkers and showed overall suboptimal study designs, methods, results, interpretation, reproducible research standards, and transparency. The authors also demonstrated for the first time that the limited number of studies challenged the added value of their candidate biomarkers against standard-of-care routine patient monitoring parameters. Most biomarker studies tended to be single-center, retrospective studies with a small number of patients and clinical events. Less than 5% of the studies performed an external validation. The authors also showed the poor transparency reporting and identified a data beautification phenomenon. These findings suggest that there is much wasted research effort in transplant biomarker medical research and highlight the need to produce more rigorous studies so that more biomarkers may be validated and successfully implemented in clinical practice. Background Despite the increasing number of biomarker studies published in the transplant literature over the past 20 years, demonstrations of their clinical benefit and their implementation in routine clinical practice are lacking. We hypothesized that suboptimal design, data, methodology, and reporting might contribute to this phenomenon. Methods We formed a consortium of experts in systematic reviews, nephrologists, methodologists, and epidemiologists. A systematic literature search was performed in PubMed, Embase, Scopus, Web of Science, and Cochrane Library between January 1, 2005, and November 12, 2022 (PROSPERO ID: CRD42020154747). All English language, original studies investigating the association between a biomarker and kidney allograft outcome were included. The final set of publications was assessed by expert reviewers. After data collection, two independent reviewers randomly evaluated the inconsistencies for 30% of the references for each reviewer. If more than 5% of inconsistencies were observed for one given reviewer, a re-evaluation was conducted for all the references of the reviewer. The biomarkers were categorized according to their type and the biological milieu from which they were measured. The study characteristics related to the design, methods, results, and their interpretation were assessed, as well as reproducible research practices and transparency indicators. Results A total of 7372 publications were screened and 804 studies met the inclusion criteria. A total of 1143 biomarkers were assessed among the included studies from blood ( n =821, 71.8%), intragraft ( n =169, 14.8%), or urine ( n =81, 7.1%) compartments. The number of studies significantly increased, with a median, yearly number of 31.5 studies (interquartile range [IQR], 23.8–35.5) between 2005 and 2012 and 57.5 (IQR, 53.3–59.8) between 2013 and 2022 ( P < 0.001). A total of 655 studies (81.5%) were retrospective, while 595 (74.0%) used data from a single center. The median number of patients included was 232 (IQR, 96–629) with a median follow-up post-transplant of 4.8 years (IQR, 3.0–6.2). Only 4.7% of studies were externally validated. A total of 346 studies (43.0%) did not adjust their biomarker for key prognostic factors, while only 3.1% of studies adjusted the biomarker for standard-of-care patient monitoring factors. Data sharing, code sharing, and registration occurred in 8.8%, 1.1%, and 4.6% of studies, respectively. A total of 158 studies (20.0%) emphasized the clinical relevance of the biomarker, despite the reported nonsignificant association of the biomarker with the outcome measure. A total of 288 studies assessed rejection as an outcome. We showed that these rejection studies shared the same characteristics as other studies. Conclusions Biomarker studies in kidney transplantation lack validation, rigorous design and methodology, accurate interpretation, and transparency. Higher standards are needed in biomarker research to prove the clinical utility and support clinical use.

Abstract Background and Aims The iBox is a validated prognostication system predicting long-term kidney allograft failure. Recently, it received regulatory endorsement by EMA, for surrogate endpoint for clinical trials. As the iBox system was primarily built using a deep phenotyped cohort, there is a need for proof of validity in extended clinical scenarios, geographic distinct medico-economic cohorts and transplant allocation systems. Method 10,851 transplant recipients were included from 17 academic medical centers from France, Belgium, Spain, Germany, Finland, United States, Brazil and Argentina. We applied to these cohorts the iBox algorithm that integrates eight independent prognostic factors including the time from transplantation to risk evaluation, functional parameters (eGFR, proteinuria), allograft histological lesions (IFTA, g+ptc, i+t, cg Banff scores), and circulating anti-HLA DSA. We stratified the performances of the iBox according to several real-life scenarios, including: 1) iBox + different eGFR formulas (MDRD186, MDRD175, CKD-Epi); 2) iBox + urinary dipstick; 3) iBox Functional + Structural (absence of DSA measurements); 4) iBox functional + Immunological (absence of histology); 5) iBox in response to treatment in T-cell mediated rejection (TCMR); 6) iBox for in response to treatment antibody mediated rejection (ABMR) clinical trials. The performances of the iBox system were assessed with the discrimination (C-index) and calibration. Results The derivation cohort included 4,000 recipients from France, and the international external validation cohort included 6,851 recipients from Europe (France, Belgium, Spain, Germany, Finland n = 4,643), the United States (n = 1,537) and South America (Brazil, Argentina n = 671). The mean recipient age was 50.26 years (14.05) with a median follow-up after evaluations of 5.41 years [IQR: 3.26 to 7]. 1336 patients (12.31%) lost their graft during the study follow-up. The performances of the iBox were confirmed in the different real-life setting with the following C-Index: 1) iBox + different eGFR formulas (MDRD186, MDRD175, CKD-Epi) 0.81; 2) iBox + urinary dipstick 0.80; 3) iBox Functional + Structural (histology) 0.80 (derivation) and 0.84 (validation); 4) iBox functional + Immunological 0.80 (derivation) and 0.83 (validation); 5) iBox in response to treatment in T-cell mediated rejection 0.81; 6) iBox for in response to treatment antibody mediated rejection trials 0.81. The score showed an accurate calibration in every scenario. Conclusion The iBoxEXTENDED trial confirms in various medico-economic settings the performances transportability and surrogacy of the iBox system, further reinforcing its use as a surrogate end point for clinical trials including TCMR and ABMR.

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.