Loupy, Alexandre

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 Objective To compare the performance of a newly developed race-free kidney recipient specific glomerular filtration rate (GFR) equation with the three current main equations for measuring GFR in kidney transplant recipients. Design Development and validation study Setting 17 cohorts in Europe, the United States, and Australia (14 transplant centres, three clinical trials). Participants 15 489 adults (3622 in development cohort (Necker, Saint Louis, and Toulouse hospitals, France), 11 867 in multiple external validation cohorts) who received kidney transplants between 1 January 2000 and 1 January 2021. Main outcome measure The main outcome measure was GFR, measured according to local practice. Performance of the GFR equations was assessed using P 30 (proportion of estimated GFR (eGFR) within 30% of measured GFR (mGFR)) and correct classification (agreement between eGFR and mGFR according to GFR stages). The race-free equation, based on creatinine level, age, and sex, was developed using additive and multiplicative linear regressions, and its performance was compared with the three current main GFR equations: Modification of Diet in Renal Disease (MDRD) equation, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation, and race-free CKD-EPI 2021 equation. Results The study included 15 489 participants, with 50 464 mGFR and eGFR values. The mean GFR was 53.18 mL/min/1.73m 2 (SD 17.23) in the development cohort and 55.90 mL/min/1.73m 2 (19.69) in the external validation cohorts. Among the current GFR equations, the race-free CKD-EPI 2021 equation showed the lowest performance compared with the MDRD and CKD-EPI 2009 equations. When race was included in the kidney recipient specific GFR equation, performance did not increase. The race-free kidney recipient specific GFR equation showed significantly improved performance compared with the race-free CKD-EPI 2021 equation and performed well in the external validation cohorts (P 30 ranging from 73.0% to 91.3%). The race-free kidney recipient specific GFR equation performed well in several subpopulations of kidney transplant recipients stratified by race (P 30 73.0-91.3%), sex (72.7-91.4%), age (70.3-92.0%), body mass index (64.5-100%), donor type (58.5-92.9%), donor age (68.3-94.3%), treatment (78.5-85.2%), creatinine level (72.8-91.3%), GFR measurement method (73.0-91.3%), and timing of GFR measurement post-transplant (72.9-95.5%). An online application was developed that estimates GFR based on recipient’s creatinine level, age, and sex ( https://transplant-prediction-system.shinyapps.io/eGFR_equation_KTX/ ). Conclusion A new race-free kidney recipient specific GFR equation was developed and validated using multiple, large, international cohorts of kidney transplant recipients. The equation showed high accuracy and outperformed the race-free CKD-EPI 2021 equation that was developed in individuals with native kidneys. Trial registration ClinicalTrials.gov NCT05229939 .

Abstract The authors have requested that this preprint be removed from Research Square.