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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.

ABSTRACT Background Creatinine-based equations are the most used to estimate glomerular filtration rate (eGFR). The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), the re-expressed Lund-Malmö Revised (r-LMR) and the European Kidney Function Consortium (EKFC) equations are the most validated. The EKFC and r-LMR equations have been suggested to have better performances in young adults, but this is debated. Methods We collected data (GFR) measured by clearance of an exogenous marker (reference method), serum creatinine, age and sex from 2366 young adults (aged between 18 and 25 years) both from Europe and the USA. Results In the European cohorts (n = 1892), the bias (in mL/min/1.73 m²) was systematically better for the EKFC and r-LMR equations compared with the CKD-EPI equation [2.28, 95% confidence interval (1.59; 2.91), –2.50 (–3.85; –1.76), 17.41 (16.49; 18.47), respectively]. The percentage of estimated GFR within 30% of measured GFR (P30) was also better for EKFC and r-LMR equations compared with the CKD-EPI equation [84.4% (82.8; 86.0), 87.2% (85.7; 88.7) and 65.4% (63.3; 67.6), respectively]. In the US cohorts (n = 474), the bias for the EKFC and r-LMR equations was better than for the CKD-EPI equation in the non-Black population [0.97 (–1.69; 3.06), –2.62 (–5.14; –1.43) and 7.74 (5.97; 9.63), respectively], whereas the bias was similar in Black US individuals. P30 results were not different between the three equations in US cohorts. Analyses in sub-populations confirmed these results, except in individuals with high GFR levels (GFR ≥120 mL/min/1.73 m²) for whom the CKD-EPI equation might have a lower bias. Conclusions We demonstrated that both the EKFC and r-LMR creatinine-based equations have a better performance than the CKD-EPI equation in a young population. The only exception might be in patients with hyperfiltration.

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 .

AimThe Cockcroft‐Gault (CG) creatinine‐based equation is still used to estimate glomerular filtration rate (eGFR) for drug dosage adjustment. Incorrect eGFR may lead to hazardous over‐ or underdosing.MethodsIn a cross‐sectional analysis, CG was validated against measured GFR (mGFR) in 14 804 participants and compared with the Modification‐of‐Diet‐in‐Renal‐Diseases (MDRD), Chronic‐Kidney‐Disease‐Epidemiology (CKD‐EPI), Lund‐Malmö‐Revised (LMR) and European‐Kidney‐Function‐Consortium (EKFC) equations. Validation focused on bias, imprecision and accuracy (percentage of estimates within ±30% of mGFR, P30), overall and stratified for mGFR, age and body mass index at mGFR <60 mL/min, as well as classification in mGFR stages.ResultsThe CG equation performed worse than the other equations, overall and in mGFR, age and BMI subgroups in terms of bias (systematic overestimation), imprecision and accuracy except for patients ≥65 years where bias and P30 were similar to MDRD and CKD‐EPI, but worse than LMR and EKFC. In subjects with mGFR <60 mL/min and at BMI 18.5‐25 kg/m2, all equations performed similarly, and for BMI < 18.5 kg/m2 CG and LMR had the best results though all equations had poor P30‐accuracy. At BMI ≥ 25 kg/m2 the bias of the CG increased with increasing BMI (+17.2 mL/min at BMI ≥ 40 kg/m2). The four more recent equations also classified mGFR stages better than CG.ConclusionsThe CG equation showed poor ability to estimate GFR overall and in analyses stratified for mGFR, age and BMI. CG was inferior to correctly classify the patients in the mGFR staging compared to more recent creatinine‐based equations.

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

Abstract Background The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation is routinely used to assess renal function but exhibits varying accuracy depending on patient characteristics and clinical presentation. The overall aim of the present study was to assess if and to what extent glomerular filtration rate (GFR) estimation based on creatinine can be improved. Methods In a cross-sectional analysis covering the years 2003–17, CKD-EPI was validated against measured GFR (mGFR; using various tracer methods) in patients with high likelihood of chronic kidney disease (CKD; five CKD cohorts, n = 8365) and in patients with low likelihood of CKD (six community cohorts, n = 6759). Comparisons were made with the Lund–Malmö revised equation (LMR) and the Full Age Spectrum equation. Results 7In patients aged 18–39 years old, CKD-EPI overestimated GFR with 5.0–16 mL/min/1.73 m2 in median in both cohort types at mGFR levels &lt;120 mL/min/1.73 m2. LMR had greater accuracy than CKD-EPI in the CKD cohorts (P30, the percentage of estimated GFR within 30% of mGFR, 83.5% versus 76.6%). CKD-EPI was generally the most accurate equation in the community cohorts, but all three equations reached P30 above the Kidney Disease Outcomes Quality Initiative benchmark of 90%. Conclusions None of the evaluated equations made optimal use of available data. Prospects for improved GFR estimation procedures based on creatinine exist, particularly in young adults and in settings where patients with suspected or manifest CKD are investigated.

Abstract Background The dearth of relevant tumor models reflecting the heterogeneity of human central nervous system metastasis (CM) has hindered development of novel therapies. Methods We established 39 CM patient-derived xenograft (PDX) models representing the histological spectrum, and performed phenotypic and multi-omic characterization of PDXs and their original patient tumors. PDX clonal evolution was also reconstructed using allele-specific copy number and somatic variants. Results PDXs retained their metastatic potential, with flank-implanted PDXs forming spontaneous metastases in multiple organs, including brain, and CM subsequent to intracardiac injection. PDXs also retained the histological and molecular profiles of the original patient tumors, including retention of genomic aberrations and signaling pathways. Novel modes of clonal evolution involving rapid expansion by a minor clone were identified in 2 PDXs, including CM13, which was highly aggressive in vivo forming multiple spontaneous metastases, including to brain. These PDXs had little molecular resemblance to the patient donor tumor, including reversion to a copy number neutral genome, no shared nonsynonymous mutations, and no correlation by gene expression. Conclusions We generated a diverse and novel repertoire of PDXs that provides a new set of tools to enhance our knowledge of CM biology and improve preclinical testing. Furthermore, our study suggests that minor clone succession may confer tumor aggressiveness and potentiate brain metastasis.

Abstract Despite recent advances in cancer therapy, options for central nervous system metastasis (CM) remain limited and patient outcomes are dismal. The lack of tumor models that reflect the heterogeneity and complexity of human CM tumors is a barrier to understanding the underlying biology and to developing novel therapies. Here, we report the development and characterization of 39 patient derived xenograft (PDX) models of CM tumors with histological subtypes representing the disease spectrum. The PDX models successfully grew both in the flank and brains of mice, and retained their histology regardless of the site of implantation. Brain metastasis also formed in 5/12 models after intra-cardiac injection. Multi-omic analysis of the PDX tumor and the patient-matched CM tumor showed that PDXs largely retained the molecular profiles of the tumor from which they were derived, including the retention of aberrations in key driver genes and signaling pathways. PDXs differed primarily from the ungrafted patient tumors by a downregulation in immunity-related pathways, which was expected due to the use of an immuno-compromised host, arguing for the validity of using the flank as a site of implantation. Integrated analysis of mutations and gene expression changes in CM revealed an upregulation of neuronal signaling and DNA damage response, and downregulation of calcium signaling and inflammation. We also assessed the clonal evolution of the PDX from the original patient CM by tracing variant allele frequencies in copy number neutral regions. We found that the PDX tumors were heterogeneous and comprised of multiple tumor clones that were either unique or in common with the original tumor, and displayed evidence of clonal expansion. Two PDXs that underwent phylogeny assessment showed evidence of minor clone expansion. One such PDX was a tumor from a Her2+ breast cancer (CM13), which largely did not molecularly resemble its matched patient tumor but was confirmed to have some shared expressed variants. The PDX was nearly copy number neutral, which included loss of the Her2 amplicon, and had few mutations compared with its parent tumor. Most noteworthy, is that CM13 displayed unique molecular patterns, aggressive growth and was highly metastatic in vivo. From the flank, it led to multiple metastases, including micrometastasis in the brain. This suggests that minor clone takeover may confer tumor aggressiveness and potentiate brain metastasis. The large and diverse repertoire of PDXs developed and characterized in this study provides a new set of tools that will help deepen our understanding of CM and improve preclinical testing for CM therapies. Our data also show that expansion of minor clones could confer aggressive tumor behavior and may be important in tumor evolution in PDX models and human cancers. Citation Format: Ben Yi Tew, Christophe Legendre, Tim Triche, Gerald C. Gooden, Kyle N. Johnson, Rae Anne Martinez, Emanuel F. Petricoin, Mariaelena Pierobon, Joyce O'Shaughnessy, Cindy Osborne, Mark A. Schroeder, Daniel J. Ma, Mark Bernstein, Jann N. Sarkaria, Steven A. Toms, Bodour Salhia. Development and characterization of patient derived xenografts from central nervous system metastasis reveal minor clone expansion linked with aggressive tumor behavior [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 991.

Abstract While genomic profiling and therapeutic selection support individualized GBM treatment, such therapeutic decision-making is usually made with reference to tumor obtained from the enhancing core region. GBM is known to be heterogeneous and exhibits a high resistance to standard therapies. To address whether non-enhancing tumor (representing the majority of tumor left behind after surgery) shows distinct genomic characteristics and therapeutic targets compared to the enhancing tumor core, we performed genome-wide exome-sequencing and RNA-sequencing for 12 patients with matched enhancing region and at least one non-enhancing region. Non-enhancing biopsies show a surprisingly high level of tumor content, with a median of 28% tumor cells and 6 of the 22 samples having greater than 50% tumor cells. Cognate non-enhancing and enhancing specimens demonstrated overall concordance in therapeutically actionable alterations (single nucleotide variants) and copy number alterations. However, non-enhancing regions were not genetically identical and did reveal additional and distinct variants compared to enhancing cores. For example, the non-enhancing region of patient 1 showed two nonsense NF1 mutations (R1534X; R2517X) while the enhancing region showed an NF1 frameshift mutation (F1247fs). Clonality analysis by LumosVar also indicated that 7 out of 12 patients harbored dissimilar cellular prevalence patterns between enhancing and non-enhancing regions. In addition, comparison of alternative polyadenylation between enhancing and non-enhancing regions uncovered distinct 3' UTR usage: e.g. SGMS2 and TOB1 tended to have longer 3' UTR in enhancing regions whereas longer 3' UTR of SYNPO and NOS1AP were prevalent in non-enhancing regions. We posit that the enhancing component of glioblastoma probably underrepresents the genomic alterations in patients' tumors. Given non-enhancing tumor is left behind after surgical debulking, genomic profiling of this region would potentially reveal more accurate tumor vulnerabilities and lead to more effective therapy. Supported by a grant from the Ben & Catherine Ivy Foundation. Citation Format: Sen Peng, Rebecca Halperin, Harshil Dhruv, Sara Byron, Christophe Legendre, Joanna Phillips, Michael Prados, Michael Berens, Nhan Tran. Probing the non-enhancing component of glioblastoma: Targeting what is left behind [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 289.