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Most previous studies of living kidney donors have been retrospective and have lacked suitable healthy controls. Needed are prospective controlled studies to better understand the effects of a mild reduction in kidney function from kidney donation in otherwise healthy individuals.

A prospective controlled study of kidney donors: baseline and 6-month follow-up.

There have been few prospective controlled studies of kidney donors. Understanding the pathophysiologic effects of kidney donation is important for judging donor safety and improving our understanding of the consequences of reduced kidney function in chronic kidney disease.

A prospective controlled study of living kidney donors: three-year follow-up.

Previous studies have suggested that kidney donors may have abnormalities of mineral and bone metabolism typically seen in chronic kidney disease. This may have important implications for the skeletal health of living kidney donors and for our understanding of the pathogenesis of long-term mineral and bone disorders in chronic kidney disease. In this prospective study, 182 of 203 kidney donors and 173 of 201 paired normal controls had markers of mineral and bone metabolism measured before and at 6 and 36 months after donation (ALTOLD Study). Donors had significantly higher serum concentrations of intact parathyroid hormone (24.6% and 19.5%) and fibroblast growth factor-23 (9.5% and 8.4%) at 6 and 36 months, respectively, as compared to healthy controls, and significantly reduced tubular phosphate reabsorption (-7.0% and -5.0%) and serum phosphate concentrations (-6.4% and -2.3%). Serum 1,25-dihydroxyvitamin D3 concentrations were significantly lower (-17.1% and -12.6%), while 25-hydroxyvitamin D (21.4% and 19.4%) concentrations were significantly higher in donors compared to controls. Moreover, significantly higher concentrations of the bone resorption markers, carboxyterminal cross-linking telopeptide of bone collagen (30.1% and 13.8%) and aminoterminal cross-linking telopeptide of bone collagen (14.2% and 13.0%), and the bone formation markers, osteocalcin (26.3% and 2.7%) and procollagen type I N-terminal propeptide (24.3% and 8.9%), were observed in donors. Thus, kidney donation alters serum markers of bone metabolism that could reflect impaired bone health. Additional long-term studies that include assessment of skeletal architecture and integrity are warranted in kidney donors.

Abnormalities in biomarkers of mineral and bone metabolism in kidney donors.

Rationale & Objective: Creatinine-based estimated glomerular filtration rate (eGFR) equations are widely used in clinical practice but exhibit inherent limitations. We developed and validated machine learning models to assess the trustworthiness (i.e. the ability of equations to estimate measured GFR (mGFR) within 10, 20% or 30%) of the European Kidney Function Consortium (EKFC) equation.
Study design: Observational study
Setting & Participants: Data from European and US cohorts, comprising 22,343 participants of all ages with available mGFR results were utilized.
Predictors: Creatinine, age, sex, height, weight, body mass index, EKFC.
Outcome: Probability that EKFC falls within 30% of mGFR.
Analytical Approach: Four machine learning and two traditional logistic regression models were trained on a cohort of 8,455 participants to predict whether the EKFC creatinine-derived eGFR fell within 30% (P30), 20% (P20) or 10% (P10) of the mGFR value. The algorithms were internally and then externally validated on cohorts of respectively 3,781 and 10,107 participants. 
Results: The random forest model proved to be the most robust model. In the external validation cohort, the model achieved an area under the curve (AUC) of 0.652 (95%CI 0.637;0.667) and an accuracy of 0.851 (95%CI 0.844;0.858) for the P30 criterion. Sensitivity was 0.989 (95%CI 0.987;0.991) and specificity was 0.06 (95%CI 0.049; 0.07) at the 50% probability level that EKFC is within 30% of mGFR. A strategy of using the EKFC equation or mGFR according to the trustworthiness assessed by the random forest model yielded a global P30 of 86.1%, not significantly better than the EKFC P30 of 85.2%.
Limitations: Observational study, creatinine as the only biomarker. No inclusion of Black participants.
Conclusion: A strategy using machine learning model did not significantly improve GFR assessment compared to using the EKFC equation alone.

Enhancing individual glomerular filtration rate assessment: can we trust the equation?

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-MalmöRevised( 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.

Estimating glomerular filtration in young people

The new creatinine-based European Kidney Function Consortium (EKFC) is used to estimate glomerular filtration rate (GFR). This equation has been developed and validated mainly in European subjects. This equation is based on rescaled creatinine, with the rescaling factor (Q-value) defined as the median normal value of serum creatinine in a given population. The validation was limited in Black and non-Black Americans. In this cross-sectional analysis, we included 12,854 participants from 9 studies with measured GFR by clearance of an exogenous marker (reference method), serum creatinine, age, sex, and self-reported race available. Two strategies were considered with population specific Q-values in Black and non-Black men and women (EKFCPS) or a race-free Q value (EKFCRF). In the whole population, only the EKFCPS equation showed no statistical bias (0.14 95%CI[-0.07;0.35] mL/min/1.73m²), and the statistical bias of the EKFCRF (0.74 95%CI[0.51;0.94] mL/min/1.73m²) was closer to zero than that of the CKD-EPI2021 equation (1.22 95%CI[0.99;1.47]) mL/min/1.73m²]. The percentage of estimated GFR within 30% of measured GFR was similar for CKD-EPI2021 (79.2% [78.5%-79.9%]) and EKFCRF (80.1% [79.4%-80.7%]), but improved with the EKFCPS equation (81.1% [80.5%-81.8%]). The EKFC-equation can be used to estimate GFR in the USA incorporating either self-reported race or unknown race at the patient’s discretion per hospital registration records.

Performance of the European Kidney Function Consortium (EKFC) creatinine-based equation in American cohorts

Background
Although the population-level differences between estimated and measured glomerular filtration 
rate (eGFR and mGFR) are well-recognized, the magnitude and potential clinical implications of 
individual-level differences are unknown. 
Methods
Using data from four community-based cohorts with mGFR (N=3,223), we calculated eGFR 
from serum creatinine alone (eGFRCR) and with cystatin C (eGFRCR-CYS). Using quantile 
regression, we assessed eGFR's individual-level inaccuracy by calculating a 95% prediction 
interval (PI), defined as the distribution of 95% of the mGFRs at a given eGFR. We also 
assessed eGFR's reliability using standard metrics, including bias (median mGFR–eGFR). All 
GFR results are presented as ml/min/1?73m2
.
Findings
The participants' mean age was 59 years, 32% were Black individuals, 55% were women, and 
the mean mGFR was 68. The bias for eGFRCR was small (–0.6); however, the individual-level 
inaccuracy was large. The 95% PI for eGFRCR 90 was 56 to 120; for eGFRCR, 60 was 36 to 87; 
for eGFRCR, 45 was 27 to 70, and; for eGFRCR 30, it was 17 to 54. eGFRCR bias among Black 
(3.7) and White (–2.9) individuals was substantially smaller than the width of the PI (97?5th–
2?5th percentiles) in Black (50) and White (57) individuals. Substantial misclassification was 
noted; 37% of individuals with eGFRCR 45 to 59 and 29% with eGFRCR <30 had mGFR above 
those thresholds. eGFRCR-CYS had similar individual-level inaccuracy; PIs were wide, and among 
those with eGFRCR-CYS 45 to 59, the agreement with mGFR was only 49%.

Title	PMID	PMCID	Public Release Type	Publication Year	DOI	Study Acronym	Request ID(s)	Public Release Origin
A prospective controlled study of kidney donors: baseline and 6-month follow-up.	23523239	PMC3724758	Journal	2013	10.1053/j.ajkd.2013.01.027	ALTOLD		Contributing Study
A prospective controlled study of living kidney donors: three-year follow-up.	25795073	PMC4485526	Journal	2015	10.1053/j.ajkd.2015.01.019	ALTOLD		Contributing Study
Abnormalities in biomarkers of mineral and bone metabolism in kidney donors.	27370408	PMC5026566	Journal	2016	10.1016/j.kint.2016.05.012	ALTOLD		Contributing Study
Enhancing individual glomerular filtration rate assessment: can we trust the equation?	https://pubmed.ncbi.nlm.nih.gov/39885391/		Journal	2025	10.1186/s12882-025-03972-0	MDRD, PERL, DCCT/EDIC, AASK Trial, ALTOLD, AASK Cohort, CRIC, CRISP	23649	Secondary Research
Estimating glomerular filtration in young people	39314869		Journal	2024	https:/doi.org/10.1093/ckj/sfae261	MDRD, PERL, AASK Trial, DCCT/EDIC, AASK Cohort, CRISP, CRIC, ALTOLD	23649	Secondary Research
Performance of the European Kidney Function Consortium (EKFC) creatinine-based equation in American cohorts	38101514		Journal	2023	10.1016/j.kint.2023.11.024	AASK Trial, MDRD, DCCT/EDIC, PERL, ALTOLD, CRISP, CRIC, AASK Cohort	23649	Secondary Research
Quantifying Individual-Level Inaccuracy in Glomerular Filtration Rate Estimation	35785532		Journal	2022	10.7326/M22-0610	ALTOLD, CRIC	23163	Secondary Research

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