Development and Validation of Prediction Models of Adverse Kidney Outcomes in the Population With and Without Diabetes

Morgan E. Grams (Lead / Corresponding author), Nigel J. Brunskill, Shoshana H. Ballew, Yingying Sang, Josef Coresh (Lead / Corresponding author), Kunihiro Matsushita, Aditya Surapaneni, Samira Bell, Juan J. Carrero, Gabriel Chodick, Marie Evans, Hiddo J. L. Heerspink, Lesley A. Inker, Kunitoshi Iseki, Philip A. Kalra, H. Lester Kirchner, Brian J. Lee, Adeera Levin, Rupert W. Major, James MedcalfGirish N. Nadkarni, David M. J. Naimark, Ana C. Ricardo, Simon Sawhney, Manish M. Sood, Natalie Staplin, Nikita Stempniewicz, Benedicte Stengel, Keiichi Sumida, Jamie P. Traynor, Jan van den Brand, Chi-Pang Wen, Mark Woodward, Jae Won Yang, Angela Yee-Moon Wang, Navdeep Tangri,

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OBJECTIVE To predict adverse kidney outcomes for use in optimizing medical management and clinical trial design. RESEARCH DESIGN AND METHODS In this meta-analysis of individual participant data, 43 cohorts (N 5 1,621,817) from research studies, electronic medical records, and clinical trials with global representation were separated into development and validation cohorts. Models were developed and validated within strata of diabetes mellitus (presence or absence) and estimated glomerular filtration rate (eGFR; ‡60 or <60 mL/min/ 1.73 m 2) to predict a composite of ‡40% decline in eGFR or kidney failure (i.e., re-ceipt of kidney replacement therapy) over 2–3 years. RESULTS There were 17,399 and 24,591 events in development and validation cohorts, re-spectively. Models predicting ‡40% eGFR decline or kidney failure incorporated age, sex, eGFR, albuminuria, systolic blood pressure, antihypertensive medication use, history of heart failure, coronary heart disease, atrial fibrillation, smoking sta-tus, and BMI, and, in those with diabetes, hemoglobin A 1c, insulin use, and oral diabetes medication use. The median C-statistic was 0.774 (interquartile range [IQR] 5 0.753, 0.782) in the diabetes and higher-eGFR validation cohorts; 0.769 (IQR 5 0.758, 0.808) in the diabetes and lower-eGFR validation cohorts; 0.740 (IQR 5 0.717, 0.763) in the no diabetes and higher-eGFR validation cohorts; and 0.750 (IQR 5 0.731, 0.785) in the no diabetes and lower-eGFR validation cohorts. Incorporating the previous 2-year eGFR slope minimally improved model performance, and then only in the higher-eGFR cohorts. CONCLUSIONS Novel prediction equations for a decline of ‡40% in eGFR can be applied success-fully for use in the general population in persons with and without diabetes with higher or lower eGFR.

Original languageEnglish
Pages (from-to)2055-2063
Number of pages9
JournalDiabetes Care
Issue number9
Early online date20 Jul 2022
Publication statusPublished - Sept 2022

ASJC Scopus subject areas

  • Advanced and Specialised Nursing
  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism


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