An official website of the United States government
Publication Information
Affiliation
Division of Nephrology and Hypertension.; Department of Biomedical Statistics and Informatics, and.; Division of Nephrology and Hypertension.; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.; Division of Nephrology, University of Chicago School of Medicine, Chicago, Illinois, USA.; Division of Nephrology, Tufts Medical Center, Tufts University School of Medicine, Boston, Massachusetts, USA.; Division of Nephrology, University of Alabama and Department of Veterans Affairs Medical Center, Birmingham, Alabama, USA.; Department of Nephrology and Hypertension, Cleveland Clinic, Cleveland, Ohio, USA.; Renal Division, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.; Department of Internal Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.; Division of Renal Diseases and Hypertension, University of Colorado Denver Anschutz Medical Campus, Aurora, Colorado, USA.; Department of Radiology and.; Center of Research on Health Care, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.; Division of Nephrology and Hypertension.; Jared Grantham Kidney Institute, Kansas University Medical Center, Kansas, Kansas, USA.; Division of Nephrology and Hypertension.; Division of Nephrology and Hypertension.
Authors
Lavu Sravanthi, Vaughan Lisa E, Senum Sarah R, Kline Timothy L, Chapman Arlene B, Perrone Ronald D, Mrug Michal, Braun William E, Steinman Theodore I, Rahbari-Oskoui Frederic F, Brosnahan Godela M, Bae Kyongtae T, Landsittel Douglas, Chebib Fouad T, Yu Alan Sl, Torres Vicente E, Harris Peter C
Studies
Abstract
BACKGROUNDA treatment option for autosomal dominant polycystic kidney disease (ADPKD) has highlighted the need to identify rapidly progressive patients. Kidney size/age and genotype have predictive power for renal outcomes, but their relative and additive value, plus associated trajectories of disease progression, are not well defined.METHODSThe value of genotypic and/or kidney imaging data (Mayo Imaging Class; MIC) to predict the time to functional (end-stage kidney disease [ESKD] or decline in estimated glomerular filtration rate [eGFR]) or structural (increase in height-adjusted total kidney volume [htTKV]) outcomes were evaluated in a Mayo Clinic PKD1/PKD2 population, and eGFR and htTKV trajectories from 20-65 years of age were modeled and independently validated in similarly defined CRISP and HALT PKD patients.RESULTSBoth genotypic and imaging groups strongly predicted ESKD and eGFR endpoints, with genotype improving the imaging predictions and vice versa; a multivariate model had strong discriminatory power (C-index = 0.845). However, imaging but not genotypic groups predicted htTKV growth, although more severe genotypic and imaging groups had larger kidneys at a young age. The trajectory of eGFR decline was linear from baseline in the most severe genotypic and imaging groups, but it was curvilinear in milder groups. Imaging class trajectories differentiated htTKV growth rates; severe classes had rapid early growth and large kidneys, but growth later slowed.CONCLUSIONThe value of imaging, genotypic, and combined data to identify rapidly progressive patients was demonstrated, and reference values for clinical trials were provided. Our data indicate that differences in kidney growth rates before adulthood significantly define patients with severe disease.FUNDINGNIDDK grants: Mayo DK058816 and DK090728; CRISP DK056943, DK056956, DK056957, and DK056961; and HALT PKD DK062410, DK062408, DK062402, DK082230, DK062411, and DK062401.