TY - JOUR
T1 - Expanded imaging classification of autosomal dominant polycystic kidney disease
AU - HALT PKD Consortium
AU - Bae, Kyongtae T.
AU - Shi, Tiange
AU - Tao, Cheng
AU - Yu, Alan S.L.
AU - Torres, Vicente E.
AU - Perrone, Ronald D.
AU - Chapman, Arlene B.
AU - Brosnahan, Godela
AU - Steinman, Theodore I.
AU - Braun, William E.
AU - Srivastava, Avantika
AU - Irazabal, Maria V.
AU - Abebe, Kaleab Z.
AU - Harris, Peter C.
AU - Landsittel, Douglas P.
AU - Bae, Kyongtae T.
AU - Torres, Vicente E.
AU - Perrone, Ronald D.
AU - Chapman, Arlene B.
AU - Brosnahan, Godela
AU - Steinman, Theodore I.
AU - Braun, William E.
AU - Abebe, Kaleab Z.
AU - Harris, Peter C.
AU - Winklhofer, Franz
AU - Czarnecki, Peter
AU - Hogan, Marie
AU - Miskulin, Dana
AU - Rahbari-Oskoui, Frederic
N1 - Funding Information:
Dr. Bae reports personal fees from Kadmon and Otsuka Pharmaceuticals, outside the submitted work. Dr. Harris reports grants from Otsuka Pharma- ceuticals, and other support from Amgen, Inc., Bayer AG, EMD Millipore Corporation (aka EMDMerck KGaA), Genzyme Corporation, GlaxoSmithKline LLC, Mitobridge, Inc., Otsuka Pharmaceuticals, Regulus, and Vertex Pharmaceuticals, outside the submitted work. Dr. Perrone reports grants and personal fees from Otsuka Pharmaceuticals, Reata, and Sanofi-Genzyme; personal fees from Goldfinch, Palladio Biosciences, and Vertex Pharmaceuticals; grants from Kadmon; and other support from UpToDate, outside the submitted work. Dr. Torres reports grants from Acceleron Pharma, Inc., Blueprint Medicines, Otsuka Pharmaceuticals, Palladio Biosciences, and Regulus Therapeutics, and other support from Mironid, Otsuka Pharmaceuticals, Palladio Biosciences, Sanofi-Genzyme, and Vertex Pharmaceuticals, outside the submitted work. Dr. Yu reports grants from the National Institute of Diabetes and Digestive and Kidney Diseases during the conduct of the study, and personal fees from Otsuka Pharmaceuticals and Regulus Therapeutics, outside the submitted work. All remaining authors have nothing to disclose.
Funding Information:
This work has been supported by National Institute of Diabetes and Digestive and Kidney Diseases grants DK62402 (to Dr. Torres), DK082230, DK62411 (to Dr. Perrone), DK62410, DK62408 (to Dr. Chapman), DK62401 (to Washington University in St. Louis), and DK090728 (to the Mayo Translational PKD Center); National Center for Research Resources General Clinical Research Centers grants RR000585 (to the Mayo Clinic), RR000039 (to Emory University), RR000054 (to Tufts Medical Center), RR000051 (to the University of Colorado), RR023940 (to the University of Kansas Medical Center), and RR001032 (to Beth Israel Deaconess Medical Center); National Center for Advancing Translational Sciences Clinical and Translational Science awards RR024150 and TR00135 (to the Mayo Clinic), RR025008 and TR000454 (to Emory University), RR025752 and TR001064 (to Tufts University), RR025780 and TR001082 (to the University of Colorado), RR025758 and TR001102 (to Beth Israel Deaconess Medical Center), RR033179 and TR000001 (to the University of Kansas Medical Center), and RR024989 and TR000439 (to Cleveland Clinic); the Zell Family Foundation (to the University of Colorado); and the PKD Foundation.
Publisher Copyright:
Copyright © 2020 by the American Society of Nephrology
PY - 2020/7
Y1 - 2020/7
N2 - Background The Mayo Clinic imaging classification of autosomal dominant polycystic kidney disease (ADPKD) uses height-adjusted total kidney volume (htTKV) and age to identify patients at highest risk for disease progression. However, this classification applies only to patients with typical diffuse cystic disease (class 1). Because htTKV poorly predicts eGFR decline for the 5%-10% of patients with atypical morphology (class 2), imaging-based risk modeling remains unresolved. Methods Of 558 adults with ADPKD in the HALT-A study, we identified 25 patients of class 2A with prominent exophytic cysts (class 2Ae) and 43 patients of class 1 with prominent exophytic cysts; we recalculated their htTKVs to exclude exophytic cysts. Using original and recalculated htTKVs in association with imaging classification in logistic and mixed linear models, we compared predictions for developing CKD stage 3 and for eGFR trajectory. Results Using recalculated htTKVs increased specificity for developing CKD stage 3 in all participants from 82.6% to 84.2% after adjustment for baseline age, eGFR, BMI, sex, and race. The predicted proportion of class 2Ae patients developing CKD stage 3 using a cutoff of 0.5 for predicting case status was better calibrated to the observed value of 13.0% with recalculated htTKVs (45.5%) versus original htTKVs (63.6%). Using recalculated htTKVs reduced the mean paired difference between predicted and observed eGFR from 17.6 (using original htTKVs) to 4.0 ml/min per 1.73 m2 for class 2Ae, and from 21.7 (using original htTKVs) to 0.1 ml/min per 1.73 m2 for class 1. Conclusions Use of a recalculated htTKV measure that excludes prominent exophytic cysts facilitates inclusion of class 2 patients and reclassification of class 1 patients in the Mayo classification model.
AB - Background The Mayo Clinic imaging classification of autosomal dominant polycystic kidney disease (ADPKD) uses height-adjusted total kidney volume (htTKV) and age to identify patients at highest risk for disease progression. However, this classification applies only to patients with typical diffuse cystic disease (class 1). Because htTKV poorly predicts eGFR decline for the 5%-10% of patients with atypical morphology (class 2), imaging-based risk modeling remains unresolved. Methods Of 558 adults with ADPKD in the HALT-A study, we identified 25 patients of class 2A with prominent exophytic cysts (class 2Ae) and 43 patients of class 1 with prominent exophytic cysts; we recalculated their htTKVs to exclude exophytic cysts. Using original and recalculated htTKVs in association with imaging classification in logistic and mixed linear models, we compared predictions for developing CKD stage 3 and for eGFR trajectory. Results Using recalculated htTKVs increased specificity for developing CKD stage 3 in all participants from 82.6% to 84.2% after adjustment for baseline age, eGFR, BMI, sex, and race. The predicted proportion of class 2Ae patients developing CKD stage 3 using a cutoff of 0.5 for predicting case status was better calibrated to the observed value of 13.0% with recalculated htTKVs (45.5%) versus original htTKVs (63.6%). Using recalculated htTKVs reduced the mean paired difference between predicted and observed eGFR from 17.6 (using original htTKVs) to 4.0 ml/min per 1.73 m2 for class 2Ae, and from 21.7 (using original htTKVs) to 0.1 ml/min per 1.73 m2 for class 1. Conclusions Use of a recalculated htTKV measure that excludes prominent exophytic cysts facilitates inclusion of class 2 patients and reclassification of class 1 patients in the Mayo classification model.
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U2 - 10.1681/ASN.2019101121
DO - 10.1681/ASN.2019101121
M3 - Article
C2 - 32487558
AN - SCOPUS:85087467827
SN - 1046-6673
VL - 31
SP - 1640
EP - 1651
JO - Journal of the American Society of Nephrology
JF - Journal of the American Society of Nephrology
IS - 7
ER -