title: Comparison of methods for determining renal function decline in early autosomal dominant polycystic kidney disease: the consortium of radiologic imaging studies of polycystic kidney disease cohort.
abstract: A decline in renal function suggests progression of chronic kidney disease. This can be determined by measured GFR (e.g., iothalamate clearance), serum creatinine (SCr)-based GFR estimates, or creatinine clearance. A cohort of 234 patients with autosomal dominant polycystic kidney disease and baseline creatinine clearance>70 ml/min were followed annually for four visits. Iothalamate clearance, SCr, and creatinine clearance were obtained at each visit. Estimated GFR (eGFR) was determined with the Modification of Diet in Renal Disease (MDRD) and Cockcroft-Gault equations. Renal function slopes had a mean residual SD of 10.7% by iothalamate clearance, 8.2% by MDRD equation, 7.7% by Cockcroft-Gault equation, and 14.8% by creatinine clearance. By each method, a decline in renal function (lowest quintile slope) was compared among baseline predictors. Hypertension was associated with a decline in iothalamate clearance (odds ratio [OR] 5.8; 95% confidence interval [CI] 2.3 to 14), eGFR (OR [MDRD] 2.0 [95% CI 1.0 to 4.2] or OR [Cockcroft-Gault] 1.9 [95% CI 0.9 to 3.9]), and creatinine clearance (OR 2.0; 95% CI 1.0 to 4.2). Each doubling of kidney volume at baseline was associated with a decline in iothalamate clearance (OR 2.4; 95% CI 1.5 to 3.7), eGFR (OR 1.7 [95% CI 1.1 to 2.6] or 2.1 [95% CI 1.4 to 3.3]), and creatinine clearance (OR 1.7; 95% CI 1.1 to 2.5). Predictor associations were strongest with measured GFR. Misclassification from changes in non-GFR factors (e.g., creatinine production, tubular secretion) conservatively biased associations with eGFR. Misclassification from method imprecision attenuated associations with creatinine clearance.
authors.affiliation: Division of Nephrology, Mayo Foundation, 200 First Street SW, Rochester, MN 55905, and University of Alabama, Birmingham, USA. rule.andrew@mayo.edu
authors.forename: Andrew D
authors.initials: AD
authors.lastname: Rule
authors.forename: Vicente E
authors.initials: VE
authors.lastname: Torres
authors.forename: Arlene B
authors.initials: AB
authors.lastname: Chapman
authors.forename: Jared J
authors.initials: JJ
authors.lastname: Grantham
authors.forename: Lisa M
authors.initials: LM
authors.lastname: Guay-Woodford
authors.forename: Kyongtae T
authors.initials: KT
authors.lastname: Bae
authors.forename: Saulo
authors.initials: S
authors.lastname: Klahr
authors.forename: William M
authors.initials: WM
authors.lastname: Bennett
authors.forename: Catherine M
authors.initials: CM
authors.lastname: Meyers
authors.forename: Paul A
authors.initials: PA
authors.lastname: Thompson
authors.forename: J Philip
authors.initials: JP
authors.lastname: Miller
mesh_terms: D000293:Adolescent; D000328:Adult; D015331:Cohort Studies; D003404:Creatinine / Q000652:urine; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D005919:Glomerular Filtration Rate; D006801:Humans; D007677:Kidney Function Tests / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D016891:Polycystic Kidney, Autosomal Dominant / Q000175:diagnosis* / Q000503:physiopathology; D011237:Predictive Value of Tests; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D013997:Time Factors; D016482:Urinalysis
chemical_list: D003404:Creatinine