Braun, William E.

BACKGROUND A 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. METHODS The 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. RESULTS Both 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. CONCLUSION The 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. FUNDING NIDDK grants: Mayo DK058816 and DK090728; CRISP DK056943, DK056956, DK056957, and DK056961; and HALT PKD DK062410, DK062408, DK062402, DK082230, DK062411, and DK062401.

Significance Statement Accurate prediction of risk for disease progression is crucial for clinical management of autosomal dominant polycystic kidney disease (ADPKD). The Mayo imaging classification of ADPKD uses height-adjusted total kidney volume (htTKV) and age to identify patients at highest risk. Because the current Mayo classification applies only to patients with typical diffuse cystic disease (class 1) and poorly predicts eGFR decline for the remaining 5%–10% of patients with atypical morphology (class 2), imaging-based risk modeling remains unresolved. The authors report an expanded imaging classification model in which use of a recalculated htTKV value that excludes prominent exophytic cysts improved prediction for eGFR trajectory. Using a recalculated htTKV may allow inclusion of class 2 patients in the Mayo classification of ADPKD and reclassification of class 1 patients with prominent exophytic cysts. 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 m 2 for class 2Ae, and from −1.7 (using original htTKVs) to 0.1 ml/min per 1.73 m 2 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.

Abstract Background Patients with mild autosomal dominant polycystic kidney disease (ADPKD) are less likely to be informative in randomized clinical trials (RCTs). We previously developed an imaging classification of ADPKD (typical diffuse cyst distribution Class 1A–E and atypical cyst distribution Class 2) for prognostic enrichment design in RCTs. We investigated whether using this classification would have increased the power to detect a beneficial treatment effect of rigorous blood pressure (BP) control on HALT-PKD participants with early disease (Study A). Methods Post hoc analysis of the early disease HALT-PKD study, an RCT that studied the effect of rigorous versus standard BP control on rates of total kidney volume (TKV) increase and estimated glomerular filtration rate (eGFR) decline in ADPKD patients with eGFR >60 mL/min/1.73 m2. Results Five hundred and fifty-one patients were classified by two observers (98.2% agreement) into Class 1A (6.2%), 1B (20.3%), 1C (34.1%), 1D (22.1%), 1E (11.8%) and 2 (5.4%). The TKV increase and eGFR decline became steeper from Class 1A through 1E. Rigorous BP control had been shown to be associated with slower TKV increase, without a significant overall effect on the rate of eGFR decline (faster in the first 4 months and marginally slower thereafter). Merging Classes 1A and 2 (lowest severity), 1B and 1C (intermediate severity) and 1D and 1E (highest severity) detected stronger beneficial effects on TKV increase and eGFR decline in Class 1D and E with a smaller number of patients. Conclusions Strategies for prognostic enrichment, such as image classification, should be used in the design of RCTs for ADPKD to increase their power and reduce their cost.

Autosomal dominant polycystic kidney disease (ADPKD) often results in ESRD but with a highly variable course. Mutations to PKD1 or PKD2 cause ADPKD; both loci have high levels of allelic heterogeneity. We evaluated genotype-phenotype correlations in 1119 patients (945 families) from the HALT Progression of PKD Study and the Consortium of Radiologic Imaging Study of PKD Study. The population was defined as: 77.7% PKD1, 14.7% PKD2, and 7.6% with no mutation detected (NMD). Phenotypic end points were sex, eGFR, height–adjusted total kidney volume (htTKV), and liver cyst volume. Analysis of the eGFR and htTKV measures showed that the PKD1 group had more severe disease than the PKD2 group, whereas the NMD group had a PKD2-like phenotype. In both the PKD1 and PKD2 populations, men had more severe renal disease, but women had larger liver cyst volumes. Compared with nontruncating PKD1 mutations, truncating PKD1 mutations associated with lower eGFR, but the mutation groups were not differentiated by htTKV. PKD1 nontruncating mutations were evaluated for conservation and chemical change and subdivided into strong (mutation strength group 2 [MSG2]) and weak (MSG3) mutation groups. Analysis of eGFR and htTKV measures showed that patients with MSG3 but not MSG2 mutations had significantly milder disease than patients with truncating cases (MSG1), an association especially evident in extreme decile populations. Overall, we have quantified the contribution of genic and PKD1 allelic effects and sex to the ADPKD phenotype. Intrafamilial correlation analysis showed that other factors shared by families influence htTKV, with these additional genetic/environmental factors significantly affecting the ADPKD phenotype.