Imaging classification of autosomal dominant polycystic kidney disease: a simple model for selecting patients for clinical trials

Abstract

The rate of renal disease progression varies widely among patients with autosomal dominant polycystic kidney disease (ADPKD), necessitating optimal patient selection for enrollment into clinical trials. Patients from the Mayo Clinic Translational PKD Center with ADPKD (n=590) with computed tomography/magnetic resonance images and three or more eGFR measurements over ≥6 months were classified radiologically as typical (n=538) or atypical (n=52). Total kidney volume (TKV) was measured using stereology (TKVs) and ellipsoid equation (TKVe). Typical patients were randomly partitioned into development and internal validation sets and subclassified according to height-adjusted TKV (HtTKV) ranges for age (1A-1E, in increasing order). Consortium for Radiologic Imaging Study of PKD (CRISP) participants (n=173) were used for external validation. TKVe correlated strongly with TKVs, without systematic underestimation or overestimation. A longitudinal mixed regression model to predict eGFR decline showed that log2HtTKV and age significantly interacted with time in typical patients, but not in atypical patients. When 1A-1E classifications were used instead of log2HtTKV, eGFR slopes were significantly different among subclasses and, except for 1A, different from those in healthy kidney donors. The equation derived from the development set predicted eGFR in both validation sets. The frequency of ESRD at 10 years increased from subclass 1A (2.4%) to 1E (66.9%) in the Mayo cohort and from 1C (2.2%) to 1E (22.3%) in the younger CRISP cohort. Class and subclass designations were stable. An easily applied classification of ADPKD based on HtTKV and age should optimize patient selection for enrollment into clinical trials and for treatment when one becomes available.

Keywords: ADPKD; cystic kidney; kidney volume; polycystic kidney disease; progression of chronic renal failure; survival.

Figure 1.

Flowchart of the study design and classification. We reviewed electronically available abdominal CT or MRI of 1069 patients with ADPKD from the Mayo Clinic, of whom 590 were classified as having typical ADPKD (class 1) or atypical ADPKD (class 2). The 538 class 1 patients were randomly partitioned into a development set (70%) or an internal validation set (30%). Assuming a theoretical starting HtTKV of 150 ml/m and a yearly increase of 1.5%, 3%, 4.5%, or 6%, HtTKV limits were calculated for each age in the development set. Patients were then subclassified as 1A–1E on the basis of the HtTKV for their specific age. The same classification criteria were applied to the internal validation set. In addition, the images from 177 non-Mayo CRISP participants were reviewed and 173 were classified as class 1 to form the external validation set. Atypical patients (class 2) were subclassified as 2A or 2B according to imaging characteristics (Supplemental Figure 1, Table 1). FU, follow-up; SCr, serum creatinine.

Figure 2.

TKV by ellipsoid correlates strongly with TKV by stereology. Comparison of TKVe from CT or MRI versus TKVs in the MTPC (A and B) and CRISP (C and D) cohorts. TKVs and TKVe were strongly correlated (A and C) without systematic under- or overestimation of TKVe (B and D) in both cohorts. In 175 of the 590 MTPC patients (29.7%; B) and in 10 of the 177 CRISP patients (5.6%; D), the percentage difference between TKVe and TKVs exceeded 10%. The difference exceeded 20% in only 5.9% of the MTPC and in none of the CRISP patients.

Figure 3.

Classification by HtTKV0 and age at HtTKV0 predicts the change in eGFR over time in class 1 patients. (A) Subclassification of patients with class 1 ADPKD at baseline based on HtTKV limits for their age. Limits are defined based on estimated kidney growth rates of 1.5%, 3.0%, 4.5%, and 6.0%. (B) Slopes for men based on the model presented in Table 5. As a reference, the average eGFR at baseline (75 ml/min per 1.73 m²) and the average age at baseline (44 years) for all class 1 patients were used for the model. Estimated slopes (ml/min per 1.73 m² per year) by subclass (A–E) are −0.23,−1.33, −2.63, −3.48, and −4.78, respectively, for men and 0.03, −1.13, −2.43, −3.29 and −4.58, respectively, for women (not plotted). Values for normal slope (*) were obtained from a population of healthy kidney donors.

Figure 4.

Equation derived from the development set predicted eGFR in both validation sets. Prediction of eGFR in patients with class 1 ADPKD: internal (A and B) and external (C and D) validation sets. (A and C) Scatterplot of the observed eGFR (estimated by Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI] equation) versus the predicted eGFR derived from the model obtained from the development set. Ellipse represents the 95% CI. (B and D) Differences between predicted eGFR by the model and eGFR values by the CKD-EPI equation plotted against the eGFR values by CKD-EPI equation. The average predicted errors were 13.5 and 17.1 ml/min per 1.73 m² in the internal and external validation sets, respectively, and were lower for patients with an observed eGFR<60 ml/min per 1.73 m² than in those with an observed eGFR≥60 ml/min per 1.73 m² (10.1 and 14.9 versus 16.2 and 17.7).

Figure 5.

Classification by HtTKV0 and age at HtTKV0 predicts renal survival in class 1 patients. Kaplan-Meier survival plots of time to ESRD by subclasses in the class 1 MTPC (A) and CRISP (B) patients and for the class 2 MTPC (C) patients.

Figure 6.

Classification remains stable in most patients over time. Years of imaging follow-up and stability of patients with class 1 ADPKD. Years of imaging follow-up (A and C) and stability of patients with class 1 (typical) ADPKD (B and D) during imaging follow-up period in MTPC (A and B) and CRISP (C and D) patients. Most MTPC and CRISP patients remained in their baseline classification. A few patients moved to the immediate lower subclass, whereas some progressed to a higher class, in most cases the immediate higher class, at the end of imaging follow-up.