Baseline total kidney volume and the rate of kidney growth are associated with chronic kidney disease progression in Autosomal Dominant Polycystic Kidney Disease

Abstract

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive enlargement of kidney cysts leading to chronic kidney disease (CKD) and end-stage renal disease (ESRD). Identification of an early biomarker that can predict progression of CKD is urgently needed. In an earlier Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) study (a prospective, multicenter, observational analysis of 241 patients with ADPKD initiated in 2000), baseline height-adjusted total kidney volume (htTKV) was shown to be associated with development of CKD stage 3 after eight years of follow-up. Here we conducted an extended study and found that in a multivariable logistic regression model, baseline htTKV was shown to be a strong, independent predictor for the development of CKD after a median follow-up of 13 years. The odds ratio of reaching each CKD stage per 100 mL/m increment in htTKV was 1.38 (95% confidence interval 1.19-1.60) for stage 3, 1.42 (1.23-1.64) for stage 4, and 1.35 (1.18-1.55) for stage 5 or ESRD. Baseline htTKV was also associated with relative decreases in the glomerular filtration rate of 30%, and 57% or more. Moreover, the rate of change in htTKV was negatively correlated with the slope of the glomerular filtration rate. While ADPKD genotype was also associated with CKD outcomes, it was not an independent prognostic factor after adjusting for htTKV. Thus, baseline total kidney volume and the rate of kidney growth are strongly associated with the development of advanced stages of CKD. These findings support the use of total kidney volume as a prognostic and potentially monitoring biomarker in ADPKD.

Keywords: ADPKD; chronic kidney disease; glomerular filtration rate.

Fig. 1

Flow diagram showing the enrolled study participants that were included in the final analysis. Numbers shown are for analysis of the outcome of CKD stage 3, as determined from measured GFR. LTFU, lost to follow-up.

Fig. 2

Linear correlations between baseline htTKV and iothalamate GFR during follow-up. Best-fit lines and Spearman’s correlation coefficients (r) were determined at baseline and 7 subsequent visits. htTKV, height-adjusted total kidney volume. P values for all time points < 0.0001.

Fig. 3

Scatter plots showing the correlation between annual percentage change in htTKV, determined over the course of the entire study (A) or using data from the first 4 years only (B), and the annual change in iothalamate GFR during the study. Spearman’s correlation coefficients (r) are shown.

Fig. 4

Improvement in the ability of the models to predict various CKD outcomes after addition of htTKV and/or ADPKD genotype, as assessed by the net reclassification index (NRI). Model 1 (Base model): Sex, race, BMI, baseline age and GFR; Model 2: Base model + genotype; Model 3: Base model + htTKV; Model 4: Base model + genotype + htTKV.