Integrated use of autosomal dominant polycystic kidney disease prediction tools for risk prognostication

Background: Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic cause of kidney failure. Specific treatment is indicated upon observed or predicted rapid progression. For the latter, risk stratification tools have been developed independently based on either total kidney volume or genotyping as well as clinical variables. This study aimed to improve risk prediction by combining both imaging and clinical-genetic scores.

Methods: We conducted a retrospective multi-center cohort study of 468 patients diagnosed with ADPKD. Clinical, imaging, and genetic data were analyzed for risk prediction. We defined rapid disease progression as an estimated glomerular filtration rate (eGFR) slope ≥3 ml/min/1.73m2/year over two years, Mayo imaging classification (MIC) 1D-1E, or a Predicting Renal Outcome in Polycystic Kidney Disease (PROPKD) score of ≥7 points. Using MIC, PROPKD, and Rare Exome Variant Ensemble Learner (REVEL) scores, several combined models were designed to develop a new classification with improved risk stratification. Primary endpoints were the development of advanced chronic kidney disease (aCKD) stages G4-G5, longitudinal changes in eGFR, and clinical variables such as hypertension or urological events. Statistically, logistic regression, survival, Receiver Operating Characteristic (ROC) analyses, linear mixed models, and Cox proportional hazards models were used.

Results: PKD1-genotype (p <0.001), MIC class 1E (p <0.001), early-onset hypertension (p <0.001) and early-onset urological events (p =0.003) correlated best with rapid progression in multivariable analysis. While the MIC showed satisfactory specificity (77%), the PROPKD was more sensitive (59%). Among individuals with an intermediate risk in one of the scores, integration of the other score (combined scoring) allowed for more accurate stratification.

Conclusions: The combined use of both risk scores was associated with higher ability to identify rapid progressors and resulted in a better stratification, notably among intermediate risk patients.