Key Points:
The Mayo clinic imaging classification and the predicting renal outcome in polycystic kidney disease score are used to assess the risk of progression to kidney failure in autosomal dominant polycystic kidney disease.
Mayo imaging classification and predicting renal outcome in polycystic kidney disease show little concordance; combined use increased the ability to identify rapid progression especially among intermediate risk patients.
Accurate risk prediction is key for determining indication for specific treatment.
Background: Autosomal dominant polycystic kidney disease is the most common genetic cause of kidney failure. Specific treatment is indicated on 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 multicenter cohort study of 468 patients diagnosed with autosomal dominant polycystic kidney disease. Clinical, imaging, and genetic data were analyzed for risk prediction. We defined rapid disease progression as an eGFR slope ≥3 ml/min per 1.73 m2 per year over 2 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 scores, several combined models were designed to develop a new classification with improved risk stratification. Primary endpoints were the development of advanced CKD stages G4–G5, longitudinal changes in eGFR, and clinical variables such as hypertension or urological events. Statistically, logistic regression, survival, receiver operating characteristic 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.