There are six specific clinical variables that can accurately predict rapid decline among patients with autosomal dominant polycystic kidney disease (ADPKD), a researcher reported.
In a study that used real-world data on 1,744 ADPKD patients, a total of 125 (7%) experienced rapid decline in estimated glomerular filtration rate (eGFR) values during a 15-year follow-up period, said John J. Sim, MD, of Kaiser Permanente Los Angeles Medical Center, in a poster presentation at the National Kidney Foundation Spring Clinical Meetings.
Out of a collection of 42 baseline measurements, these six specific variables were older age, lower hemoglobin, proteinuria, hypertension, cerebrovascular disease, and male sex.
After swapping out serum creatinine and liver disease from the original model and replacing them with male sex, the final model was able to identify rapid decline in ADPKD patients with 72% sensitivity, 70% specificity and accuracy, and 0.77 area under the curve (AUC).
As for progression to end-stage kidney disease, this occurred in 38% of these "rapid decliners" and only 7% of non-rapid decliners in the cohort.
"We wanted to demonstrate a distinct high-risk group of ADPKD patients who can be identified with clinical information at the time of their presentation," Sim told Ƶ. "Using these variables, we hope to help develop some prediction models to give doctors additional insights on who are the high-risk ADPKD patients so that it can help determine their management."
Sim explained that his group honed in on this 7% subset of patients whose eGFR trajectory and decline was starkly different from the rest of the ADPKD cohort.
"We observed that this rapid decliner group were able to be distinguished from the non-rapid decliner group based on several clinical variables at presentation including hemoglobin levels, which was interesting and somewhat surprising," he added.
Sim also noted that it was important that the team use information regularly available in clinical practice to allow for greater applicability as a practical screening tool in a real-world environment to pinpoint patients who could benefit more from earlier and more intensive management of ADPKD.
The researchers pointed out on their poster that creatinine alone is an unreliable predictor of ADPKD progression, and that other methods like resource-intensive prognostic strategies such as predicting renal outcomes in ADPKD genetic testing and Mayo Imaging Classification MRI aren't as accessible in everyday clinical practice. Genetic and imaging data also were not available for this entire cohort.
The retrospective cohort study included patients treated at Kaiser Permanente Southern California from 2002 to 2018. Incident ADPKD was defined as two or more ICD diagnostic codes in an inpatient or outpatient setting without a prior diagnosis within the year prior.
At baseline, average eGFR was 85.2 mL/min/1.73 m2 in the rapid decline group and 72.9 mL/min/1.73 m2 in the non-rapid decline group.
Sim and his fellow researchers suggested that the model be validated in other clinical environments as well.
"We hope that our real-world findings from clinical practice can help provide additional insights into the ADPKD population, which will eventually hopefully lead to improved management and spring newer therapies for ADPKD, which is the most common genetic kidney disease," Sim concluded.
Disclosures
The study was funded by Otsuka Pharmaceutical.
Primary Source
National Kidney Foundation
Sim J, et al "Predictors associated with rapid decline of eGFR to end-stage kidney disease (ESKD) among a diverse autosomal dominant polycystic kidney disease (ADPKD) population" NKF 2022; Poster #349.