Abstract: PO2343
A Population Health Survey-Based Prediction Equation for Incident CKD: The CKD Population Risk Tool CKDPort/PREDICT-CKD LIFESTYLE
Session Information
- Reassessing Race in Predicting Progression
November 04, 2021 | Location: On-Demand, Virtual Only
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2101 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention
Authors
- Noel, Ariana, University of Ottawa Faculty of Medicine, Ottawa, Ontario, Canada
- Rhodes, Emily, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
- Knoll, Greg A., University of Ottawa Faculty of Medicine, Ottawa, Ontario, Canada
- Sood, Manish M., University of Ottawa Faculty of Medicine, Ottawa, Ontario, Canada
Background
Chronic kidney disease awareness among the general public is less than 10%. Patients’ health behaviours are known to be associated with CKD development and disease progression. Prediction tools that engage the general public with their self-reported health information could increase awareness, identify modifiable lifestyle risk factors, empower patients, and prevent disease. The study objective was to develop and validate a population health survey-based prediction equation to determine the risk of incident CKD in the general public.
Methods
Participants who completed the Canadian Community Health Survey (CCHS) were linked to laboratory and hospital admission data between 2000 and 2015 in Ontario, Canada. The primary outcome was incident CKD (eGFR < 60 ml/min/1.73m2) with up to 8 years of follow-up. Models accounted for the competing risk of all-cause mortality. The CCHS is a random, comprehensive, prospective, general population survey that captures information on demographics, co-morbid illnesses, lifestyle and behaviours, diet, body mass index and mood. External validation was performed using data from the UK Biobank.
Results
From 22,200 eligible adults, 1,981 (8.9%) developed incident CKD during a mean follow-up time of 8 years. Domains included in the final reduced model were baseline eGFR, smoking, alcohol, physical activity, education, mood, fruit and vegetable intake, diabetes, hypertension, heart and lung disease, urinary incontinence, cancer, and BMI. The model demonstrated excellent discrimination in individuals with and without a baseline eGFR measure (5-year c-statistic with baseline eGFR: 0.84 95%CI 0.82-0.85, without 0.81 95%CI 0.80-0.82), was well calibrated (Brier score at 5-years with baseline eGFR: 0.07 95%CI 0.007-0.08, without 0.08 95%CI 0.07-0.08), and was consistent in a sensitivity analysis using 2 measures of eGFR > 90 days apart to define the outcome. The model was consistent with external validation.
Conclusion
Lifestyle and health behaviour information from population-based health surveys can predict incident CKD in the population with excellent discrimination and can be used to improve public engagement in CKD awareness.