A Health Survey–Based Prediction Equation for Incident CKD. Issue 1 (January 2023) - Noel, Ariana J.; Eddeen, Anan Badder; Manuel, Douglas G.; Rhodes, Emily; Tangri, Navdeep; Hundemer, Gregory L.; Tanuseputro, Peter; Knoll, Gregory A.; Mallick, Ranjeeta; Sood, Manish M.
Visual Abstract: Abstract : Background: Prediction tools that incorporate self-reported health information could increase CKD awareness, identify modifiable lifestyle risk factors, and prevent disease. We developed and validated a survey-based prediction equation to identify individuals at risk for incident CKD (eGFR <60 ml/min per 1.73 m 2 ), with and without a baseline eGFR. Methods: A cohort of adults with an eGFR ≥70 ml/min per 1.73 m 2 from Ontario, Canada, who completed a comprehensive general population health survey between 2000 and 2015 were included ( n =22, 200). Prediction equations included demographics (age, sex), comorbidities, lifestyle factors, diet, and mood. Models with and without baseline eGFR were derived and externally validated in the UK Biobank ( n =15, 522). New-onset CKD (eGFR <60 ml/min per 1.73 m 2 ) with ≤8 years of follow-up was the primary outcome. Results: Among Ontario individuals (mean age, 55 years; 58% women; baseline eGFR, 95 (SD 15) ml/min per 1.73 m 2 ), new-onset CKD occurred in 1981 (9%) during a median follow-up time of 4.2 years. The final models included lifestyle factors (smoking, alcohol, physical activity) and comorbid illnesses (diabetes, hypertension, cancer). The model was discriminating in individuals with and without a baseline eGFR measure (5-year c-statistic with baseline eGFR: 83.5, 95% confidence interval [CI], 82.2 to 84.9; without: 81.0, 95% CI, 79.8 to 82.4) and well calibrated. In external validation, the 5-year c-statistic was 78.1 (95% CI, 74.2 to 82.0) and 66.0 (95% CI, 61.6 to 70.4), with and without baseline eGFR, respectively, and maintained calibration. Conclusions: Self-reported lifestyle and health behavior information from health surveys may aid in predicting incident CKD. Podcast: This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast.aspx?p=CJASN&e=2023_01_10_CJN05650522.mp3