Simplified end stage renal failure risk prediction model for the low-risk general population with chronic kidney disease - Lim, Cynthia C.; Chee, Miao Li; Cheng, Ching-Yu; Kwek, Jia Liang; Foo, Majorie; Wong, Tien Yin; Sabanayagam, Charumathi (PloS one, 2019)
Chronic kidney disease (CKD) contributes significant morbidity and mortality among Asians; hence interventions should focus on those most at-risk of progression. However, current end stage renal failure (ESRF) risk stratification tools are complex and not validated in multi-ethnic Asians. We hence aimed to develop an ESRF risk prediction model by taking into account ethnic differences within a fairly homogenous socioeconomic setting and using parameters readily accessible to primary care clinicians managing the vast majority of patients with CKD. We performed a prospective cohort study of 1970 adults with CKD estimated glomerular filtration rate <60 ml/min/1.73m2 or albuminuria >30 mg/g from the population-based Singapore Epidemiology of Eye Diseases study (n = 10,033). Outcome was incident ESRF, ascertained by linkage to the Singapore Renal Registry until 2015. Mean follow up was 8.5 ± 1.8 years and ESRF occurred in 32 individuals (1.6%). ESRF incidence rates were 2.8, 0.8 and 2.6 per 1000 patient years in Malays, Indians and Chinese respectively. The best ESRF prediction model included age, gender, eGFR and albuminuria (calibration χ2 = 0.45, P = 0.93; C-statistic 0.933, 95% confidence interval (CI) 0.889-0.978, p = 0.01; AIC 356). Addition of ethnicity improved discrimination marginally (C statistic 0.942, 95% CI 0.903-0.981, p = 0.21). Addition of clinical variables such as diabetes and hyperlipidemia did not improve model performance significantly. We affirmed the utility of commonly available clinical information (age, gender, eGFR and UACR) in prognosticating ESRF for multi-ethnic Asians with CKD.