Estimating the prevalence of chronic kidney disease while accounting for nonrandom testing with inverse probability weighting

Abstract

Listen

Translate article

Chronic kidney disease (CKD) prevalence estimation is central to guiding the medical community and policymakers on where to focus prevention and disease management strategies. Population sources make the estimation of CKD prevalence challenging. In screening cohort studies, healthy individuals are more likely to participate than nonhealthy individuals, which may lead to the underestimation of CKD prevalence. In routine care cohorts, persons undergoing testing for creatinine to estimate glomerular filtration rate (eGFR) and albuminuria may be sicker and with indication for the testing (i.e., with diabetes or hypertension), which may lead to the overestimation of CKD prevalence.