Self-Reported Medication Use and Urinary Drug Metabolites in the German Chronic Kidney Disease (GCKD) Study

Significance Statement Medication adherence is a well-recognized problem in the management of patients requiring polypharmacy. Pharmacometabolomics is an emerging approach that may illuminate medication use among persons with CKD. The authors evaluated self-reported use of 158 prescribed substances and 41 medication groups, along with measurements of 90 urinary drug metabolites, among 4885 individuals with CKD participating in a prospective cohort study. Accuracy and specificity were excellent, with high sensitivity for many cardiovascular drugs. Drug metabolites of over-the-counter analgesics were detected at levels higher than the self-reported use of these drugs. Pharmacometabolomics also revealed prescription patterns, including the recommended avoidance of combinations potentially causing serious adverse effects. This study generates a comprehensive resource that maps self-reported medication use and urinary drug metabolite levels, and supports the use of pharmacometabolomics for future research. Background Polypharmacy is common among patients with CKD, but little is known about the urinary excretion of many drugs and their metabolites among patients with CKD. Methods To evaluate self-reported medication use in relation to urine drug metabolite levels in a large cohort of patients with CKD, the German Chronic Kidney Disease study, we ascertained self-reported use of 158 substances and 41 medication groups, and coded active ingredients according to the Anatomical Therapeutic Chemical Classification System. We used a nontargeted mass spectrometry–based approach to quantify metabolites in urine; calculated specificity, sensitivity, and accuracy of medication use and corresponding metabolite measurements; and used multivariable regression models to evaluate associations and prescription patterns. Results Among 4885 participants, there were 108 medication-drug metabolite pairs on the basis of reported medication use and 78 drug metabolites. Accuracy was excellent for measurements of 36 individual substances in which the unchanged drug was measured in urine (median, 98.5%; range, 61.1%–100%). For 66 pairs of substances and their related drug metabolites, median measurement-based specificity and sensitivity were 99.2% (range, 84.0%–100%) and 71.7% (range, 1.2%–100%), respectively. Commonly prescribed medications for hypertension and cardiovascular risk reduction—including angiotensin II receptor blockers, calcium channel blockers, and metoprolol—showed high sensitivity and specificity. Although self-reported use of prescribed analgesics (acetaminophen, ibuprofen) was <3% each, drug metabolite levels indicated higher usage (acetaminophen, 10%–26%; ibuprofen, 10%–18%). Conclusions This comprehensive screen of associations between urine drug metabolite levels and self-reported medication use supports the use of pharmacometabolomics to assess medication adherence and prescription patterns in persons with CKD, and indicates under-reported use of medications available over the counter, such as analgesics.