MO492SELF-REPORTED MEDICATION USE AND URINARY DRUG METABOLITES IN THE GERMAN CHRONIC KIDNEY DISEASE (GCKD) STUDY: A PHARMACOMETABOLOMIC APPROACH. (29th May 2021)

• Record Type: Journal Article
• Authors: Kotsis, Fruzsina Kinga; Schultheiß, Ulla T; Wuttke, Matthias; Schlosser, Pascal; Oefner, Peter; Mohney, Robert P; Eckardt, Kai-Uwe; Mielke, Johanna; Becker, Michael; Sekula, Peggy; Köttgen, Anna
• Is Part Of: Nephrology dialysis transplantation. Volume 36(2021)Supplement 1
• Publication Date: 2021-05-29
• Subjects: Nephrology -- Periodicals; Hemodialysis -- Periodicals; Kidneys -- Transplantation -- Periodicals; Hemodialysis; Kidneys -- Transplantation; Nephrology; Periodicals; 616.61
• DOI: 10.1093/ndt/gfab087.0012
• Languages: English
• ISSNs: 0931-0509

Abstract

Abstract: Background and Aims: Chronic kidney disease (CKD) patients are prone to prescription of multiple medications. Medication adherence is a well-recognized problem in the management of patients with chronic diseases requiring polypharmacy. This study aimed to evaluate the connection between self-reported medication use and urine drug metabolite levels in a large cohort of CKD patients, the GCKD study, as a basis for future pharmacometabolomics studies. Method: Self-reported medication use of 160 substances and 41 medication groups was ascertained at study baseline and coded according to the Anatomical Therapeutic Chemical classification system. A non-targeted mass spectrometry-based approach (Metabolon HD4™) was used for concomitant metabolite quantification in urine. Specificity, sensitivity and accuracy of medication use and the corresponding urine metabolite measurements were calculated. Multivariable regression models (adjusted to age, sex, eGFR, log(UACR), systolic blood pressure, LDL, log(triglycerides), log(HBA1c) were used to establish associations in prescription patterns. Results: Among 4, 885 participants, 78 drug metabolites were detected in urine (frequency range: 0.4-58%) and assigned into 110 medication – drug metabolite pairs (MMPs) based on reported individual substances and medication groups. For all 68 MMPs of individual substances, accuracy of medication use and the corresponding drug metabolite measurement was excellent (median 97.0%, range 43%-100%), as was measurement-based specificity (median 99.3%, range 73.3%-100%; Fig. 1 ). Median measurement-based sensitivity was 72.1% (range 1.1%-100%, Fig. 1 ). Sensitivity and specificity were especially high for angiotensin-II receptor blockers (92%-96%; 99-100%), calcium channel blockers (85-100%; 91-100%), and metoprolol (90%; 98% respectively) commonly prescribed and important medications for blood pressure control and cardiovascular risk reduction in CKD patients. MMPs showing sensitivity <80% included several substances found in over-the-counter (OTC) analgesic medications, suggesting that their use is not always reported. While self-reported use of the OTC analgesics acetaminophen and ibuprofen was <3% each, their corresponding drug metabolites indicated higher usage (acetaminophen: 10-26%; ibuprofen: 10-18%, depending on the number of evaluated drug metabolites). Typical examples of medication co-prescriptions (e.g., trimethoprim and sulfamethoxazole) were detected as the combined presence of their drug metabolites in urine. This result validates the abstraction of single substances from combination medications and this urine-based metabolomic approach. Conclusion: This study provides a comprehensive screen of the associations between urine drug metabolite levels and self-reported medication use. It supports the usefulness of pharmacometabolomics to assess medication use, frequency of OTC analgesics use, and prescription patterns in persons with CKD.