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

Abstract

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.

Keywords: chronic kidney disease; medication use; pharmacometabolomics; urine metabolites.

Graphical abstract

Figure 1.

Overlap of drug metabolites and self-reported medication use in the GCKD study. Overall, 90 drug metabolites and 199 medications (158 substances and 41 medication groups) were available, resulting in 108 MMPs after accounting for multiple assignments of drug metabolites to substances and medication groups and vice versa (gray area). Among 90 drug metabolites, 78 could be assigned to at least one medication (38 unmodified drugs, 42 drug metabolites*). Of the 199 medications, 53 could be assigned to metabolites (36 substances, 17 drug groups). The total of 108 MMPs was composed of 66 MMPs based on substances and 42 MMPs of medication groups. For the remaining 12 metabolites without assignment (left side), the respective medications were reported by <20 users and thus not considered further. The 146 medications not assigned to drug metabolites (right side) had missing or too few measurements. *Because prednisone and prednisolone are interconverted, both metabolites were assigned to both medications (Prednisone, Prednisolone) and thus counted twice, as an unmodified drug and as a drug metabolite. ChEBI, Chemical Entities of Biological Interest.

Figure 2.

Accuracy of medication-drug metabolite pairs in relation to the fraction of extrarenal excretion of the unmodified drug. The x axis shows accuracy of 36 MMPs: 33 MMPs based on the unmodified drug (category MMP-0), and 3 MMPs based on a single drug metabolite when the unmodified drug was unavailable (category MMP-1*). Accuracy (%)=100%×(N[++]+N[–])/Ntotal; where ++ represents self-reported medication use with urine measurement, and – represents no self-reported medication use without urine measurement. Q0 values represent the fraction of extrarenal excretion when kidney function is normal (range, 0–1; https://dosing.de); that is, 1-Q0 represents the fraction of a drug that is removed unchanged via the kidneys. Color code: red represents Q0≥0.5, i.e., mainly extrarenal excretion; blue represents Q0<0.5, i.e., mainly renal elimination of unmodified drug. ¹Drug metabolites (MMP-1*); ²Q0-values were obtained from a different source than the one described above (Sulfamethoxazole^,; Lisinopril⁵⁴).

Figure 3.

Sensitivity and specificity of MMPs involving substances. A total of 66 MMPs, based on 36 substances and all of their available drug metabolites, were evaluated (A) using measured drug metabolites as the reference (“measurement-based”), and (B) using reported medication use as the reference (“medication-based”). MMPs with <80% sensitivity or specificity are annotated. Tables summarize the results of (A) and (B): both measurement- (meas) and medication-based (med) sensitivity and specificity ≥80% (right table) or both <80% (left table). MMPs with ≥80% specificity for both measurement- and medication-based analysis but <80% sensitivity in either are shown in the middle table. Obs., observation; Sens.: sensitivity; *Metabolon is highly confident in the identity of the metabolite. Metabolites without an asterisk conform to the highest confidence level of identification of the Metabolomics Standards Initiative (Level 1).

Figure 4.

Sensitivity and specificity of cardiovascular medication-drug metabolite pairs. Sensitivity and specificity were calculated in relation to metabolite measurements as the reference. Sensitivity=100%×N(users with metabolite measurements)/N(all patients with metabolite measurements). Specificity=100%×N(nonusers without measurements)/N(all patients without measurements).

Figure 5.

Metabolites of (A) Acetaminophen and (B) Ibuprofen and their proportions measured from urine of GCKD participants. Left column: Illustration of initial steps of metabolism. Metabolites highlighted in bold have been reported by Loo et al. as main drug metabolites in urine, and were used to assess analgesic use based on metabolomics. Right column: Bar plot representing proportions of reported medication use (white) and of urine measurements of unmodified drug metabolites (4-acetamidophenol) and main metabolites (black and gray, respectively). The bottom bar of each bar plot panel represents a summary measure of the measured metabolites, and is used to evaluate the use of the respective medication based on metabolomics. Acetaminophen comb, combination of unmodified drug (4-acetamidophenol) together with at least two of the three main drug metabolites (light gray), or with all three main metabolites (dark gray); Ibuprofen comb, combination of at least two of the three main drug metabolites (light gray), or combination of all three main metabolites (dark gray); MCU, mercapturate (synonym, 3-[N-acetyl-L-cystein-S-yl] acetaminophen); NAPQI, N-acetyl-p-benzoquinone.