| Home > Publications Database > Validation of self-reported medication use applying untargeted mass spectrometry-based metabolomics techniques in the Rhineland study. |
| Journal Article | DZNE-2022-00026 |
; ; ;
2022
Wiley-Blackwell
Oxford
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Please use a persistent id in citations: doi:10.1111/bcp.15175
Abstract: To assess the validity of self-reported continuous medication use with drug metabolites measured in plasma by using untargeted mass spectrometric techniques.In a population-based cohort in Bonn, Germany, we compared interview-based, self-reported medication intake with drug-specific metabolites measured in plasma (based on participants who completed their study visits between March 2016 and February 2020). Analyses were done stratified by sex and age (<65 years vs ≥65 years). Cohen's kappa (κ) statistics with 95% confidence intervals (CI) were calculated.A total of 13 drugs used to treat hypertension, gout, diabetes, epilepsy and depression were analysed in a sample of 4386 individuals (mean age 55 years, 56.1% women). Eleven drugs showed almost perfect agreement (κ > 0.8), whereas sitagliptin and hydrochlorothiazide showed substantial (κ = 0.8, 95% CI 0.71-0.90) and moderate agreement (κ = 0.61, 95% CI 0.56-0.66), respectively. Frequency of use allowed sex- and age-stratified analyses for eight and nine drugs, respectively. For five drugs, concordance tended to be higher for women than for men. For most drugs, concordance was higher among individuals aged ≥65 years than among individuals aged <65 years, but these age-related differences were not statistically significant.High concordance rates between self-reported drug use and metabolites measured in plasma suggest that self-reported drug use is reliable and accurate for assessing drug use.
Keyword(s): Diabetes Mellitus: drug therapy (MeSH) ; Female (MeSH) ; Humans (MeSH) ; Hypertension: drug therapy (MeSH) ; Male (MeSH) ; Mass Spectrometry (MeSH) ; Metabolomics (MeSH) ; Middle Aged (MeSH) ; Reproducibility of Results (MeSH) ; Self Report (MeSH) ; mass spectrometry ; metabolomics ; molecular epidemiology ; pharmacoepidemiology ; self-reported data ; validity
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