BACKGROUND: Drug nonadherence is one of the major challenges faced by resistant hypertension patients, and identification of this problem is needed for optimizing pharmacotherapy. Dried blood spot (DBS) sampling is a minimally invasive method designed to detect and determine the degree of nonadherence. In this study, a DBS method for qualifying 8 antihypertensive drugs (AHDs) and 4 active metabolites was developed and validated using ultra high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). METHOD: The DBS assay was validated analytically and clinically, in accordance with FDA requirements. Analytical validation was accomplished using UHPLC-MS/MS. For clinical validation, paired peak and trough levels of DBS and plasma samples were simultaneously collected and comparatively analyzed using Deming regression and Bland-Altman analyses. All concentrations below the set lower limit were excluded. Deming regression analysis was used to predict comparison bias between the collected plasma and DBS samples, with DBS concentrations corrected accordingly. RESULTS: The UHPLC-MS/MS method for simultaneously measuring 8 AHDs and their metabolites in DBS, was successfully validated. With Deming regression no bias was observed in N = 1; constant bias was seen in N = 6 and proportional bias in N = 11 of the AHDs and metabolites. After correction for bias, only one metabolite (canrenone) met the 20% acceptance limit for quantification, after Bland-Altman analyses. In addition, amlodipine, valsartan, and [enalaprilate] met the 25% acceptance limit. CONCLUSIONS: A novel DBS assay for simultaneously qualifying and quantifying 8 AHDs and their metabolites, has been successfully developed and validated. The DBS assay is therefore a suitable method to detect drug nonadherence. However, with the exception of canrenone, the interchangeable use of plasma and DBS sampling to interpret drug quantities should be avoided.
BACKGROUND: Drug nonadherence is one of the major challenges faced by resistant hypertensionpatients, and identification of this problem is needed for optimizing pharmacotherapy. Dried blood spot (DBS) sampling is a minimally invasive method designed to detect and determine the degree of nonadherence. In this study, a DBS method for qualifying 8 antihypertensive drugs (AHDs) and 4 active metabolites was developed and validated using ultra high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). METHOD: The DBS assay was validated analytically and clinically, in accordance with FDA requirements. Analytical validation was accomplished using UHPLC-MS/MS. For clinical validation, paired peak and trough levels of DBS and plasma samples were simultaneously collected and comparatively analyzed using Deming regression and Bland-Altman analyses. All concentrations below the set lower limit were excluded. Deming regression analysis was used to predict comparison bias between the collected plasma and DBS samples, with DBS concentrations corrected accordingly. RESULTS: The UHPLC-MS/MS method for simultaneously measuring 8 AHDs and their metabolites in DBS, was successfully validated. With Deming regression no bias was observed in N = 1; constant bias was seen in N = 6 and proportional bias in N = 11 of the AHDs and metabolites. After correction for bias, only one metabolite (canrenone) met the 20% acceptance limit for quantification, after Bland-Altman analyses. In addition, amlodipine, valsartan, and [enalaprilate] met the 25% acceptance limit. CONCLUSIONS: A novel DBS assay for simultaneously qualifying and quantifying 8 AHDs and their metabolites, has been successfully developed and validated. The DBS assay is therefore a suitable method to detect drug nonadherence. However, with the exception of canrenone, the interchangeable use of plasma and DBS sampling to interpret drug quantities should be avoided.
Authors: Laura E J Peeters; Soma Bahmany; Tim Dekker; Aya Aliawi; Bart van Domburg; Jorie Versmissen; Birgit C P Koch Journal: Ther Drug Monit Date: 2022-04-05 Impact factor: 3.118
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Authors: Laura E J Peeters; Leonardien K Tjong; Wim J R Rietdijk; Teun van Gelder; Birgit C P Koch; Jorie Versmissen Journal: Biomedicines Date: 2022-01-08
Authors: Valeria Avataneo; Elvira Fanelli; Amedeo De Nicolò; Franco Rabbia; Alice Palermiti; Marco Pappaccogli; Jessica Cusato; Francesco Giuseppe De Rosa; Antonio D'Avolio; Franco Veglio Journal: Front Pharmacol Date: 2022-01-05 Impact factor: 5.810
Authors: Tanja R Zijp; Zamrotul Izzah; Daan J Touw; Job F M van Boven; Christoffer Åberg; C Tji Gan; Stephan J L Bakker Journal: Drugs Date: 2021-11-01 Impact factor: 9.546