A Comparison of Two Multiple-Characteristic Decision-Making Models for the Comparison of Antihypertensive Drug Classes

Abstract

Multiple-characteristics decision-making (MCDM) models can be used to calculate a score, based on a set of characteristics, for a number of alternative drugs or drug classes to allow comparison between them and thus enhance evidence-based pharmacotherapy. To compare two MCDM models, Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), in determining first-line antihypertensive drug class. Five different classes of antihypertensive drugs were analyzed: diuretics, beta-adrenoceptor antagonists (beta-blockers), dihydropyridine calcium channel blockers (DHP-CCBs), ACE inhibitors, and angiotensin II type 1 receptor antagonists (angiotensin receptor blockers [ARBs]). Four characteristics were deemed relevant for the determination of first-line antihypertensive drug class: effectiveness, persistence with treatment as a measure of tolerability, cost, and clinical experience. Weight factors were determined by sending questionnaires to cardiologists, pharmacists, general practitioners (GPs), and internists in The Netherlands. Absolute scores for the characteristics were determined from literature (effectiveness and persistence) and health insurance data (costs and clinical experience). Ninety-two cardiologists (33% of those sent the questionnaire), 90 GPs (31%), 87 internists (31%), and 123 pharmacists (43%) completed the questionnaire. Among all professions, according to both SAW and TOPSIS, ACE inhibitors were ranked as the first-line antihypertensive drug class, typically followed by beta-blockers. Both SAW and TOPIS analyses, using weight factors assigned by cardiologists, pharmacists, GPs, and internists from The Netherlands, rank ACE inhibitors as the first choice among antihypertensive drug classes for the treatment of uncomplicated hypertension. Both methods are valuable tools in the development of evidence-based pharmacotherapy.