Patients with stable coronary artery disease (CAD) constitute a heterogeneous group in which the treatment benefits by angiotensin-converting enzyme (ACE)-inhibitor therapy vary between individuals. Our objective was to integrate clinical and pharmacogenetic determinants in an ultimate combined risk prediction model.

Background-Patients with stable coronary artery disease (CAD) constitute a heterogeneous group in which the treatment benefits by angiotensin-converting enzyme (ACE)-inhibitor therapy vary between individuals. Our objective was to integrate clinical and pharmacogenetic determinants in an ultimate combined risk prediction model. Methods and Results-Clinical, genetic, and outcomes data were used from 8726 stable CAD patients participating in the EUROPA/PERGENE trial of perindopril versus placebo. Multivariable analysis of phenotype data resulted in a clinical risk score (range, 0-21 points). Three single-nucleotide polymorphisms (rs275651 and rs5182 in the angiotensin-II type I-receptor gene and rs12050217 in the bradykinin type I-receptor gene) were used to construct a pharmacogenetic risk score (PGXscore; range, 0-6 points). Seven hundred eighty-five patients (9.0%) experienced the primary endpoint of cardiovascular mortality, nonfatal myocardial infarction or resuscitated cardiac arrest, during 4.2 years of follow-up. Absolute risk reductions ranged from 1.2% to 7.5% in the 73.5% of patients with PGXscore of 0 to 2. As a consequence, estimated annual numbers needed to treat ranged from as low as 29 (clinical risk score ≥10 and PGXscore of 0) to 521 (clinical risk score ≤6 and PGXscore of 2). Furthermore, our data suggest that long-term perindopril prescription in patients with a PGXscore of 0 to 2 is cost-effective. Conclusions--Both baseline clinical phenotype, as well as genotype determine the efficacy of widely prescribed ACE inhibition in stable CAD. Integration of clinical and pharmacogenetic determinants in a combined risk prediction model demonstrated a very wide range of gradients of absolute treatment benefit.

Individualized angiotensin-converting enzyme (ACE)-inhibitor therapy in stable coronary artery disease based on clinical and pharmacogenetic determinants: The PERindopril GENEtic (PERGENE) risk model

FERRARI, Roberto;
2015

Abstract

Background-Patients with stable coronary artery disease (CAD) constitute a heterogeneous group in which the treatment benefits by angiotensin-converting enzyme (ACE)-inhibitor therapy vary between individuals. Our objective was to integrate clinical and pharmacogenetic determinants in an ultimate combined risk prediction model. Methods and Results-Clinical, genetic, and outcomes data were used from 8726 stable CAD patients participating in the EUROPA/PERGENE trial of perindopril versus placebo. Multivariable analysis of phenotype data resulted in a clinical risk score (range, 0-21 points). Three single-nucleotide polymorphisms (rs275651 and rs5182 in the angiotensin-II type I-receptor gene and rs12050217 in the bradykinin type I-receptor gene) were used to construct a pharmacogenetic risk score (PGXscore; range, 0-6 points). Seven hundred eighty-five patients (9.0%) experienced the primary endpoint of cardiovascular mortality, nonfatal myocardial infarction or resuscitated cardiac arrest, during 4.2 years of follow-up. Absolute risk reductions ranged from 1.2% to 7.5% in the 73.5% of patients with PGXscore of 0 to 2. As a consequence, estimated annual numbers needed to treat ranged from as low as 29 (clinical risk score ≥10 and PGXscore of 0) to 521 (clinical risk score ≤6 and PGXscore of 2). Furthermore, our data suggest that long-term perindopril prescription in patients with a PGXscore of 0 to 2 is cost-effective. Conclusions--Both baseline clinical phenotype, as well as genotype determine the efficacy of widely prescribed ACE inhibition in stable CAD. Integration of clinical and pharmacogenetic determinants in a combined risk prediction model demonstrated a very wide range of gradients of absolute treatment benefit.
2015
Oemrawsingh, Rohit M; Akkerhuis, K. Martijn; Van Vark, Laura C; Redekop, W. Ken; Rudez, Goran; Remme, Willem J; Bertrand, Michel E; Fox, Kim M; Ferrari, Roberto; Danser, A. H. Jan; de Maat, Moniek; Simoons, Maarten L; Brugts, Jasper J; Boersma, Eric
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2349774
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