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Randomized Controlled Trial
. 2015 Dec 15:201:499-507.
doi: 10.1016/j.ijcard.2015.07.080. Epub 2015 Aug 16.

Biomarkers in stable coronary heart disease, their modulation and cardiovascular risk: The LIPID biomarker study

Affiliations
Randomized Controlled Trial

Biomarkers in stable coronary heart disease, their modulation and cardiovascular risk: The LIPID biomarker study

Andrew M Tonkin et al. Int J Cardiol. .

Abstract

Aims: In patients with stable coronary heart disease (CHD), we aimed to assess 1. the prognostic power of biomarkers reflecting haemodynamics, micronecrosis, inflammation, coagulation, lipids, neurohumoral activity, and renal function; 2. whether changes in concentrations of these biomarkers over 12 months affected subsequent CHD risk; and 3. whether pravastatin modified the change in biomarker concentrations and this influenced the risk of future events.

Methods: In the LIPID study, 9014 patients were randomised to pravastatin 40 mg or placebo 3-36 months after an acute coronary syndrome. Eight biomarkers were measured at baseline (n=7863) and 12 months later (n=6434).

Results: During a median of 6.0 (IQR 5.5-6.5) years follow-up, 1100 CHD-related deaths and nonfatal myocardial infarctions occurred, 694 after biomarker measurement at 12 months. Baseline BNP, CRP, cystatin C, D-dimer, midregional pro-adrenomedullin, and sensitive troponin I predicted recurrent CHD events. In a multivariable model, sensitive troponin I, BNP, and cystatin C had the strongest associations with outcome (P<0.001 for trend). The strongest improvement in risk prediction was achieved by including sensitive troponin I (net reclassification improvement (NRI) 5.5%; P=0.003), BNP (4.3%; P=0.02), history of MI (NRI 7.0%; P<0.001). In landmark analyses, among biomarkers, changes to 12 months in sensitive troponin I (HR 1.32 (1.03-1.70) for T3/T1), BNP (HR 1.37 (1.10-1.69) for Q4/Q1) and Lp-PLA2 (HR 1.52 (1.16-1.97)) improved CHD risk prediction.

Conclusions: Baseline levels and changes in sensitive troponin I, and BNP may have the potential to guide the intensity of secondary prevention therapy.

Keywords: Biomarkers; Coronary heart disease; Risk estimation; Statin therapy.

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