Andrew M Tonkin1, Stefan Blankenberg2, Adrienne Kirby3, Tanja Zeller2, David M Colquhoun4, Anne Funke-Kaiser2, Wendy Hague3, David Hunt5, Anthony C Keech3, Paul Nestel6, Ralph Stewart7, David R Sullivan8, Peter L Thompson9, Malcolm West10, Harvey D White7, John Simes3. 1. Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia. Electronic address: Andrew.Tonkin@monash.edu. 2. University Heart Centre Hamburg, Hamburg, Germany. 3. National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, Australia. 4. Wesley Medical Centre and Greenslopes Hospital, Brisbane, Australia. 5. Department of Medicine, University of Melbourne, Melbourne, Australia. 6. Baker IDI Heart & Diabetes Institute, Melbourne, Australia. 7. Green Lane Cardiovascular Service, Auckland City Hospital, Auckland, New Zealand. 8. Department of Clinical Biochemistry, Royal Prince Alfred Hospital, Sydney, Australia. 9. School of Population Health, University of WA, Perth, Australia. 10. Department of Medicine, University of QLD, Brisbane, Australia.
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.
RCT Entities:
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.
Authors: Claire Sweeney; Fiona Ryan; Mark Ledwidge; Cristin Ryan; Ken McDonald; Chris Watson; Rebabonye B Pharithi; Joe Gallagher Journal: Cochrane Database Syst Rev Date: 2019-10-15
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