Predictors for major cardiovascular outcomes in stable ischaemic heart disease (PREMAC): statistical analysis plan for data originating from the CLARICOR (clarithromycin for patients with stable coronary heart disease) trial

Per Winkel, Janus Christian Jakobsen, Jørgen Hilden, Theis Lange, Gorm Boje Jensen, Erik Kjøller, Ahmad Sajadieh, Jens Kastrup, Hans Jørn Kolmos, Anders Larsson, Johan Ärnlöv, Christian Gluud, Per Winkel, Janus Christian Jakobsen, Jørgen Hilden, Theis Lange, Gorm Boje Jensen, Erik Kjøller, Ahmad Sajadieh, Jens Kastrup, Hans Jørn Kolmos, Anders Larsson, Johan Ärnlöv, Christian Gluud

Abstract

Background: The purpose of the predictors for major cardiovascular outcomes in stable ischaemic heart disease (PREMAC) study is exploratory and hypothesis generating. We want to identify biochemical quantities which-conditionally on the values of available standard demographic, anamnestic, and biochemical data-may improve the prediction of cardiovascular outcomes and/or death in patients suffering from stable ischaemic heart disease. The candidate biochemical quantities include N-terminal pro-B-type natriuretic peptide, YKL-40, osteoprotegerin, high-sensitive assay cardiac troponin T (hs-cTnT), pregnancy-associated plasma protein-A (PAPP-A), cathepsin B, cathepsin S, soluble TNF receptor 1 and 2, neutrophil gelatinase-associated lipocalin, endostatin, and calprotectin. As an extra objective, we also want to assess if skewness in these predictors may explain why the clarithromycin for patients with stable coronary heart disease (CLARICOR) trial found increased all-cause and cardiovascular (CV) mortality on a brief clarithromycin regimen compared with placebo.

Methods: Baseline data were obtained from the hospital files at five cardiology clinics covering the Copenhagen area. The CLARICOR trial included data from 4372 stable coronary artery disease patients recruited among such patients alive and diagnosed with acute myocardial infarction or unstable angina pectoris during 1993 to 1999 in Copenhagen and randomised during October 1999 to April 2000 to the CLARICOR trial of 14 days clarithromycin versus placebo.Initial follow-up lasted for 2.6 years, during which outcomes were collected through hospital and death registries and assessed by an adjudication committee. Corresponding register data later showed to produce similar results. The adjudicated outcomes were therefore replaced and augmented by register data on outcomes to cover 10 years of follow-up. Biochemical marker data were obtained from analysis of serum from the CLARICOR bio-bank collected at randomisation and stored at -80° C.Using Cox proportional hazard method, we will identify among the candidate biochemical quantities those which are significant predictors when used alone and in combination with the standard predictors as defined in the present study.

Discussion: Patients who became stable during the period 1993 to 1999 and died before October 1999 are missing. The data from the placebo patients are nevertheless useful to identify new prognostic biomarkers in patients with stable coronary artery disease, and data from both trial groups are useful to assess important potential skewness between randomised groups. However, due to the potential selection bias, we do not feel that it is advisable to try to rank identified biochemical predictors relative to each other nor to use the results for predictive purposes.

Trial registration: ClinicalTrials.gov, NCT00121550 Date of registration 13 July 2005Date of enrolment of first participant 12 October 1999.

Keywords: Biomarkers; CLARICOR; Ischaemic heart disease; Mortality; Predictors.

Conflict of interest statement

The authors declare that they have no competing interests.

References

    1. Nichols M, Townsend N, Scarborough P, Rayner M. Cardiovascular disease in Europe 2014: epidemiological update. Eur Heart J. 2014;35:2929. doi: 10.1093/eurheartj/ehu378.
    1. Cooper R, Cutler J, Desvigne-Nickens P, Fortmann SP, Friedman L, Havlik R, et al. Trends and disparities in coronary heart disease, stroke, and other cardiovascular diseases in the United States: findings of the national conference on cardiovascular disease prevention. Circulation. 2000;102:3137–3147. doi: 10.1161/01.CIR.102.25.3137.
    1. Schmidt M, Jacobsen JB, Lash TL, Botker HE, Sorensen HT. 25 year trends in first time hospitalisation for acute myocardial infarction, subsequent short and long term mortality, and the prognostic impact of sex and comorbidity: a Danish nationwide cohort study. BMJ. 2012;344:e356. doi: 10.1136/bmj.e356.
    1. Wilson PWF, Cannon CP, Downey BC. Overview of the risk equivalents and established risk factors for cardiovascular disease. UpToDate. Post TW, Editors, UpToDate Waltham; 2015. Accessed 2 Mar 2017.
    1. WHO. 2015. . Accessed 2 Mar 2017.
    1. Vilarino-Rico J, Pita-Fernandez S, Segura-Iglesias RJ. Clinical predictors of major adverse cardiovascular events during long-term follow-up after carotid endarterectomy. Ann Vasc Surg. 2015;29:419–425. doi: 10.1016/j.avsg.2014.08.018.
    1. Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ. 2015;350:g7594. doi: 10.1136/bmj.g7594.
    1. Hemingway H, Croft P, Perel P, Hayden JA, Abrams K, Timmis A, Briggs A, Udumyan R, Moons KG, Steyerberg EW, et al. Prognosis research strategy (PROGRESS) 1: a framework for researching clinical outcomes. BMJ. 2013;346:e5595. doi: 10.1136/bmj.e5595.
    1. Wynants L, Collins GS, Van Calster B. Key steps and common pittfalls in developing and validating risk models. BJOG. 2016. doi:10.1111/1471-0528.14170.
    1. Jespersen CM, Als-Nielsen B, Damgaard M, Hansen JF, Hansen S, Helo OH, et al. Randomised placebo controlled multicentre trial to assess short term clarithromycin for patients with stable coronary heart disease: CLARICOR trial. BMJ. 2006;332:22–27. doi: 10.1136/bmj.38666.653600.55.
    1. Hansen S, Als-Nielsen B, Damgaard M, Helø OH, Petersen L, Jespersen CM, et al. Intervention with clarithromycin in patients with stable coronary heart disease: the CLARICOR trial design. Heart Drug. 2001;1:14–9. doi: 10.1159/000022705.
    1. Winkel P, Hilden J, Hansen JF, Kastrup J, Kolmos HJ, Kjoller E, et al. Clarithromycin for stable coronary heart disease increases all-cause and cardiovascular mortality and cerebrovascular morbidity over 10 years in the CLARICOR randomised, blinded clinical trial. Int J Cardiol. 2015;182:459–465. doi: 10.1016/j.ijcard.2015.01.020.
    1. Winkel P, Hilden J, Fischer Hansen J, Hildebrandt P, Kastrup J, Kolmos HJ, et al. Excess sudden cardiac deaths after short-term clarithromycin administration in the CLARICOR trial: why is this so, and why are statins protective? Cardiology. 2011;118:63–67. doi: 10.1159/000324533.
    1. Gluud C, Als-Nielsen B, Damgaard M, Fischer Hansen J, Hansen S, Helo OH, et al. Clarithromycin for 2 weeks for stable coronary heart disease: 6-year follow-up of the CLARICOR randomized trial and updated meta-analysis of antibiotics for coronary heart disease. Cardiology. 2008;111:280–287. doi: 10.1159/000128994.
    1. Harutyunyan MJ, Mathiasen AB, Winkel P, Gotze JP, Hansen JF, Hildebrandt P, et al. High-sensitivity C-reactive protein and N-terminal pro-B-type natriuretic peptide in patients with stable coronary artery disease: a prognostic study within the CLARICOR trial. Scand J Clin Lab Invest. 2011;71:52–62. doi: 10.3109/00365513.2010.538081.
    1. Kastrup J, Johansen JS, Winkel P, Hansen JF, Hildebrandt P, Jensen GB, et al. High serum YKL40 concentration is associated with cardiovascular and all-cause mortality in patients with stable coronary artery disease. Eur Heart J. 2009;30:1066–72. doi: 10.1093/eurheartj/ehp049.
    1. Lyngbaek S, Winkel P, Gotze JP, Kastrup J, Gluud C, Kolmos HJ, et al. Risk stratification in stable coronary artery disease is possible at cardiac troponin levels below conventional detection and is improved by use of N-terminal pro-B-type natriuretic peptide. Eur J Prev Cardiol. 2014;21:1275–1284. doi: 10.1177/2047487313492099.
    1. Iversen KK, Teisner B, Winkel P, Gluud C, Kjoller E, Kolmos HJ, et al. Pregnancy associated plasma protein-A as a marker for myocardial infarction and death in patients with stable coronary artery disease: a prognostic study within the CLARICOR Trial. Atherosclerosis. 2011;214:203–208. doi: 10.1016/j.atherosclerosis.2010.10.025.
    1. Wang N, Bai X, Jin B, Han W, Sun X, Chen X. The association of serum cathepsin-B concentration with age-related cardiovascular-renal subclinical state in a healthy Chinese population. Arch Gerontol Geriatr. 2016;65:146–55. doi: 10.1016/j.archger.2016.03.015.
    1. Ärnlöv J, Ruge T, Ingelsson E, Sundstrom J, Lind L. Serum endostatin and risk of mortality in the elderly: findings from 2 community-based cohorts. Arterioscler Thromb Vasc Biol. 2013;33:2689–95. doi: 10.1161/ATVBAHA.113.301704.
    1. Jobs E, Ingelsson E, Risérus U, Nerpin E, Jobs M, Sundström J, et al. Association between serum cathepsin S and mortality in older adults. JAMA. 2011;306:1113–21. doi: 10.1001/jama.2011.1246.
    1. Carlsson AC, Larsson TE, Helmersson-Karlqvist J, Larsson A, Lind L, Ärnlöv J. Soluble TNF receptors and kidney dysfunction in the elderly. J Am Soc Nephrol. 2014;25:1313–20. doi: 10.1681/ASN.2013080860.
    1. Helmersson-Karlqvist J, Larsson A, Carlsson AC, Venge P, Sundstrom J, Ingelsson E, et al. Urinary neutrophil gelatinase-associated lipocalin (NGAL) is associated with mortality in a community-based cohort of older Swedish men. Atherosclerosis. 2013;227:408–13. doi: 10.1016/j.atherosclerosis.2013.01.009.
    1. Larsen SB, Grove EL, Pareek M, Kristensen SD, Hvas AM. Calprotectin and platelet aggregation in patients with stable coronary artery disease. PLoS ONE. 2015;10(5):e0125992. doi: 10.1371/journal.pone.0125992.
    1. Bjerre M, Hilden J, Kastrup J, Skoog M, Hansen JF, Kolmos HJ, et al. Osteoprotegerin independently predicts mortality in patients with stable coronary artery disease: the CLARICOR trial. Scand J Clin Lab Invest. 2014;74:657–664. doi: 10.3109/00365513.2014.930510.
    1. Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med. 2012;367:20–9. doi: 10.1056/NEJMoa1114248.
    1. Helweg-Larsen K. The Danish register of causes of death. Scand J Public Health. 2011;39(7 30.Suppl):26–9. doi: 10.1177/1403494811399958.
    1. Lynge E, Sandegaard JL, Rebolj M. The Danish National Patient Register. Scand J Public Health. 2011;39(7 suppl):30–3. doi: 10.1177/1403494811401482.
    1. Kjoller E, Hilden J, Winkel P, Frandsen NJ, Galatius S, Jensen G, et al. Good interobserver agreement was attainable on outcome adjudication in patients with stable coronary heart disease. J Clin Epidemiol. 2012;65:444–53. doi: 10.1016/j.jclinepi.2011.09.011.
    1. Kjoller E, Hilden J, Winkel P, Galatius S, Frandsen NJ, Jensen GB, et al. Agreement between public register and adjudication committee outcome in a cardiovascular randomized clinical trial. Am Heart J. 2014;168:197–204. doi: 10.1016/j.ahj.2013.12.032.
    1. Wong ND. Epidemiological studies of CHD and the evolution of preventive cardiology. Nat Rev Cardiol. 2014;11:276–289. doi: 10.1038/nrcardio.2014.26.
    1. Solomon SD, Claggett B, Desai AS, Packer M, Zile M, Swedberg K, et al. Influence of ejection fraction on outcomes and efficacy of sacubitril/valsartan (LCZ696) in heart failure with reduced ejection fraction. Circ Heart Fail. 2016;9:e00274. doi: 10.1161/CIRCHEARTFAILURE.115.002744.
    1. Boot RG, van Achterberg TAE, van Aken BE, Renkema GH, Jacobs MHM, Aerts JMFG, de Vries CJM. Strong induction of members of the chitinase family of proteins in atherosclerosis. Chitotriosidase and human cartilage gp-39 expressed in lesion macrophages. Arterioscler Thromb Vasc Biol. 1999;19:687–694. doi: 10.1161/01.ATV.19.3.687.
    1. Vik A, Mathiesen EB, Noto AT, Sveinbjornsson B, Brox J, Hansen JB. Serum osteoprotegerin is inversely assiociated to carotid plaque echogenecity in humans. Atherosclerosis. 2007;191:128–34. doi: 10.1016/j.atherosclerosis.2006.03.002.
    1. Lindstedt L, Lee M, Oörni K, Brömme D, Kovanen PT. Cathepsins F and S block HDL3-induced cholesterol efflux from macrophage foam cells. Biochem Biophys Res Commun. 2003;312(4):1019–1024. doi: 10.1016/j.bbrc.2003.11.020.
    1. Rodgers KJ, Watkins DJ, Miller AL, Chan PY, Karanam S, Brissette WH, Long CJ, Jackson CL. Destabilizing role of cathepsin S in murine atherosclerotic plaques. Arterioscler Thromb Vasc Biol. 2006;26(4):851–6. doi: 10.1161/01.ATV.0000203526.75772.4b.
    1. Sluimer JC, Gasc JM, van Wanroij JL, Kisters N, Groeneweg M, Sollewijn Gelpke MD, Cleutjens JP, van den Akker LH, Corvol P, Wouters BG, Daemen MJ, Bijnens AP. Hypoxia, hypoxia-inducible transcription factor, and macrophages in human atherosclerotic plaques are correlated with intraplaque angiogenesis. J Am Coll Cardiol. 2008;51(13):1258–65. doi: 10.1016/j.jacc.2007.12.025.
    1. Heljasvaara R, Nyberg P, Luostarinen J, Parikka M, Heikkilä P, Rehn M, Sorsa T, Salo T, Pihlajaniemi T. Generation of biologically active endostatin fragments from human collagen XVIII by distinct matrix metalloproteases. Exp Cell Res. 2005;307(2):292–304. doi: 10.1016/j.yexcr.2005.03.021.
    1. Libby P. Inflammation in atherosclerosis. Arterioscler Thromb Vasc Biol. 2012;32:2045-51.
    1. Carlsson AC, Juhlin CC, Larsson TE, Larsson A, Ingelsson E, Sundström J, Lind L, Ärnlöv J. Soluble tumor necrosis factor receptor 1 (sTNFR1) is associated with increased total mortality due to cancer and cardiovascular causes—findings from two community based cohorts of elderly. Atherosclerosis. 2014;237(1):236–42. doi: 10.1016/j.atherosclerosis.2014.09.005.
    1. Liu J, Ma L, Yang J, Ren A, Sun Z, Yan G, Sun J, Fu H, Xu W, Hu C, Shi GP. Increased serum cathepsin S in patients with atherosclerosis and diabetes. Atherosclerosis. 2006;186(2):411–9. doi: 10.1016/j.atherosclerosis.2005.08.001.
    1. Seko Y, Fukuda S, Nagai R. Serum levels of endostatin, vascular endothelial growth factor (VEGF) and hepatocyte growth factor (HGF) in patients with acute myocardial infarction undergoing early reperfusion therapy. Clin Sci (Lond) 2004;106(5):439–42. doi: 10.1042/CS20030365.
    1. Blankenberg S, McQueen MJ, Smieja M, Pogue J, Balion C, Lonn E, Rupprecht HJ, Bickel C, Tiret L, Cambien F, Gerstein H, Münzel T, Yusuf S, HOPE Study Investigators Comparative impact of multiple biomarkers and N-Terminal pro-brain natriuretic peptide in the context of conventional risk factors for the prediction of recurrent cardiovascular events in the Heart Outcomes Prevention Evaluation (HOPE) Study. Circulation. 2006;114:201–8. doi: 10.1161/CIRCULATIONAHA.105.590927.
    1. Carbone F, Mach F, Montecucco F. Update on the role of neutrophils in atherosclerotic plaque vulnerability. Curr Drug Targets. 2015;16:321–33. doi: 10.2174/1389450115666141110093013.
    1. Elneihoum AM, Falke P, Hedblad B, Lindgärde F, Ohlsson K. Leukocyte activation in atherosclerosis: correlation with risk factors. Atherosclerosis. 1997;131:79–84. doi: 10.1016/S0021-9150(96)06077-7.
    1. Lin DY, Wei LJ, Ying Z. Checking the Cox model with cumulative sums of martingale-based residuals. Biometrika. 1993;80:557–72. doi: 10.1093/biomet/80.3.557.
    1. Kerr KF, Wang Z, Janes H, McClelland RL, Psaty BM, Pepe MS. Net reclassification indices for evaluating risk-prediction instruments: a critical review. Epidemiology. 2014;25:114–121. doi: 10.1097/EDE.0000000000000018.
    1. Newson RB. Comparing the predictive powers of survival models using Harrell’s C or Somers’ D. Stata J. 2010;10:339–58.
    1. Little R. A test of missing completely at random for multivariate data with missing values. J Am Stat Assoc. 1988;83:1198–1202.
    1. Pepe MS, Fan J, Feng Z, Gerds T, Hilden J. The Net Reclassification Index (NRI): a misleading measure of prediction improvement even with independent test data sets. Stat Biosci. 2015;7:282–295. doi: 10.1007/s12561-014-9118-0.
    1. Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making. 2006;26:565–574. doi: 10.1177/0272989X06295361.

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