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267 results on '"Dagenais, GR"'

1. Life expectancy associated with different ages at diagnosis of type 2 diabetes in high-income countries: 23 million person-years of observation

Author

Kaptoge, S, Seshasai, SRK, Sun, L, Walker, M, Bolton, T, Spackman, S, Ataklte, F, Willeit, P, Bell, S, Burgess, S, Pennells, L, Altay, S, Assmann, G, Ben-Shlomo, Y, Best, LG, Björkelund, C, Blazer, DG, Brenner, H, Brunner, EJ, Dagenais, GR, Cooper, JA, Cooper, C, Crespo, CJ, Cushman, M, D'Agostino, RB, Sr, Daimon, M, Daniels, LB, Danker, R, Davidson, KW, de Jongh, RT, Donfrancesco, C, Ducimetiere, P, Elders, PJM, Engström, G, Ford, I, Gallacher, I, Bakker, SJL, Goldbourt, U, de La Cámara, G, Grimsgaard, S, Gudnason, V, Hansson, PO, Imano, H, Jukema, JW, Kabrhel, C, Kauhanen, J, Kavousi, M, Kiechl, S, Knuiman, MW, Kromhout, D, Krumholz, HM, Kuller, LH, Laatikainen, T, Lowler, DA, Meyer, HE, Mukamal, K, Nietert, PJ, Ninomiya, T, Nitsch, D, Nordestgaard, BG, Palmieri, L, Price, JF, Ridker, PM, Sun, Q, Rosengren, A, Roussel, R, Sakurai, M, Salomaa, V, Schöttker, B, Shaw, JE, Strandberg, TE, Sundström, J, Tolonen, H, Tverdal, A, Verschuren, WMM, Völzke, H, Wagenknecht, L, Wallace, RB, Wannamethee, SG, Wareham, NJ, Wassertheil-Smoller, S, Yamagishi, K, Yeap, BB, Harrison, S, Inouye, M, Griffin, S, Butterworth, AS, Wood, AM, Thompson, SG, Sattar, N, Danesh, J, Di Angelantonio, E, Tipping, RW, Russell, S, Johansen, M, Bancks, MP, Mongraw-Chaffin, M, Magliano, D, Barr, ELM, Zimmet, PZ, Whincup, PH, Willeit, J, Leitner, C, Lawlor, DA, Elwood, P, Sutherland, SE, Hunt, KJ, Selmer, RM, Haheim, LL, Ariansen, I, Tybjaer-Hansen, A, Frikkle-Schmidt, R, Langsted, A, Lo Noce, C, Balkau, B, Bonnet, F, Fumeron, F, Pablos, DL, Ferro, CR, Morales, TG, Mclachlan, S, Guralnik, J, Khaw, KT, Holleczek, B, Stocker, H, Nissinen, A, Vartiainen, E, Jousilahti, P, Harald, K, Massaro, JM, Pencina, M, Lyass, A, Susa, S, Oizumi, T, Kayama, T, Chetrit, A, Roth, J, Orenstein, L, Welin, L, Svärdsudd, K, Lissner, L, Hange, D, Mehlig, K, Tilvis, RS, Dennison, E, Westbury, L, Norman, PE, Almeida, OP, Hankey, GJ, Hata, J, Shibata, M, Furuta, Y, Bom, MT, Rutters, F, Muilwijk, M, Kraft, P, Lindstrom, S, Turman, C, Kiyama, M, Kitamura, A, Gerber, Y, Salonen, JT, van Schoor, LN, van Zutphen, EM, Melander, O, Psaty, BM, Blaha, M, de Boer, IH, Kronmal, RA, Grandits, G, Shin, H-C, Albertorio, JR, Gillum, RF, Hu, FB, Humphries, S, Hill- Briggs, F, Vrany, E, Butler, M, Schwartz, JE, Iso, H, Amouyel, P, Arveiler, D, Ferrieres, J, Gansevoort, RT, de Boer, R, Kieneker, L, Trompet, S, Kearney, P, Cantin, B, Després, JP, Lamarche, B, Laughlin, G, McEvoy, L, Aspelund, T, Thorsson, B, Sigurdsson, G, Tilly, M, Ikram, MA, Dorr, M, Schipf, S, Fretts, AM, Umans, JG, Ali, T, Shara, N, Davey-Smith, G, Can, G, Yüksel, H, Özkan, U, Nakagawa, H, Morikawa, Y, Ishizaki, M, Njølstad, I, Wilsgaard, T, Mathiesen, E, Buring, J, Cook, N, Arndt, V, Rothenbacher, D, Manson, J, Tinker, L, Shipley, M, Tabak, AG, Kivimaki, M, Packard, C, Robertson, M, Feskens, E, and Geleijnse, M

Published
2023
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3. Major lipids, apolipoproteins, and risk of vascular disease

Author

Emerging Risk Factors Collaboration, Di Angelantonio E, Sarwar N, Perry P, Kaptoge S, Ray KK, Thompson A, Wood AM, Lewington S, Sattar N, Packard CJ, Collins R, Thompson SG, Tipping RW, Ford CE, Pressel SL, Walldius G, Jungner I, Folsom AR, Chambless LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Goldbourt U, Benderly M, Tanne D, Whincup PH, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Santer P, Mayr A, Wald N, Ebrahim S, Lawlor DA, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Psaty BM, Tracy RP, Tybjaerg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Smith FB, Taylor J, Guralnik JM, Phillips CL, Wallace R, Guralnik J, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Rodriguez B, Dekker JM, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Deeg DJ, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engstrom G, Verschuren WM, Blokstra A, Döring A, Koenig W, Meisinger C, Mraz W, Verschure WM, Bas Bueno de Mesquita H, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson J, Knottenbelt C, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Ford I, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe GD, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Lind L, Giedraitis V, Lannfelt L, Gaziano JM, Stampfer M, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Marmot M, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Cobbe SM, Robertson M, He Y, Marin Ibañez A, Feskens EJ, Kromhout D, Walker M, Watson S, Erqou S, Orfei L, Pennells L, Perry PL, Alexander M, Wensley F, White IR, Danesh J., PANICO, SALVATORE, Developmental Genetics, EMGO+ - Lifestyle, Overweight and Diabetes, Epidemiology and Data Science, General practice, Psychiatry, EMGO - Lifestyle, overweight and diabetes, Emerging Risk Factors, Collaboration, Di Angelantonio, E, Sarwar, N, Perry, P, Kaptoge, S, Ray, Kk, Thompson, A, Wood, Am, Lewington, S, Sattar, N, Packard, Cj, Collins, R, Thompson, Sg, Tipping, Rw, Ford, Ce, Pressel, Sl, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Goldbourt, U, Benderly, M, Tanne, D, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, R, Guralnik, J, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Rodriguez, B, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engstrom, G, Verschuren, Wm, Blokstra, A, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Verschure, Wm, Bas Bueno de Mesquita, H, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, Knottenbelt, C, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Ford, I, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Lind, L, Giedraitis, V, Lannfelt, L, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Marmot, M, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Robertson, M, He, Y, Marin Ibañez, A, Feskens, Ej, Kromhout, D, Walker, M, Watson, S, Erqou, S, Orfei, L, Pennells, L, Perry, Pl, Alexander, M, Wensley, F, White, Ir, and Danesh, J.

Subjects
medicine.medical_specialty, Apolipoprotein B, biology, Triglyceride, business.industry, Vascular disease, Cholesterol, Proportional hazards model, Hazard ratio, Context (language use), General Medicine, 11 Medical And Health Sciences, medicine.disease, Gastroenterology, Article, chemistry.chemical_compound, Endocrinology, chemistry, Internal medicine, General & Internal Medicine, biology.protein, Medicine, lipids (amino acids, peptides, and proteins), Myocardial infarction, business
Abstract

Udgivelsesdato: 2009-Nov-11 CONTEXT: Associations of major lipids and apolipoproteins with the risk of vascular disease have not been reliably quantified. OBJECTIVE: To assess major lipids and apolipoproteins in vascular risk. DESIGN, SETTING, AND PARTICIPANTS: Individual records were supplied on 302,430 people without initial vascular disease from 68 long-term prospective studies, mostly in Europe and North America. During 2.79 million person-years of follow-up, there were 8857 nonfatal myocardial infarctions, 3928 coronary heart disease [CHD] deaths, 2534 ischemic strokes, 513 hemorrhagic strokes, and 2536 unclassified strokes. MAIN OUTCOME MEASURES: Hazard ratios (HRs), adjusted for several conventional factors, were calculated for 1-SD higher values: 0.52 log(e) triglyceride, 15 mg/dL high-density lipoprotein cholesterol (HDL-C), 43 mg/dL non-HDL-C, 29 mg/dL apolipoprotein AI, 29 mg/dL apolipoprotein B, and 33 mg/dL directly measured low-density lipoprotein cholesterol (LDL-C). Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. RESULTS: The rates of CHD per 1000 person-years in the bottom and top thirds of baseline lipid distributions, respectively, were 2.6 and 6.2 with triglyceride, 6.4 and 2.4 with HDL-C, and 2.3 and 6.7 with non-HDL-C. Adjusted HRs for CHD were 0.99 (95% CI, 0.94-1.05) with triglyceride, 0.78 (95% CI, 0.74-0.82) with HDL-C, and 1.50 (95% CI, 1.39-1.61) with non-HDL-C. Hazard ratios were at least as strong in participants who did not fast as in those who did. The HR for CHD was 0.35 (95% CI, 0.30-0.42) with a combination of 80 mg/dL lower non-HDL-C and 15 mg/dL higher HDL-C. For the subset with apolipoproteins or directly measured LDL-C, HRs were 1.50 (95% CI, 1.38-1.62) with the ratio non-HDL-C/HDL-C, 1.49 (95% CI, 1.39-1.60) with the ratio apo B/apo AI, 1.42 (95% CI, 1.06-1.91) with non-HDL-C, and 1.38 (95% CI, 1.09-1.73) with directly measured LDL-C. Hazard ratios for ischemic stroke were 1.02 (95% CI, 0.94-1.11) with triglyceride, 0.93 (95% CI, 0.84-1.02) with HDL-C, and 1.12 (95% CI, 1.04-1.20) with non-HDL-C. CONCLUSION: Lipid assessment in vascular disease can be simplified by measurement of either total and HDL cholesterol levels or apolipoproteins without the need to fast and without regard to triglyceride.

Published
2016

4. Collaborative meta-analysis of prospective studies of plasma fibrinogen and cardiovascular disease

Author

Kostis, JB, Wilson, AC, Folsom, AR, Chambless, L, Wu, K, Benderly, M, Goldbourt, U, Willeit, J, Kiechl, S, Yarnell, JWG, Sweetnam, PM, Elwood, PC, Cushman, M, Psaty, BM, Tybjaerg-Hansen, A, Haverkate, F, de Maat, MPM, Thompson, SG, Fowkes, FGR, Lee, AJ, Smith, FB, Salomaa, V, Rasi, V, Vahtera, E, Jousilahti, P, Pekkanen, J, D'Agostino, R, Kannel, WB, Levy, D, Wilson, PWF, Arocha-Pinango, CL, Rodriguez-Larralde, A, Nagy, E, Mijares, M, Espinosa, R, Roa, E, Ryder, E, Diez-Ewald, MP, Campos, G, Fernandez, V, Torres, E, Marchioli, R, Valagussa, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Cremer, P, Nagel, D, Curb, JD, Rodriguez, B, Yano, K, Salonen, JT, Nyyssonen, K, Tuomainen, TP, Hedblad, B, Lind, P, Loewel, H, Hense, HW, Koenig, W, Meade, TW, Cooper, JA, De Stavola, B, Garrow, K, Knottenbelt, C, Miller, GJ, Bauer, KA, Rosenberg, RD, Sato, S, Kitamura, A, Naito, Y, Iso, H, Palosuo, T, Ducimetiere, P, Amouyel, P, Arveiler, D, Evans, AE, Ferrieres, J, Juhan-Vague, I, Schulte, H, Assmann, G, Cantin, B, Lamarche, B, Despres, JP, Dagenais, GR, Tunstall-Pedoe, H, Lowe, GDO, Collins, R, Danesh, J, Dickinson, A, Lewington, S, Memon, A, Thompson, S, Walker, M, Wheeler, J, Ben-Shlomo, Y, Smith, GD, Palmieri, V, Yeh, JL, Rudnicka, A, Brennan, P, Cooper, J, Rodeghiero, F, Tosetto, A, Shepherd, J, Ford, I, Norrie, J, Brunner, E, Shipley, M, Feskens, EJM, Kromhout, D, and Collaboration, FS

Subjects
medicine.medical_specialty, Epidemiology, business.industry, Regression dilution, Confounding, Fibrinogen, Regression analysis, Fibrinogen Measurement, Surgery, Meta-Analysis as Topic, Cardiovascular Diseases, Internal medicine, Meta-analysis, Data Interpretation, Statistical, Medicine, Humans, Prospective Studies, Risk factor, Cooperative Behavior, Cardiology and Cardiovascular Medicine, business, Prospective cohort study, Biomarkers, medicine.drug
Abstract

BACKGROUND: Many long-term studies have reported on associations of plasma fibrinogen concentration with cardiovascular disease, but few have been large enough to provide reliable estimates in different circumstances. Moreover, most published prospective studies have related disease risk only to baseline values of plasma fibrinogen (which can lead to substantial underestimation of any risk relationships) and have corrected only for baseline values of possible confounding factors (which can lead to residual biases). OBJECTIVES: By appropriate combination of data from individual participants from all relevant prospective studies in a systematic 'meta-analysis', with correction for regression dilution, the Fibrinogen Studies Collaboration will aim to characterize more precisely than has previously been possible the strength and shape of the age- and sex-specific associations of plasma fibrinogen with coronary heart disease (and, where data are sufficient, with other vascular diseases). It will also help to determine to what extent such associations are independent of possible confounding factors. METHODS: A central database has been established containing data on plasma fibrinogen, sex and other potential confounding factors, age at baseline fibrinogen measurement, age at event or at last follow-up, major vascular morbidity and cause-specific mortality. Information about any repeat measurements of fibrinogen and potential confounding factors is being sought to allow study-specific correction for regression dilution. The analyses will involve age-specific regression models. Synthesis of the available prospective studies of plasma fibrinogen will yield information on more than 10000 incident cardiovascular deaths and events among the approximately 200000 total participants who have been monitored, on average, for about 10 years.

Published
2016

5. Glycated hemoglobin measurement and prediction of cardiovascular disease

Author

Emerging Risk Factors Collaboration, Di Angelantonio E, Gao P, Khan H, Butterworth AS, Wormser D, Kaptoge S, Kondapally Seshasai SR, Thompson A, Sarwar N, Willeit P, Ridker PM, Barr EL, Khaw KT, Psaty BM, Brenner H, Balkau B, Dekker JM, Lawlor DA, Daimon M, Willeit J, Njølstad I, Nissinen A, Brunner EJ, Kuller LH, Price JF, Sundström J, Knuiman MW, Feskens EJ, Verschuren WM, Wald N, Bakker SJ, Whincup PH, Ford I, Goldbourt U, Gómez de la Cámara A, Gallacher J, Simons LA, Rosengren A, Sutherland SE, Björkelund C, Blazer DG, Wassertheil Smoller S, Onat A, Marín Ibañez A, Casiglia E, Jukema JW, Simpson LM, Giampaoli S, Nordestgaard BG, Selmer R, Wennberg P, Kauhanen J, Salonen JT, Dankner R, Barrett Connor E, Kavousi M, Gudnason V, Evans D, Wallace RB, Cushman M, D'Agostino RB Sr, Umans JG, Kiyohara Y, Nakagawa H, Sato S, Gillum RF, Folsom AR, van der Schouw YT, Moons KG, Griffin SJ, Sattar N, Wareham NJ, Selvin E, Thompson SG, Danesh J. Collaborators Simpson LM, Coresh J, Wagenknecht L, Shaw JE, Zimmet PZ, Magliano D, Wannamethee SG, Morris RW, Kiechl S, Santer P, Bonora E, Casas JP, Ebrahim S, Ben Shlomo Y, Yarnell JW, Elwood P, Bachman DL, Nietert PJ, Håheim LL, Søgaard AJ, Tybjaerg Hansen A, Frikke Schmidt R, Benn M, Palmieri L, Vanuzzo D, Bonnet F, Copin N, Roussel R, Gómez Gerique JA, Rubio Herrera MA, Gutiérrez Fuentes JA, Friedlander Y, McCallum J, Simons J, Lee AJ, McLachlan S, Taylor JO, Guralnik JM, Phillips CL, Evans DA, Kohout F, Cohen H, George L, Fillenbaum G, McGloin JM, Khaw K., Schöttker B, Müller H, Rothenbacher D, Jansson J., Hallmans G, Tuomilehto J, Donfrancesco C, Woodward M, Oizumi T, Kayama T, Kato T, Danker R, Chetrit A, Wilhelmsen L, Eriksson H, Lappas G, Bengtsson C, Lissner L, Skoog I, Cremer P, Arima H, Ninomiya T, Hata J, Nijpels G, Stehouwer CD, Tuomainen T., Voutilainen S, Kurl S, de Boer IH, Bertoni AG, Veschuren WM, Dullaart RP, Lambers Heerspink HJ, Hilege HL, Trompet S, Stott DJ, Dagenais GR, Cantin B, Dehghan D, Hofman A, Franco OH, Tunstall Pedoe H, Lee E, Best L, Howard BV, Can G, Ademoğlu E, Sakurai M, Nakamura K, Morikawa Y, Løchen M., Mathiesen EB, Wilsgaard T, Byberg L, Cederholm T, Olsson E, Pradhan AD, Cook NR, Kromhout D, Walker M, Watson S, Burgess S, Gregson J, Harshfield E, Pennells L, Spackman S, Warnakula S, Wood AM, Danesh J., PANICO, SALVATORE, Emerging Risk Factors, Collaboration, Di Angelantonio, E, Gao, P, Khan, H, Butterworth, A, Wormser, D, Kaptoge, S, Kondapally Seshasai, Sr, Thompson, A, Sarwar, N, Willeit, P, Ridker, Pm, Barr, El, Khaw, Kt, Psaty, Bm, Brenner, H, Balkau, B, Dekker, Jm, Lawlor, Da, Daimon, M, Willeit, J, Njølstad, I, Nissinen, A, Brunner, Ej, Kuller, Lh, Price, Jf, Sundström, J, Knuiman, Mw, Feskens, Ej, Verschuren, Wm, Wald, N, Bakker, Sj, Whincup, Ph, Ford, I, Goldbourt, U, Gómez de la Cámara, A, Gallacher, J, Simons, La, Rosengren, A, Sutherland, Se, Björkelund, C, Blazer, Dg, Wassertheil Smoller, S, Onat, A, Marín Ibañez, A, Casiglia, E, Jukema, Jw, Simpson, Lm, Giampaoli, S, Nordestgaard, Bg, Selmer, R, Wennberg, P, Kauhanen, J, Salonen, Jt, Dankner, R, Barrett Connor, E, Kavousi, M, Gudnason, V, Evans, D, Wallace, Rb, Cushman, M, D'Agostino RB, Sr, Umans, Jg, Kiyohara, Y, Nakagawa, H, Sato, S, Gillum, Rf, Folsom, Ar, van der Schouw, Yt, Moons, Kg, Griffin, Sj, Sattar, N, Wareham, Nj, Selvin, E, Thompson, Sg, Danesh J., Collaborators Simpson LM, Coresh, J, Wagenknecht, L, Shaw, Je, Zimmet, Pz, Magliano, D, Wannamethee, Sg, Morris, Rw, Kiechl, S, Santer, P, Bonora, E, Casas, Jp, Ebrahim, S, Ben Shlomo, Y, Yarnell, Jw, Elwood, P, Bachman, Dl, Nietert, Pj, Håheim, Ll, Søgaard, Aj, Tybjaerg Hansen, A, Frikke Schmidt, R, Benn, M, Palmieri, L, Vanuzzo, D, Panico, Salvatore, Bonnet, F, Copin, N, Roussel, R, Gómez Gerique, Ja, Rubio Herrera, Ma, Gutiérrez Fuentes, Ja, Friedlander, Y, Mccallum, J, Simons, J, Lee, Aj, Mclachlan, S, Taylor, Jo, Guralnik, Jm, Phillips, Cl, Evans, Da, Kohout, F, Cohen, H, George, L, Fillenbaum, G, Mcgloin, Jm, Khaw, K., Schöttker, B, Müller, H, Rothenbacher, D, Jansson, J., Hallmans, G, Tuomilehto, J, Donfrancesco, C, Woodward, M, Oizumi, T, Kayama, T, Kato, T, Danker, R, Chetrit, A, Wilhelmsen, L, Eriksson, H, Lappas, G, Bengtsson, C, Lissner, L, Skoog, I, Cremer, P, Arima, H, Ninomiya, T, Hata, J, Nijpels, G, Stehouwer, Cd, Tuomainen, T., Voutilainen, S, Kurl, S, de Boer, Ih, Bertoni, Ag, Veschuren, Wm, Dullaart, Rp, Lambers Heerspink, Hj, Hilege, Hl, Trompet, S, Stott, Dj, Dagenais, Gr, Cantin, B, Dehghan, D, Hofman, A, Franco, Oh, Tunstall Pedoe, H, Lee, E, Best, L, Howard, Bv, Can, G, Ademoğlu, E, Sakurai, M, Nakamura, K, Morikawa, Y, Løchen, M., Mathiesen, Eb, Wilsgaard, T, Byberg, L, Cederholm, T, Olsson, E, Pradhan, Ad, Cook, Nr, Kromhout, D, Walker, M, Watson, S, Burgess, S, Gregson, J, Harshfield, E, Pennells, L, Spackman, S, Warnakula, S, Wood, Am, and Danesh, J.

Published
2014

6. Plasma fibrinogen level and the risk of major cardiovascular diseases and nonvascular mortality : an individual participant Metaanalysis

Author

Danesh, J, Lewington, S, Thompson, SG, Lowe, GD, Collins, R, Kostis, JB, Wilson, AC, Folsom, AR, Wu, K, Benderly, M, Goldbourt, U, Willeit, J, Kiechl, S, Yarnell, JW, Sweetnam, PM, Elwood, PC, Cushman, M, Psaty, BM, Tracy, RP, Tybjaerg-Hansen, A, Haverkate, F, de Maat, MP, Fowkes, FG, Lee, AJ, Smith, FB, Salomaa, V, Harald, K, Rasi, R, Vahtera, E, Jousilahti, P, Pekkanen, J, D'Agostino, R, Kannel, WB, Wilson, PW, Tofler, G, Arocha-Piñango, CL, Rodriguez-Larralde, A, Nagy, E, Mijares, M, Espinosa, R, Rodriquez-Roa, E, Ryder, E, Diez-Ewald, MP, Campos, G, Fernandez, V, Torres, E, Marchioli, R, Valagussa, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Cremer, P, Nagel, D, Curb, JD, Rodriguez, B, Yano, K, Salonen, JT, Nyyssönen, K, Tuomainen, TP, Hedblad, B, Lind, P, Loewel, H, Koenig, W, Meade, TW, Cooper, JA, De Stavola, B, Knottenbelt, C, Miller, GJ, Bauer, KA, Rosenberg, RD, Sato, S, Kitamura, A, Naito, Y, Palosuo, T, Ducimetiere, P, Amouyel, P, Arveiler, D, Evans, AE, Ferrieres, J, Juhan-Vague, I, Bingham, A, Schulte, H, Assmann, G, Cantin, B, Lamarche, B, Després, JP, Dagenais, GR, Tunstall-Pedoe, H, Woodward, M, Ben-Shlomo, Y, Davey Smith, G, Palmieri, V, Yeh, JL, Rudnicka, A, Ridker, P, Rodeghiero, F, Tosetto, A, Shepherd, J, Ford, I, Robertson, M, Brunner, E, Shipley, M, Feskens, EJ, Kromhout, D, Dickinson, A, Ireland, B, Juzwishin, K, Kaptoge, S, Memon, A, Sarwar, N, Walker, M, Wheeler, J, White, I, and Wood, A

Subjects
Adult, Risk, medicine.medical_specialty, base-line findings, blood-viscosity, Nutrition and Disease, Regression dilution, Blood viscosity, Myocardial Infarction, Context (language use), Coronary Disease, c-reactive protein, edinburgh artery, Internal medicine, Cause of Death, Voeding en Ziekte, medicine, follow-up, Humans, Vascular Diseases, Stroke, Aged, Proportional Hazards Models, VLAG, hemostatic factors, business.industry, Proportional hazards model, Confounding, Hazard ratio, Fibrinogen, General Medicine, Middle Aged, medicine.disease, myocardial-infarction, Surgery, relative risk, Relative risk, factor-vii, business, coronary-heart-disease
Abstract

CONTEXT: Plasma fibrinogen levels may be associated with the risk of coronary heart disease (CHD) and stroke. OBJECTIVE: To assess the relationships of fibrinogen levels with risk of major vascular and with risk of nonvascular outcomes based on individual participant data. DATA SOURCES: Relevant studies were identified by computer-assisted searches, hand searches of reference lists, and personal communication with relevant investigators. STUDY SELECTION: All identified prospective studies were included with information available on baseline fibrinogen levels and details of subsequent major vascular morbidity and/or cause-specific mortality during at least 1 year of follow-up. Studies were excluded if they recruited participants on the basis of having had a previous history of cardiovascular disease; participants with known preexisting CHD or stroke were excluded. DATA EXTRACTION: Individual records were provided on each of 154,211 participants in 31 prospective studies. During 1.38 million person-years of follow-up, there were 6944 first nonfatal myocardial infarctions or stroke events and 13,210 deaths. Cause-specific mortality was generally available. Analyses involved proportional hazards modeling with adjustment for confounding by known cardiovascular risk factors and for regression dilution bias. DATA SYNTHESIS: Within each age group considered (40-59, 60-69, and > or =70 years), there was an approximately log-linear association with usual fibrinogen level for the risk of any CHD, any stroke, other vascular (eg, non-CHD, nonstroke) mortality, and nonvascular mortality. There was no evidence of a threshold within the range of usual fibrinogen level studied at any age. The age- and sex- adjusted hazard ratio per 1-g/L increase in usual fibrinogen level for CHD was 2.42 (95% confidence interval [CI], 2.24-2.60); stroke, 2.06 (95% CI, 1.83-2.33); other vascular mortality, 2.76 (95% CI, 2.28-3.35); and nonvascular mortality, 2.03 (95% CI, 1.90-2.18). The hazard ratios for CHD and stroke were reduced to about 1.8 after further adjustment for measured values of several established vascular risk factors. In a subset of 7011 participants with available C-reactive protein values, the findings for CHD were essentially unchanged following additional adjustment for C-reactive protein. The associations of fibrinogen level with CHD or stroke did not differ substantially according to sex, smoking, blood pressure, blood lipid levels, or several features of study design. CONCLUSIONS: In this large individual participant meta-analysis, moderately strong associations were found between usual plasma fibrinogen level and the risks of CHD, stroke, other vascular mortality, and nonvascular mortality in a wide range of circumstances in healthy middle-aged adults. Assessment of any causal relevance of elevated fibrinogen levels to disease requires additional research.

Published
2005

7. C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis

Author

Emerging Risk Factors Collaboration, Kaptoge S, Di Angelantonio E, Lowe G, Pepys MB, Thompson SG, Collins R, Danesh JTipping RW, Ford CE, Pressel SL, Walldius G, Jungner I, Folsom AR, Chambless L, Ballantyne CM, Panagiotakos D, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman MW, Goldbourt U, Benderly M, Tanne D, Whincup P, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Mayr A, Schett G, Wald N, Ebrahim S, Lawlor D, Yarnell J, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Psaty BM, Tracy R, Tybjaerg Hansen A, Nordestgaard BG, Zacho J, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, de la Cámara AG, Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee A, Taylor J, Guralnik JM, Phillips CL, Wallace RB, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Benjamin EJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Kiyohara Y, Arima H, Doi Y, Ninomiya T, Rodriguez B, Dekker J, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Laukkanen JA, Deeg DJ, Bremmer MA, Meade TW, Cooper JA, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Shea S, Döring A, Koenig W, Meisinger C, Bueno de Mesquita HB, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum RF, Mussolino M, Hankinson S, Manson JE, Knottenbelt C, Bauer KA, Davidson K, Kirkland S, Shaffer J, Korin MR, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Luc G, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Packard CJ, Sattar N, Westendorp RG, Buckley BM, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt RR, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler MM, Hofman A, Tunstall Pedoe H, Tavendale R, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Basu S, Cederholm T, Byberg L, Gaziano JM, Stampfer M, Ridker PM, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Wassertheil Smoller S, Marmot IM, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Shepherd J, Cobbe S, Ford I, Robertson M, He Y, Ibañez AM, Feskens EJ, Walker M, Watson S, Erqou S, Lewington S, Pennells L, Perry PL, Ray KK, Sarwar N, Alexander M, Thompson A, White IR, Wood AM, Danesh J., PANICO, SALVATORE, Interne Geneeskunde, MUMC+: MA Interne Geneeskunde (3), RS: CARIM School for Cardiovascular Diseases, General practice, EMGO - Lifestyle, overweight and diabetes, Psychiatry, EMGO - Mental health, Emerging Risk Factors, Collaboration, Kaptoge, S, Di Angelantonio, E, Lowe, G, Pepys, Mb, Thompson, Sg, Collins, R, Danesh JTipping, Rw, Ford, Ce, Pressel, Sl, Walldius, G, Jungner, I, Folsom, Ar, Chambless, L, Ballantyne, Cm, Panagiotakos, D, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, Mw, Goldbourt, U, Benderly, M, Tanne, D, Whincup, P, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Mayr, A, Schett, G, Wald, N, Ebrahim, S, Lawlor, D, Yarnell, J, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, R, Tybjaerg Hansen, A, Nordestgaard, Bg, Zacho, J, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, de la Cámara, Ag, Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, A, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, Rb, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Benjamin, Ej, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, J, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Laukkanen, Ja, Deeg, Dj, Bremmer, Ma, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Shea, S, Döring, A, Koenig, W, Meisinger, C, Bueno de Mesquita, Hb, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, Rf, Mussolino, M, Hankinson, S, Manson, Je, Knottenbelt, C, Bauer, Ka, Davidson, K, Kirkland, S, Shaffer, J, Korin, Mr, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Luc, G, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Packard, Cj, Sattar, N, Westendorp, Rg, Buckley, Bm, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, Rr, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, Mm, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Basu, S, Cederholm, T, Byberg, L, Gaziano, Jm, Stampfer, M, Ridker, Pm, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Wassertheil Smoller, S, Marmot, Im, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Shepherd, J, Cobbe, S, Ford, I, Robertson, M, He, Y, Ibañez, Am, Feskens, Ej, Walker, M, Watson, S, Erqou, S, Lewington, S, Pennells, L, Perry, Pl, Ray, Kk, Sarwar, N, Alexander, M, Thompson, A, White, Ir, Wood, Am, and Danesh, J.

Subjects
Lung Diseases, Male, Databases, Factual, Plasma-fibrinogen, Blood Pressure, Coronary Disease, 030204 cardiovascular system & hematology, Associations, Body Mass Index, Low-density-lipoprotein, Leukocyte Count, 0302 clinical medicine, Risk Factors, Neoplasms, 030212 general & internal medicine, Stroke, Framingham Risk Score, biology, Smoking, 11 Medical And Health Sciences, General Medicine, Articles, Middle Aged, 3. Good health, C-Reactive Protein, Cholesterol, Regression Analysis, low-density lipoprotein cardiovascular-disease nonvascular mortality regression dilution plasma-fibrinogen mendelian randomization independent predictor prospective cohorts vascular-disease inflammation, Female, Risk assessment, medicine.medical_specialty, Alcohol Drinking, Regression dilution, Motor Activity, Risk Assessment, 03 medical and health sciences, Sex Factors, Cardiovascular-disease, General & Internal Medicine, Internal medicine, Diabetes Mellitus, medicine, Humans, Women, Risk factor, Serum Albumin, Triglycerides, Inflammation, Markers, Independent predictor, Interleukin-6, business.industry, Vascular disease, C-reactive protein, Fibrinogen, medicine.disease, Surgery, Relative risk, biology.protein, Nonvascular mortality, business, Biomarkers
Abstract

Udgivelsesdato: 2010-Jan-9 BACKGROUND: Associations of C-reactive protein (CRP) concentration with risk of major diseases can best be assessed by long-term prospective follow-up of large numbers of people. We assessed the associations of CRP concentration with risk of vascular and non-vascular outcomes under different circumstances. METHODS: We meta-analysed individual records of 160 309 people without a history of vascular disease (ie, 1.31 million person-years at risk, 27 769 fatal or non-fatal disease outcomes) from 54 long-term prospective studies. Within-study regression analyses were adjusted for within-person variation in risk factor levels. RESULTS: Log(e) CRP concentration was linearly associated with several conventional risk factors and inflammatory markers, and nearly log-linearly with the risk of ischaemic vascular disease and non-vascular mortality. Risk ratios (RRs) for coronary heart disease per 1-SD higher log(e) CRP concentration (three-fold higher) were 1.63 (95% CI 1.51-1.76) when initially adjusted for age and sex only, and 1.37 (1.27-1.48) when adjusted further for conventional risk factors; 1.44 (1.32-1.57) and 1.27 (1.15-1.40) for ischaemic stroke; 1.71 (1.53-1.91) and 1.55 (1.37-1.76) for vascular mortality; and 1.55 (1.41-1.69) and 1.54 (1.40-1.68) for non-vascular mortality. RRs were largely unchanged after exclusion of smokers or initial follow-up. After further adjustment for fibrinogen, the corresponding RRs were 1.23 (1.07-1.42) for coronary heart disease; 1.32 (1.18-1.49) for ischaemic stroke; 1.34 (1.18-1.52) for vascular mortality; and 1.34 (1.20-1.50) for non-vascular mortality. INTERPRETATION: CRP concentration has continuous associations with the risk of coronary heart disease, ischaemic stroke, vascular mortality, and death from several cancers and lung disease that are each of broadly similar size. The relevance of CRP to such a range of disorders is unclear. Associations with ischaemic vascular disease depend considerably on conventional risk factors and other markers of inflammation. FUNDING: British Heart Foundation, UK Medical Research Council, BUPA Foundation, and GlaxoSmithKline.

Published
2010

8. Emerging Risk Factors Collaboration. Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies

Author

hompson S, Kaptoge S, White I, Wood A, Thompson SG, White IR, Wood AM, Perry PL, Danesh J, Tipping RW, Ford CE, Simpson LM, Walldius G, Jungner I, Chambless LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Goldbourt U, Benderly M, Tanne D, Whincup PH, Wannamethee SG, Morris RW, Willeit J, Kiechl S, Santer P, Mayr A, Lawlor DA, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Tracy RP, Tybjærg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Taylor J, Guralnik JM, Wallace R, Guralnik J, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Lappas G, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Kiyohara Y, Arima H, Doi Y, Ninomiya T, Rodriguez B, Dekker JM, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Tuomainen TP, Deeg DJ, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engstrom G, Verschuren WM, Blokstra A, Shea S, Döring A, Koenig W, Meisinger C, Mraz W, Bas Bueno de Mesquita H, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson JE, Knottenbelt C, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Crespo CJ, Garcia MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Packard CJ, Sattar N, Ford I, Cantin B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe GD, Ben Shlomo Y, Davey Smith G, Howard BV, Zhang Y, Umans J, Onat A, Wilsgaard T, Ingelsson E, Lind L, Giedraitis V, Lannfelt L, Gaziano JM, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Wassertheil Smoller S, Marmot M, Clarke R, Collins R, Brunner E, Shipley M, Buring J, Cobbe SM, Robertson M, He Y, Marín Ibañez A, Feskens EJ, Kromhout D, Di Angelantonio E, Erqou S, Lewington S, Orfei L, Pennells L, Ray KK, Sarwar N, Alexander M, Thompson A, Walker M, Watson S, Wensley F, Perry P, Danesh J., PANICO, SALVATORE, Hompson, S, Kaptoge, S, White, I, Wood, A, Thompson, Sg, White, Ir, Wood, Am, Perry, Pl, Danesh, J, Tipping, Rw, Ford, Ce, Simpson, Lm, Walldius, G, Jungner, I, Chambless, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Goldbourt, U, Benderly, M, Tanne, D, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Tracy, Rp, Tybjærg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Taylor, J, Guralnik, Jm, Wallace, R, Guralnik, J, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Lappas, G, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engstrom, G, Verschuren, Wm, Blokstra, A, Shea, S, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bas Bueno de Mesquita, H, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, Je, Knottenbelt, C, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Crespo, Cj, Garcia, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, Cj, Sattar, N, Ford, I, Cantin, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Ben Shlomo, Y, Davey Smith, G, Howard, Bv, Zhang, Y, Umans, J, Onat, A, Wilsgaard, T, Ingelsson, E, Lind, L, Giedraitis, V, Lannfelt, L, Gaziano, Jm, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Wassertheil Smoller, S, Marmot, M, Clarke, R, Collins, R, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Robertson, M, He, Y, Marín Ibañez, A, Feskens, Ej, Kromhout, D, Di Angelantonio, E, Erqou, S, Lewington, S, Orfei, L, Pennells, L, Ray, Kk, Sarwar, N, Alexander, M, Thompson, A, Walker, M, Watson, S, Wensley, F, Perry, P, and Danesh, J.

Published
2010

9. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality

Author

Emerging Risk Factors Collaboration, Erqou S, Kaptoge S, Perry PL, Di Angelantonio E, Thompson A, White IR, Marcovina SM, Collins R, Thompson SG, Tipping RW, Ford CE, Simpson LM, Walldius G, Jungner I, Folsom AR, Chambless L, Panagiotakos D, Pitsavos C, Chrysohoou C, Stefanadis C, Goldbourt U, Benderly M, Tanne D, Whincup P, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Santer P, Mayr A, Wald N, Ebrahim S, Lawlor D, Yarnell J, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Cushman M, Psaty BM, Tracy R, Tybjaerg Hansen A, Nordestgaard BG, Frikke Schmidt R, Kamstrup PR, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee A, Smith FB, Taylor J, Guralnik JM, Phillips CL, Wallace RB, Blazer DG, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Rodriguez B, Dekker J, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Deeg DJ, Poppelaars JL, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Döring A, Koenig W, Meisinger C, Mraz W, Bueno de Mesquita HB, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum RF, Mussolino M, Hankinson S, Manson JE, Cooper JA, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Luc G, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Packard CJ, Sattar N, Ford I, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Daniels LB, Laughlin GA, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler MM, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe G, Ben Shlomo Y, Davey Smith G, Howard BV, Zhang Y, Best L, Umans J, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Sundström J, Lind L, Lannfelt L, Gaziano JM, Stampfer M, Ridker PM, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Marmot M, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Cobbe S, Robertson M, He Y, Marin Ibanñez A, Feskens E, Kromhout D, Walker M, Watson S, Lewington S, Orfei L, Pennells L, Ray KK, Sarwar N, Alexander M, Wensley F, Wood AM, Danesh J., PANICO, SALVATORE, Developmental Genetics, EMGO+ - Lifestyle, Overweight and Diabetes, Emerging Risk Factors, Collaboration, Erqou, S, Kaptoge, S, Perry, Pl, Di Angelantonio, E, Thompson, A, White, Ir, Marcovina, Sm, Collins, R, Thompson, Sg, Tipping, Rw, Ford, Ce, Simpson, Lm, Walldius, G, Jungner, I, Folsom, Ar, Chambless, L, Panagiotakos, D, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Goldbourt, U, Benderly, M, Tanne, D, Whincup, P, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, D, Yarnell, J, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Cushman, M, Psaty, Bm, Tracy, R, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Kamstrup, Pr, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, A, Smith, Fb, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, Rb, Blazer, Dg, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Rodriguez, B, Dekker, J, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bueno de Mesquita, Hb, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, Rf, Mussolino, M, Hankinson, S, Manson, Je, Cooper, Ja, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Luc, G, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, Cj, Sattar, N, Ford, I, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Daniels, Lb, Laughlin, Ga, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, Mm, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, G, Ben Shlomo, Y, Davey Smith, G, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Sundström, J, Lind, L, Lannfelt, L, Gaziano, Jm, Stampfer, M, Ridker, Pm, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Marmot, M, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Cobbe, S, Robertson, M, He, Y, Marin Ibanñez, A, Feskens, E, Kromhout, D, Walker, M, Watson, S, Lewington, S, Orfei, L, Pennells, L, Ray, Kk, Sarwar, N, Alexander, M, Wensley, F, Wood, Am, and Danesh, J.

Subjects
medicine.medical_specialty, Context (language use), Coronary Disease, Article, Risk Factors, General & Internal Medicine, Internal medicine, Cause of Death, medicine, Humans, Myocardial infarction, Prospective cohort study, Stroke, biology, business.industry, 11 Medical And Health Sciences, General Medicine, Lipoprotein(a), medicine.disease, Surgery, Relative risk, Nested case-control study, biology.protein, business, Cohort study
Abstract

Udgivelsesdato: 2009-Jul-22 CONTEXT: Circulating concentration of lipoprotein(a) (Lp[a]), a large glycoprotein attached to a low-density lipoprotein-like particle, may be associated with risk of coronary heart disease (CHD) and stroke. OBJECTIVE: To assess the relationship of Lp(a) concentration with risk of major vascular and nonvascular outcomes. STUDY SELECTION: Long-term prospective studies that recorded Lp(a) concentration and subsequent major vascular morbidity and/or cause-specific mortality published between January 1970 and March 2009 were identified through electronic searches of MEDLINE and other databases, manual searches of reference lists, and discussion with collaborators. DATA EXTRACTION: Individual records were provided for each of 126,634 participants in 36 prospective studies. During 1.3 million person-years of follow-up, 22,076 first-ever fatal or nonfatal vascular disease outcomes or nonvascular deaths were recorded, including 9336 CHD outcomes, 1903 ischemic strokes, 338 hemorrhagic strokes, 751 unclassified strokes, 1091 other vascular deaths, 8114 nonvascular deaths, and 242 deaths of unknown cause. Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. Analyses excluded participants with known preexisting CHD or stroke at baseline. DATA SYNTHESIS: Lipoprotein(a) concentration was weakly correlated with several conventional vascular risk factors and it was highly consistent within individuals over several years. Associations of Lp(a) with CHD risk were broadly continuous in shape. In the 24 cohort studies, the rates of CHD in the top and bottom thirds of baseline Lp(a) distributions, respectively, were 5.6 (95% confidence interval [CI], 5.4-5.9) per 1000 person-years and 4.4 (95% CI, 4.2-4.6) per 1000 person-years. The risk ratio for CHD, adjusted for age and sex only, was 1.16 (95% CI, 1.11-1.22) per 3.5-fold higher usual Lp(a) concentration (ie, per 1 SD), and it was 1.13 (95% CI, 1.09-1.18) following further adjustment for lipids and other conventional risk factors. The corresponding adjusted risk ratios were 1.10 (95% CI, 1.02-1.18) for ischemic stroke, 1.01 (95% CI, 0.98-1.05) for the aggregate of nonvascular mortality, 1.00 (95% CI, 0.97-1.04) for cancer deaths, and 1.00 (95% CI, 0.95-1.06) for nonvascular deaths other than cancer. CONCLUSION: Under a wide range of circumstances, there are continuous, independent, and modest associations of Lp(a) concentration with risk of CHD and stroke that appear exclusive to vascular outcomes.

Published
2009

10. The Emerging Risk Factors Collaboration: analysis of individual data on lipid, inflammatory and other markers in over 1.1 million participants in 104 prospective studies of cardiovascular diseases

Author

Danesh, J, Erqou, S, Walker, M, Thompson, Sg, Tipping, R, Ford, C, Pressel, S, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, Edoardo, Tikhonoff, Valerie, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, S, Vanuzzo, D, Pilotto, L, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, J, Phillips, C, Wallace, R, Blazer, D, Khaw, Kt, Jansson, Jh, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, Rs, Pencina, Mj, Bladbjerg, Em, Jorgensen, T, Moller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Bjorkelund, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, T, Rodriguez, B, Bouter, Lm, Heine, Rj, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, J, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, D, Poppelaars, Jl, Meade, T, Cooper, J, Hedblad, B, Berglund, G, Engstrom, G, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Kuller, L, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, De Stavola, B, Knottenbelt, C, Cooper, Ja, Bauer, Ka, Rosenberg, Rd, Naito, Y, Holme, I, Nakagawa, H, Miura, H, Ducimetiere, P, Jouven, X, Crespo, C, Garcia Palmieri, M, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, C, Sattar, N, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, D, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Ben Shlomo, Y, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Meade, Tw, Njolstad, I, Mathiesen, E, Lochen, Ml, Wilsgaard, T, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Rodeghiero, F, Tosetto, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Ford, I, Robertson, M, He, Y, Ibanez, Am, Feskens, Ej, Kromhout, D, Collins, R, Di Angelantonio, E, Kaptoge, S, Lewington, S, Orfei, L, Pennells, L, Perry, P, Ray, K, Sarwar, N, Scherman, M, Thompson, A, Watson, S, Wensley, F, White, Ir, Wood, Am, Emerging Risk Factors Collaboration, Interne Geneeskunde, RS: NUTRIM School of Nutrition and Translational Research in Metabolism, RS: CARIM School for Cardiovascular Diseases, Movement Behavior, Executive board Vrije Universiteit, Clinical Child and Family Studies, Sociology and Social Gerontology, Earth and Climate, Environmental Policy Analysis, Developmental Genetics, Danesh, J, Erqou, S, Walker, M, Thompson, Sg, Tipping, R, Ford, C, Pressel, S, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, J, Phillips, C, Wallace, R, Blazer, D, Khaw, Kt, Jansson, Jh, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jorgensen, T, Moller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Bjorkelund, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, T, Rodriguez, B, Bouter, Lm, Heine, Rj, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, J, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, D, Poppelaars, Jl, Meade, T, Cooper, J, Hedblad, B, Berglund, G, Engstrom, G, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Kuller, L, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, De Stavola, B, Knottenbelt, C, Cooper, Ja, Bauer, Ka, Rosenberg, Rd, Naito, Y, Holme, I, Nakagawa, H, Miura, H, Ducimetiere, P, Jouven, X, Crespo, C, Garcia Palmieri, M, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, C, Sattar, N, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, D, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Ben Shlomo, Y, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Meade, Tw, Njolstad, I, Mathiesen, E, Lochen, Ml, Wilsgaard, T, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Rodeghiero, F, Tosetto, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Ford, I, Robertson, M, He, Y, Ibanez, Am, Feskens, Ej, Kromhout, D, Collins, R, Di Angelantonio, E, Kaptoge, S, Lewington, S, Orfei, L, Pennells, L, Perry, P, Ray, K, Sarwar, N, Scherman, M, Thompson, A, Watson, S, Wensley, F, White, Ir, and Wood, A. M.

Subjects
Databases, Factual, Nutrition and Disease, Epidemiology, Inflammatory markers, middle-aged men, Disease, Leukocyte Count, c-reactive protein, Risk Factors, Voeding en Ziekte, adult-treatment-panel, Prospective Studies, Myocardial infarction, Prospective cohort study, education.field_of_study, biology, plasma-fibrinogen, Asia, Eastern, Confounding, density-lipoprotein cholesterol, Cardiovascular disease, Lipids, myocardial-infarction, Coronary heart disease, Cardiovascular Diseases, Meta-analysis, Lipoproteins, HDL, high blood cholesterol, medicine.medical_specialty, low-dose aspirin, Population, 10-year follow-up, SDG 3 - Good Health and Well-being, Albumins, medicine, Humans, education, Triglycerides, VLAG, Inflammation, Estimation, business.industry, C-reactive protein, medicine.disease, Surgery, Emergency medicine, biology.protein, business, coronary-heart-disease, Biomarkers
Abstract

Many long-term prospective studies have reported on associations of cardiovascular diseases with circulating lipid markers and/or inflammatory markers. Studies have not, however, generally been designed to provide reliable estimates under different circumstances and to correct for within-person variability. The Emerging Risk Factors Collaboration has established a central database on over 1.1 million participants from 104 prospective population-based studies, in which subsets have information on lipid and inflammatory markers, other characteristics, as well as major cardiovascular morbidity and cause-specific mortality. Information on repeat measurements on relevant characteristics has been collected in approximately 340,000 participants to enable estimation of and correction for within-person variability. Re-analysis of individual data will yield up to approximately 69,000 incident fatal or nonfatal first ever major cardiovascular outcomes recorded during about 11.7 million person years at risk. The primary analyses will involve age-specific regression models in people without known baseline cardiovascular disease in relation to fatal or nonfatal first ever coronary heart disease outcomes. This initiative will characterize more precisely and in greater detail than has previously been possible the shape and strength of the age-and sex-specific associations of several lipid and inflammatory markers with incident coronary heart disease outcomes (and, secondarily,with other incident cardiovascular outcomes) under a wide range of circumstances. It will, therefore, help to determine to what extent such associations are independent from possible confounding factors and to what extent such markers (separately and in combination) provide incremental predictive value.

Published
2007

11. Rationale, design, implementation, and baseline characteristics of patients in the dig trial: A large, simple, long-term trial to evaluate the effect of digitalis on mortality in heart failure

Author

Abernathy, GT, Abrams, J, Akhtar, S, Albitar, I, Amidi, M, Anand, IS, Arnold, JMO, Ashton, T, Aubrey, B, Auger, P, Babb, J, Baigrie, R, Baird, MG, Baitz, T, Barber, NC, Barbour, DJ, Barr, DM, Basu, AK, Baughman, KL, Beckham, V, BekheitSaad, S, Berkson, DM, Bertoglio, M, Bessoudo, R, Beaudoin, J, Bhaskar, G, Binder, A, Bloomfield, D, Bodine, K, Boehmer, JP, Borgersen, K, Borts, D, Bouchard, G, Bourassa, MG, Boutros, G, Bozek, B, Brisbin, D, Brophy, J, Brossoit, R, Brown, E, Brown, J, Bruinsma, N, Burton, G, Cameron, A, Campbell, R, Campeau, J, Campos, EE, Cardello, FP, Carter, RP, Chan, YK, Charles, FR, Chaudhry, MA, Chiaramida, A, Chiaramida, S, Chohan, A, Christie, LG, Clemson, BS, Collin, R, Cook, TH, Copen, DL, Cossett, J, Costantino, T, Crawford, MH, Croke, RP, Crowell, R, DAmours, G, Dagenais, GR, Danisa, K, Davidson, S, Davies, ML, Davies, R, Davies, RA, DeLarochelliere, R, DeLeon, AC, Delage, F, Denes, P, Dennish, GW, Denny, DM, DeVilla, MA, DeYoung, JP, Dhurandhar, RW, DibnerDunlap, M, Dodek, A, Doherty, JE, Dominguez, J, Dubbin, J, Dufton, J, Effron, MB, ElSherif, N, Eladasari, B, Fly, D, Ericson, K, Fahrenholtz, D, Fast, A, Fell, DA, Fishman, S, Fitchett, D, Fleg, JL, Flint, E, Folger, JS, Folkins, D, Forker, AD, Fowles, RE, Fraker, TD, Francis, G, Frerking, TR, Friesinger, GC, Fulop, JC, Gagnon, J, Gamble, L, Ganjavi, F, Garrou, BW, Gervais, PB, Gheorghiade, M, Gilbert, L, Gillie, E, Glatter, TR, Godley, ML, Goeres, M, Goldberger, MH, Gollapudi, A, Goode, JE, Goodman, LS, Gordon, R, Gossard, D, Gosselin, G, Goulet, C, Grant, C, Graettinger, WF, Greene, JG, Greenwood, PV, Gregoratos, G, Gregory, JJ, Groden, DL, Grover, J, Gudapati, R, Guess, MA, Gupta, SC, Habib, N, Hack, I, Hamilton, WP, Hankey, TL, Hanna, M, Harper, D, Harris, DE, Hassapoyannes, CA, Hatheway, RJ, Heinsimer, J, Pequignot, MH, Heiselman, DE, Hess, AR, Hickner, J, Hickey, JE, Higgins, T, Higginson, L, Hill, L, Hobbs, RE, Honos, G, Horner, BA, Horwitz, L, Hsieh, A, Hsueh, JT, Hubbard, J, Hughes, DF, Hui, W, Imrie, JR, Jacobs, MH, Jarmukli, N, Johnson, TH, Johnstone, D, Jutila, CK, Kadri, N, Kahl, FR, Kaimal, PK, Karnegis, J, Kay, R, Kelly, KJ, Kenefick, G, Kennelly, BM, Kent, E, Khan, AH, Khanijo, V, Khouri, M, Kinloch, D, Kirlin, PC, Kiwan, GS, Kline, MD, Kohn, RM, Koilpillai, C, Kornder, JM, Kouz, S, Kumar, VA, Kumar, U, Kuntz, A, Kuritzky, RA, Kuruvilla, G, Kwok, KK, Lader, E, Laforest, M, LaForge, D, Lalonde, G, Lalonde, L, Lang, RM, Latour, Y, Lawal, O, LeBlanc, MH, Lee, AB, Lee, RW, Legault, C, Lemay, M, Lenis, JHF, Lepage, S, Letarte, P, Levesque, C, LevinoffRoth, SN, Lewis, BK, Lipshutz, H, Loungani, RR, Lowery, ML, Lubell, DL, Lucariello, R, LugoRodriguez, JE, Lui, C, Lutterodt, AT, Lutz, L, Machel, T, Macina, G, MacLellan, K, Magnan, O, Mansuri, M, Manyari, DE, Mallis, GI, Marr, D, Mast, DJ, Mathew, J, McBarron, FD, McIntyre, KM, McLean, RW, McMahon, DP, Mercier, M, Methe, M, Miller, AB, Minkowitz, J, Milton, JR, Mizgala, HF, Mohanty, PK, Mohiuddin, S, Montero, A, Mookherjee, S, Morris, A, Morris, L, Morrison, J, Moten, M, Nafziger, A, Nair, PH, Nawaz, S, Neiman, JC, Nutting, P, NguyenPho, HT, OBrien, TK, OKelly, RL, OReilly, MV, Okerson, D, Patel, G, Pande, PN, Papa, LA, Patrick, L, Payne, RM, Perry, G, Philbin, EF, Pierpont, G, Pitt, WA, Poirier, C, Pollak, EM, Popio, K, Poulin, JF, Probst, PA, Pruneau, G, Pu, C, Puram, BS, Putatunda, B, Quinn, B, Rabkin, SW, Racine, N, Raco, DL, Radant, L, Radford, MJ, Radwany, S, Rajachar, M, Ramanathan, KB, Rashkow, A, Rausch, DC, Read, L, Reddy, KR, Reid, R, Rich, MW, Ricci, AJ, Richman, HG, Riley, A, Rim, DA, Rinne, C, Roberge, G, Roberts, DK, Robinson, V, Rodeheffer, RT, Rosenstein, R, Roth, DL, Rothbart, R, Rouleau, JL, Ruble, P, Sacco, J, Safford, RE, Salmon, D, Sahay, BM, Sarma, RJ, Sayeed, MAR, Schick, EC, Schroeder, GS, Seifert, M, Senaratne, MPJ, Sestier, F, Shah, A, Shanes, JG, Sheesley, K, Silverman, A, Shiva, T, Shrestha, DD, Silver, MA, Silverberg, L, Simard, L, Singh, BN, Small, RS, Smith, MR, Smith, S, Sochowski, RA, Southern, RF, Sridharan, MR, StHilaire, R, Stein, M, Stewart, JW, Stillabower, ME, Sullivan, BHM, Sturrock, WA, Sussex, BA, Swan, J, Swenson, L, Talbot, P, Talibi, T, Tamilia, M, Tan, A, Tanser, PH, Tarry, L, Teo, KK, Thadani, U, Thagirisa, S, Thompson, B, Thornton, R, Timmis, GC, Tobin, M, Tommaso, C, Toren, M, Tsuyuki, R, Turek, M, Utley, K, Vanderbush, EJ, VanVoorhees, L, Ventura, H, Vertes, G, Vizel, S, Wagner, KR, Wagner, S, Weeks, A, Weingert, ME, Weinstein, C, Weiss, MM, Weiss, R, Wickemeyer, W, Wielgoz, A, Willens, HJ, Williams, WL, Wong, D, Yarows, SA, Yao, L, Shalev, Y, Young, JB, Yousefian, M, Zajac, EJ, Zatuchni, J, Ziperman, DB, Zoble, RG, Zoneraich, S, Gorlin, R, Sleight, P, Cohn, JN, Collins, R, Deykin, D, Hennekens, C, Kjekshus, J, Smith, TW, Tognoni, G, Collins, JF, Williford, WO, Fye, C, Sather, R, Jolly, MK, Held, CP, Verter, J, Yusuf, S, Egan, D, Garg, R, Johnstone, DE, Montague, T, Bristow, D, Engelhardt, HT, Gent, M, Hood, WB, Jones, S, Meier, P, Pitt, B, Waters, D, Baker, A, Barnhill, S, Carew, B, Hagar, S, Liuni, C, Martin, S, Miles, R, Arthur, MM, Feldbush, MW, Highfield, DA, Hobbins, TE, Kurz, R, Leviton, SP, Libonati, JP, Moore, M, Perez, E, Mills, P, Geller, N, Hunsberger, S, Gold, J, Huang, PC, Burns, A, Caleb, H, Cline, DR, Harris, S, Hockenbrock, R, Horney, RA, Jadwin, LM, King, J, Sexton, P, Spence, ME, Chacon, F, Gagne, W, Maple, S, and Martinez, G

Subjects
Heart Failure, Male, Pharmacology, Digoxin, Treatment Outcome, Patient Selection, Digitalis Glycosides, Humans, Multicenter Studies as Topic, Female, Middle Aged, Aged, Randomized Controlled Trials as Topic
Abstract

This article provides a detailed overview of the rationale for key aspects of the protocol of the Digitalis Investigation Group (DIG) trial. It also highlights unusual aspects of the study implementation and the baseline characteristics. The DIG trial is a large, simple, international placebo-controlled trial whose primary objective is to determine the effect of digoxin on all cause mortality in patients with clinical heart failure who are in sinus rhythm and whose ejection fraction isor = 0.45. An ancillary study examines the effect in those with an ejection fraction0.45. Key aspects of the trial include the simplicity of the design, broad eligibility criteria, essential data collection, and inclusion of various types of centers. A total of 302 centers in the United States and Canada enrolled 7788 patients between February 1991 and September 1993. Follow-up continued until December 1995 with the results available in Spring 1996.

Published
1996

12. n-3 fatty acids and cardiovascular outcomes in patients with dysglycemia

Author

ORIGIN Trial Investigators and Bosch J, Gerstein HC, Dagenais GR, Díaz R, Dyal L, Jung H, Maggiono AP, Probstfield J, Ramachandran A, Riddle MC, Rydén LE, Yusuf S.

Subjects
diabetes mellitus type 2, n-3 fatty acids
Abstract

BACKGROUND: The use of n-3 fatty acids may prevent cardiovascular events in patients with recent myocardial infarction or heart failure. Their effects in patients with (or at risk for) type 2 diabetes mellitus are unknown. METHODS: In this double-blind study with a 2-by-2 factorial design, we randomly assigned 12, 536 patients who were at high risk for cardiovascular events and had impaired fasting glucose, impaired glucose tolerance, or diabetes to receive a 1-g capsule containing at least 900 mg (90% or more) of ethyl esters of n-3 fatty acids or placebo daily and to receive either insulin glargine or standard care. The primary outcome was death from cardiovascular causes. The results of the comparison between n-3 fatty acids and placebo are reported here. RESULTS: During a median follow up of 6.2 years, the incidence of the primary outcome was not significantly decreased among patients receiving n-3 fatty acids, as compared with those receiving placebo (574 patients [9.1%] vs. 581 patients [9.3%] ; hazard ratio, 0.98 ; 95% confidence interval [CI], 0.87 to 1.10 ; P=0.72). The use of n-3 fatty acids also had no significant effect on the rates of major vascular events (1034 patients [16.5%] vs. 1017 patients [16.3%] ; hazard ratio, 1.01 ; 95% CI, 0.93 to 1.10 ; P=0.81), death from any cause (951 [15.1%] vs. 964 [15.4%] ; hazard ratio, 0.98 ; 95% CI, 0.89 to 1.07 ; P=0.63), or death from arrhythmia (288 [4.6%] vs. 259 [4.1%] ; hazard ratio, 1.10 ; 95% CI, 0.93 to 1.30 ; P=0.26). Triglyceride levels were reduced by 14.5 mg per deciliter (0.16 mmol per liter) more among patients receiving n-3 fatty acids than among those receiving placebo (P

Published
2012

13. Systematically missing confounders in individual participant data meta-analysis of observational cohort studies

Author

Fibrinogen Studies Collaboration, Jackson, D, White, I, Kostis, JB, Wilson, AC, Folsom, AR, Wu, K, Chambless, L, Benderly, M, Goldbourt, U, Willeit, J, Kiechl, S, Yarnell, JW, Sweetnam, PM, Elwood, PC, Cushman, M, Psaty, BM, Tracy, RP, Tybjaerg-Hansen, A, Haverkate, F, de Maat, MP, Thompson, SG, Fowkes, FG, Lee, AJ, Smith, FB, Salomaa, V, Harald, K, Rasi, V, Vahtera, E, Jousilahti, P, D'Agostino, R, Kannel, WB, Wilson, PW, Tofler, G, Levy, D, Marchioli, R, Valagussa, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Cremer, P, Nagel, D, Curb, JD, Rodriguez, B, Yano, K, Salonen, J, Nyyssönen, K, Tuomainen, TP, Hedblad, B, Engström, G, Berglund, G, Loewel, H, Koenig, W, Hense, HW, Meade, TW, Cooper, JA, De Stavola, B, Knottenbelt, C, Miller, GJ, Bauer, KA, Rosenberg, RD, Sato, S, Kitamura, A, Naito, Y, Iso, H, Palosuo, T, Ducimetiere, P, Amouyel, P, Arveiler, D, Evans, AE, Ferrieres, J, Juhan-Vague, I, Bingham, A, Schulte, H, Assmann, G, Cantin, B, Lamarche, B, Despres, JP, Dagenais, GR, Tunstall-Pedoe, H, Lowe, GD, Woodward, M, Ben-Shlomo, Y, Davey Smith, G, Palmieri, V, Yeh, JL, Rudnicka, A, Brennan, P, Ridker, P, Rodeghiero, F, Tosetto, A, Shepherd, J, Ford, I, Robertson, M, Brunner, E, Shipley, M, Feskens, EJ, Di Angelantonio, E, Kaptoge, S, Lewington, S, Sarwar, N, Walker, M, Watson, S, White, IR, Wood, AM, and Danesh, J

Abstract

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohorts

Published
2009

14. Systematically missing confounders in individual participant data meta-analysis of observational cohort studies

Author

Jackson, D, White, I, Kostis, JB, Wilson, AC, Folsom, AR, Wu, K, Chambless, L, Benderly, M, Goldbourt, U, Willeit, J, Kiechl, S, Yarnell, JW, Sweetnam, PM, Elwood, PC, Cushman, M, Psaty, BM, Tracy, RP, Tybjaerg-Hansen, A, Haverkate, F, de Maat, MP, Thompson, SG, Fowkes, FG, Lee, AJ, Smith, FB, Salomaa, V, Harald, K, Rasi, V, Vahtera, E, Jousilahti, P, D'Agostino, R, Kannel, WB, Wilson, PW, Tofler, G, Levy, D, Marchioli, R, Valagussa, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Cremer, P, Nagel, D, Curb, JD, Rodriguez, B, Yano, K, Salonen, J, Nyyssönen, K, Tuomainen, TP, Hedblad, B, Engström, G, Berglund, G, Loewel, H, Koenig, W, Hense, HW, Meade, TW, Cooper, JA, De Stavola, B, Knottenbelt, C, Miller, GJ, Bauer, KA, Rosenberg, RD, Sato, S, Kitamura, A, Naito, Y, Iso, H, Palosuo, T, Ducimetiere, P, Amouyel, P, Arveiler, D, Evans, AE, Ferrieres, J, Juhan-Vague, I, Bingham, A, Schulte, H, Assmann, G, Cantin, B, Lamarche, B, Despres, JP, Dagenais, GR, Tunstall-Pedoe, H, Lowe, GD, Woodward, M, Ben-Shlomo, Y, Davey Smith, G, Palmieri, V, Yeh, JL, Rudnicka, A, Brennan, P, Ridker, P, Rodeghiero, F, Tosetto, A, Shepherd, J, Ford, I, Robertson, M, Brunner, E, Shipley, M, Feskens, EJ, Di Angelantonio, E, Kaptoge, S, Lewington, S, Sarwar, N, Walker, M, Watson, S, White, IR, Wood, AM, and Danesh, J

Subjects
Statistics and Probability, Male, Nutrition and Disease, Epidemiology, Coronary Disease, Bivariate analysis, Logistic regression, 01 natural sciences, survival analysis, Cohort Studies, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Meta-Analysis as Topic, Voeding en Ziekte, Statistics, Medicine, Humans, Computer Simulation, 030212 general & internal medicine, 0101 mathematics, observational studies, patient data, Survival analysis, time, VLAG, Models, Statistical, aggregate data, model, business.industry, Incidence (epidemiology), Confounding, Fibrinogen, confounders, event outcomes, meta-analysis, Meta-analysis, Data Interpretation, Statistical, missing covariates, logistic-regression analysis, Observational study, Female, heterogeneity, business, Demography, Cohort study, Research Article
Abstract

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154 012 participants in 31 cohorts.† Copyright © 2009 John Wiley & Sons, Ltd.

Published
2009

15. Plasma fibrinogen level and the risk of major cardiovascular diseases and nonvascular mortality: an individual participant meta-analysis

Author

Fibrinogen Studies Collaboration, Danesh, John, Lewington, Sarah, Thompson, Simon G, Lowe, Gordon DO, Collins, Rory, Kostis, JB, Wilson, AC, Folsom, AR, Wu, K, Benderly, M, Goldbourt, U, Willeit, J, Kiechl, S, Yarnell, JWG, Sweetnam, PM, Elwood, PC, Cushman, M, Psaty, BM, Tracy, RP, Tybjaerg-Hansen, A, Haverkate, F, de Maat, MPM, Fowkes, FGR, Lee, AJ, Smith, FB, Salomaa, V, Harald, K, Rasi, R, Vahtera, E, Jousilahti, P, Pekkanen, J, D'Agostino, R, Kannel, WB, Wilson, PWF, Tofler, G, Arocha-Piñango, CL, Rodriguez-Larralde, A, Nagy, E, Mijares, M, Espinosa, R, Rodriquez-Roa, E, Ryder, E, Diez-Ewald, MP, Campos, G, Fernandez, V, Torres, E, Marchioli, R, Valagussa, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Cremer, P, Nagel, D, Curb, JD, Rodriguez, B, Yano, K, Salonen, JT, Nyyssönen, K, Tuomainen, T-P, Hedblad, B, Lind, P, Loewel, H, Koenig, W, Meade, TW, Cooper, JA, De Stavola, B, Knottenbelt, C, Miller, GJ, Bauer, KA, Rosenberg, RD, Sato, S, Kitamura, A, Naito, Y, Palosuo, T, Ducimetiere, P, Amouyel, P, Arveiler, D, Evans, AE, Ferrieres, J, Juhan-Vague, I, Bingham, A, Schulte, H, Assmann, G, Cantin, B, Lamarche, B, Després, J-P, Dagenais, GR, Tunstall-Pedoe, H, Woodward, M, Ben-Shlomo, Y, Davey Smith, G, Palmieri, V, Yeh, JL, Rudnicka, A, Ridker, P, Rodeghiero, F, Tosetto, A, Shepherd, J, Ford, I, Robertson, M, Brunner, E, Shipley, M, Feskens, EJM, Kromhout, D, Dickinson, A, Ireland, B, Juzwishin, K, Kaptoge, S, Lewington, S, Memon, A, Sarwar, N, Walker, M, Wheeler, J, White, I, and Wood, A

Abstract

CONTEXT: Plasma fibrinogen levels may be associated with the risk of coronary heart disease (CHD) and stroke. OBJECTIVE: To assess the relationships of fibrinogen levels with risk of major vascular and with risk of nonvascular outcomes based on individual participant data. DATA SOURCES: Relevant studies were identified by computer-assisted searches, hand searches of reference lists, and personal communication with relevant investigators. STUDY SELECTION: All identified prospective studies were included with information available on baseline fibrinogen levels and details of subsequent major vascular morbidity and/or cause-specific mortality during at least 1 year of follow-up. Studies were excluded if they recruited participants on the basis of having had a previous history of cardiovascular disease; participants with known preexisting CHD or stroke were excluded. DATA EXTRACTION: Individual records were provided on each of 154,211 participants in 31 prospective studies. During 1.38 million person-years of follow-up, there were 6944 first nonfatal myocardial infarctions or stroke events and 13,210 deaths. Cause-specific mortality was generally available. Analyses involved proportional hazards modeling with adjustment for confounding by known cardiovascular risk factors and for regression dilution bias. DATA SYNTHESIS: Within each age group considered (40-59, 60-69, and > or =70 years), there was an approximately log-linear association with usual fibrinogen level for the risk of any CHD, any stroke, other vascular (eg, non-CHD, nonstroke) mortality, and nonvascular mortality. There was no evidence of a threshold within the range of usual fibrinogen level studied at any age. The age- and sex- adjusted hazard ratio per 1-g/L increase in usual fibrinogen level for CHD was 2.42 (95% confidence interval [CI], 2.24-2.60); stroke, 2.06 (95% CI, 1.83-2.33); other vascular mortality, 2.76 (95% CI, 2.28-3.35); and nonvascular mortality, 2.03 (95% CI, 1.90-2.18). The hazard ratios for CHD and stroke were reduced to about 1.8 after further adjustment for measured values of several established vascular risk factors. In a subset of 7011 participants with available C-reactive protein values, the findings for CHD were essentially unchanged following additional adjustment for C-reactive protein. The associations of fibrinogen level with CHD or stroke did not differ substantially according to sex, smoking, blood pressure, blood lipid levels, or several features of study design. CONCLUSIONS: In this large individual participant meta-analysis, moderately strong associations were found between usual plasma fibrinogen level and the risks of CHD, stroke, other vascular mortality, and nonvascular mortality in a wide range of circumstances in healthy middle-aged adults. Assessment of any causal relevance of elevated fibrinogen levels to disease requires additional research.

Published
2005

20. Glucose levels are associated with cardiovascular disease and death in an international cohort of normal glycaemic and dysglycaemic men and women: the EpiDREAM cohort study

Author

Anand, SS, primary, Dagenais, GR, additional, Mohan, V, additional, Diaz, R, additional, Probstfield, J, additional, Freeman, R, additional, Shaw, J, additional, Lanas, F, additional, Avezum, A, additional, Budaj, A, additional, Jung, H, additional, Desai, D, additional, Bosch, J, additional, Yusuf, S, additional, and Gerstein, HC, additional

Published
2011
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25. Erectile dysfunction predicts cardiovascular events in high-risk patients receiving telmisartan, ramipril, or both: The ONgoing Telmisartan Alone and in combination with Ramipril Global Endpoint Trial/Telmisartan Randomized AssessmeNt Study in ACE iNtolerant subjects with cardiovascular Disease (ONTARGET/TRANSCEND) Trials.

Author

Böhm M, Baumhäkel M, Teo K, Sleight P, Probstfield J, Gao P, Mann JF, Diaz R, Dagenais GR, Jennings GL, Liu L, Jansky P, Yusuf S, and ONTARGET/TRANSCEND Erectile Dysfunction Substudy Investigators

Published
2010
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26. Comparison of plaque sealing with paclitaxel-eluting stents versus medical therapy for the treatment of moderate nonsignificant saphenous vein graft lesions: the moderate vein graft lesion stenting with the taxus stent and intravascular ultrasound (VELETI) pilot trial.

Author

Rodés-Cabau J, Bertrand OF, Larose E, Déry JP, Rinfret S, Bagur R, Proulx G, Nguyen CM, Côté M, Landcop MC, Boudreault JR, Rouleau J, Roy L, Gleeton O, Barbeau G, Noël B, Courtis J, Dagenais GR, Després JP, and DeLarochellière R

Published
2009
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27. Effect of telmisartan on renal outcomes: a randomized trial.

Author

Mann JF, Schmieder RE, Dyal L, McQueen MJ, Schumacher H, Pogue J, Wang X, Probstfield JL, Avezum A, Cardona-Munoz E, Dagenais GR, Diaz R, Fodor G, Maillon JM, Rydén L, Yu CM, Teo KK, Yusuf S, TRANSCEND (Telmisartan Randomised Assessment Study in ACE Intolerant Subjects with Cardiovascular Disease) Investigators, and Mann, Johannes F E

Abstract

Background: Angiotensin-receptor blockers (ARBs) blunt progression of advanced diabetic nephropathy, but their long-term renal effects in other patients are not clear.Objective: To examine the long-term renal effects of telmisartan versus placebo in adults at high vascular risk.Design: Randomized trial. Patients were randomly assigned by a central automated system between November 2001 and May 2004 and were followed until March 2008. Participants and investigators were blinded to intervention status.Setting: Multicenter, multinational study.Patients: 5927 adults with known cardiovascular disease or diabetes with end-organ damage but without macroalbuminuria or heart failure who cannot tolerate angiotensin-converting enzyme inhibitors.Intervention: Telmisartan, 80 mg/d (n = 2954), or matching placebo (n = 2972) plus standard treatment for a mean of 56 months.Measurements: Composite renal outcome of dialysis or doubling of serum creatinine, changes in estimated glomerular filtration rate (GFR), and changes in albuminuria.Results: No important difference was found in the composite renal outcome with telmisartan (58 patients [1.96%]) versus placebo (46 patients [1.55%]) (hazard ratio, 1.29 [95% CI, 0.87 to 1.89]; P = 0.20). Among the telmisartan and placebo groups, 7 and 10 patients had dialysis and 56 and 36 patients had doubling of serum creatinine, respectively (hazard ratio, 1.59 [CI, 1.04 to 2.41]; P = 0.031). Albuminuria increased less with telmisartan than with placebo (32% [CI, 23% to 41%] vs. 63% [CI, 52% to 76%]; P < 0.001). Decreases in estimated GFR were greater with telmisartan than with placebo (mean change in estimated GFR, -3.2 mL/min per 1.73 m(2) [SD, 18.3] vs. -0.26 mL/min per 1.73 m(2) [SD, 18.0]; P < 0.001).Limitation: Only 17 participants had dialysis.Conclusion: In adults with vascular disease but without macroalbuminuria, the effects of telmisartan on major renal outcomes were similar to those of placebo. [ABSTRACT FROM AUTHOR]

Published
2009
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28. Effects of ramipril and rosiglitazone on cardiovascular and renal outcomes in people with impaired glucose tolerance or impaired fasting glucose: results of the Diabetes REduction Assessment with ramipril and rosiglitazone Medication (DREAM) trial.

Author

Dagenais GR, Gerstein HC, Holman R, Budaj A, Escalante A, Hedner T, Keltai M, Lonn E, McFarlane S, McQueen M, Teo K, Sheridan P, Bosch J, Pogue J, Yusuf S, and DREAM Trial Investigators

Abstract

OBJECTIVE: Impaired glucose tolerance (IGT) and/or impaired fasting glucose (IFG) are risk factors for diabetes, cardiovascular disease (CVD), and kidney disease. We determined the effects of ramipril and rosiglitazone on combined and individual CVD and renal outcomes in people with IGT and/or IFG in the Diabetes REduction Assessment With ramipril and rosiglitazone Medication (DREAM) trial. RESEARCH DESIGN AND METHODS: A total of 5,269 people aged >or=30 years, with IGT and/or IFG without known CVD or renal insufficiency, were randomized to 15 mg/day ramipril versus placebo and 8 mg/day rosiglitazone versus placebo. A composite cardiorenal outcome and its CVD and renal components were assessed during the 3-year follow-up. RESULTS: Compared with placebo, neither ramipril (15.7% [412 of 2,623] vs. 16.0% [424 of 2,646]; hazard ratio [HR] 0.98 [95% CI 0.84-1.13]; P = 0.75) nor rosiglitazone (15.0% [394 of 2,635] vs. 16.8% [442 of 2,634]; 0.87 [0.75-1.01]; P = 0.07) reduced the risk of the cardiorenal composite outcome. Ramipril had no impact on the CVD and renal components. Rosiglitazone increased heart failure (0.53 vs. 0.08%; HR 7.04 [95% CI 1.60-31.0]; P = 0.01) but reduced the risk of the renal component (0.80 [0.68-0.93]; P = 0.005); prevention of diabetes was independently associated with prevention of the renal component (P < 0.001). CONCLUSIONS: Ramipril did not alter the cardiorenal outcome or its components. Rosiglitazone, which reduced diabetes, also reduced the development of renal disease but not the cardiorenal outcome and increased the risk of heart failure. [ABSTRACT FROM AUTHOR]

Published
2008

34. Triglyceride-mediated pathways and coronary disease: collaborative analysis of 101 studies

Author

Triglyceride Coronary Disease Genetics Consortium, Emerging Risk Factors Collaboration, Sarwar, N, Sandhu, Ms, Ricketts, Sl, Butterworth, As, Di Angelantonio, E, Boekholdt, Sm, Ouwehand, W, Watkins, H, Samani, Nj, Saleheen, D, Lawlor, D, Reilly, Mp, Hingorani, Ad, Talmud, Pj, Collaborators: Braund PS, Danesh J., Hall, As, Thompson, J, März, W, Sivapalaratnam, S, Soranzo, N, Trip, M, Lawlor, Da, Casas, Jp, Ebrahim, S, Arsenault, Bj, Khaw, Kt, Wareham, Nj, Grallert, H, Illig, T, Humphries, Se, Talmud, T, Rader, Dj, He, J, Clarke, R, Hamsten, A, Hopewell, Jc, Frossard, P, Deloukas, P, Danesh, J, Ye, S, Simpson, Ia, Onat, A, Kömürcü Bayrak, E, Martinelli, Nicola, Olivieri, Oliviero, Girelli, Domenico, Kivimäki, M, Kumari, M, Aouizerat, Be, Baum, L, Campos, H, Chaaba, R, Chen, Bs, Cho, Ey, Evans, D, Hill, J, Hsu, La, Hubacek, Ja, Lai, Cq, Lee, Jh, Klos, K, Liu, H, Masana, L, Melegh, B, Nabika, T, Ribalta, J, Ruiz Narvaez, E, Thomas, Gn, Tomlinson, B, Szalai, C, Vaverkova, H, Yamada, Y, Yang, Y, Tipping, Rw, Ford, Ce, Pressel, Sl, Ballantyne, C, Brautbar, A, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Santer, P, Mayr, A, Wald, N, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, S, Vanuzzo, D, Pilotto, L, de la Cámara AG, Gómez Gerique JA, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, R, Blazer, Dg, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, D'Agostino, Rb, Vasan, Rs, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Rodriguez, B, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Voutilainen, S, Meade, Tw, Cooper, Ja, Kuller, Lh, Grandits, G, Gillum, R, Mussolino, M, Rimm, E, Hankinson, S, Manson, Ja, Pai, Jk, Bauer, Ka, Naito, Y, Amouyel, P, Arveiler, D, Evans, A, Ferrières, J, Schulte, H, Assmann, G, Packard, Cj, Sattar, N, Westendorp, Rg, Buckley, Bm, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Woodward, M, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Lind, L, Giedraitis, V, Michaëlsson, K, Brunner, E, Shipley, M, Ridker, P, Buring, J, Shepherd, J, Cobbe, Sm, Ford, I, Robertson, M, Ibañez, Am, Feskens, Ej, Kromhout, D, Walker, M, Watson, S, Collins, R, Kaptoge, S, Perry, Pl, Thompson, A, Thompson, Sg, White, Ir, Wood, Am, Danesh, J., ACS - Amsterdam Cardiovascular Sciences, Cardiology, Vascular Medicine, Interne Geneeskunde, MUMC+: MA Interne Geneeskunde (3), RS: CARIM School for Cardiovascular Diseases, Sarwar, N, Sandhu, M, Ricketts, Sl, Butterworth, A, Braund, P, Hall, A, Samani, Nj, Thompson, J, März, W, Ouwehand, W, Sivapalaratnam, S, Soranzo, N, Trip, M, Lawlor, Da, Casas, Jp, Ebrahim, S, Arsenault, Bj, Boekholdt, Sm, Khaw, Kt, Wareham, Nj, Grallert, H, Illig, T, Humphries, Se, Talmud, T, Rader, Dj, He, J, Reilly, Mp, Clarke, R, Hamsten, A, Hopewell, Jc, Watkins, H, Saleheen, D, Frossard, P, Deloukas, P, Danesh, J, Ye, S, Simpson, Ia, Onat, A, Kömürcü Bayrak, E, Martinelli, N, Olivieri, O, Girelli, D, Hingorani, Ad, Kivimäki, M, Kumari, M, Aouizerat, Be, Baum, L, Campos, H, Chaaba, R, Chen, B, Cho, Ey, Evans, D, Hill, J, Hsu, La, Hubacek, Ja, Lai, Cq, Lee, Jh, Klos, K, Liu, H, Masana, L, Melegh, B, Nabika, T, Ribalta, J, Ruiz Narvaez, E, Thomas, Gn, Tomlinson, B, Szalai, C, Vaverkova, H, Yamada, Y, Yang, Y, Kastelein, Jj, Tipping, Rw, Ford, Ce, Pressel, Sl, Ballantyne, C, Brautbar, A, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Santer, P, Mayr, A, Wald, N, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, de la Cámara, Ag, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, R, Blazer, Dg, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, D'Agostino, Rb, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Rodriguez, B, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Voutilainen, S, Meade, Tw, Cooper, Ja, Kuller, Lh, Grandits, G, Gillum, R, Mussolino, M, Rimm, E, Hankinson, S, Manson, Ja, Pai, Jk, Bauer, Ka, Naito, Y, Amouyel, P, Arveiler, D, Evans, A, Ferrières, J, Schulte, H, Assmann, G, Packard, Cj, Sattar, N, Westendorp, Rg, Buckley, Bm, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Woodward, M, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Lind, L, Giedraitis, V, Michaëlsson, K, Brunner, E, Shipley, M, Ridker, P, Buring, J, Shepherd, J, Cobbe, Sm, Ford, I, Robertson, M, Ibañez, Am, Feskens, Ej, Kromhout, D, Walker, M, Watson, S, Collins, R, Di Angelantonio, E, Kaptoge, S, Perry, Pl, Thompson, A, Thompson, Sg, White, Ir, Wood, Am, Lawlor, D, Talmud, Pj, Danesh, J., Epidemiology and Data Science, General practice, and EMGO - Lifestyle, overweight and diabetes

Subjects
Very low-density lipoprotein, Nutrition and Disease, Heart disease, Coronary Disease, Lipoproteins, VLDL, 030204 cardiovascular system & hematology, low-density-lipoprotein apolipoprotein-a-v transfer protein heart-disease myocardial-infarction metabolic syndrome rich lipoproteins risk dyslipidemia association, Bioinformatics, chemistry.chemical_compound, 0302 clinical medicine, triglyceride, APOA5 gene polymorphysm, coronary heart disease, Gene Frequency, Risk Factors, Voeding en Ziekte, Medicine, Myocardial infarction, Promoter Regions, Genetic, risk, 0303 health sciences, Men, Mendelian Randomization Analysis, Articles, General Medicine, Lipids, myocardial-infarction, 3. Good health, Lipoproteins, LDL, Low-density lipoprotein, Lipoproteins, HDL, apolipoprotein-a-v, Receptor, medicine.medical_specialty, Genotype, transfer protein, Snp, Polymorphism, Single Nucleotide, metabolic syndrome, 03 medical and health sciences, Internal medicine, Humans, Particle Size, Apolipoproteins A, Triglycerides, VLAG, 030304 developmental biology, low-density-lipoprotein, Triglyceride, business.industry, dyslipidemia, association, rich lipoproteins, medicine.disease, heart-disease, Apolipoproteins, Endocrinology, chemistry, Apolipoprotein A-V, Metabolic syndrome, business, Dyslipidemia
Abstract

Udgivelsesdato: May-8 BACKGROUND: Whether triglyceride-mediated pathways are causally relevant to coronary heart disease is uncertain. We studied a genetic variant that regulates triglyceride concentration to help judge likelihood of causality. METHODS: We assessed the -1131T>C (rs662799) promoter polymorphism of the apolipoprotein A5 (APOA5) gene in relation to triglyceride concentration, several other risk factors, and risk of coronary heart disease. We compared disease risk for genetically-raised triglyceride concentration (20,842 patients with coronary heart disease, 35,206 controls) with that recorded for equivalent differences in circulating triglyceride concentration in prospective studies (302 430 participants with no history of cardiovascular disease; 12,785 incident cases of coronary heart disease during 2.79 million person-years at risk). We analysed -1131T>C in 1795 people without a history of cardiovascular disease who had information about lipoprotein concentration and diameter obtained by nuclear magnetic resonance spectroscopy. FINDINGS: The minor allele frequency of -1131T>C was 8% (95% CI 7-9). -1131T>C was not significantly associated with several non-lipid risk factors or LDL cholesterol, and it was modestly associated with lower HDL cholesterol (mean difference per C allele 3.5% [95% CI 2.6-4.6]; 0.053 mmol/L [0.039-0.068]), lower apolipoprotein AI (1.3% [0.3-2.3]; 0.023 g/L [0.005-0.041]), and higher apolipoprotein B (3.2% [1.3-5.1]; 0.027 g/L [0.011-0.043]). By contrast, for every C allele inherited, mean triglyceride concentration was 16.0% (95% CI 12.9-18.7), or 0.25 mmol/L (0.20-0.29), higher (p=4.4x10(-24)). The odds ratio for coronary heart disease was 1.18 (95% CI 1.11-1.26; p=2.6x10(-7)) per C allele, which was concordant with the hazard ratio of 1.10 (95% CI 1.08-1.12) per 16% higher triglyceride concentration recorded in prospective studies. -1131T>C was significantly associated with higher VLDL particle concentration (mean difference per C allele 12.2 nmol/L [95% CI 7.7-16.7]; p=9.3x10(-8)) and smaller HDL particle size (0.14 nm [0.08-0.20]; p=7.0x10(-5)), factors that could mediate the effects of triglyceride. INTERPRETATION: These data are consistent with a causal association between triglyceride-mediated pathways and coronary heart disease. FUNDING: British Heart Foundation, UK Medical Research Council, Novartis.

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35. Psychological stress and incidence of ischaemic heart disease.

Author

Moore, L, Meyer, F, Perusse, M, Cantin, B, Dagenais, GR, Bairati, I, Savard, J, and Dagenais, G R

Abstract

Background: We assessed the relationship between psychological stress and ischaemic heart disease (IHD) incidence in a population of 868 men over a 10-year follow-up period.Methods: In 1981, 869 men aged 42-60, free from IHD and living around Quebec City completed a questionnaire assessing the presence of psychological stress in different areas of their life. They also underwent a medical examination and provided information on IHD risk factors. From 1981 to 1991, the incidence of IHD events was ascertained. The relationship between 13 stress dimensions and IHD incidence was investigated using Cox regression while controlling for important IHD risk factors. Cross-sectional analyses were also performed to investigate the relationship between stress dimensions and IHD risk factors.Results: Between 1981 and 1991, 79 men (9%) experienced a first IHD event. The following risk factors were associated with the risk of IHD: age, (rate ratio (RR) = 1.93, 95% CI: 1.21-3.09), hypertension (RR = 1.90, 95% CI: 1.22-2.98), triglycerides (RR = 1.87, 95% CI: 1.19-2.95) and high density lipoprotein (HDL) cholesterol (RR = 1.64, 95% CI: 1.05-2.55). After controlling for risk factors, not one of the psychological stress dimensions significantly altered the risk of IHD.Conclusions: While confirming the influence of hypertension, age, triglycerides and HDL cholesterol on IHD incidence, this study suggests that there is no important connection between the explored stress dimensions and IHD incidence. It is unlikely that this lack of association is due to the stress questionnaire since the 13 stress dimensions were rigorously developed through independent evaluation of the questions by three specialists and many statistically significant relationships were observed between stress dimensions and IHD risk factors. [ABSTRACT FROM AUTHOR]

Published
1999
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37. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies

Author

Emerging Risk Factors Collaboration, Sarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, Di Angelantonio E, Ingelsson E, Lawlor DA, Selvin E, Stampfer M, Stehouwer CD, Lewington S, Pennells L, Thompson A, Sattar N, White IR, Ray KK, Danesh J. Tipping RW, Ford CE, Pressel SL, Folsom AR, Chambless LE, Wagenknecht LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Whincup PH, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Oberhollenzer F, Mayr A, Wald N, Ebrahim S, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, de Boer IH, Kizer JR, Mukamal KJ, Tybjaerg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Palmieri L, Vanuzzo D, Pilotto L, de la Cámara AG, Rubio MA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Taylor J, Guralnik JM, Phillips CL, Wallace R, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Giampaoli S, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Vasan RS, Fox CS, Pencina MJ, Bladbjerg E, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Wilhelmsen L, Eriksson H, Svärdsudd K, Welin L, Rosengren A, Lappas G, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Strandberg TE, Tilvis RS, Miettinen TA, Kiyohara Y, Arima H, Doi Y, Ninomiya T, Rodriguez B, Dekker JM, Nijpels G, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Goldbourt U, Nyyssönen K, Tuomainen TP, Salonen JT, Deeg D, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Cushman M, Psaty BM, Shea S, Döring A, Koenig W, Meisinger C, Mraz W, Bueno de Mesquita HB, Fletcher A, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson JE, Bauer KA, Davidson KW, Kirkland S, Shaffer J, Korin MR, Holme I, Ducimetiere P, Jouven X, Bakker SJ, Gansevoort RT, Hillege HL, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrières J, Schulte H, Assmann G, Westendorp RG, Buckley BM, Packard CJ, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe GD, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Hergenç G, Can G, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Zethelius B, Risérus U, Berne C, Gaziano JM, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Tinker L, Liu S, Marmot IM, Clarke R, Collins R, Brunner E, Shipley M, Buring J, Shepherd J, Cobbe SM, Ford I, Robertson M, Ibañez AM, Feskens EJ, Kromhout D, Walker M, Watson S, Alexander M, Erqou S, Haycock P, Perry PL, Thompson SG, Wood AM, Wormser D, Danesh J., PANICO, SALVATORE, Interne Geneeskunde, RS: NUTRIM - R1 - Metabolic Syndrome, RS: CARIM School for Cardiovascular Diseases, Emerging Risk Factors, Collaboration, Sarwar, N, Gao, P, Seshasai, Sr, Gobin, R, Kaptoge, S, Di Angelantonio, E, Ingelsson, E, Lawlor, Da, Selvin, E, Stampfer, M, Stehouwer, Cd, Lewington, S, Pennells, L, Thompson, A, Sattar, N, White, Ir, Ray, Kk, Danesh J., Tipping RW, Ford, Ce, Pressel, Sl, Folsom, Ar, Chambless, Le, Wagenknecht, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Oberhollenzer, F, Mayr, A, Wald, N, Ebrahim, S, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, de Boer, Ih, Kizer, Jr, Mukamal, Kj, Tybjaerg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, de la Cámara, Ag, Rubio, Ma, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, R, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Giampaoli, S, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Vasan, R, Fox, C, Pencina, Mj, Bladbjerg, E, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Wilhelmsen, L, Eriksson, H, Svärdsudd, K, Welin, L, Rosengren, A, Lappas, G, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Strandberg, Te, Tilvis, R, Miettinen, Ta, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, Jm, Nijpels, G, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Nyyssönen, K, Tuomainen, Tp, Salonen, Jt, Deeg, D, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Cushman, M, Psaty, Bm, Shea, S, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bueno de Mesquita, Hb, Fletcher, A, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, Je, Bauer, Ka, Davidson, Kw, Kirkland, S, Shaffer, J, Korin, Mr, Holme, I, Ducimetiere, P, Jouven, X, Bakker, Sj, Gansevoort, Rt, Hillege, Hl, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrières, J, Schulte, H, Assmann, G, Westendorp, Rg, Buckley, Bm, Packard, Cj, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Hergenç, G, Can, G, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Zethelius, B, Risérus, U, Berne, C, Gaziano, Jm, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Tinker, L, Liu, S, Marmot, Im, Clarke, R, Collins, R, Brunner, E, Shipley, M, Buring, J, Shepherd, J, Cobbe, Sm, Ford, I, Robertson, M, Ibañez, Am, Feskens, Ej, Kromhout, D, Walker, M, Watson, S, Alexander, M, Erqou, S, Haycock, P, Perry, Pl, Thompson, Sg, Wood, Am, Wormser, D, Danesh, J., and University of Groningen

Subjects
Adult, Blood Glucose, Male, medicine.medical_specialty, PATHOPHYSIOLOGY, 030209 endocrinology & metabolism, Coronary Disease, Disease, 030204 cardiovascular system & hematology, THERAPY, Diabetes Complications, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Diabetes mellitus, Internal medicine, General & Internal Medicine, medicine, Diabetes Mellitus, Humans, CORONARY-HEART-DISEASE, Prospective cohort study, Stroke, Aged, Glucose Metabolism Disorders, business.industry, Vascular disease, MORTALITY, Absolute risk reduction, ASIA-PACIFIC REGION, WOMEN, General Medicine, Fasting, 11 Medical And Health Sciences, Articles, Middle Aged, medicine.disease, Impaired fasting glucose, 3. Good health, Endocrinology, Blood pressure, ATHEROSCLEROSIS, Cardiovascular Diseases, CARDIOVASCULAR-DISEASES, Female, coronary-heart-disease asia-pacific region cardiovascular-diseases task-force pathophysiology atherosclerosis mortality therapy women, business, TASK-FORCE
Abstract

Summary Background Uncertainties persist about the magnitude of associations of diabetes mellitus and fasting glucose concentration with risk of coronary heart disease and major stroke subtypes. We aimed to quantify these associations for a wide range of circumstances. Methods We undertook a meta-analysis of individual records of diabetes, fasting blood glucose concentration, and other risk factors in people without initial vascular disease from studies in the Emerging Risk Factors Collaboration. We combined within-study regressions that were adjusted for age, sex, smoking, systolic blood pressure, and body-mass index to calculate hazard ratios (HRs) for vascular disease. Findings Analyses included data for 698 782 people (52 765 non-fatal or fatal vascular outcomes; 8·49 million person-years at risk) from 102 prospective studies. Adjusted HRs with diabetes were: 2·00 (95% CI 1·83–2·19) for coronary heart disease; 2·27 (1·95–2·65) for ischaemic stroke; 1·56 (1·19–2·05) for haemorrhagic stroke; 1·84 (1·59–2·13) for unclassified stroke; and 1·73 (1·51–1·98) for the aggregate of other vascular deaths. HRs did not change appreciably after further adjustment for lipid, inflammatory, or renal markers. HRs for coronary heart disease were higher in women than in men, at 40–59 years than at 70 years and older, and with fatal than with non-fatal disease. At an adult population-wide prevalence of 10%, diabetes was estimated to account for 11% (10–12%) of vascular deaths. Fasting blood glucose concentration was non-linearly related to vascular risk, with no significant associations between 3·90 mmol/L and 5·59 mmol/L. Compared with fasting blood glucose concentrations of 3·90–5·59 mmol/L, HRs for coronary heart disease were: 1·07 (0·97–1·18) for lower than 3·90 mmol/L; 1·11 (1·04–1·18) for 5·60–6·09 mmol/L; and 1·17 (1·08–1·26) for 6·10–6·99 mmol/L. In people without a history of diabetes, information about fasting blood glucose concentration or impaired fasting glucose status did not significantly improve metrics of vascular disease prediction when added to information about several conventional risk factors. Interpretation Diabetes confers about a two-fold excess risk for a wide range of vascular diseases, independently from other conventional risk factors. In people without diabetes, fasting blood glucose concentration is modestly and non-linearly associated with risk of vascular disease. Funding British Heart Foundation, UK Medical Research Council, and Pfizer.

38. Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis

Author

Paige, E, Barrett, J, Pennells, L, Sweeting, M, Willeit, P, Di Angelantonio, E, Gudnason, V, Nordestgaard, BG, Psaty, BM, Goldbourt, U, Best, LG, Assmann, G, Salonen, JT, Nietert, PJ, Verschuren, WM, Brunner, EJ, Kronmal, RA, Salomaa, V, Bakker, SJ, Dagenais, GR, Sato, S, Jansson, J-H, Willeit, J, Onat, A, De La Cámara, AG, Roussel, R, Völzke, H, Dankner, R, Tipping, RW, Meade, TW, Donfrancesco, C, Kuller, LH, Peters, A, Gallacher, J, Kromhout, D, Iso, H, Knuiman, M, Casiglia, E, Kavousi, M, Palmieri, L, Sundström, J, Davis, BR, Njølstad, I, Couper, D, Danesh, J, Thompson, SG, and Wood, A

Subjects
repeated risk factors, risk prediction, cardiovascular disease, longitudinal measurements, 3. Good health
Abstract

The added value of incorporating information from repeated measurements of blood pressure and cholesterol for cardiovascular disease (CVD) risk prediction has not been rigorously assessed. We used data from the Emerging Risk Factors Collaboration on 191,445 adults (38 cohorts from across 17 countries with data from 1962-2014) with > 1 million measurements of systolic blood pressure, total cholesterol and high-density lipoprotein cholesterol; over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative means of repeated measurements and summary measures from longitudinal modelling of the repeated measurements were compared to models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analysed across studies. Compared to the single time point model, the cumulative means and the longitudinal models increased the C-index by 0.0040 (95% CI: 0.0023, 0.0057) and 0.0023 (0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared to the single time point model, overall net reclassification improvements were 0.0369 (0.0303, 0.0436) for the cumulative means model and 0.0177 (0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.

41. The Cost-Effectiveness of Rivaroxaban Plus Aspirin Compared with Aspirin Alone in the COMPASS Trial: A US Perspective.

Author

Lamy A, Eikelboom J, Tong W, Yuan F, Bangdiwala SI, Bosch J, Connolly S, Lonn E, Dagenais GR, Branch KRH, Wang WJ, Bhatt DL, Probstfield J, Ertl G, Störk S, Steg PG, Aboyans V, Durand-Zaleski I, Ryden L, and Yusuf S

Subjects
Humans, Cost-Benefit Analysis, Drug Therapy, Combination, Factor Xa Inhibitors, Stroke prevention & control, Aspirin economics, Aspirin therapeutic use, Myocardial Infarction prevention & control, Peripheral Arterial Disease drug therapy, Rivaroxaban economics, Rivaroxaban therapeutic use
Abstract

Background: Rivaroxaban 2.5 mg twice daily with aspirin 100 mg daily was shown to be better than aspirin 100 mg daily for preventing cardiovascular (CV) death, stroke or myocardial infarction in patients with either stable coronary artery disease (CAD) or peripheral artery disease (PAD). The cost-effectiveness of this regimen in this population is essential for decision-makers to know., Methods: US direct healthcare system costs (in USD) were applied to hospitalized events, procedures and study drugs utilized by all patients. We determined the mean cost per participant for the full duration of the trial (mean follow-up of 23 months) plus quality-adjusted life years (QALYs) and the incremental cost-effectiveness ratio (ICER) over a lifetime using a two-state Markov model with 1-year cycle length. Sensitivity analyses were performed on the price of rivaroxaban and the annual discontinuation rate., Results: The costs of events and procedures were reduced for Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) patients who received rivaroxaban 2.5 mg orally (BID) plus acetylsalicylic acid (ASA) compared with ASA alone. Total costs were higher for the combination group ($7426 versus $4173) after considering acquisition costs of the study drug. Over a lifetime, patients receiving rivaroxaban plus ASA incurred $27,255 more and gained 1.17 QALYs compared with those receiving ASA alone resulting in an ICER of $23,295/QALY. ICERs for PAD only and polyvascular disease subgroups were lower., Conclusion: Rivaroxaban 2.5 mg BID plus ASA compared with ASA alone was cost-effective (high value) in the USA. COMPASS ClinicalTrials.gov identifier: NCT01776424., (© 2023. The Author(s).)

Published
2024
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42. Psychosocial Stressors at Work and Coronary Heart Disease Risk in Men and Women: 18-Year Prospective Cohort Study of Combined Exposures.

Author

Lavigne-Robichaud M, Trudel X, Talbot D, Milot A, Gilbert-Ouimet M, Vézina M, Laurin D, Dionne CE, Pearce N, Dagenais GR, and Brisson C

Subjects
Male, Humans, Female, Adult, Middle Aged, Prospective Studies, Stress, Psychological diagnosis, Stress, Psychological epidemiology, Surveys and Questionnaires, Risk Factors, Cardiovascular Diseases, Coronary Disease diagnosis, Coronary Disease epidemiology
Abstract

Background: Psychosocial stressors at work, like job strain and effort-reward imbalance (ERI), can increase coronary heart disease (CHD) risk. ERI indicates an imbalance between the effort and received rewards. Evidence about the adverse effect of combined exposure to these work stressors on CHD risk is scarce. This study examines the separate and combined effect of job strain and ERI exposure on CHD incidence in a prospective cohort of white-collar workers in Quebec, Canada., Methods: Six thousand four hundred sixty-five white-collar workers without cardiovascular disease (mean age, 45.3±6.7) were followed for 18 years (from 2000 to 2018). Job strain and ERI were measured with validated questionnaires. CHD events were retrieved from medico-administrative databases using validated algorithms. Marginal Cox models were used to calculate hazard ratios (HR) stratified by sex. Multiple imputation and inverse probability weights were applied to minimize potential threats to internal validity., Results: Among 3118 men, 571 had a first CHD event. Exposure to either job strain or ERI was associated with an adjusted 49% CHD risk increase (HR, 1.49 [95% CI, 1.07-2.09]). Combined exposure to job strain and ERI was associated with an adjusted 103% CHD risk increase (HR, 2.03 [95% CI, 1.38-2.97]). Exclusion of early CHD cases and censoring at retirement did not alter these associations. Among 3347 women, 265 had a first CHD event. Findings were inconclusive (passive job HR, 1.24 [95% CI, 0.80-1.91]; active job HR, 1.16 [95% CI, 0.70-1.94]; job strain HR, 1.08 [95% CI, 0.66-1.77]; ERI HR, 1.02 [95% CI, 0.72-1.45])., Conclusions: In this prospective cohort study, men exposed to job strain or ERI, separately and in combination, were at increased risk of CHD. Early interventions on these psychosocial stressors at work in men may be effective prevention strategies to reduce CHD burden. Among women, further investigation is required., Competing Interests: Disclosures Drs Talbot, Gilbert-Ouimet, Vézina, Trudel, Milot, and Brisson reported receiving grants from the Canadian Institute of Health Research during the conduct of the study. M. Lavigne-Robichaud was supported by a PhD grant from les Fonds de Recherche du Québec en santé. Dr Talbot is supported by a research career award from the Fonds de Recherche du Québec en Santé. The other authors report no conflicts.

Published
2023
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43. Association between psychosocial work-related factors at midlife and arterial stiffness at older age in a prospective cohort of 1736 white-collar workers.

Author

Massamba VK, Talbot D, Milot A, Trudel X, Dionne CE, Vézina M, Mâsse B, Gilbert-Ouimet M, Dagenais GR, Pearce N, and Brisson C

Subjects
Humans, Female, Aged, Prospective Studies, Blood Pressure, Canada, Pulse Wave Analysis, Vascular Stiffness
Abstract

Objective: Arterial stiffness and exposure to psychosocial work-related factors increase the risk of developing cardiovascular disease. However, little is known about the relationship between psychosocial work-related factors and arterial stiffness. We aimed to examine this relationship., Design: Prospective cohort study., Setting: Public organisations in Quebec City, Canada., Participants: The study included 1736 white-collar workers (women 52%) from 19 public organisations., Primary and Secondary Outcome Measures: Association between psychosocial work-related factors from the job strain and effort-reward imbalance (ERI) models assessed at study baseline (1999-2001) with validated instruments and arterial stiffness assessed using carotid-femoral pulse wave velocity at follow-up, on average 16 years later (2015-2018). Generalised estimating equations were used to estimate differences in arterial stiffness between exposed and unexposed participants. Subgroup analyses according to sex, age, blood pressure (BP), cardiovascular risk score and employment status were conducted., Results: Among participants with high diastolic BP (≥90 mm Hg) at baseline, aged 47 on average, those exposed to high job strain had higher arterial stiffness (1.38 m/s (95% CI: 0.57 to 2.19)) at follow-up, 16 years later, following adjustment for a large set of potential confounders. The trend was similar in participants with high systolic BP (≥140 mm Hg) exposed to high job strain (0.84 m/s (95% CI: -0.35 to 2.03)). No association was observed for ERI in the total sample and counterintuitive associations were observed in subgroup analyses., Conclusions: Job strain may have a long-term deleterious effect on arterial stiffness in people with high BP. Interventions at midlife to reduce job strain may mitigate arterial stiffness progression., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Published
2023
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44. Fixed dose combination therapies in primary cardiovascular disease prevention in different groups: an individual participant meta-analysis.

Author

Dagenais GR, Pais P, Gao P, Roshandel G, Malekzadeh R, Joseph P, and Yusuf S

Subjects
Aged, Humans, Antihypertensive Agents adverse effects, Aspirin adverse effects, Drug Combinations, Hemorrhage chemically induced, Primary Prevention, Randomized Controlled Trials as Topic, Cardiovascular Diseases drug therapy, Myocardial Infarction epidemiology, Stroke epidemiology
Abstract

Objective: To evaluate the effects of fixed dose combination (FDC) medications on cardiovascular outcomes in different age groups in an individual participant meta-analysis of three primary prevention randomised trials., Methods: Participants at intermediate risk (17.7% mean 10-year Framingham Cardiovascular Risk Score), randomised to FDC of two or more antihypertensives and a statin with or without aspirin, or to their respective control, were followed up for 5 years. Age groups were <60, 60-65 and ≥65 years. The primary outcome was cardiovascular death, myocardial infarction, stroke or revascularisation. Cox proportional HRs and 95% CIs were computed within each age group., Results: The primary outcome risk was reduced by 37% (3.3% in FDC vs 5.2% in control (HR 0.63; 95% CI 0.54 to 0.74)) in the total population of 18 162 participants with larger benefits in older groups (HR 0.58; 95% CI 0.42 to 0.78, 60 to 65 years) and (HR 0.57; 95% CI 0.47 to 0.70, ≥65 years), as were their numbers needed to treat to avoid one primary outcome: 53 and 33, respectively. The primary outcome risk was reduced in the two oldest groups with FDC with aspirin (n=8951) by 54% and 54%, and without aspirin (n=12 061) by 34% and 38%. Dizziness, the most frequent FDC adverse effects, was higher in participants aged <65 years. Aspirin was not associated with significant bleeding excess., Conclusions: In participants with intermediate cardiovascular risk, FDCs produce larger cardiovascular benefits in older individuals, which appear greater with aspirin., Trial Registration Number: HOPE-3, NCT00468923; TIPS-3, NCT016464137; PolyIran, NCT01271985., Competing Interests: Competing interests: PP was co-principal investigator for the TIPS-3 Study, and his institution received study grants from the study sponsor Cadila Pharmaceuticals, India. RM was the principal investigator for the PolyIran study that was supported by Barakat Foundation and Alborz Daru Company. SY was the principal investigator for the HOPE-3 and TIPS-3 studies and his institution received funding from the Canadian Institutes of Health Research and AstraZeneca for HOPE-3 study, and from the Wellcome Trust, Cadila Pharmaceuticals, India, Canadian Institutes of Health Research, and Heart and Stroke Foundation of Canada for TIPS-3 study. All other authors have no relationships relevant to the contents of this paper to disclose., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Published
2023
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45. The cost-effectiveness of rivaroxaban with or without aspirin in the COMPASS trial.

Author

Lamy A, Eikelboom J, Tong W, Yuan F, Bangdiwala SI, Bosch J, Connolly S, Lonn E, Dagenais GR, Branch KRH, Wang WJ, Bhatt DL, Probstfield J, Ertl G, Störk S, Steg PG, Aboyans V, Durand-Zaleski I, Ryden L, and Yusuf S

Subjects
Humans, Cost-Benefit Analysis, Drug Therapy, Combination, Factor Xa Inhibitors therapeutic use, Rivaroxaban therapeutic use, Aspirin therapeutic use, Peripheral Arterial Disease drug therapy
Abstract

Aims: The Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) trial demonstrated that rivaroxaban 2.5 mg BID with aspirin 100 mg was more effective than aspirin 100 mg daily alone for the prevention of cardiovascular (CV) death, stroke, or myocardial infarction in patients with stable coronary artery disease (CAD) or peripheral artery disease (PAD). We aimed to examine the cost-effectiveness of rivaroxaban using patient-level data from the COMPASS trial., Methods and Results: We performed an in-trial analysis and extrapolated our results for 33 years using a two-state Markov model with a 1-year cycle length. Hospitalization events, procedures, and study drugs were documented for patients. We applied country-specific (Canada, France, and Germany) direct healthcare system costs (in USD) to healthcare resources consumed by patients. Average cost per patient during the trial (mean follow-up of 23 months), quality-adjusted life years (QALYs), and lifetime cost-effectiveness were calculated. Costs of events and procedures were reduced with rivaroxaban 2.5 mg BID with aspirin. The addition of rivaroxaban 2.5 mg BID increased total costs for the combination group. Over a lifetime horizon (in trial +33 years), rivaroxaban plus aspirin was associated with 1.17 QALYs gained, yielding an incremental cost-effectiveness ratio (ICER) of $3946/QALY, $9962/QALY, and $10 264/QALY in Canada, France, and Germany, respectively. PAD and polyvascular disease subgroups had lower ICERs., Conclusion: Rivaroxaban 2.5 mg twice daily plus aspirin compared with aspirin alone reduces direct healthcare costs. After acquisition costs of rivaroxaban, the lifetime cost-effectiveness of 2.5 mg twice daily plus aspirin is highly cost-effective in Canada, France, and Germany.(COMPASS ClinicalTrials.gov identifier: NCT01776424)., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Published
2023
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46. A hybrid automated event adjudication system for clinical trials.

Author

Yuan F, Bosch J, Eikelboom J, Dagenais GR, Connolly S, Belanger J, Marsden T, Tang C, Swaminathan B, Renters M, Dyal L, and Bangdiwala SI

Subjects
Humans, Rivaroxaban therapeutic use, Factor Xa therapeutic use, Factor Xa Inhibitors therapeutic use, Double-Blind Method, Aspirin therapeutic use, Embolic Stroke complications, Embolic Stroke drug therapy, Stroke prevention & control, Stroke drug therapy, Embolism complications, Embolism drug therapy, Myocardial Infarction drug therapy
Abstract

Introduction: In clinical trials, event adjudication is a process to review and confirm the accuracy of outcomes reported by site investigators. Despite efforts to automate the communication between a clinical-data-and-coordination center and an event adjudication committee, the review and confirmation of outcomes, as the core function of the process, still fully rely on human labor. To address this issue, we present an automated event adjudication system and its application in two randomized controlled trials., Methods: Centrally executed by a clinical-data-and-coordination center, the automated event adjudication system automatedly assessed and classified outcomes in a clinical data management system. By checking clinically predefined criteria, the automated event adjudication system either confirmed or unconfirmed an outcome and automatedly updated its status in the database. It also served as a management tool to assist staff to oversee the process of event adjudication. The system has been applied in: (1) the Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) trial and (2) the New Approach riVaroxaban Inhibition of Factor Xa in a Global trial versus Aspirin to prevenT Embolism in Embolic Stroke of Undetermined Source (NAVIGATE ESUS) trial. The automated event adjudication system first screened outcomes reported on a case report form and confirmed those with data matched to preset definitions. For selected primary efficacy, secondary, and safety outcomes, the unconfirmed cases were referred to a human event adjudication committee for a final decision. In the New Approach riVaroxaban Inhibition of Factor Xa in a Global trial versus Aspirin to prevenT Embolism in Embolic Stroke of Undetermined Source (NAVIGATE ESUS) trial, human adjudicators were given priority to review cases, while the automated event adjudication system took the lead in the Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) trial., Results: Outcomes that were adjudicated in a hybrid model are discussed here. The COMPASS automated event adjudication system adjudicated 3283 primary efficacy outcomes and confirmed 1652 (50.3%): 132 (21.1%) strokes, 522 (53%) myocardial infarctions, and 998 (59.7%) causes of deaths. The NAVIGATE ESUS one adjudicated 737 cases of selected outcomes and confirmed 383 (52%): 219 (51.5%) strokes, 34 (42.5%) myocardial infarctions, 73 (54.9%) causes of deaths, and 57 (57.6%) major bleedings. After one deducts the time needed for migrating the system to a new study, the automated event adjudication system helped to reduce the time required for human review from approximately 1303 to 716.5 h for the Cardiovascular Outcomes for People Using Anticoagulation Strategies trial and from 387 to 196 h for the New Approach riVaroxaban Inhibition of Factor Xa in a Global trial versus Aspirin to prevenT Embolism in Embolic Stroke of Undetermined Source trial., Conclusion: The automated event adjudication system in combination with human adjudicators provides a streamlined and efficient approach to event adjudication in clinical trials. To immediately apply automated event adjudication, one can first consider the automated event adjudication system and involve human assistance for cases unconfirmed by the former.

Published
2023
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47. Long-Term Treatment with the Combination of Rivaroxaban and Aspirin in Patients with Chronic Coronary or Peripheral Artery Disease: Outcomes During the Open Label Extension of the COMPASS trial.

Author

Eikelboom JW, Bosch J, Connolly SJ, Tyrwitt J, Fox KAA, Muehlhofer E, Neumann C, Tasto C, Bangdiwala SI, Diaz R, Alings M, Dagenais GR, Leong DP, Lonn EM, Avezum A, Piegas LS, Widimsky P, Parkhomenko AN, Bhatt DL, Branch KRH, Probstfield JL, Lopez-Jaramillo P, Rydén L, Pogosova N, Keltai K, Keltai M, Ertl G, Stoerk S, Dans AL, Lanas F, Liang Y, Zhu J, Torp-Pedersen C, Maggioni AP, Commerford PJ, Guzik TJ, Vanassche T, Verhamme P, O'Donnell M, Tonkin AM, Varigos JD, Vinereanu D, Felix C, Kim JH, Ibrahim KS, Lewis BS, Metsarinne KP, Aboyans V, Steg PG, Hori M, Kakkar A, Anand SS, Lamy A, Sharma M, and Yusuf S

Subjects
Humans, Infant, Aspirin, Drug Therapy, Combination, Rivaroxaban, Myocardial Infarction epidemiology, Peripheral Arterial Disease diagnosis, Peripheral Arterial Disease drug therapy, Peripheral Arterial Disease epidemiology, Stroke epidemiology
Abstract

Aims: To describe outcomes of patients with chronic coronary artery disease (CAD) and/or peripheral artery disease (PAD) enrolled in the Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) randomized trial who were treated with the combination of rivaroxaban 2.5 mg twice daily and aspirin 100 mg once daily during long-term open-label extension (LTOLE)., Methods and Results: Of the 27 395 patients enrolled in COMPASS, 12 964 (mean age at baseline 67.2 years) from 455 sites in 32 countries were enrolled in LTOLE and treated with the combination of rivaroxaban and aspirin for a median of 374 additional days (range 1-1191 days). During LTOLE, the incident events per 100 patient years were as follows: for the primary outcome [cardiovascular death, stroke, or myocardial infarction (MI)] 2.35 [95% confidence interval (CI) 2.11-2.61], mortality 1.87 (1.65-2.10), stroke 0.62 (0.50-0.76), and MI 1.02 (0.86-1.19), with CIs that overlapped those seen during the randomized treatment phase with the combination of rivaroxaban and aspirin. The incidence rates for major and minor bleeding were 1.01 (0.86-1.19) and 2.49 (2.24-2.75), compared with 1.67 (1.48-1.87) and 5.11 (95% CI 4.77-5.47), respectively, during the randomized treatment phase with the combination., Conclusion: In patients with chronic CAD and/or PAD, extended combination treatment for a median of 1 year and a maximum of 3 years was associated with incidence rates for efficacy and bleeding that were similar to or lower than those seen during the randomized treatment phase, without any new safety signals., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Published
2022
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48. Comparison of Investigator-Reported vs Centrally Adjudicated Major Adverse Cardiac Events: A Secondary Analysis of the COMPASS Trial.

Author

Gaba P, Bhatt DL, Dagenais GR, Bosch J, Maggioni AP, Widimsky P, Leong D, Fox KAA, Yusuf S, and Eikelboom JW

Subjects
Male, Humans, Aged, Female, Rivaroxaban therapeutic use, Drug Therapy, Combination, Aspirin, Stroke drug therapy, Myocardial Infarction epidemiology, Myocardial Infarction prevention & control, Myocardial Infarction chemically induced, Atherosclerosis drug therapy
Abstract

Importance: In the Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) trial, there was a significant reduction in the adjudicated primary outcome among patients with stable atherosclerotic vascular disease randomized to dual pathway inhibition (rivaroxaban 2.5 mg twice daily plus aspirin 100 mg daily) vs aspirin monotherapy, but not with rivaroxaban 5 mg twice daily vs aspirin monotherapy. Whether the results are similar without adjudication is unknown., Objective: To examine the impact of dual pathway inhibition (with rivaroxaban plus aspirin) or rivaroxaban monotherapy compared with aspirin monotherapy on investigator-reported CV events and to understand the extent of concordance between investigator-reported and centrally adjudicated clinical events., Design, Setting, and Participants: This is a secondary analysis of the COMPASS trial, an international, double-blind, double-dummy, randomized clinical trial with a 3-by-2 partial factorial design that evaluated participants with stable atherosclerotic vascular disease receiving rivaroxaban plus aspirin, rivaroxaban monotherapy, or aspirin monotherapy. End points were collected by blinded site investigators and adjudicated by a blinded clinical end point committee. Data were analyzed from March 2013 through February 2017., Interventions: Participants received dual inhibition pathway (2.5 mg rivaroxaban twice daily plus 100 mg aspirin once daily), rivaroxaban monotherapy (5 mg twice daily), or aspirin monotherapy (100 mg once daily)., Main Outcomes and Measures: The primary efficacy outcome was a composite of cardiovascular (CV) death, stroke, or myocardial infarction (MI). Adjudicated and investigator-reported end points were compared., Results: A total of 27 395 patients (mean [SD] age, 68.2 [7.9] years; 78.0% men) were assessed, including 9152 patients randomized to dual pathway inhibition, 9117 patients randomized to rivaroxaban monotherapy, and 9126 patients randomized to aspirin monotherapy. Adjudication reduced the number of events by 10% to 15% for most end points. Among investigator-reported end points, dual pathway inhibition significantly reduced the rate of the primary efficacy outcome compared with aspirin alone (411 patients [4.5%] vs 542 patients [5.9%]; hazard ratio [HR], 0.75 [95% CI, 0.66-0.85]; P < .001), with similar reduction in adjudicated end points, (379 patients [4.1%] vs 496 patients [5.4%]; HR, 0.76 [95% CI, 0.66-0.86]; P < .001). Likewise, effects on ischemic end points were highly concordant (κ statistic = 0.94 [95% CI, 0.93-0.95] for the primary composite end point). Unlike with adjudicated outcomes, there was a significant reduction in the primary end point with rivaroxaban monotherapy vs aspirin monotherapy using investigator-reported events (477 patients [5.2%] vs 542 patients [5.9%]; HR, 0.88 [95% CI, 0.78-0.99]; P = .04) compared with adjudicated events (448 patients [4.9%] vs 496 patients [5.4%]; HR, 0.90 [95% CI, 0.79-1.03]; P = .12)., Conclusions and Relevance: This secondary analysis of the COMPASS trial found that whether assessed by blinded site investigators or adjudicators, dual pathway inhibition significantly reduced CV events among patients with stable atherosclerotic disease compared with aspirin plus placebo. These findings suggest that using investigator-reported events in blinded clinical trials may be a more efficient alternative to adjudication., Trial Registration: ClinicalTrials.gov Identifier: NCT01776424.

Published
2022
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49. Dulaglutide and cardiovascular and heart failure outcomes in patients with and without heart failure: a post-hoc analysis from the REWIND randomized trial.

Author

Branch KRH, Dagenais GR, Avezum A, Basile J, Conget I, Cushman WC, Jansky P, Lakshmanan M, Lanas F, Leiter LA, Pais P, Pogosova N, Raubenheimer PJ, Ryden L, Shaw JE, Sheu WHH, Temelkova-Kurktschiev T, Bethel MA, Gerstein HC, Chinthanie R, and Probstfield JL

Subjects
Humans, Hypoglycemic Agents therapeutic use, Hypoglycemic Agents adverse effects, Treatment Outcome, Incretins therapeutic use, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 drug therapy, Diabetes Mellitus, Type 2 epidemiology, Heart Failure drug therapy, Heart Failure epidemiology, Heart Failure chemically induced, Cardiovascular Diseases epidemiology
Abstract

Aims: People with diabetes are at high risk for cardiovascular events including heart failure (HF). We examined the effect of the glucagon-like peptide 1 agonist dulaglutide on incident HF events and other cardiovascular outcomes in those with or without prior HF in the randomized placebo-controlled Researching Cardiovascular Events with a Weekly Incretin in Diabetes (REWIND) trial., Methods and Results: The REWIND major adverse cardiovascular event (MACE) outcome was the first occurrence of a composite endpoint of non-fatal myocardial infarction, non-fatal stroke, or death from cardiovascular causes (including unknown causes). In this post-hoc analysis, a HF event was defined as an adjudication-confirmed hospitalization or urgent evaluation for HF. Of the 9901 participants studied over a median follow-up of 5.4 years, 213/4949 (4.3%) randomly assigned to dulaglutide and 226/4952 (4.6%) participants assigned to placebo experienced a HF event (hazard ratio [HR] 0.93, 95% confidence interval [CI] 0.77-1.12; p = 0.456). In the 853 (8.6%) participants with HF at baseline, there was no change in either MACE or HF events with dulaglutide as compared to participants without HF (p = 0.44 and 0.19 for interaction, respectively). Combined cardiovascular death and HF events were marginally reduced with dulaglutide compared to placebo (HR 0.88, 95% CI 0.78-1.00; p = 0.050) but unchanged in patients with and without HF at baseline (p = 0.31)., Conclusions: Dulaglutide was not associated with a reduction in HF events in patients with type 2 diabetes regardless of baseline HF status over 5.4 years of follow-up., (© 2022 European Society of Cardiology.)

Published
2022
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50. A novel kidney disease index reflecting both the albumin-to-creatinine ratio and estimated glomerular filtration rate, predicted cardiovascular and kidney outcomes in type 2 diabetes.

Author

Gerstein HC, Ramasundarahettige C, Avezum A, Basile J, Conget I, Cushman WC, Dagenais GR, Franek E, Lakshmanan M, Lanas F, Leiter LA, Pogosova N, Probstfield J, Raubenheimer PJ, Riddle M, Shaw J, Sheu WH, Temelkova-Kurktschiev T, Turfanda I, and Xavier D

Subjects
Albumins, Albuminuria complications, Albuminuria diagnosis, Albuminuria epidemiology, Creatinine, Glomerular Filtration Rate, Humans, Kidney, Risk Factors, Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology, Cardiovascular Diseases etiology, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 diagnosis, Diabetes Mellitus, Type 2 epidemiology, Kidney Diseases
Abstract

Background: The estimated glomerular filtration rate (eGFR) and the albumin-to-creatinine ratio (ACR) are risk factors for diabetes-related outcomes. A composite that captures information from both may provide a simpler way of assessing risk., Methods: 9115 of 9901 Researching Cardiovascular Events with a Weekly Incretin in Diabetes (REWIND) participants with both an ACR and eGFR at baseline were included in this post hoc epidemiologic analysis. The hazard of higher baseline levels of 1/eGFR and natural log transformed ACR (calculated as ln [ACR × 100] to eliminate negative values) and their interaction for incident major adverse cardiovascular events (MACE), kidney outcomes, and deaths was estimated. The hazard of the geometric mean of these two baseline measures (the kidney disease index or KDI) was also assessed., Results: A non-linear relationship was observed between 1/eGFR and all three outcomes, and between ln [ACR × 100] and the kidney outcome. There was also a negative interaction between these two risk factors with respect to MACE and death. Conversely, a linear relationship was noted between the KDI and all three outcomes. People in the highest KDI fifth experienced the highest incidence of MACE, death, and the kidney outcome (4.43, 4.56, and 5.55/100 person-years respectively). C statistics for the KDI were similar to those for eGFR and albuminuria., Conclusions: The KDI combines the baseline eGFR and ACR into a novel composite risk factor that has a simple linear relationship with incident serious outcomes in people with diabetes and additional CV risk factors. Trial Registration clinicaltrials.gov NCT01394952., (© 2022. The Author(s).)

Published
2022
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