@article {979, title = {Associations of plasma fibrinogen levels with established cardiovascular disease risk factors, inflammatory markers, and other characteristics: individual participant meta-analysis of 154,211 adults in 31 prospective studies: the fibrinogen studies collab}, journal = {Am J Epidemiol}, volume = {166}, year = {2007}, month = {2007 Oct 15}, pages = {867-79}, abstract = {

Long-term increases in plasma fibrinogen levels of 1 g/liter are associated with an approximate doubling of risk of major cardiovascular disease outcomes, but causality remains uncertain. To quantify cross-sectional associations of fibrinogen levels with established risk factors and other characteristics, the investigators combined individual data on 154,211 apparently healthy adults from 31 prospective studies conducted between 1967 and 2003, using a linear mixed model that included random effects at the cohort level. Fibrinogen levels increased with age and showed continuous, approximately linear relations with several risk markers and slightly curvilinear associations with log triglycerides, albumin, and tobacco and alcohol consumption. Female sex, Black ethnicity, lower socioeconomic status, and alcohol abstinence were each associated with modestly higher fibrinogen levels. Approximately one third of the variation in fibrinogen levels was explained by cohort, age, and sex. An additional 7\% was explained by established risk factors (notably, positive associations with smoking and body mass index and an inverse association with high density lipoprotein cholesterol), and a further 10\% was explained by inflammatory markers (notably, a positive association with C-reactive protein). The association with body mass index was twice as strong in women as in men, whereas the association with smoking was much stronger in men. These findings substantially advance understanding of the correlates and possible determinants of fibrinogen levels.

}, keywords = {Adult, African Americans, Age Factors, Biomarkers, Body Mass Index, C-Reactive Protein, Cardiovascular Diseases, Cohort Studies, Female, Fibrinogen, Humans, Linear Models, Male, Prospective Studies, Risk Factors, Sex Factors, Smoking, Social Class, United States}, issn = {0002-9262}, doi = {10.1093/aje/kwm191}, author = {Kaptoge, S and White, I R and Thompson, S G and Wood, A M and Lewington, S and Lowe, G D O and Danesh, J} } @article {984, title = {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.}, journal = {Eur J Epidemiol}, volume = {22}, year = {2007}, month = {2007}, pages = {839-69}, 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.

}, keywords = {Albumins, Biomarkers, Cardiovascular Diseases, Databases, Factual, Far East, Humans, Inflammation, Leukocyte Count, Lipids, Lipoproteins, HDL, Prospective Studies, Risk Factors, Triglycerides}, issn = {0393-2990}, doi = {10.1007/s10654-007-9165-7}, author = {Danesh, J and Erqou, S and Walker, M and Thompson, S G and Tipping, R and Ford, C and Pressel, S and Walldius, G and Jungner, I and Folsom, A R and Chambless, L E and Knuiman, M and Whincup, P H and Wannamethee, S G and Morris, R W and Willeit, J and Kiechl, S and Santer, P and Mayr, A and Wald, N and Ebrahim, S and Lawlor, D A and Yarnell, J W G and Gallacher, J and Casiglia, E and Tikhonoff, V and Nietert, P J and Sutherland, S E and Bachman, D L and Keil, J E and Cushman, M and Psaty, B M and Tracy, R P and Tybjaerg-Hansen, A and Nordestgaard, B G and Frikke-Schmidt, R and Giampaoli, S and Palmieri, L and Panico, S and Vanuzzo, D and Pilotto, L and Simons, L and McCallum, J and Friedlander, Y and Fowkes, F G R and Lee, A J and Smith, F B and Taylor, J and Guralnik, J and Phillips, C and Wallace, R and Blazer, D and Khaw, K T and Jansson, J H and Donfrancesco, C and Salomaa, V and Harald, K and Jousilahti, P and Vartiainen, E and Woodward, M and D{\textquoteright}Agostino, R B and Wolf, P A and Vasan, R S and Pencina, M J and Bladbjerg, E M and Jorgensen, T and Moller, L and Jespersen, J and Dankner, R and Chetrit, A and Lubin, F and Rosengren, A and Wilhelmsen, L and Lappas, G and Eriksson, H and Bjorkelund, C and Cremer, P and Nagel, D and Tilvis, R and Strandberg, T and Rodriguez, B and Bouter, L M and Heine, R J and Dekker, J M and Nijpels, G and Stehouwer, C D A and Rimm, E and Pai, J and Sato, S and Iso, H and Kitamura, A and Noda, H and Goldbourt, U and Salomaa, V and Salonen, J T and Nyyss{\"o}nen, K and Tuomainen, T-P and Deeg, D and Poppelaars, J L and Meade, T and Cooper, J and Hedblad, B and Berglund, G and Engstrom, G and D{\"o}ring, A and Koenig, W and Meisinger, C and Mraz, W and Kuller, L and Selmer, R and Tverdal, A and Nystad, W and Gillum, R and Mussolino, M and Hankinson, S and Manson, J and De Stavola, B and Knottenbelt, C and Cooper, J A and Bauer, K A and Rosenberg, R D and Sato, S and Naito, Y and Holme, I and Nakagawa, H and Miura, H and Ducimetiere, P and Jouven, X and Crespo, C and Garcia-Palmieri, M and Amouyel, P and Arveiler, D and Evans, A and Ferrieres, J and Schulte, H and Assmann, G and Shepherd, J and Packard, C and Sattar, N and Cantin, B and Lamarche, B and Despr{\'e}s, J-P and Dagenais, G R and Barrett-Connor, E and Wingard, D and Bettencourt, R and Gudnason, V and Aspelund, T and Sigurdsson, G and Thorsson, B and Trevisan, M and Witteman, J and Kardys, I and Breteler, M and Hofman, A and Tunstall-Pedoe, H and Tavendale, R and Lowe, G D O and Ben-Shlomo, Y and Howard, B V and Zhang, Y and Best, L and Umans, J and Onat, A and Meade, T W and Njolstad, I and Mathiesen, E and Lochen, M L and Wilsgaard, T and Gaziano, J M and Stampfer, M and Ridker, P and Ulmer, H and Diem, G and Concin, H and Rodeghiero, F and Tosetto, A and Brunner, E and Shipley, M and Buring, J and Cobbe, S M and Ford, I and Robertson, M and He, Y and Ibanez, A M and Feskens, E J M and Kromhout, D and Collins, R and Di Angelantonio, E and Kaptoge, S and Lewington, S and Orfei, L and Pennells, L and Perry, P and Ray, K and Sarwar, N and Scherman, M and Thompson, A and Watson, S and Wensley, F and White, I R and Wood, A M} } @article {1079, title = {Systematically missing confounders in individual participant data meta-analysis of observational cohort studies.}, journal = {Stat Med}, volume = {28}, year = {2009}, month = {2009 Apr 15}, pages = {1218-37}, 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

}, keywords = {Cohort Studies, Computer Simulation, Coronary Disease, Data Interpretation, Statistical, Female, Fibrinogen, Humans, Male, Meta-Analysis as Topic, Models, Statistical}, issn = {0277-6715}, doi = {10.1002/sim.3540}, author = {Jackson, Dan and White, Ian and Kostis, J B and Wilson, A C and Folsom, A R and Wu, K and Chambless, L and Benderly, M and Goldbourt, U and Willeit, J and Kiechl, S and Yarnell, J W G and Sweetnam, P M and Elwood, P C and Cushman, M and Psaty, B M and Tracy, R P and Tybjaerg-Hansen, A and Haverkate, F and de Maat, M P M and Thompson, S G and Fowkes, F G R and Lee, A J and Smith, F B and Salomaa, V and Harald, K and Rasi, V and Vahtera, E and Jousilahti, P and D{\textquoteright}Agostino, R and Kannel, W B and Wilson, P W F and Tofler, G and Levy, D and Marchioli, R and Valagussa, F and Rosengren, A and Wilhelmsen, L and Lappas, G and Eriksson, H and Cremer, P and Nagel, D and Curb, J D and Rodriguez, B and Yano, K and Salonen, J T and Nyyss{\"o}nen, K and Tuomainen, T-P and Hedblad, B and Engstrom, G and Berglund, G and Loewel, H and Koenig, W and Hense, H W and Meade, T W and Cooper, J A and De Stavola, B and Knottenbelt, C and Miller, G J and Cooper, J A and Bauer, K A and Rosenberg, R D and Sato, S and Kitamura, A and Naito, Y and Iso, H and Salomaa, V and Harald, K and Rasi, V and Vahtera, E and Jousilahti, P and Palosuo, T and Ducimetiere, P and Amouyel, P and Arveiler, D and Evans, A E and Ferrieres, J and Juhan-Vague, I and Bingham, A and Schulte, H and Assmann, G and Cantin, B and Lamarche, B and Despr{\'e}s, J-P and Dagenais, G R and Tunstall-Pedoe, H and Lowe, G D O and Woodward, M and Ben-Shlomo, Y and Davey Smith, G and Palmieri, V and Yeh, J L and Meade, T W and Rudnicka, A and Brennan, P and Knottenbelt, C and Cooper, J A and Ridker, P and Rodeghiero, F and Tosetto, A and Shepherd, J and Lowe, G D O and Ford, I and Robertson, M and Brunner, E and Shipley, M and Feskens, E J M and Di Angelantonio, E and Kaptoge, S and Lewington, S and Lowe, G D O and Sarwar, N and Thompson, S G and Walker, M and Watson, S and White, I R and Wood, A M and Danesh, J} } @article {1213, title = {Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies.}, journal = {Lancet}, volume = {375}, year = {2010}, month = {2010 Jun 26}, pages = {2215-22}, abstract = {

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.

}, keywords = {Adult, Aged, Blood Glucose, Coronary Disease, Diabetes Complications, Diabetes Mellitus, Fasting, Female, Humans, Male, Middle Aged, Risk Factors, Stroke}, issn = {1474-547X}, doi = {10.1016/S0140-6736(10)60484-9}, author = {Sarwar, N and Gao, P and Seshasai, S R Kondapally and Gobin, R and Kaptoge, S and Di Angelantonio, E and Ingelsson, E and Lawlor, D A and Selvin, E and Stampfer, M and Stehouwer, C D A and Lewington, S and Pennells, L and Thompson, A and Sattar, N and White, I R and Ray, K K and Danesh, J} }