@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 {1039, title = {Ankle brachial index combined with Framingham Risk Score to predict cardiovascular events and mortality: a meta-analysis.}, journal = {JAMA}, volume = {300}, year = {2008}, month = {2008 Jul 09}, pages = {197-208}, abstract = {

CONTEXT: Prediction models to identify healthy individuals at high risk of cardiovascular disease have limited accuracy. A low ankle brachial index (ABI) is an indicator of atherosclerosis and has the potential to improve prediction.

OBJECTIVE: To determine if the ABI provides information on the risk of cardiovascular events and mortality independently of the Framingham risk score (FRS) and can improve risk prediction.

DATA SOURCES: Relevant studies were identified. A search of MEDLINE (1950 to February 2008) and EMBASE (1980 to February 2008) was conducted using common text words for the term ankle brachial index combined with text words and Medical Subject Headings to capture prospective cohort designs. Review of reference lists and conference proceedings, and correspondence with experts was conducted to identify additional published and unpublished studies.

STUDY SELECTION: Studies were included if participants were derived from a general population, ABI was measured at baseline, and individuals were followed up to detect total and cardiovascular mortality.

DATA EXTRACTION: Prespecified data on individuals in each selected study were extracted into a combined data set and an individual participant data meta-analysis was conducted on individuals who had no previous history of coronary heart disease.

RESULTS: Sixteen population cohort studies fulfilling the inclusion criteria were included. During 480,325 person-years of follow-up of 24,955 men and 23,339 women, the risk of death by ABI had a reverse J-shaped distribution with a normal (low risk) ABI of 1.11 to 1.40. The 10-year cardiovascular mortality in men with a low ABI (< or = 0.90) was 18.7\% (95\% confidence interval [CI], 13.3\%-24.1\%) and with normal ABI (1.11-1.40) was 4.4\% (95\% CI, 3.2\%-5.7\%) (hazard ratio [HR], 4.2; 95\% CI, 3.3-5.4). Corresponding mortalities in women were 12.6\% (95\% CI, 6.2\%-19.0\%) and 4.1\% (95\% CI, 2.2\%-6.1\%) (HR, 3.5; 95\% CI, 2.4-5.1). The HRs remained elevated after adjusting for FRS (2.9 [95\% CI, 2.3-3.7] for men vs 3.0 [95\% CI, 2.0-4.4] for women). A low ABI (< or = 0.90) was associated with approximately twice the 10-year total mortality, cardiovascular mortality, and major coronary event rate compared with the overall rate in each FRS category. Inclusion of the ABI in cardiovascular risk stratification using the FRS would result in reclassification of the risk category and modification of treatment recommendations in approximately 19\% of men and 36\% of women.

CONCLUSION: Measurement of the ABI may improve the accuracy of cardiovascular risk prediction beyond the FRS.

}, keywords = {Adult, Age Factors, Aged, Aged, 80 and over, Ankle, Atherosclerosis, Blood Pressure, Brachial Artery, Cardiovascular Diseases, Cohort Studies, Confidence Intervals, Female, Global Health, Humans, Male, Middle Aged, Odds Ratio, Predictive Value of Tests, Risk Assessment, Risk Factors, Severity of Illness Index}, issn = {1538-3598}, doi = {10.1001/jama.300.2.197}, author = {Fowkes, F G R and Murray, G D and Butcher, I and Heald, C L and Lee, R J and Chambless, L E and Folsom, A R and Hirsch, A T and Dramaix, M and deBacker, G and Wautrecht, J-C and Kornitzer, M and Newman, A B and Cushman, M and Sutton-Tyrrell, K and Fowkes, F G R and Lee, A J and Price, J F and D{\textquoteright}Agostino, R B and Murabito, J M and Norman, P E and Jamrozik, K and Curb, J D and Masaki, K H and Rodr{\'\i}guez, B L and Dekker, J M and Bouter, L M and Heine, R J and Nijpels, G and Stehouwer, C D A and Ferrucci, L and McDermott, M M and Stoffers, H E and Hooi, J D and Knottnerus, J A and Ogren, M and Hedblad, B and Witteman, J C and Breteler, M M B and Hunink, M G M and Hofman, A and Criqui, M H and Langer, R D and Fronek, A and Hiatt, W R and Hamman, R and Resnick, H E and Guralnik, J and McDermott, M 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 {6803, title = {Development and validation of an ankle brachial index risk model for the prediction of cardiovascular events.}, journal = {Eur J Prev Cardiol}, volume = {21}, year = {2014}, month = {2014 Mar}, pages = {310-20}, abstract = {

BACKGROUND: The ankle brachial index (ABI) is related to risk of cardiovascular events independent of the Framingham risk score (FRS). The aim of this study was to develop and evaluate a risk model for cardiovascular events incorporating the ABI and FRS.

DESIGN: An analysis of participant data from 18 cohorts in which 24,375 men and 20,377 women free of coronary heart disease had ABI measured and were followed up for events.

METHODS: Subjects were divided into a development and internal validation dataset and an external validation dataset. Two models, comprising FRS and FRS + ABI, were fitted for the primary outcome of major coronary events.

RESULTS: In predicting events in the external validation dataset, C-index for the FRS was 0.672 (95\% CI 0.599 to 0.737) in men and 0.578 (95\% CI 0.492 to 0.661) in women. The FRS + ABI led to a small increase in C-index in men to 0.685 (95\% CI 0.612 to 0.749) and large increase in women to 0.690 (95\% CI 0.605 to 0.764) with net reclassification improvement (NRI) of 4.3\% (95\% CI 0.0 to 7.6\%, p = 0.050) and 9.6\% (95\% CI 6.1 to 16.4\%, p < 0.001), respectively. Restricting the FRS + ABI model to those with FRS intermediate 10-year risk of 10 to 19\% resulted in higher NRI of 15.9\% (95\% CI 6.1 to 20.6\%, p < 0.001) in men and 23.3\% (95\% CI 13.8 to 62.5\%, p = 0.002) in women. However, incorporating ABI in an improved newly fitted risk factor model had a nonsignificant effect: NRI 2.0\% (95\% CI 2.3 to 4.2\%, p = 0.567) in men and 1.1\% (95\% CI 1.9 to 4.0\%, p = 0.483) in women.

CONCLUSIONS: An ABI risk model may improve prediction especially in individuals at intermediate risk and when performance of the base risk factor model is modest.

}, keywords = {Adult, Aged, Aged, 80 and over, Ankle Brachial Index, Cardiovascular Diseases, Europe, European Continental Ancestry Group, Female, Humans, Male, Middle Aged, Models, Statistical, Predictive Value of Tests, Prognosis, Reproducibility of Results, Risk Assessment, Risk Factors, Sex Factors, Time Factors, United States, Young Adult}, issn = {2047-4881}, doi = {10.1177/2047487313516564}, author = {Fowkes, F G R and Murray, G D and Butcher, I and Folsom, A R and Hirsch, A T and Couper, D J and deBacker, G and Kornitzer, M and Newman, A B and Sutton-Tyrrell, K C and Cushman, M and Lee, A J and Price, J F and D{\textquoteright}Agostino, R B and Murabito, J M and Norman, Pe and Masaki, K H and Bouter, L M and Heine, R J and Stehouwer, C D A and McDermott, M M and Stoffers, H E J H and Knottnerus, J A and Ogren, M and Hedblad, B and Koenig, W and Meisinger, C and Cauley, J A and Franco, Oh and Hunink, M G M and Hofman, A and Witteman, J C and Criqui, M H and Langer, R D and Hiatt, W R and Hamman, R F} }