@article {931, title = {Regression dilution methods for meta-analysis: assessing long-term variability in plasma fibrinogen among 27,247 adults in 15 prospective studies.}, journal = {Int J Epidemiol}, volume = {35}, year = {2006}, month = {2006 Dec}, pages = {1570-8}, abstract = {

BACKGROUND: Within-person variability in measured values of a risk factor can bias its association with disease. The extent of this regression dilution bias for plasma fibrinogen was investigated using repeat measurement data collected at varying time intervals on 27 247 adults in 15 prospective studies.

METHODS: Regression dilution ratios (RDRs) were estimated from a linear regression of repeat measurements on baseline values in each study and for each time interval, and pooled allowing for within- and between-study heterogeneity. RDRs were estimated both without and with adjustment for confounders, and factors were investigated that might influence the RDRs.

RESULTS: The unadjusted overall RDR was 0.51 (95\% CI: 0.47, 0.55), which decreased to 0.46 (95\% CI: 0.42, 0.49) after adjustment for age, sex and measured values of other established vascular risk factors. The RDR did not vary materially by assay method, age, sex or smoking status, but decreased at higher levels of baseline fibrinogen.

CONCLUSION: It is appropriate to use an RDR of 0.5 to correct approximately for regression dilution bias in plasma fibrinogen values; however, this correction factor may produce somewhat conservative hazard ratios in adjusted analyses, at higher fibrinogen concentrations and in follow-up beyond a decade. More generally, the methods described in this report have widespread applicability to quantifying regression dilution bias in repeatability data from multiple prospective studies.

}, keywords = {Adult, Age Factors, Bias, Cardiovascular Diseases, Female, Fibrinogen, Humans, Male, Meta-Analysis as Topic, Prospective Studies, Regression Analysis, Risk Factors, Sex Factors, Smoking, Time Factors}, issn = {0300-5771}, doi = {10.1093/ije/dyl233}, author = {Wood, Angela M and White, Ian and Thompson, Simon G and Lewington, Sarah and Danesh, John} } @article {1563, title = {Separate and combined associations of body-mass index and abdominal adiposity with cardiovascular disease: collaborative analysis of 58 prospective studies.}, journal = {Lancet}, volume = {377}, year = {2011}, month = {2011 Mar 26}, pages = {1085-95}, abstract = {

BACKGROUND: Guidelines differ about the value of assessment of adiposity measures for cardiovascular disease risk prediction when information is available for other risk factors. We studied the separate and combined associations of body-mass index (BMI), waist circumference, and waist-to-hip ratio with risk of first-onset cardiovascular disease.

METHODS: We used individual records from 58 cohorts to calculate hazard ratios (HRs) per 1 SD higher baseline values (4.56 kg/m(2) higher BMI, 12.6 cm higher waist circumference, and 0.083 higher waist-to-hip ratio) and measures of risk discrimination and reclassification. Serial adiposity assessments were used to calculate regression dilution ratios.

RESULTS: Individual records were available for 221,934 people in 17 countries (14,297 incident cardiovascular disease outcomes; 1.87 million person-years at risk). Serial adiposity assessments were made in up to 63,821 people (mean interval 5.7 years [SD 3.9]). In people with BMI of 20 kg/m(2) or higher, HRs for cardiovascular disease were 1.23 (95\% CI 1.17-1.29) with BMI, 1.27 (1.20-1.33) with waist circumference, and 1.25 (1.19-1.31) with waist-to-hip ratio, after adjustment for age, sex, and smoking status. After further adjustment for baseline systolic blood pressure, history of diabetes, and total and HDL cholesterol, corresponding HRs were 1.07 (1.03-1.11) with BMI, 1.10 (1.05-1.14) with waist circumference, and 1.12 (1.08-1.15) with waist-to-hip ratio. Addition of information on BMI, waist circumference, or waist-to-hip ratio to a cardiovascular disease risk prediction model containing conventional risk factors did not importantly improve risk discrimination (C-index changes of -0.0001, -0.0001, and 0.0008, respectively), nor classification of participants to categories of predicted 10-year risk (net reclassification improvement -0.19\%, -0.05\%, and -0.05\%, respectively). Findings were similar when adiposity measures were considered in combination. Reproducibility was greater for BMI (regression dilution ratio 0.95, 95\% CI 0.93-0.97) than for waist circumference (0.86, 0.83-0.89) or waist-to-hip ratio (0.63, 0.57-0.70).

INTERPRETATION: BMI, waist circumference, and waist-to-hip ratio, whether assessed singly or in combination, do not importantly improve cardiovascular disease risk prediction in people in developed countries when additional information is available for systolic blood pressure, history of diabetes, and lipids.

FUNDING: British Heart Foundation and UK Medical Research Council.

}, keywords = {Age Factors, Blood Pressure, Body Mass Index, Cardiovascular Diseases, Cholesterol, Cholesterol, HDL, Diabetes Mellitus, Female, Humans, Male, Middle Aged, Obesity, Abdominal, Proportional Hazards Models, Prospective Studies, Risk Assessment, Sex Factors, Smoking, Systole, Waist Circumference, Waist-Hip Ratio}, issn = {1474-547X}, doi = {10.1016/S0140-6736(11)60105-0}, author = {Wormser, David and Kaptoge, Stephen and Di Angelantonio, Emanuele and Wood, Angela M and Pennells, Lisa and Thompson, Alex and Sarwar, Nadeem and Kizer, Jorge R and Lawlor, Debbie A and Nordestgaard, B{\o}rge G and Ridker, Paul and Salomaa, Veikko and Stevens, June and Woodward, Mark and Sattar, Naveed and Collins, Rory and Thompson, Simon G and Whitlock, Gary and Danesh, John} } @article {1399, title = {Lipid-related markers and cardiovascular disease prediction.}, journal = {JAMA}, volume = {307}, year = {2012}, month = {2012 Jun 20}, pages = {2499-506}, abstract = {

CONTEXT: The value of assessing various emerging lipid-related markers for prediction of first cardiovascular events is debated.

OBJECTIVE: To determine whether adding information on apolipoprotein B and apolipoprotein A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 to total cholesterol and high-density lipoprotein cholesterol (HDL-C) improves cardiovascular disease (CVD) risk prediction.

DESIGN, SETTING, AND PARTICIPANTS: Individual records were available for 165,544 participants without baseline CVD in 37 prospective cohorts (calendar years of recruitment: 1968-2007) with up to 15,126 incident fatal or nonfatal CVD outcomes (10,132 CHD and 4994 stroke outcomes) during a median follow-up of 10.4 years (interquartile range, 7.6-14 years).

MAIN OUTCOME MEASURES: Discrimination of CVD outcomes and reclassification of participants across predicted 10-year risk categories of low (<10\%), intermediate (10\%-<20\%), and high (>=20\%) risk.

RESULTS: The addition of information on various lipid-related markers to total cholesterol, HDL-C, and other conventional risk factors yielded improvement in the model{\textquoteright}s discrimination: C-index change, 0.0006 (95\% CI, 0.0002-0.0009) for the combination of apolipoprotein B and A-I; 0.0016 (95\% CI, 0.0009-0.0023) for lipoprotein(a); and 0.0018 (95\% CI, 0.0010-0.0026) for lipoprotein-associated phospholipase A2 mass. Net reclassification improvements were less than 1\% with the addition of each of these markers to risk scores containing conventional risk factors. We estimated that for 100,000 adults aged 40 years or older, 15,436 would be initially classified at intermediate risk using conventional risk factors alone. Additional testing with a combination of apolipoprotein B and A-I would reclassify 1.1\%; lipoprotein(a), 4.1\%; and lipoprotein-associated phospholipase A2 mass, 2.7\% of people to a 20\% or higher predicted CVD risk category and, therefore, in need of statin treatment under Adult Treatment Panel III guidelines.

CONCLUSION: In a study of individuals without known CVD, the addition of information on the combination of apolipoprotein B and A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 mass to risk scores containing total cholesterol and HDL-C led to slight improvement in CVD prediction.

}, keywords = {Aged, Biomarkers, Cardiovascular Diseases, Cholesterol, HDL, Cohort Studies, Female, Humans, Lipoproteins, Male, Middle Aged, Risk Assessment}, issn = {1538-3598}, doi = {10.1001/jama.2012.6571}, author = {Di Angelantonio, Emanuele and Gao, Pei and Pennells, Lisa and Kaptoge, Stephen and Caslake, Muriel and Thompson, Alexander and Butterworth, Adam S and Sarwar, Nadeem and Wormser, David and Saleheen, Danish and Ballantyne, Christie M and Psaty, Bruce M and Sundstr{\"o}m, Johan and Ridker, Paul M and Nagel, Dorothea and Gillum, Richard F and Ford, Ian and Ducimetiere, Pierre and Kiechl, Stefan and Koenig, Wolfgang and Dullaart, Robin P F and Assmann, Gerd and D{\textquoteright}Agostino, Ralph B and Dagenais, Gilles R and Cooper, Jackie A and Kromhout, Daan and Onat, Altan and Tipping, Robert W and G{\'o}mez-de-la-C{\'a}mara, Agust{\'\i}n and Rosengren, Annika and Sutherland, Susan E and Gallacher, John and Fowkes, F Gerry R and Casiglia, Edoardo and Hofman, Albert and Salomaa, Veikko and Barrett-Connor, Elizabeth and Clarke, Robert and Brunner, Eric and Jukema, J Wouter and Simons, Leon A and Sandhu, Manjinder and Wareham, Nicholas J and Khaw, Kay-Tee and Kauhanen, Jussi and Salonen, Jukka T and Howard, William J and Nordestgaard, B{\o}rge G and Wood, Angela M and Thompson, Simon G and Boekholdt, S Matthijs and Sattar, Naveed and Packard, Chris and Gudnason, Vilmundur and Danesh, John} } @article {6811, title = {Association of Cardiometabolic Multimorbidity With Mortality.}, journal = {JAMA}, volume = {314}, year = {2015}, month = {2015 Jul 7}, pages = {52-60}, abstract = {

IMPORTANCE: The prevalence of cardiometabolic multimorbidity is increasing.

OBJECTIVE: To estimate reductions in life expectancy associated with cardiometabolic multimorbidity.

DESIGN, SETTING, AND PARTICIPANTS: Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689,300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128,843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499,808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates.

EXPOSURES: A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI).

MAIN OUTCOMES AND MEASURES: All-cause mortality and estimated reductions in life expectancy.

RESULTS: In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95\% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95\% CI, 2.0-2.2) in those with stroke, 2.0 (95\% CI, 1.9-2.2) in those with MI, 3.7 (95\% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95\% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95\% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95\% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy.

CONCLUSIONS AND RELEVANCE: Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.

}, keywords = {Adult, Aged, Comorbidity, Diabetes Mellitus, Female, Humans, Life Expectancy, Male, Middle Aged, Mortality, Myocardial Infarction, Risk Factors, Stroke}, issn = {1538-3598}, doi = {10.1001/jama.2015.7008}, author = {Di Angelantonio, Emanuele and Kaptoge, Stephen and Wormser, David and Willeit, Peter and Butterworth, Adam S and Bansal, Narinder and O{\textquoteright}Keeffe, Linda M and Gao, Pei and Wood, Angela M and Burgess, Stephen and Freitag, Daniel F and Pennells, Lisa and Peters, Sanne A and Hart, Carole L and H{\r a}heim, Lise Lund and Gillum, Richard F and Nordestgaard, B{\o}rge G and Psaty, Bruce M and Yeap, Bu B and Knuiman, Matthew W and Nietert, Paul J and Kauhanen, Jussi and Salonen, Jukka T and Kuller, Lewis H and Simons, Leon A and van der Schouw, Yvonne T and Barrett-Connor, Elizabeth and Selmer, Randi and Crespo, Carlos J and Rodriguez, Beatriz and Verschuren, W M Monique and Salomaa, Veikko and Sv{\"a}rdsudd, Kurt and van der Harst, Pim and Bj{\"o}rkelund, Cecilia and Wilhelmsen, Lars and Wallace, Robert B and Brenner, Hermann and Amouyel, Philippe and Barr, Elizabeth L M and Iso, Hiroyasu and Onat, Altan and Trevisan, Maurizio and D{\textquoteright}Agostino, Ralph B and Cooper, Cyrus and Kavousi, Maryam and Welin, Lennart and Roussel, Ronan and Hu, Frank B and Sato, Shinichi and Davidson, Karina W and Howard, Barbara V and Leening, Maarten J G and Leening, Maarten and Rosengren, Annika and D{\"o}rr, Marcus and Deeg, Dorly J H and Kiechl, Stefan and Stehouwer, Coen D A and Nissinen, Aulikki and Giampaoli, Simona and Donfrancesco, Chiara and Kromhout, Daan and Price, Jackie F and Peters, Annette and Meade, Tom W and Casiglia, Edoardo and Lawlor, Debbie A and Gallacher, John and Nagel, Dorothea and Franco, Oscar H and Assmann, Gerd and Dagenais, Gilles R and Jukema, J Wouter and Sundstr{\"o}m, Johan and Woodward, Mark and Brunner, Eric J and Khaw, Kay-Tee and Wareham, Nicholas J and Whitsel, Eric A and Nj{\o}lstad, Inger and Hedblad, Bo and Wassertheil-Smoller, Sylvia and Engstr{\"o}m, Gunnar and Rosamond, Wayne D and Selvin, Elizabeth and Sattar, Naveed and Thompson, Simon G and Danesh, John} } @article {7664, title = {Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies.}, journal = {Lancet}, volume = {391}, year = {2018}, month = {2018 04 14}, pages = {1513-1523}, abstract = {

BACKGROUND: Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular disease.

METHODS: We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose-response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12{\textperiodcentered}5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5{\textperiodcentered}6 years [5th-95th percentile 1{\textperiodcentered}04-13{\textperiodcentered}5]) from 71 011 participants from 37 studies.

FINDINGS: In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5{\textperiodcentered}4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality risk around or below 100 g per week. Alcohol consumption was roughly linearly associated with a higher risk of stroke (HR per 100 g per week higher consumption 1{\textperiodcentered}14, 95\% CI, 1{\textperiodcentered}10-1{\textperiodcentered}17), coronary disease excluding myocardial infarction (1{\textperiodcentered}06, 1{\textperiodcentered}00-1{\textperiodcentered}11), heart failure (1{\textperiodcentered}09, 1{\textperiodcentered}03-1{\textperiodcentered}15), fatal hypertensive disease (1{\textperiodcentered}24, 1{\textperiodcentered}15-1{\textperiodcentered}33); and fatal aortic aneurysm (1{\textperiodcentered}15, 1{\textperiodcentered}03-1{\textperiodcentered}28). By contrast, increased alcohol consumption was log-linearly associated with a lower risk of myocardial infarction (HR 0{\textperiodcentered}94, 0{\textperiodcentered}91-0{\textperiodcentered}97). In comparison to those who reported drinking >0-<=100 g per week, those who reported drinking >100-<=200 g per week, >200-<=350 g per week, or >350 g per week had lower life expectancy at age 40 years of approximately 6 months, 1-2 years, or 4-5 years, respectively.

INTERPRETATION: In current drinkers of alcohol in high-income countries, the threshold for lowest risk of all-cause mortality was about 100 g/week. For cardiovascular disease subtypes other than myocardial infarction, there were no clear risk thresholds below which lower alcohol consumption stopped being associated with lower disease risk. These data support limits for alcohol consumption that are lower than those recommended in most current guidelines.

FUNDING: UK Medical Research Council, British Heart Foundation, National Institute for Health Research, European Union Framework 7, and European Research Council.

}, issn = {1474-547X}, doi = {10.1016/S0140-6736(18)30134-X}, author = {Wood, Angela M and Kaptoge, Stephen and Butterworth, Adam S and Willeit, Peter and Warnakula, Samantha and Bolton, Thomas and Paige, Ellie and Paul, Dirk S and Sweeting, Michael and Burgess, Stephen and Bell, Steven and Astle, William and Stevens, David and Koulman, Albert and Selmer, Randi M and Verschuren, W M Monique and Sato, Shinichi and Nj{\o}lstad, Inger and Woodward, Mark and Salomaa, Veikko and Nordestgaard, B{\o}rge G and Yeap, Bu B and Fletcher, Astrid and Melander, Olle and Kuller, Lewis H and Balkau, Beverley and Marmot, Michael and Koenig, Wolfgang and Casiglia, Edoardo and Cooper, Cyrus and Arndt, Volker and Franco, Oscar H and Wennberg, Patrik and Gallacher, John and de la C{\'a}mara, Agustin G{\'o}mez and V{\"o}lzke, Henry and Dahm, Christina C and Dale, Caroline E and Bergmann, Manuela M and Crespo, Carlos J and van der Schouw, Yvonne T and Kaaks, Rudolf and Simons, Leon A and Lagiou, Pagona and Schoufour, Josje D and Boer, Jolanda M A and Key, Timothy J and Rodriguez, Beatriz and Moreno-Iribas, Conchi and Davidson, Karina W and Taylor, James O and Sacerdote, Carlotta and Wallace, Robert B and Quiros, J Ramon and Tumino, Rosario and Blazer, Dan G and Linneberg, Allan and Daimon, Makoto and Panico, Salvatore and Howard, Barbara and Skeie, Guri and Strandberg, Timo and Weiderpass, Elisabete and Nietert, Paul J and Psaty, Bruce M and Kromhout, Daan and Salamanca-Fernandez, Elena and Kiechl, Stefan and Krumholz, Harlan M and Grioni, Sara and Palli, Domenico and Huerta, Jos{\'e} M and Price, Jackie and Sundstr{\"o}m, Johan and Arriola, Larraitz and Arima, Hisatomi and Travis, Ruth C and Panagiotakos, Demosthenes B and Karakatsani, Anna and Trichopoulou, Antonia and K{\"u}hn, Tilman and Grobbee, Diederick E and Barrett-Connor, Elizabeth and van Schoor, Natasja and Boeing, Heiner and Overvad, Kim and Kauhanen, Jussi and Wareham, Nick and Langenberg, Claudia and Forouhi, Nita and Wennberg, Maria and Despr{\'e}s, Jean-Pierre and Cushman, Mary and Cooper, Jackie A and Rodriguez, Carlos J and Sakurai, Masaru and Shaw, Jonathan E and Knuiman, Matthew and Voortman, Trudy and Meisinger, Christa and Tj{\o}nneland, Anne and Brenner, Hermann and Palmieri, Luigi and Dallongeville, Jean and Brunner, Eric J and Assmann, Gerd and Trevisan, Maurizio and Gillum, Richard F and Ford, Ian and Sattar, Naveed and Lazo, Mariana and Thompson, Simon G and Ferrari, Pietro and Leon, David A and Smith, George Davey and Peto, Richard and Jackson, Rod and Banks, Emily and Di Angelantonio, Emanuele and Danesh, John} }