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117 results on '"D'Agostino, R.B."'

6. Stability of the Framingham Nutritional Risk Score and its component nutrients over 8 years: the Framingham Nutrition Studies

Author

Kimokoti, R.W., Newby, P.K., Gona, P., Zhu, L., Campbell, W.R., D'Agostino, R.B., and Millen, B.E.

Subjects
Epidemiology -- Research, Diet -- Physiological aspects -- Health aspects, Food/cooking/nutrition, Health
Abstract

Background/Objectives: Diet quality indices are increasingly used in nutrition epidemiology as dietary exposures in relation to health outcomes. However, literature on the long-term stability of these indices is limited. We aimed to assess the stability of the validated Framingham Nutritional Risk Score (FNRS) and its component nutrients over 8 years, as well as the validity of the follow-up FNRS. Subjects/Methods: Framingham Offspring/Spouse Study women and men (n = 1734) aged 22-76 years were evaluated over 8 years. Individuals' nutrient intake and nutritional risk scores were assessed using 3-day dietary records administered at baseline (1984-1988) and at follow-up (1992-1996). Agreement between baseline and follow-up FNRS and nutrient intakes was evaluated by Bland-Altman method; stability was assessed using intra-class correlation (ICC) and weighted Kappa statistics. The effect of diet quality (as assessed by the FNRS) on cardiometabolic risk factors was evaluated using analysis of covariance. Results: Modest changes from baseline ([less than or equal to] 15%) were observed in nutrient intake. The stability coefficients for the FNRS (ICC: women, 0.49; men, 0.46; P < 0.0001) and many nutrients (ICC ≥ 0.3) were moderate. Over half of the women and men (58%) remained in the same or contiguous baseline and follow-up quartile of the FNRS and few (3-4%) shifted > 1 quartile. The FNRS was directly associated with body mass index in women (P Conclusions: The FNRS and its constituent nutrients remained relatively stable over 8 years of follow-up. The stability of diet quality has implications for prospective epidemiological investigations. European journal of Clinical Nutrition (2012) 66, 336-344; doi: 10.1038/ejcn.2011.167; published online 5 October 2011 Keywords: long-term stability; dietary quality indices; nutrients, Introduction Diet is a key determinant of health outcomes (Willett, 1998). Historically, studies have focused on single nutrient or food exposures. However, such approaches are inherently confounded by food and [...]

Published
2012
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7. Genetic and non-genetic correlates of vitamins K and D

Author

Shea, M.K., Benjamin, E.J., Dupuis, J., Massaro, J.M., Jacques, P.F., D'Agostino, R.B., Sr., Ordovas, J.M., O'Donnell, C.J., Dawson-Hughes, B., Vasan, R.S., and Booth, S.L.

Subjects
Vitamin K -- Genetic aspects, Alfacalcidol -- Genetic aspects, Calcifediol -- Genetic aspects, Vitamin D -- Genetic aspects, Genetic research
Abstract

Objective: To assess the genetic and nongenetic correlates of circulating measures of vitamins K and D status in a community-based sample of men and women. Subjects/Methods: A cross-sectional study of 1762 participants of the Framingham Offspring Study (919 women; mean age 59 years). Vitamin K status was measured as plasma phylloquinone and serum percent undercarboxylated osteocalcin (ucOC), and vitamin D was measured using plasma 25-hydroxyvitamin D (25(OH)D). Associations between vitamin K status and vitamin D status with biologically plausible nongenetic factors were assessed using stepwise regression. Heritability and linkage were determined using Sequential Oligogenic Linkage Analysis Routines (SOLAR). Results: Nongenetic factors accounted for 20.1 and 12.3% of the variability in plasma phylloquinone in men and women respectively, with triglycerides and phylloquinone intake being the primary correlates. In men 12.2% and in women 14.6% of the variability in %ucOC was explained by nongenetic factors in our models. Heritability estimates for these vitamin K status biomarkers were nonsignificant. Season, vitamin D intake, high-density lipoprotein (HDL) cholesterol and waist circumference explained 24.7% (men) and 24.2% (women) of the variability in plasma 25(OH)D. Of the three vitamins examined, only 25(OH)D was significantly heritable (heritability estimate = 28.8%, P Conclusions: Variability in biomarkers of vitamin K status was attributed to nongenetic factors, whereas plasma 25(OH)D was found to be significantly heritable. Further studies are warranted to investigate genetic loci influencing vitamin D status. doi:10.1038/sj.ejcn.1602959; published online 21 November 2007 Keywords: vitamin K; phylloquinone; undercarboxylated osteocalcin; vitamin D; heritability; genetics, Introduction Vitamins K and D are two nutrients involved in bone health (Cockayne et al., 2006). Vitamin K functions as a cofactor in the y-carboxylation of specific proteins, of which [...]

Published
2009

8. World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions

Author

Angelantonio, E. di, Kaptoge, S., Pennells, L., Bacquer, D. de, Cooney, M.T., Kavousi, M., Stevens, G., Riley, L., Savin, S., Altay, S., Amouyel, P., Assmann, G., Bell, S., Ben-Shlomo, Y., Berkman, L., Beulens, J.W., Bjorkelund, C., Blaha, M.J., Blazer, D.G., Bolton, T., Bonita, R., Brenner, B.H., Brunner, E.J., Casiglia, E., Chamnan, P., Choi, Y.H., Chowdhury, R., Coady, S., Crespo, C.J., Cushman, M., Dagenais, G.R., D'Agostino, R.B., Daimon, M., Davidson, K.W., Engstrom, G., Fang, X.H., Ford, I., Gallacher, J., Gansevoort, R.T., Gaziano, T.A., Giampaoli, S., Grandits, G., Grimsgaard, S., Grobbee, D.E., Gudnason, V., Guo, Q., Humphries, S., Iso, H., Jukema, J.W., Kauhanen, J., Kengne, A.P., Khalili, D., Khan, T., Knuiman, M., Koenig, W., Kromhout, D., Krumholz, H.M., Lam, T.H., Laughlin, G., Ibanez, A.M., Moons, K.G.M., Nietert, P.J., Ninomiya, T., Nordestgaard, B.G., O'Donnell, C., Palmieri, L., Patel, A., Perel, P., Price, J.F., Costa, R.B.D.E., Ridker, P.M., Rodriguez, B., Rosengren, A., Roussel, R., Sakurai, M., Salomaa, V., Sato, S., Schottker, B., Shara, N., Shaw, J.E., Shin, H.C., Simons, L.A., Sofianopoulou, E., Sundstrom, J., Tolonen, H., Ueshima, H., Volzke, H., Wallace, R.B., Wareham, N.J., Willeit, P., Wood, D., Wood, A., Zhao, D., Onuma, O., Woodward, M., Danaei, G., Roth, G., Mendis, S., Graham, I., Varghese, C., Ezzati, M., Jackson, R., Danesh, J., Nambi, V., Matsushita, K., Couper, D., Diabetes, A., Zimmet, P.Z., Barr, E.L.M., Atkins, R., Whincup, P.H., Study, B., Kiechl, S., Willeit, J., Rungger, G., Sofat, R., Dale, C., Casas, J.P., Tikhonoff, V., Hunt, K.J., Sutherland, S.E., Psaty, B.M., Tracy, R., Frikke-Schmidt, R., Jensen, G.B., Schnohr, P., Donfrancesco, C., Vanuzzo, D., Panico, S., Balkau, B., Bonnet, F., Fumeron, F., Simons, J., McLachlan, S., Guralnik, J., Khaw, K.T., Brenner, H., Zhang, Y., Holleczek, B., Cohort, F., Vartiainen, E., Jousilahti, P., Harald, K., Massaro, J.J., Pencina, M., Ramachandran, V., Susa, S., Oizumi, T., Kayama, T., Wilhelmsen, L., Lissner, L., Hange, D., Mehlig, K., Hata, J., Yoshida, D., Hirakawa, Y., Rutters, F., Elders, P.J.M., Kyowa, I., Kiyama, M., Yamagishi, K., Tuomainen, T.P., Virtanen, J., Salonen, J.T., Meade, T.W., Nilsson, P.M., Melander, O., Boer, I.H. de, DeFilippis, A.P., Kuller, L.H., Juan, S.I., Gillum, R.F., Kirkland, S., Shimbo, D., Schwartz, J.E., Imano, H., Harst, P. van der, Hillige, J.L., Bakker, S.J., Dallongeville, J., Ferrieres, J., Moitry, M., Stott, D.J., Despres, J.P., Laughlin, G.A., Daniels, L.B., McEvoy, L.K., Aspelund, T., Thorsson, B., Gudmundsson, E.F., Aribas, E., Rueda-Ochoa, O.L., Ikram, M.K., Heshmatollah, A., Ikram, M.A., Dorr, M., Nauck, M., Howard, B., Can, G., Ishizaki, M., Wilsgaard, T., Mathiesen, E., Giedraitis, V., Ingelsson, M., Cook, N., Buring, J., Schouw, Y.T. van der, Claessen, H., Rothenbacher, D., Arndt, V., Study, W.I., Shipley, M., Packard, C., Robertson, M., Young, R., Feskens, E., Geleijnse, J.M., Fang, X., Gu, D.F., Huxley, R., Imai, Y., Kim, H.C., Pan, W.H., Rodgers, A., Suh, I., Town, A., Okayama, A., Maegawa, H., Nakamura, M., Aoki, N., Wu, Z.S., Yao, C.H., Luszcz, M., Tang, Z., Liu, L.S., Xie, J.X., Norton, R., Ameratunga, S., MacMahon, S., Whitlock, G., Knuiman, M.W., Christensen, H., Wu, X.G., Zhou, J., Yu, X.H., Tamakoshi, W.A., Wu, Z.L., Chen, L.Q., Shan, G.L., Sritara, P., Duan, X.F., Li, Y.H., Jiang, C.Q., Woo, J., Ho, S.C., Hong, Z., Huang, M.S., Zhou, B., Fuh, J.L., Kita, Y., Choudhury, S.R., Jee, S.H., Kim, Woodward, M, Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Epidemiology, Epidemiology and Data Science, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, and APH - Health Behaviors & Chronic Diseases

Subjects
Male, 10-YEAR RISK, BLOOD-PRESSURE, 0302 clinical medicine, Risk Factors, Medicine and Health Sciences, Medicine, Uganda, Cardiac and Cardiovascular Systems, Prospective Studies, 030212 general & internal medicine, Aged, 80 and over, Medicine(all), Kardiologi, lcsh:Public aspects of medicine, PRIMARY-CARE, Public Health, Global Health, Social Medicine and Epidemiology, General Medicine, Middle Aged, 3. Good health, Pooled analysis, Cardiovascular Diseases, Egypt, Female, Adult, PROSPECTIVE COHORTS, 030231 tropical medicine, 195 COUNTRIES, Primary care, World Health Organization, Risk Assessment, Article, World health, POOLED ANALYSIS, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Primary prevention, Environmental health, SYSTEMATIC ANALYSIS, Humans, Aged, CHINESE POPULATION, Chinese population, business.industry, Individual participant data, lcsh:RA1-1270, R1, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Disease risk, business, INDIVIDUAL PARTICIPANT DATA, PRIMARY PREVENTION
Abstract

Background: To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. Methods: In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40–80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. Findings: Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0·685 (95% CI 0·629–0·741) to 0·833 (0·783–0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40–64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. Interpretation: We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. Funding: World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research. The WHO CVD Risk Chart Working Group, for complete list of authors see http://dx.doi.org/10.1016/S2214-109X(19)30318-3

Published
2019
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10. The internal validity of a dietary pattern analysis. The Framingham Nutrition Studies. (Research Report)

Author

Quatromoni, P.A., Copenhafer, D.L., Demissie, S., D'Agostino, R.B., O'Horo, C.E., Nam, B-H, and Millen, B.E.

Subjects
Heart diseases -- Risk factors -- Research, Observational studies -- Evaluation -- Health aspects -- Research, Nutrition -- Research -- Health aspects, Food habits -- Health aspects -- Research, Health, Social sciences, Evaluation, Research, Risk factors, Health aspects
Abstract

Study objectives: To examine the internal validity of a dietary pattern analysis and its ability to discriminate clusters of people with similar dietary patterns using independently assessed nutrient intakes and [...]

Published
2002

12. Predicting new-onset HF in patients undergoing coronary or peripheral angiography: results from the Catheter Sampled Blood Archive in Cardiovascular Diseases (CASABLANCA) study

Author

Ibrahim, N.E., Lyass, A., Gaggin, H.K., Liu, Yuyin, Kimmenade, R.R.J. van, Motiwala, S.R., D'Agostino, R.B., Sr., and Januzzi, J.L., Jr.

Subjects
All institutes and research themes of the Radboud University Medical Center, Vascular damage Radboud Institute for Health Sciences [Radboudumc 16], GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries)
Abstract

Contains fulltext : 191420.pdf (Publisher’s version ) (Open Access)

Published
2018

13. Single-Molecule Counting of High-Sensitivity Troponin I in Patients Referred for Diagnostic Angiography: Results From the CASABLANCA (Catheter Sampled Blood Archive in Cardiovascular Diseases) Study

Author

McCarthy, C.P., Ibrahim, N.E., Lyass, A., Li, Y., Gaggin, H.K., Simon, M.L., Mukai, R., Gandhi, P., Kelly, N., Motiwala, S.R., Kimmenade, R.R.J. van, Massaro, J.M., D'Agostino, R.B., Sr., Januzzi, J.L., Jr., McCarthy, C.P., Ibrahim, N.E., Lyass, A., Li, Y., Gaggin, H.K., Simon, M.L., Mukai, R., Gandhi, P., Kelly, N., Motiwala, S.R., Kimmenade, R.R.J. van, Massaro, J.M., D'Agostino, R.B., Sr., and Januzzi, J.L., Jr.

Abstract

Contains fulltext : 190538.pdf (publisher's version ) (Open Access), BACKGROUND: The meaning of high-sensitivity troponin I (hsTnI) concentrations in patients without acute myocardial infarction (MI) requires clarity. We hypothesized that among patients referred for diagnostic coronary angiography without acute MI, hsTnI concentrations would correlate with prevalent coronary artery disease (CAD) and predict incident cardiovascular events and mortality. METHODS AND RESULTS: We measured hsTnI using a single-molecule counting assay (99th percentile, 6 ng/L) in samples from 991 patients obtained at the time of angiography. Concentrations of hsTnI were assessed relative to the severity of CAD and prognosis during mean follow-up of 3.7 years. Median hsTnI concentration was 4.19 ng/L; 38% of patients had hsTnI concentrations >/=99th percentile. Across increasing hsTnI quartiles, patients had higher prevalence of angiographic CAD; in multivariate models, hsTnI >/=99th percentile independently predicted obstructive CAD (odds ratio: 2.57; P<0.001) and incident MI (hazard ratio [HR]: 2.68; P<0.001), cardiovascular death (HR: 2.29; P=0.001), and all-cause death (HR: 1.84; P=0.004). In those with >70% coronary stenosis, hsTnI >/=99th percentile independently predicted incident MI (HR: 1.87; P=0.01), cardiovascular mortality (HR: 2.74; P=0.001), and the composite end point of MI and all-cause death (HR: 2.06; P<0.001). In participants with coronary stenosis <70%, hsTnI >/=99th percentile even more strongly predicted incident MI (HR: 8.41; P<0.001), cardiovascular mortality (HR: 3.60; P=0.03), and the composite end point of MI and all-cause death (HR: 3.62; P<0.001). CONCLUSIONS: In a large prospective cohort of patients who were free of prevalent MI and undergoing diagnostic coronary angiography, hsTnI concentrations were associated with higher prevalence of CAD and predicted incident MI, cardiovascular death, and all-cause death. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00842868.

Published
2018

14. Endothelin-1 Measurement in Patients Undergoing Diagnostic Coronary Angiography-Results from the Catheter Sampled Blood Archive in Cardiovascular Diseases (CASABLANCA) Study

Author

Ibrahim, N.E., Gupta, R., Lyass, A., Li, Yiwei, Shrestha, Shreya, McCarthy, C.P., Kimmenade, R.R.J. van, D'Agostino, R.B., Januzzi, J.L., Jr., Ibrahim, N.E., Gupta, R., Lyass, A., Li, Yiwei, Shrestha, Shreya, McCarthy, C.P., Kimmenade, R.R.J. van, D'Agostino, R.B., and Januzzi, J.L., Jr.

Abstract

Item does not contain fulltext

Published
2018

15. Association of Cardiometabolic Multimorbidity With Mortality The Emerging Risk Factors Collaboration

Author

Angelantonio, E. di, Kaptoge, S., Wormser, D., Willeit, P., Butterworth, A.S., Bansal, N., O'Keeffe, L.M., Gao, P., Wood, A.M., Burgess, S., Freitag, D.F., Pennells, L., Peters, S.A., Hart, C.L., Haheim, L.L., Gillum, R.F., Nordestgaard, B.G., Psaty, B.M., Yeap, B.B., Knuiman, M.W., Nietert, P.J., Kauhanen, J., Salonen, J.T., Kuller, L.H., Simons, L.A., Schouw, Y.T. van der, Barrett-Connor, E., Selmer, R., Crespo, C.J., Rodriguez, B., Verschuren, W.M.M., Salomaa, V., Svardsudd, K., Harst, P. van der, Bjorkelund, C., Wilhelmsen, L., Wallace, R.B., Brenner, H., Amouyel, P., Barr, E.L.M., Iso, H., Onat, A., Trevisan, M., D'Agostino, R.B., Cooper, C., Kavousi, M., Welin, L., Roussel, R., Hu, F.B., Sato, S., Davidson, K.W., Howard, B.V., Leening, M., Rosengren, A., Dorr, M., Deeg, D.J.H., Kiechl, S., Stehouwer, C.D.A., Nissinen, A., Giampaoli, S., Donfrancesco, C., Kromhout, D., Price, J.F., Peters, A., Meade, T.W., Casiglia, E., Lawlor, D.A., Gallacher, J., Nagel, D., Franco, O.H., Assmann, G., Dagenais, G.R., Jukema, J.W., Sundstrom, J., Woodward, M., Brunner, E.J., Khaw, K.T., Wareham, N.J., Whitsel, E.A., Njolstad, I., Hedblad, B., Wassertheil-Smoller, S., Engstrom, G., Rosamond, W.D., Selvin, E., Sattar, N., Thompson, S.G., Danesh, J., and Emerging Risk Factors Collaboratio

Published
2015

16. Incident Type 2 Myocardial Infarction in a Cohort of Patients Undergoing Coronary or Peripheral Arterial Angiography

Author

Gaggin, H.K., Liu, Y., Lyass, A., Kimmenade, R.R.J. van, Motiwala, S.R., Kelly, N.P., Mallick, A., Gandhi, P.U., Ibrahim, N.E., Simon, M.L., Bhardwaj, A., Belcher, A.M., Harisiades, J.E., Massaro, J.M., D'Agostino, R.B., Sr., Januzzi, J.L., Jr., Gaggin, H.K., Liu, Y., Lyass, A., Kimmenade, R.R.J. van, Motiwala, S.R., Kelly, N.P., Mallick, A., Gandhi, P.U., Ibrahim, N.E., Simon, M.L., Bhardwaj, A., Belcher, A.M., Harisiades, J.E., Massaro, J.M., D'Agostino, R.B., Sr., and Januzzi, J.L., Jr.

Abstract

Item does not contain fulltext, BACKGROUND: Despite growing recognition of type 2 myocardial infarction (T2MI; related to supply/demand mismatch), little is known about its risk factors or its association with outcome. METHODS: A single-center cohort of patients undergoing coronary or peripheral angiography with or without intervention was prospectively enrolled and followed for incident type 1 and T2MI, and major adverse cardiovascular events (MACE, a composite of all-cause death, nonfatal myocardial infarction [MI], heart failure, stroke, transient ischemic attack, peripheral arterial complication, and cardiac arrhythmia), as well. T2MI was adjudicated using criteria from the Third Universal Definition of MI. Baseline characteristics, blood samples, and angiography information were obtained. Major end points subsequent to first MI were assessed using landmark analyses to compare the rates of first events only where everyone with a prior history of any MACE before MI were censored and adjusted for follow-up times. Cox proportional hazard models were used for time-to-event analyses with age and sex forced into all models and additional covariates evaluated by using the stepwise option for the selection. RESULTS: One thousand two hundred fifty-one patients were enrolled and followed for a median of 3.4 years. Of these patients, 152 (12.2%) had T2MI during follow-up; T2MI was frequently recurrent. Multivariable predictors of T2MI were older age, lower systolic blood pressure, history of coronary artery disease, heart failure, chronic obstructive pulmonary disease, diabetes mellitus, nitrate use, and elevated concentrations of glucose, N-terminal pro-B type natriuretic peptide, and cystatin C. Patients with T2MI had higher rates of subsequent adverse events than those without T2MI (per 100 person-years: MACE, 53.7 versus 21.1, P<0.001; all-cause death, 23.3 versus 3.3, P<0.001; cardiovascular death, 17.5 versus 2.6, P<0.001; heart failure events, 22.4 versus 7.4, P<0.001); these rates are similar to

Published
2017

17. Mortality following cardiovascular and bleeding events occurring beyond 1 year after coronary stenting: A secondary analysis of the Dual Antiplatelet Therapy (DAPT) Study.

Author

Hopkins J., McGarry T., Nygaard T., Pow T., Larkin T., Caulfield T., Stys T., Lee T., Mansouri V., Srinivas V., Gupta V., Marquardt W., Ballard W., Bachinsky W., Colyer W., Dillon W., Felten W., French W., Kuehl W., Nicholas W., Nicholson W., Phillips W., Khatib Y., Al-Saghir Y., Hawa Z., Masud Z., Jafar Z., Muller D., Meredith I., Rankin J., Worthley M., Jepson N., Thompson P., Hendriks R., Whitbourn R., Duffy S., Stasek J., Novobilsky K., Naplava R., Coufal Z., Vaquette B., Bressollette E., Teiger E., Coste P., Rihani R., Darius H., Bergmann M.W., Radke P., Sebastian P., Strasser R., Hoffmann S., Behrens S., Moebius-Winkler S., Rutsch W., Lupkovics G., Horvath I., Kancz S., Forster T., Koszegi Z., Devlin G., Hart H., Elliott J., Ormiston J., Abernathy M., Fisher N., Kay P., Harding S., Jaffe W., Hoffmann A., Sosnowski C., Trebacz J., Buszman P., Dobrzycki S., Kornacewicz-Jach Z., Iancu A.C., Ginghina C.D., Matei C., Dobreanu D., Bolohan F.R., Dorobantu M., Jacques A., Jain A., Bakhai A., Gershlick A., Adamson D., Newby D., Felmeden D., Purcell I., Edmond J., Irving J., De Belder M., Pitt M., Kelly P., O'Kane P., Clifford P., Suresh V., Secemsky E.A., Yeh R.W., Kereiakes D.J., Cutlip D.E., Cohen D.J., Steg P.G., Cannon C.P., Apruzzese P.K., D'Agostino R.B., Massaro J.M., Mauri L., Kaplan A., Ahmed A., Ahmed A.-H., Albirini A., Moreyra A., Rabinowitz A., Shroff A., Moak A., Jacobs A., Kabour A., Gupta A., Irimpen A., Rosenthal A., Taussig A., Ferraro A., Chhabra A., Pucillo A., Spaedy A., White A., Pratsos A., Shakir A., Ghitis A., Agarwal A., Chawla A., Tang A., Barker B., Bertolet B., Uretsky B., Erickson B., Rama B., McLaurin B., Dearing B., Negus B., Price B., Brott B., Bhambi B., Bowers B., Watt B., Donohue B., Hassel C.D., Croft C., Lambert C., O'Shaughnessy C., Shoultz C., Kim C., Caputo C., Nielson C., Scott C., Wolfe C., McKenzie C., Brachfeld C., Thieling C., Fisher D., Simon D., Churchill D., Dobies D., Eich D., Goldberg D., Griffin D., Henderson D., Kandzari D., Lee D., Lewis D., Mego D., Paniagua D., Rizik D., Roberts D., Safley D., Abbott D., Shaw D., Temizer D., Canaday D., Myears D., Westerhausen D., Ebersole D., Netz D., Baldwin D., Letts D., Harlamert E., Kosinski E., Portnay E., Mahmud E., Korban E., Hockstad E., Rivera E., Shawl F., Shamoon F., Kiernan F., Aycock G.R., Schaer G., Kunz G., Kichura G., Myers G., Pilcher G., Tadros G., Kaddissi G.I., Ramadurai G., Eaton G., Elsner G., Mishkel G., Simonian G., Piegari G., Chen H., Liberman H., Aronow H., Tamboli H.P., Dotani I., Marin J., Fleischhauer J.F., Leggett J., Mills J., Phillips J., Revenaugh J., Mann J.T., Wilson J., Pattanayak J., Aji J., Strain J., Patel J., Carr J., Moses J., Chen J.-C., Williams J., Greenberg J., Cohn J., Douglas J., Gordon J., Griffin J., Hawkins J., Katopodis J., Lopez J., Marshall J., Wang J., Waltman J., Saucedo J., Galichia J., McClure M., Kozina J., Stella J., Tuma J., Kieval J., Giri K., Ramanathan K., Allen K., Atassi K., Baran K., Khaw K., Clayton K., Croce K., Skelding K., Patel K., Garratt K., Harjai K., Chandrasekhar K., Kalapatapu K., Lin L., Dean L., Barr L., MacDonald L., Cannon L., Satler L., Gruberg L., Tami L., Bikkina M., Shah M., Atieh M., Chauhan M., Litt M., Unterman M., Lechin M., Zughaib M., Fisch M., Grabarczyk M., Greenberg M., Lurie M., Rothenberg M., Stewart M., Purvis M., Hook M., Leesar M., Buchbinder M., Weiss M., Guerrero M., Abu-Fadel M., Ball M., Chang M., Cunningham M., Del Core M., Jones M., Kelberman M., Lim M., Ragosta M., Rinaldi M., Rosenberg M., Savage M., Tamberella M., Kellett M., Vidovich M., Effat M., Mirza M.A., Khan M., Dib N., Laufer N., Kleiman N., Farhat N., Amjadi N., Schechtmann N., Bladuell N., Quintana O., Gigliotti O., Best P., Flaherty P., Hall P., Gordon P., Gurbel P., Ho P., Luetmer P., Mahoney P., Mullen P., Teirstein P., Tolerico P., Ramanathan P., Kerwin P., Lee P.V., Kraft P., Wyman R.M., Gonzalez R., Kamineni R., Dave R., Sharma R., Prashad R., Aycock R., Quesada R., Goodroe R., Magorien R., Randolph R., Bach R., Kettelkamp R., Paulus R., Waters R., Zelman R., Ganim R., Bashir R., Applegate R., Feldman R., Frankel R., Hibbard R., Jobe R., Jumper R., Maholic R., Siegel R., Smith R., Stoler R., Watson R., Wheatley R., Gammon R., Hill R., Sundrani R., Caputo R., Jenkins R., Stella R., Germanwala S., Hadeed S., Ledford S., Dube S., Gupta S., Davis S., Martin S., Waxman S., Dixon S., Naidu S., Potluri S., Cook S., Crowley S., Kirkland S., McIntyre S., Thew S., Lin S., Marshalko S., Guidera S., Hearne S., Karas S., Manoukian S., Rowe S., Yakubov S., Pollock S., Banerjee S., Allaqaband S., Choi S., Mulukutla S., Papadakos S., Bajwa T., Addo T., Schreiber T., Haldis T., Mathew T., Hopkins J., McGarry T., Nygaard T., Pow T., Larkin T., Caulfield T., Stys T., Lee T., Mansouri V., Srinivas V., Gupta V., Marquardt W., Ballard W., Bachinsky W., Colyer W., Dillon W., Felten W., French W., Kuehl W., Nicholas W., Nicholson W., Phillips W., Khatib Y., Al-Saghir Y., Hawa Z., Masud Z., Jafar Z., Muller D., Meredith I., Rankin J., Worthley M., Jepson N., Thompson P., Hendriks R., Whitbourn R., Duffy S., Stasek J., Novobilsky K., Naplava R., Coufal Z., Vaquette B., Bressollette E., Teiger E., Coste P., Rihani R., Darius H., Bergmann M.W., Radke P., Sebastian P., Strasser R., Hoffmann S., Behrens S., Moebius-Winkler S., Rutsch W., Lupkovics G., Horvath I., Kancz S., Forster T., Koszegi Z., Devlin G., Hart H., Elliott J., Ormiston J., Abernathy M., Fisher N., Kay P., Harding S., Jaffe W., Hoffmann A., Sosnowski C., Trebacz J., Buszman P., Dobrzycki S., Kornacewicz-Jach Z., Iancu A.C., Ginghina C.D., Matei C., Dobreanu D., Bolohan F.R., Dorobantu M., Jacques A., Jain A., Bakhai A., Gershlick A., Adamson D., Newby D., Felmeden D., Purcell I., Edmond J., Irving J., De Belder M., Pitt M., Kelly P., O'Kane P., Clifford P., Suresh V., Secemsky E.A., Yeh R.W., Kereiakes D.J., Cutlip D.E., Cohen D.J., Steg P.G., Cannon C.P., Apruzzese P.K., D'Agostino R.B., Massaro J.M., Mauri L., Kaplan A., Ahmed A., Ahmed A.-H., Albirini A., Moreyra A., Rabinowitz A., Shroff A., Moak A., Jacobs A., Kabour A., Gupta A., Irimpen A., Rosenthal A., Taussig A., Ferraro A., Chhabra A., Pucillo A., Spaedy A., White A., Pratsos A., Shakir A., Ghitis A., Agarwal A., Chawla A., Tang A., Barker B., Bertolet B., Uretsky B., Erickson B., Rama B., McLaurin B., Dearing B., Negus B., Price B., Brott B., Bhambi B., Bowers B., Watt B., Donohue B., Hassel C.D., Croft C., Lambert C., O'Shaughnessy C., Shoultz C., Kim C., Caputo C., Nielson C., Scott C., Wolfe C., McKenzie C., Brachfeld C., Thieling C., Fisher D., Simon D., Churchill D., Dobies D., Eich D., Goldberg D., Griffin D., Henderson D., Kandzari D., Lee D., Lewis D., Mego D., Paniagua D., Rizik D., Roberts D., Safley D., Abbott D., Shaw D., Temizer D., Canaday D., Myears D., Westerhausen D., Ebersole D., Netz D., Baldwin D., Letts D., Harlamert E., Kosinski E., Portnay E., Mahmud E., Korban E., Hockstad E., Rivera E., Shawl F., Shamoon F., Kiernan F., Aycock G.R., Schaer G., Kunz G., Kichura G., Myers G., Pilcher G., Tadros G., Kaddissi G.I., Ramadurai G., Eaton G., Elsner G., Mishkel G., Simonian G., Piegari G., Chen H., Liberman H., Aronow H., Tamboli H.P., Dotani I., Marin J., Fleischhauer J.F., Leggett J., Mills J., Phillips J., Revenaugh J., Mann J.T., Wilson J., Pattanayak J., Aji J., Strain J., Patel J., Carr J., Moses J., Chen J.-C., Williams J., Greenberg J., Cohn J., Douglas J., Gordon J., Griffin J., Hawkins J., Katopodis J., Lopez J., Marshall J., Wang J., Waltman J., Saucedo J., Galichia J., McClure M., Kozina J., Stella J., Tuma J., Kieval J., Giri K., Ramanathan K., Allen K., Atassi K., Baran K., Khaw K., Clayton K., Croce K., Skelding K., Patel K., Garratt K., Harjai K., Chandrasekhar K., Kalapatapu K., Lin L., Dean L., Barr L., MacDonald L., Cannon L., Satler L., Gruberg L., Tami L., Bikkina M., Shah M., Atieh M., Chauhan M., Litt M., Unterman M., Lechin M., Zughaib M., Fisch M., Grabarczyk M., Greenberg M., Lurie M., Rothenberg M., Stewart M., Purvis M., Hook M., Leesar M., Buchbinder M., Weiss M., Guerrero M., Abu-Fadel M., Ball M., Chang M., Cunningham M., Del Core M., Jones M., Kelberman M., Lim M., Ragosta M., Rinaldi M., Rosenberg M., Savage M., Tamberella M., Kellett M., Vidovich M., Effat M., Mirza M.A., Khan M., Dib N., Laufer N., Kleiman N., Farhat N., Amjadi N., Schechtmann N., Bladuell N., Quintana O., Gigliotti O., Best P., Flaherty P., Hall P., Gordon P., Gurbel P., Ho P., Luetmer P., Mahoney P., Mullen P., Teirstein P., Tolerico P., Ramanathan P., Kerwin P., Lee P.V., Kraft P., Wyman R.M., Gonzalez R., Kamineni R., Dave R., Sharma R., Prashad R., Aycock R., Quesada R., Goodroe R., Magorien R., Randolph R., Bach R., Kettelkamp R., Paulus R., Waters R., Zelman R., Ganim R., Bashir R., Applegate R., Feldman R., Frankel R., Hibbard R., Jobe R., Jumper R., Maholic R., Siegel R., Smith R., Stoler R., Watson R., Wheatley R., Gammon R., Hill R., Sundrani R., Caputo R., Jenkins R., Stella R., Germanwala S., Hadeed S., Ledford S., Dube S., Gupta S., Davis S., Martin S., Waxman S., Dixon S., Naidu S., Potluri S., Cook S., Crowley S., Kirkland S., McIntyre S., Thew S., Lin S., Marshalko S., Guidera S., Hearne S., Karas S., Manoukian S., Rowe S., Yakubov S., Pollock S., Banerjee S., Allaqaband S., Choi S., Mulukutla S., Papadakos S., Bajwa T., Addo T., Schreiber T., Haldis T., and Mathew T.

Abstract

Importance: Early cardiovascular and bleeding events after coronary stenting are associated with high risk of morbidity and mortality. Objective(s): To assess the prognosis of cardiovascular and bleeding events occurring beyond 1 year after coronary stenting. Design, Setting, and Participant(s): This secondary analysis is derived from data from the Dual Antiplatelet Therapy (DAPT) Study, a multi center trial involving 220 US and in ternational clinical sites from 11 countries. The study dateswere August 2009 to May 2014. Individuals who underwent coronary stenting and completed 12 months of thienopyridine plus aspirin therapy without ischemic or bleeding events remained on an aspirin regimen and were randomized to continued thienopyridine therapy vs placebo for 18 additional months. Individuals were then followed up for 3 additional months while receiving aspirin therapy alone. The analysis began in August 2015. Exposures: Ischemic events (myocardial infarction not related to stent thrombosis, stent thrombosis, and ischemic stroke) and bleeding events (Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Arteries [GUSTO] classification moderate or severe bleeding). Main Outcomes and Measures: Ischemic events (myocardial infarction not related to stent thrombosis, stent thrombosis, and ischemic stroke) and bleeding events (GUSTO classification moderate or severe bleeding). Death at 21 months after randomization (33 months after coronary stenting). Result(s): Intotal, 25 682 individuals older than 18 years with an indication for coronarystentingwere enrolled, and 11 648(meanage,61.3 years; 25.1%female)were randomized. After randomization, 478 individuals (4.1%) had 502 ischemic events (306 with myocardial infarction, 113 with stent thrombosis, and 83 with ischemic stroke), and 232 individuals (2.0%) had 235 bleeding events (155 with moderate and 80 with severe bleeding). Among individuals with ischemic events, 52(10.9%) died. The annualize

Published
2017

18. A genome-wide scan for circulating levels of fibrinogen in the Framingham Heart Study

Author

Yang, Q., Tofler, G.H., Cupples, L.A., Larson, M.G., Levy, D., D'Agostino, R.B., and O'Donnell, C.J.

Subjects
Framingham, Massachusetts -- Health aspects, Genetic disorders -- Research, Fibrinogen -- Physiological aspects, Coronary heart disease -- Genetic aspects, Stroke (Disease) -- Genetic aspects, Biological sciences
Published
2001

19. RE: Drug risk assessment and data reuse

Author

Toh, S., Avorn, J., D'Agostino, R.B., Gurwitz, J.H., Psaty, B.M., Rothman, K.J., Saag, K.G., Sturkenboom, M.C.J.M., Vandenbroucke, J.P., Winterstein, A.G., Strom, B.L., and Medical Informatics

Published
2014

20. Re-using Mini-Sentinel data following rapid assessments of potential safety signals via modular analytic programs

Author

Toh, S., Avorn, J., D'Agostino, R.B., Gurwitz, J.H., Psaty, B.M., Rothman, K.J., Saag, K.G., Sturkenboom, M.C.J.M., Vandenbroucke, J.P., Winterstein, A.G., Strom, B.L., and Medical Informatics

Subjects
Mini-Sentinel, pharmacoepidemiology, active surveillance, empirical Bayesian, data splitting
Abstract

The U.S. Food and Drug Administration (FDA)'s Mini-Sentinel pilot has created a distributed data system with over 125 million lives and nearly 350 million person-years of observation time. The pilot allows the FDA to use modular analytic programs to assess suspected safety signals quickly. The FDA convened a committee to assess the implications of such rapid assessments on subsequent analyses of the same product-outcome pair using the same data. The committee offers several non-binding recommendations based on the strength of the knowledge of the suspected association before running the analysis: signal generation (an analysis with no prior), signal refinement (an analysis with a weak or moderate prior), and signal evaluation (an analysis with a strong prior). The committee believes that modular programs (MPs) are most useful for signal refinement. If MPs are used for analyses with no or weak/moderate priors, the committee members generally agree that the data may be re-used if certain conditions are met. When there is a strong prior, the committee recommends that a protocol-based assessment be used; Mini-Sentinel data may be analyzed by MPs and re-used only under very uncommon circumstances. The committee agrees that any subsequent assessment of the same product-outcome pair that follows an MP analysis should not be interpreted as independent confirmation of the association, such as would be established via replication of the same product-outcome association in two different populations. Instead, the follow-up assessment should be interpreted as an analysis that has reduced insofar as possible systematic errors that may have been present or residual in the original MP analysis. The committee also discussed how this general framework may apply to two completed rapid assessments of dabigatran and bleeding risk and of olmesartan and celiac disease risk. Copyright (c) 2013 John Wiley & Sons, Ltd.

Published
2013

21. Adult height and the risk of cause-specific death and vascular morbidity in 1 million people: individual participant meta-analysis

Author

Wormser, D., Angelantonio, E. di, Kaptoge, S., Wood, A.M., Gao, P., Sun, Q., Walldius, G., Selmer, R., Verschuren, W.M.M., Bueno-de-Mesquita, H.B., Engstrom, G., Ridker, P.M., Njolstad, I., Iso, H., Holme, I., Giampaoli, S., Tunstall-Pedoe, H., Gaziano, J.M., Brunner, E., Kee, F., Tosetto, A., Meisinger, C., Brenner, H., Ducimetiere, P., Whincup, P.H., Tipping, R.W., Ford, I., Cremer, P., Hofman, A., Wilhelmsen, L., Clarke, R., Boer, I.H. de, Jukema, J.W., Ibanez, A.M., Lawlor, D.A., D'Agostino, R.B., Rodriguez, B., Casiglia, E., Stehouwer, C.D.A., Simons, L.A., Nietert, P.J., Barrett-Connor, E., Panagiotakos, D.B., Bjorkelund, C., Strandberg, T.E., Wassertheil-Smoller, S., Blazer, D.G., Meade, T.W., Welin, L., Svardsudd, K., Woodward, M., Nissinen, A., Kromhout, D., Jorgensen, T., Tilvis, R.S., Guralnik, J.M., Rosengren, A., Taylor, J.O., Kiechl, S., Dagenais, G.R., Fowkes, F.G.R., Wallace, R.B., Khaw, K.T., Shaffer, J.A., Visser, M., Kauhanen, J., Salonen, J.T., Gallacher, J., Ben-Shlomo, Y., Kitamura, A., Sundstrom, J., Wennberg, P., Kiyohara, Y., Daimon, M., Camara, A.G. de la, Cooper, J.A., Onat, A., Devereux, R., Mukamal, K.J., Dankner, R., Knuiman, M.W., Crespo, C.J., Gansevoort, R.T., Goldbourt, U., Nordestgaard, B.G., Shaw, J.E., Mussolino, M., Nakagawa, H., Fletcher, A., Kuller, L.H., Gillum, R.F., Gudnason, V., Assmann, G., Wald, N., Jousilahti, P.R., Greenland, P., Trevisan, M., Ulmer, H., Butterworth, A.S., Folsom, A.R., Davey-Smith, G., Hu, F.B., Danesh, J., and Emerging Risk Factors Collaboratio

Subjects
meta-analysis, epidemiological study, Height, cardiovascular disease, cause-specific mortality, cancer
Published
2012

22. Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease

Author

Min, J.K. (James), Dunning, A. (Allison), Gransar, H. (Heidi), Achenbach, S. (Stephan), Lin, F.Y. (Fay), Al-Mallah, M. (Mouaz), Budoff, M.J. (Matthew J.), Callister, T.Q. (Tracy), Chang, H.-J. (Hyuk-Jae), Cademartiri, F. (Filippo), Maffei, E. (Erica), Chinnaiyan, K. (Kavitha), Chow, B.J.W. (Benjamin), D'Agostino, R.B. (Ralph), Delago, A. (Augustin), Friedman, J. (John), Hadamitzky, M. (Martin), Hausleiter, J. (Jörg), Hayes, S.W. (Sean W.), Kaufmann, P.A. (Philipp A.), Raff, G.L. (Gilbert), Shaw, L.J. (Leslee J.), Thomson, L.E.J. (Louise), Villines, T.C. (Todd), Cury, R.C. (Ricardo), Feuchtner, G.M. (Gudrun), Kim, Y.-J. (Yong-Jin), Leipsic, J. (Jonathon), Marques, H. (Hugo), Berman, D.S. (Daniel S.), Pencina, M. (Michael), Min, J.K. (James), Dunning, A. (Allison), Gransar, H. (Heidi), Achenbach, S. (Stephan), Lin, F.Y. (Fay), Al-Mallah, M. (Mouaz), Budoff, M.J. (Matthew J.), Callister, T.Q. (Tracy), Chang, H.-J. (Hyuk-Jae), Cademartiri, F. (Filippo), Maffei, E. (Erica), Chinnaiyan, K. (Kavitha), Chow, B.J.W. (Benjamin), D'Agostino, R.B. (Ralph), Delago, A. (Augustin), Friedman, J. (John), Hadamitzky, M. (Martin), Hausleiter, J. (Jörg), Hayes, S.W. (Sean W.), Kaufmann, P.A. (Philipp A.), Raff, G.L. (Gilbert), Shaw, L.J. (Leslee J.), Thomson, L.E.J. (Louise), Villines, T.C. (Todd), Cury, R.C. (Ricardo), Feuchtner, G.M. (Gudrun), Kim, Y.-J. (Yong-Jin), Leipsic, J. (Jonathon), Marques, H. (Hugo), Berman, D.S. (Daniel S.), and Pencina, M. (Michael)

Abstract

Objective To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors. Methods Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9093 patients for coronary computed tomography angiography (CCTA) followed for 2.0 years (CCTA-1); 2) 2132 patients for CCTA followed for 1.6 years (CCTA-2); and 3) 2779 patients for exercise myocardial perfusion scintigraphy (MPS) followed for 5.0 years. A best-fit model from CCTA-1 for prediction of death or myocardial infarction was developed, with integer values proportional to regression coefficients. Discrimination was assessed using C-statistic. The validated model was tested for estimation of the likelihood of obstructive coronary artery disease, defined as ≥50% stenosis, as compared with the method of Diamond and Forrester. Primary outcomes included all-cause mortality and nonfatal myocardial infarction. Secondary outcomes included prevalent angiographically obstructive coronary artery disease. Results In CCTA-1, best-fit model discriminated individuals at risk of death or myocardial infarction (C-statistic 0.76). The integer model ranged from 3 to 13, corresponding to 3-year death risk or myocardial infarction of 0.25% to 53.8%. When applied to CCTA-2 and MPS cohorts, the model demonstrated C-statistics of 0.71 and 0.77, respectively. Both best-fit (C = 0.76; 95% confidence interval [CI], 0.746-0.771) and integer models (C = 0.71; 95% CI, 0.693-0.719) performed better than Diamond and Forrester (C = 0.64; 95% CI, 0.628-0.659) for estimating obstructive coronary artery disease. Conclusions For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease.

Published
2015
Full Text
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23. Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies

Author

Thompson, S. Kaptoge, S. White, I. Wood, A. Perry, P. Danesh, J. The Emerging Risk Factors Collaboration Thompson, S.G. Kaptoge, S. White, I.R. Wood, A.M. Perry, P.L. Tipping, R.W. Ford, C.E. Simpson, L.M. Walldius, G. Jungner, I. Chambless, L.E. Panagiotakos, D.B. Pitsavos, C. Chrysohoou, C. Stefanadis, C. Knuiman, M. Goldbourt, U. Benderly, M. Tanne, D. Whincup, P.H. Wannamethee, S.G. Morris, R.W. Willeit, J. Kiechl, S. Santer, P. Mayr, A. Lawlor, D.A. Yarnell, J.W.G. Gallacher, J. Casiglia, E. Tikhonoff, V. Nietert, P.J. Sutherland, S.E. Bachman, D.L. Keil, J.E. Cushman, M. Tracy, R.P. Tybjærg-Hansen, A. Nordestgaard, B.G. Benn, M. Frikke- Schmidt, R. Giampaoli, S. Palmieri, L. Panico, S. Vanuzzo, D. Gómez de la Cámara, A. Gómez- Gerique, J.A. Simons, L. McCallum, J. Friedlander, Y. Fowkes, F.G.R. Lee, A.J. Taylor, J. Guralnik, J.M. Wallace, R. Guralnik, J. Blazer, D.G. Guralnik, J.M. Guralnik, J.M. Khaw, K.-T. Brenner, H. Raum, E. Müller, H. Rothenbacher, D. Jansson, J.H. Wennberg, P. Nissinen, A. Donfrancesco, C. Salomaa, V. Harald, K. Jousilahti, P. Vartiainen, E. Woodward, M. D'Agostino, R.B. Vasan, R.S. Pencina, M.J. Bladbjerg, E.M. Jørgensen, T. Jespersen, J. Møller, L. Dankner, R. Chetrit, A. Lubin, F. Rosengren, A. Lappas, G. Björkelund, C. Lissner, L. Bengtsson, C. Cremer, P. Nagel, D. Tilvis, R.S. Strandberg, T.E. Kiyohara, Y. Arima, H. Doi, Y. Ninomiya, T. Rodriguez, B. Dekker, J.M. Nijpels, G. Stehouwer, C.D.A. Rimm, E. Pai, J.K. Sato, S. Kitamura, A. Iso, H. Goldbourt, U. Noda, H. Harald, K. Jousilahti, P. Vartiainen, E. Salonen, J.T. Tuomainen, T.-P. Deeg, D.J.H. Poppelaars, J.L. Meade, T.W. Cooper, J.A. Hedblad, B. Berglund, G. Engstrom, G. Verschuren, W.M.M. Blokstra, A. Cushman, M. Shea, S. Döring, A. Koenig, W. Meisinger, C. Mraz, W. Bas Bueno-de-Mesquita, H. Kuller, L.H. Grandits, G. Selmer, R. Tverdal, A. Nystad, W. Gillum, R. Mussolino, M. Rimm, E. Manson, J.E. Pai, J.K. Meade, T.W. Cooper, J.A. Cooper, J.A. Knottenbelt, C. Bauer, K.A. Naito, Y. Holme, I. Hankinson, S. Tverdal, A. Nystad, W. Nakagawa, H. Miura, K. Ducimetiere, P. Jouven, X. Crespo, C.J. Garcia Palmieri, M.R. Amouyel, P. Arveiler, D. Evans, A. Ferrieres, J. Schulte, H. Assmann, G. Shepherd, J. Packard, C.J. Sattar, N. Ford, I. Cantin, B. Després, J.-P. Dagenais, G.R. Barrett-Connor, E. Wingard, D.L. 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, G.D.O. Ben-Shlomo, Y. Howard, B.V. Zhang, Y. Umans, J. Onat, A. Davey-Smith, G. Wilsgaard, T. Ingelsson, E. Lind, L. Giedraitis, V. Lannfelt, L. Gaziano, J.M. Ridker, P. Gaziano, J.M. Ridker, P. Ulmer, H. Diem, G. Concin, H. Tosetto, A. Rodeghiero, F. Wassertheil-Smoller, S. Manson, J.E. Marmot, M. Clarke, R. Collins, R. Brunner, E. Shipley, M. Ridker, P. Buring, J. Shepherd, J. Cobbe, S.M. Robertson, M. He, Y. Marín Ibañez, A. Feskens, E.J.M. Kromhout, D. Collins, R. Di Angelantonio, E. Erqou, S. Kaptoge, S. Lewington, S. Orfei, L. Pennells, L. Perry, P.L. Ray, K.K. Sarwar, N. Alexander, M. Thompson, A. Thompson, S.G. Walker, M. Watson, S. Wensley, F. White, I.R. Wood, A.M.

Abstract

Background Meta-analysis of individual participant time-to-event data from multiple prospective epidemiological studies enables detailed investigation of exposure-risk relationships, but involves a number of analytical challenges. Methods This article describes statistical approaches adopted in the Emerging Risk Factors Collaboration, in which primary data from more than 1 million participants in more than 100 prospective studies have been collated to enable detailed analyses of various risk markers in relation to incident cardiovascular disease outcomes. Results Analyses have been principally based on Cox proportional hazards regression models stratified by sex, undertaken in each study separately. Estimates of exposure-risk relationships, initially unadjusted and then adjusted for several confounders, have been combined over studies using meta-analysis. Methods for assessing the shape of exposure-risk associations and the proportional hazards assumption have been developed. Estimates of interactions have also been combined using meta-analysis, keeping separate within-and between-study information. Regression dilution bias caused by measurement error and within-person variation in exposures and confounders has been addressed through the analysis of repeat measurements to estimate corrected regression coefficients. These methods are exemplified by analysis of plasma fibrinogen and risk of coronary heart disease, and Stata code is made available. Conclusion Increasing numbers of meta-analyses of individual participant data from observational data are being conducted to enhance the statistical power and detail of epidemiological studies. The statistical methods developed here can be used to address the needs of such analyses. © The Author 2010; all rights reserved.

Published
2010

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

Author

Tipping, R.W. Ford, C.E. Simpson, L.M. Walldius, G. Jungner, I. Folsom, A.R. Chambless, L. Panagiotakos, D. Pitsavos, C. Chrysohoou, C. Stefanadis, C. Goldbourt, U. Benderly, M. Tanne, D. Whincup, P. Wannamethee, S.G. Morris, R.W. Kiechl, S. Willeit, J. Santer, P. Mayr, A. Wald, N. Ebrahim, S. Lawlor, D. Yarnell, J. Gallacher, J. Casiglia, E. Tikhonoff, V. Nietert, P.J. Sutherland, S.E. Bachman, D.L. Cushman, M. Psaty, B.M. Tracy, R. Tybjærg-Hansen, A. Nordestgaard, B.G. Frikke-Schmidt, R. Kamstrup, P.R. Giampaoli, S. Palmieri, L. Panico, S. Vanuzzo, D. Pilotto, L. De La Cámara, A.G. Gómez Gerique, J.A. Simons, L. McCallum, J. Friedlander, Y. Fowkes, F.G.R. Lee, A. Smith, F.B. Taylor, J. Guralnik, J.M. Phillips, C.L. Wallace, R.B. Blazer, D.G. Brenner, H. Raum, E. Müller, H. Rothenbacher, D. Jansson, J.-H. Wennberg, P. Nissinen, A. Donfrancesco, C. Salomaa, V. Harald, K. Jousilahti, P. Vartiainen, E. Woodward, M. D’Agostino, R.B. Wolf, P.A. Vasan, R.S. Pencina, M.J. Bladbjerg, E.-M. 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.S. Strandberg, T.E. Rodriguez, B. Dekker, J. Nijpels, G. Stehouwer, C.D.A. Rimm, E. Pai, J.K. Sato, S. Iso, H. Kitamura, A. Noda, H. Salonen, J.T. Nyyssönen, K. Tuomainen, T.-P. Deeg, D.J.H. Poppelaars, J.L. Hedblad, B. Berglund, G. Engström, G. Verschuren, W.M.M. Blokstra, A. Döring, A. Koenig, W. Meisinger, C. Mraz, W. Bueno-De-Mesquita, H.B. Kuller, L.H. Grandits, G. Selmer, R. Tverdal, A. Nystad, W. Gillum, R.F. Mussolino, M. Hankinson, S. Manson, J.E. Cooper, J.A. Bauer, K.A. Naito, Y. Holme, I. Nakagawa, H. Miura, K. Ducimetiere, P. Jouven, X. Luc, G. Crespo, C.J. Garcia Palmieri, M.R. Amouyel, P. Arveiler, D. Evans, A. Ferrieres, J. Schulte, H. Assmann, G. Shepherd, J. Packard, C.J. Sattar, N. Ford, I. Cantin, B. Lamarche, B. Després, J.-P. Dagenais, G.R. Barrett-Connor, E. Daniels, L.B. Laughlin, G.A. Gudnason, V. Aspelund, T. Sigurdsson, G. Thorsson, B. Trevisan, M. Witteman, J. Kardys, I. Breteler, M.M.B. Hofman, A. Tunstall-Pedoe, H. Tavendale, R. Lowe, G. Ben-Shlomo, Y. Davey-Smith, G. Howard, B.V. Zhang, Y. Best, L. Umans, J. Onat, A. Njølstad, I. Mathiesen, E.B. Løchen, M.-L. Wilsgaard, T. Ingelsson, E. Sundström, J. Lind, L. Lannfelt, L. Gaziano, J.M. Stampfer, M. Ridker, P.M. Ulmer, H. Diem, G. Concin, H. Tosetto, A. Rodeghiero, F. Marmot, M. Clarke, R. Collins, R. Fletcher, A. Brunner, E. Shipley, M. Buring, J. Cobbe, S. Robertson, M. He, Y. Ibañez, A.M. Feskens, E. Kromhout, D. Walker, M. Watson, S. Di Angelantonio, E. Erqou, S. Kaptoge, S. Lewington, S. Orfei, L. Pennells, L. Perry, P.L. Ray, K.K. Sarwar, N. Alexander, M. Thompson, A. Thompson, S.G. Wensley, F. White, I.R. Wood, A.M. Danesh, J.

Abstract

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 firstever 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 personyears 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. ©2009 American Medical Association. All rights reserved.

Published
2009

25. Net reclassification improvement and integrated discrimination improvement require calibrated models: Relevance from a marker and model perspective

Author

Leening, M.J.G. (Maarten), Steyerberg, E.W. (Ewout), Calster, B. (Ben) Van, D'Agostino, R.B. (Ralph), Pencina, M. (Michael), Leening, M.J.G. (Maarten), Steyerberg, E.W. (Ewout), Calster, B. (Ben) Van, D'Agostino, R.B. (Ralph), and Pencina, M. (Michael)

Abstract

Introduction For the last three decades, clinical prediction models have mainly been evaluated on the basis of their ability to discriminate between persons who develop the event of interest and persons who do not, as quantified by the c-statistic or area under the receiver operator characteristic curve (AUC). The AUC considers sensitivity and specificity of the model over all possible cut-points of predicted risk. However, prediction models are often used to classify patients into risk categories that correspond to diagnostic or therapeutic decisions. This provoked the idea of comparing models according to their ability to adequately assign clinical risk categories based on absolute risk estimates. Analyses of risk reclassification have hit the ground running: uptake of measures such as net reclassification improvement (NRI) has been enormous, and guidance documents on evaluations of markers and prediction models embraced it as a step prior to full-blown cost-effectiveness analysis.More recently, several researchers reviewed the current applications of reclassification analysis and expressed concerns about inappropriate use.

Published
2014
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26. Glycated hemoglobin measurement and prediction of cardiovascular disease

Author

Angelantonio, E. (Emanuele) di, Gao, P. (Pei), Khan, H. (Hassan), Butterworth, A.S. (Adam), Wormser, D. (David), Kaptoge, S. (Stephen), Kondapally Seshasai, S.R. (Sreenivasa Rao), Thompson, A. (Alex), Sarwar, S. (Sheryar), Willeit, J. (Johann), Ridker, P.M. (Paul), Barr, E.L.M., Khaw, K-T. (Kay-Tee), Psaty, B.M. (Bruce), Brenner, H. (Hermann), Balkau, B. (Beverley), Dekker, J.M. (Jacqueline), Lawlor, D.A. (Debbie), Daimon, M. (Makoto), Njølstad, I. (Inger), Nissinen, A. (Aulikki), Brunner, E. (Eric), Kuller, L.H. (Lewis), Price, J.F. (Jackie F.), Sundstrom, J. (Johan), Knuiman, M.W. (Matthew), Feskens, E.J.M. (Edith), Verschuren, W.M.M. (W. M. Monique), Wald, A. (Anna), Bakker, S.J.L. (Stephan), Whincup, P.H. (Peter), Ford, I. (Ian), Goldbourt, U. (Uri), Gómez-de-la-Cámara, A. (Agustín), Gallacher, J. (John), Simons, L.A. (Leon), Rosengren, A. (Annika), Sutherland, S.E. (Susan), Björkelund, C. (Cecilia), Blazer, D.G. (Dan), Wassertheil-Smoller, S. (Sylvia), Onat, A. (Altan), Marín Ibañez, A. (Alejandro), Casiglia, E. (Edoardo), Jukema, J.W. (Jan Wouter), Simpson, L.M. (Lara), Giampaoli, S. (Simona), Nordestgaard, B.G. (Børge), Selmer, R. (Randi), Wennberg, P. (Patrik), Kauhanen, J. (Jussi), Salonen, J.T., Dankner, R. (Rachel), Barrett-Connor, E. (Elizabeth), Kavousi, M. (Maryam), Gudnason, V. (Vilmundur), Evans, D.A. (Denis), Wallace, R.B. (Robert), Cushman, M. (Mary Ann), D'Agostino, R.B. (Ralph), Umans, J.G. (Jason), Kiyohara, Y. (Yutaka), Nakagawa, H. (Hidaeki), Sato, S. (Shinichi), Gillum, R.F. (Richard), Folsom, A.R. (Aaron), Schouw, Y.T. (Yvonne) van der, Moons, K.G.M. (Karel), Griffin, S. (Simon), Sattar, N. (Naveed), Wareham, N.J. (Nick), Selvin, E. (Elizabeth), Thompson, S.G. (Simon), Danesh, J. (John), Angelantonio, E. (Emanuele) di, Gao, P. (Pei), Khan, H. (Hassan), Butterworth, A.S. (Adam), Wormser, D. (David), Kaptoge, S. (Stephen), Kondapally Seshasai, S.R. (Sreenivasa Rao), Thompson, A. (Alex), Sarwar, S. (Sheryar), Willeit, J. (Johann), Ridker, P.M. (Paul), Barr, E.L.M., Khaw, K-T. (Kay-Tee), Psaty, B.M. (Bruce), Brenner, H. (Hermann), Balkau, B. (Beverley), Dekker, J.M. (Jacqueline), Lawlor, D.A. (Debbie), Daimon, M. (Makoto), Njølstad, I. (Inger), Nissinen, A. (Aulikki), Brunner, E. (Eric), Kuller, L.H. (Lewis), Price, J.F. (Jackie F.), Sundstrom, J. (Johan), Knuiman, M.W. (Matthew), Feskens, E.J.M. (Edith), Verschuren, W.M.M. (W. M. Monique), Wald, A. (Anna), Bakker, S.J.L. (Stephan), Whincup, P.H. (Peter), Ford, I. (Ian), Goldbourt, U. (Uri), Gómez-de-la-Cámara, A. (Agustín), Gallacher, J. (John), Simons, L.A. (Leon), Rosengren, A. (Annika), Sutherland, S.E. (Susan), Björkelund, C. (Cecilia), Blazer, D.G. (Dan), Wassertheil-Smoller, S. (Sylvia), Onat, A. (Altan), Marín Ibañez, A. (Alejandro), Casiglia, E. (Edoardo), Jukema, J.W. (Jan Wouter), Simpson, L.M. (Lara), Giampaoli, S. (Simona), Nordestgaard, B.G. (Børge), Selmer, R. (Randi), Wennberg, P. (Patrik), Kauhanen, J. (Jussi), Salonen, J.T., Dankner, R. (Rachel), Barrett-Connor, E. (Elizabeth), Kavousi, M. (Maryam), Gudnason, V. (Vilmundur), Evans, D.A. (Denis), Wallace, R.B. (Robert), Cushman, M. (Mary Ann), D'Agostino, R.B. (Ralph), Umans, J.G. (Jason), Kiyohara, Y. (Yutaka), Nakagawa, H. (Hidaeki), Sato, S. (Shinichi), Gillum, R.F. (Richard), Folsom, A.R. (Aaron), Schouw, Y.T. (Yvonne) van der, Moons, K.G.M. (Karel), Griffin, S. (Simon), Sattar, N. (Naveed), Wareham, N.J. (Nick), Selvin, E. (Elizabeth), Thompson, S.G. (Simon), and Danesh, J. (John)

Published
2014
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27. Graphical assessment of incremental value of novel markers in prediction models

Author

Steyerberg, E.W. (Ewout), Vedder, M.M. (Moniek), Leening, M.J.G. (Maarten), Postmus, D. (Douwe), D'Agostino, R.B. (Ralph), Calster, B. (Ben) Van, Pencina, M. (Michael), Steyerberg, E.W. (Ewout), Vedder, M.M. (Moniek), Leening, M.J.G. (Maarten), Postmus, D. (Douwe), D'Agostino, R.B. (Ralph), Calster, B. (Ben) Van, and Pencina, M. (Michael)

Abstract

New markers may improve prediction of diagnostic and prognostic outcomes. We aimed to review options for graphical display and summary measures to assess the predictive value of markers over standard, readily available predictors. We illustrated various approaches using previously published data on 3264 participants from the Framingham Heart Study, where 183 developed coronary heart disease (10-year risk 5.6%). We considered performance measures for the incremental value of adding HDL cholesterol to a prediction model. An initial assessment may consider statistical significance (HR = 0.65, 95% confidence interval 0.53 to 0.80; likelihood ratio p < 0.001), and distributions of predicted risks (densities or box plots) with various summary measures. A range of decision thresholds is considered in predictiveness and receiver operating characteristic curves, where the area under the curve (AUC) increased from 0.762 to 0.774 by adding HDL. We can furthermore focus on reclassification of participants with and without an event in a reclassification graph, with the continuous net reclassification improvement (NRI) as a summary measure. When we focus on one particular decision threshold, the changes in sensitivity and specificity are central. We propose a net reclassification risk graph, which allows us to focus on the number of reclassified persons and their event rates. Summary measures include the binary AUC, the two-category NRI, and decision analytic variants such as the net benefit (NB). Various graphs and summary measures can be used to assess the incremental predictive value of a marker. Important insights for impact on decision making are provided by a simple graph for the net reclassification risk.

Published
2014
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28. Development and validation of an ankle brachial index risk model for the prediction of cardiovascular events

Author

Fowkes, F.G.R., Murray, G.D., Butcher, I., Folsom, A.R., Hirsch, A.T., Couper, D.J., deBacker, G., Kornitzer, M., Newman, A.B., Sutton-Tyrrell, K.C., Cushman, M., Lee, A.J., Price, J.F., D'Agostino, R.B., Murabito, J.M., Norman, P.E., Masaki, K.H., Bouter, L.M., Heine, R.J., Stehouwer, C.D.A., McDermott, M.M., Stoffers, H.E.J.H., Knottnerus, J.A., Ogren, M., Hedblad, B., Koenig, W., Meisinger, C., Cauley, J.A., Franco, O.H., Hunink, M.G.M., Hofman, A., Witteman, J.C., Criqui, M.H., Langer, R.D., Hiatt, W.R., Hamman, R.F., Fowkes, F.G.R., Murray, G.D., Butcher, I., Folsom, A.R., Hirsch, A.T., Couper, D.J., deBacker, G., Kornitzer, M., Newman, A.B., Sutton-Tyrrell, K.C., Cushman, M., Lee, A.J., Price, J.F., D'Agostino, R.B., Murabito, J.M., Norman, P.E., Masaki, K.H., Bouter, L.M., Heine, R.J., Stehouwer, C.D.A., McDermott, M.M., Stoffers, H.E.J.H., Knottnerus, J.A., Ogren, M., Hedblad, B., Koenig, W., Meisinger, C., Cauley, J.A., Franco, O.H., Hunink, M.G.M., Hofman, A., Witteman, J.C., Criqui, M.H., Langer, R.D., Hiatt, W.R., and Hamman, R.F.

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. © 2013 The European Society of Cardiology.

Published
2014
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32. Impact of enzyme replacement therapy on survival in adults with Pompe disease: Results from a prospective international observational study

Author

Güngör, D. (Deniz), Kruijshaar, M.E. (Michelle), Plug, I. (Iris), D'Agostino, R.B. (Ralph), Hagemans, M.L.C. (Marloes), Doorn, P.A. (Pieter) van, Reuser, A.J.J. (Arnold), Ploeg, A.T. (Ans) van der, Güngör, D. (Deniz), Kruijshaar, M.E. (Michelle), Plug, I. (Iris), D'Agostino, R.B. (Ralph), Hagemans, M.L.C. (Marloes), Doorn, P.A. (Pieter) van, Reuser, A.J.J. (Arnold), and Ploeg, A.T. (Ans) van der

Abstract

Background: Pompe disease is a rare metabolic myopathy for which disease-specific enzyme replacement therapy (ERT) has been available since 2006. ERT has shown efficacy concerning muscle strength and pulmonary function in adult patients. However, no data on the effect of ERT on the survival of adult patients are currently available. The aim of this study was to assess the effect of ERT on survival in adult patients with Pompe disease. Methods. Data were collected as part of an international observational study conducted between 2002 and 2011, in which patients were followed on an annual basis. Time-dependent Cox's proportional hazards models were used for univariable and multivariable analyses. Results: Overall, 283 adult patients with a median age of 48 years (range, 19 to 81 years) were included in the study. Seventy-two percent of patients started ERT at some time during follow-up, and 28% never received ERT. During follow-up (median, 6 years; range, 0.04 to 9 years), 46 patients died, 28 (61%) of whom had never received ERT. After adjustment for age, sex, country of residence, and disease severity (based on wheelchair and ventilator use), ERT was positively associated with survival (hazard ratio, 0.41; 95% CI, 0.19 to 0.87). Conclusion: This prospective study was the first to demonstrate the positive effect of ERT on survival in adults with Pompe disease. Given the relatively recent registration of ERT for Pompe disease, these findings further support its beneficial impact in adult patients.

Published
2013
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33. Lipid-related markers and cardiovascular disease prediction

Author

Angelantonio, E. (Emanuele) di, Gao, P. (Pei), Pennells, L. (Lisa), Kaptoge, S. (Stephen), Caslake, M. (Muriel), Thompson, A. (Alexander), Butterworth, A.S. (Adam), Sarwar, S. (Sheryar), Wormser, D. (David), Saleheen, D., Ballantyne, C. (Christie), Psaty, B.M. (Bruce), Sundstrom, J. (Johan), Ridker, P.M. (Paul), Nagel, D. (Dorothea), Gillum, R.F. (Richard), Ford, I. (Ian), Ducimetiere, P. (Pierre), Kiechl, S. (Stefan), Koenig, W. (Wolfgang), Dullaart, R.P.F. (Robin), Assmann, G. (Gerd), D'Agostino, R.B. (Ralph), Dagenais, G.R. (Gilles R), Cooper, J.A. (Jackie), Kromhout, D. (Daan), Onat, A. (Altan), Tipping, A. (Alex), Gómez-de-la-Cámara, A. (Agustín), Rosengren, A. (Annika), Sutherland, S.E. (Susan), Gallacher, J. (John), Fowkes, F.G.R. (F. Gerald R.), Casiglia, E. (Edoardo), Hofman, A. (Albert), Salomaa, V. (Veikko), Barrett-Connor, E. (Elizabeth), Clarke, R. (Robert), Brunner, E. (Eric), Jukema, J.W. (Jan Wouter), Simons, L.A. (Leon), Sandhu, M.S. (Manjinder), Wareham, N.J. (Nick), Khaw, K-T. (Kay-Tee), Kauhanen, J. (Jussi), Salonen, J.T., Howard, W.J. (William), Nordestgaard, B.G. (Børge), Wood, A.M. (Angela), Thompson, S.G. (Simon), Boekholdt, S.M. (Matthijs), Sattar, N. (Naveed), Packard, C. (Chris), Gudnason, V. (Vilmundur), Danesh, J. (John), Angelantonio, E. (Emanuele) di, Gao, P. (Pei), Pennells, L. (Lisa), Kaptoge, S. (Stephen), Caslake, M. (Muriel), Thompson, A. (Alexander), Butterworth, A.S. (Adam), Sarwar, S. (Sheryar), Wormser, D. (David), Saleheen, D., Ballantyne, C. (Christie), Psaty, B.M. (Bruce), Sundstrom, J. (Johan), Ridker, P.M. (Paul), Nagel, D. (Dorothea), Gillum, R.F. (Richard), Ford, I. (Ian), Ducimetiere, P. (Pierre), Kiechl, S. (Stefan), Koenig, W. (Wolfgang), Dullaart, R.P.F. (Robin), Assmann, G. (Gerd), D'Agostino, R.B. (Ralph), Dagenais, G.R. (Gilles R), Cooper, J.A. (Jackie), Kromhout, D. (Daan), Onat, A. (Altan), Tipping, A. (Alex), Gómez-de-la-Cámara, A. (Agustín), Rosengren, A. (Annika), Sutherland, S.E. (Susan), Gallacher, J. (John), Fowkes, F.G.R. (F. Gerald R.), Casiglia, E. (Edoardo), Hofman, A. (Albert), Salomaa, V. (Veikko), Barrett-Connor, E. (Elizabeth), Clarke, R. (Robert), Brunner, E. (Eric), Jukema, J.W. (Jan Wouter), Simons, L.A. (Leon), Sandhu, M.S. (Manjinder), Wareham, N.J. (Nick), Khaw, K-T. (Kay-Tee), Kauhanen, J. (Jussi), Salonen, J.T., Howard, W.J. (William), Nordestgaard, B.G. (Børge), Wood, A.M. (Angela), Thompson, S.G. (Simon), Boekholdt, S.M. (Matthijs), Sattar, N. (Naveed), Packard, C. (Chris), Gudnason, V. (Vilmundur), and Danesh, J. (John)

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 (1

Published
2012
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34. C-reactive protein, fibrinogen, and cardiovascular disease prediction

Author

Kaptoge, S. (Stephen), Angelantonio, E. (Emanuele) di, Pennells, L. (Lisa), Wood, A.M. (Angela), White, I.R. (Ian), Gao, P. (Pei), Walker, M. (Mark), Thompson, A. (Alexander), Sarwar, S. (Sheryar), Caslake, M. (Muriel), Butterworth, A.S. (Adam), Amouyel, P. (Philippe), Assmann, G. (Gerd), Bakker, S.J.L. (Stephan), Barr, E.L.M., Barrett-Connor, E. (Elizabeth), Benjamin, E.J. (Emelia), Björkelund, C. (Cecilia), Brenner, H. (Hermann), Brunner, E. (Eric), Clarke, R. (Robert), Cooper, J.A. (Jackie), Cremer, P., Cushman, M. (Mary Ann), Dagenais, G.R. (Gilles R), D'Agostino, R.B. (Ralph), Dankner, R. (Rachel), Davey-Smith, G. (George), Deeg, D.J.H. (Dorly), Dekker, J.M. (Jacqueline), Engström, G., Folsom, A.R. (Aaron), Fowkes, F.G.R. (F. Gerald R.), Gallacher, J. (John), Gaziano, J.M. (J. Michael), Giampaoli, S. (Simona), Gillum, R.F. (Richard), Hofman, A. (Albert), Howard, B.V. (Barbara), Ingelsson, E. (Erik), Iso, H. (Hiroyasu), Jorgensen, T. (Torben), Kiechl, S. (Stefan), Kitamura, A., Kiyohara, Y. (Yutaka), Koenig, W. (Wolfgang), Kromhout, D. (Daan), Kuller, L.H. (Lewis), Lawlor, D.A. (Debbie), Meade, T. (Tom), Nissinen, A. (Aulikki), Nordestgaard, B.G. (Børge), Onat, A. (Altan), Panagiotakos, D.B. (Demosthenes), Psaty, B.M. (Bruce), Rodriguez, B. (Beatriz), Rosengren, A. (Annika), Salomaa, V. (Veikko), Kauhanen, J. (Jussi), Salonen, J.T., Shaffer, J.A. (Jonathan), Shea, S. (Steven), Ford, I. (Ian), Stehouwer, C.D. (Coen), Strandberg, T.E. (Timo), Tipping, A. (Alex), Tosetto, A. (Alberto), Wassertheil-Smoller, S. (Sylvia), Wennberg, P. (Patrik), Westendorp, R.G.J. (Rudi), Whincup, P.H. (Peter), Wilhelmsen, L. (Lars), Woodward, M. (Mark), Lowe, G.D.O. (Gordon), Wareham, N.J. (Nick), Khaw, K-T. (Kay-Tee), Sattar, N. (Naveed), Packard, C. (Chris), Gudnason, V. (Vilmundur), Ridker, P.M. (Paul), Pepys, M.B. (Mark), Thompson, S.G. (Simon), Danesh, J. (John), Kaptoge, S. (Stephen), Angelantonio, E. (Emanuele) di, Pennells, L. (Lisa), Wood, A.M. (Angela), White, I.R. (Ian), Gao, P. (Pei), Walker, M. (Mark), Thompson, A. (Alexander), Sarwar, S. (Sheryar), Caslake, M. (Muriel), Butterworth, A.S. (Adam), Amouyel, P. (Philippe), Assmann, G. (Gerd), Bakker, S.J.L. (Stephan), Barr, E.L.M., Barrett-Connor, E. (Elizabeth), Benjamin, E.J. (Emelia), Björkelund, C. (Cecilia), Brenner, H. (Hermann), Brunner, E. (Eric), Clarke, R. (Robert), Cooper, J.A. (Jackie), Cremer, P., Cushman, M. (Mary Ann), Dagenais, G.R. (Gilles R), D'Agostino, R.B. (Ralph), Dankner, R. (Rachel), Davey-Smith, G. (George), Deeg, D.J.H. (Dorly), Dekker, J.M. (Jacqueline), Engström, G., Folsom, A.R. (Aaron), Fowkes, F.G.R. (F. Gerald R.), Gallacher, J. (John), Gaziano, J.M. (J. Michael), Giampaoli, S. (Simona), Gillum, R.F. (Richard), Hofman, A. (Albert), Howard, B.V. (Barbara), Ingelsson, E. (Erik), Iso, H. (Hiroyasu), Jorgensen, T. (Torben), Kiechl, S. (Stefan), Kitamura, A., Kiyohara, Y. (Yutaka), Koenig, W. (Wolfgang), Kromhout, D. (Daan), Kuller, L.H. (Lewis), Lawlor, D.A. (Debbie), Meade, T. (Tom), Nissinen, A. (Aulikki), Nordestgaard, B.G. (Børge), Onat, A. (Altan), Panagiotakos, D.B. (Demosthenes), Psaty, B.M. (Bruce), Rodriguez, B. (Beatriz), Rosengren, A. (Annika), Salomaa, V. (Veikko), Kauhanen, J. (Jussi), Salonen, J.T., Shaffer, J.A. (Jonathan), Shea, S. (Steven), Ford, I. (Ian), Stehouwer, C.D. (Coen), Strandberg, T.E. (Timo), Tipping, A. (Alex), Tosetto, A. (Alberto), Wassertheil-Smoller, S. (Sylvia), Wennberg, P. (Patrik), Westendorp, R.G.J. (Rudi), Whincup, P.H. (Peter), Wilhelmsen, L. (Lars), Woodward, M. (Mark), Lowe, G.D.O. (Gordon), Wareham, N.J. (Nick), Khaw, K-T. (Kay-Tee), Sattar, N. (Naveed), Packard, C. (Chris), Gudnason, V. (Vilmundur), Ridker, P.M. (Paul), Pepys, M.B. (Mark), Thompson, S.G. (Simon), and Danesh, J. (John)

Abstract

BACKGROUND: There is debate about the value of assessing levels of C-reactive protein (CRP) and other biomarkers of inflammation for the prediction of first cardiovascular events. METHODS: We analyzed data from 52 prospective studies that included 246,669 participants without a history of cardiovascular disease to investigate the value of adding CRP or fibrinogen levels to conventional risk factors for the prediction of cardiovascular risk. We calculated measures of discrimination and reclassification during follow-up and modeled the clinical implications of initiation of statin therapy after the assessment of CRP or fibrinogen. RESULTS: The addition of information on high-density lipoprotein cholesterol to a prognostic model for cardiovascular disease that included age, sex, smoking status, blood pressure, history of diabetes, and total cholesterol level increased the C-index, a measure of risk discrimination, by 0.0050. The further addition to this model of information on CRP or fibrinogen increased the C-index by 0.0039 and 0.0027, respectively (P<0.001), and yielded a net reclassification improvement of 1.52% and 0.83%, respectively, for the predicted 10-year risk categories of "low" (<10%), "intermediate" (10% to <20%), and "high" (≥20%) (P<0.02 for both comparisons). We estimated that among 100,000 adults 40 years of age or older, 15,025 persons would initially be classified as being at intermediate risk for a cardiovascular event if conventional risk factors alone were used to calculate risk. Assuming that statin therapy would be initiated in accordance with Adult Treatment Panel III guidelines (i.e., for persons with a predicted risk of ≥20% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), additional targeted assessment of CRP or fibrinogen levels in the 13,199 remaining participants at intermediate risk could help prevent approximately 30 additional cardiovascular events over the course of 10 ye

Published
2012
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36. Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque

Author

Bis, J.C. (Joshua), Kavousi, M. (Maryam), Franceschini, N. (Nora), Isaacs, A.J. (Aaron), Abecasis, G.R. (Gonçalo), Schminke, U. (Ulf), Post, W.S. (Wendy S.), Smith, A.V. (Albert Vernon), Cupples, L.A. (Adrienne), Markus, H.S. (Hugh S.), Schmidt, R. (Reinhold), Huffman, J.E. (Jennifer), Lehtimäki, T. (Terho), Baumert, J. (Jens), Münzel, T. (Thomas), Heckbert, S.R. (Susan), Dehghan, A. (Abbas), North, K.E. (Kari), Oostra, B.A. (Ben), Bevan, S. (Steve), Stoegerer, E.M. (Eva Maria), Hayward, C. (Caroline), Raitakari, O. (Olli), Meisinger, C. (Christa), Schillert, A. (Arne), Sanna, S. (Serena), Völzke, H. (Henry), Cheng, Y.C. (Yu Ching), Thorsson, B. (Bolli), Fox, C.S. (Caroline), Rice, K. (Kenneth), Rivadeneira Ramirez, F. (Fernando), Nambi, V. (Vijay), Halperin, E. (Eran), Petrovic, K. (Katja), Peltonen, L. (Leena Johanna), Wichmann, H.E. (Heinz Erich), Schnabel, R.B. (Renate), Dörr, M. (Marcus), Parsa, A. (Afshin), Aspelund, T. (Thor), Demissie, S. (Serkalem), Kathiresan, S. (Sekar), Reilly, M.P. (Muredach), Taylor, K.D. (Kent), Uitterlinden, A.G. (André), Couper, D.J. (David), Sitzer, M. (Matthias), Kähönen, M. (Mika), Illig, T. (Thomas), Wild, P.S. (Philipp), Orrù, M. (Marco), Lüdemann, J. (Jan), Shuldiner, A.R. (Alan), Eiriksdottir, G. (Gudny), White, C.C. (Charles), Rotter, J.I. (Jerome), Hofman, A. (Albert), Seissler, J. (Jochen), Zeller, T. (Tanja), Usala, G., Ernst, F.D.J. (Florian), Launer, L.J. (Lenore), D'Agostino, R.B. (Ralph), O'Leary, D.H. (Daniel H.), Ballantyne, C. (Christie), Thiery, J.P. (Joachim), Ziegler, A. (Andreas), Lakatta, E. (Edward), Chilukoti, R.K. (Ravi Kumar), Harris, T.B. (Tamara), Wolf, P.A. (Philip), Psaty, B.M. (Bruce), Polak, J.F. (Joseph F.), Rathmann, W. (Wolfgang), Uda, M. (Manuela), Boerwinkle, E.A. (Eric), Klopp, N. (Norman), Wilson, J.F. (James), Viikari, J. (Jorma), Koenig, W. (Wolfgang), Blankenberg, S. (Stefan), Newman, A.B. (Anne), Witteman, J.C.M. (Jacqueline), Li, X. (Xia), Heiss, G. (Gerardo), Duijn, C.M. (Cornelia) van, Scuteri, A. (Angelo), Homuth, G. (Georg), Mitchell, B.D. (Braxton), Gudnason, V. (Vilmundur), O'Donnell, C.J. (Christopher), Bis, J.C. (Joshua), Kavousi, M. (Maryam), Franceschini, N. (Nora), Isaacs, A.J. (Aaron), Abecasis, G.R. (Gonçalo), Schminke, U. (Ulf), Post, W.S. (Wendy S.), Smith, A.V. (Albert Vernon), Cupples, L.A. (Adrienne), Markus, H.S. (Hugh S.), Schmidt, R. (Reinhold), Huffman, J.E. (Jennifer), Lehtimäki, T. (Terho), Baumert, J. (Jens), Münzel, T. (Thomas), Heckbert, S.R. (Susan), Dehghan, A. (Abbas), North, K.E. (Kari), Oostra, B.A. (Ben), Bevan, S. (Steve), Stoegerer, E.M. (Eva Maria), Hayward, C. (Caroline), Raitakari, O. (Olli), Meisinger, C. (Christa), Schillert, A. (Arne), Sanna, S. (Serena), Völzke, H. (Henry), Cheng, Y.C. (Yu Ching), Thorsson, B. (Bolli), Fox, C.S. (Caroline), Rice, K. (Kenneth), Rivadeneira Ramirez, F. (Fernando), Nambi, V. (Vijay), Halperin, E. (Eran), Petrovic, K. (Katja), Peltonen, L. (Leena Johanna), Wichmann, H.E. (Heinz Erich), Schnabel, R.B. (Renate), Dörr, M. (Marcus), Parsa, A. (Afshin), Aspelund, T. (Thor), Demissie, S. (Serkalem), Kathiresan, S. (Sekar), Reilly, M.P. (Muredach), Taylor, K.D. (Kent), Uitterlinden, A.G. (André), Couper, D.J. (David), Sitzer, M. (Matthias), Kähönen, M. (Mika), Illig, T. (Thomas), Wild, P.S. (Philipp), Orrù, M. (Marco), Lüdemann, J. (Jan), Shuldiner, A.R. (Alan), Eiriksdottir, G. (Gudny), White, C.C. (Charles), Rotter, J.I. (Jerome), Hofman, A. (Albert), Seissler, J. (Jochen), Zeller, T. (Tanja), Usala, G., Ernst, F.D.J. (Florian), Launer, L.J. (Lenore), D'Agostino, R.B. (Ralph), O'Leary, D.H. (Daniel H.), Ballantyne, C. (Christie), Thiery, J.P. (Joachim), Ziegler, A. (Andreas), Lakatta, E. (Edward), Chilukoti, R.K. (Ravi Kumar), Harris, T.B. (Tamara), Wolf, P.A. (Philip), Psaty, B.M. (Bruce), Polak, J.F. (Joseph F.), Rathmann, W. (Wolfgang), Uda, M. (Manuela), Boerwinkle, E.A. (Eric), Klopp, N. (Norman), Wilson, J.F. (James), Viikari, J. (Jorma), Koenig, W. (Wolfgang), Blankenberg, S. (Stefan), Newman, A.B. (Anne), Witteman, J.C.M. (Jacqueline), Li, X. (Xia), Heiss, G. (Gerardo), Duijn, C.M. (Cornelia) van, Scuteri, A. (Angelo), Homuth, G. (Georg), Mitchell, B.D. (Braxton), Gudnason, V. (Vilmundur), and O'Donnell, C.J. (Christopher)

Abstract

Carotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 × 10 -8). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events.

Published
2011
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37. Separating the mechanism-based and off-target actions of cholesteryl ester transfer protein inhibitors with CETP gene polymorphisms

Author

Sofat, R. (Reecha), Hingorani, A. (Aroon), Smeeth, L. (Liam), Humphries, S.E. (Steve), Talmud, P.J., Cooper, J. (Jim), Shah, T. (Tina), Sandhu, M.S. (Manjinder), Ricketts, S.L. (Sally), Boekholdt, S.M. (Matthijs), Wareham, N.J. (Nick), Khaw, K-T. (Kay-Tee), Kumari, M. (Meena), Kivimaki, M. (Mika), Marmot, M. (Michael), Asselbergs, F.W. (Folkert), Harst, P. (Pim) van der, Dullaart, R.P.F. (Robin), Navis, G. (Gerjan), Veldhuisen, D.J. (Dirk) van, Gilst, W.H. (Wiek) van, Thompson, J.F. (John), McCaskie, P. (Pamela), Palmer, C. (Cameron), Arca, M. (Marcello), Quagliarini, F. (Fabiana), Gaudio, C. (Carlo), Cambien, F. (François), Nicaud, V., Poirer, O. (Odette), Gudnason, V. (Vilmundur), Isaacs, A.J. (Aaron), Witteman, J.C.M. (Jacqueline), Tikka-Kleemola, P. (Päivi), Pencina, M. (Michael), Vasan, R.S. (Ramachandran Srini), D'Agostino, R.B. (Ralph), Ordovas, J.M. (Jose), Li, T.Y. (Tricia), Kakko, S. (Sakari), Kauma, H. (Heikki), Savolainen, M.J. (Markku), Kesäniemi, Y.A. (Antero), Sandhofer, A. (Anton), Paulweber, B. (Bernhard), Sorli, J.V. (Jose), Goto, A. (Akimoto), Yokoyama, S. (Shinji), Okumura, K. (Kenji), Horne, B.D. (Benjamin), Packard, C. (Chris), Freeman, D. (Dilys), Ford, I. (Ian), Sattar, N. (Naveed), McCormack, V. (Valerie), Lawlor, D.A. (Debbie), Ebrahim, S. (Shanil), Smith, A.V. (Davey), Kastelein, J.J.P. (John), Deanfield, J. (John), Casas, J.P. (Juan), Sofat, R. (Reecha), Hingorani, A. (Aroon), Smeeth, L. (Liam), Humphries, S.E. (Steve), Talmud, P.J., Cooper, J. (Jim), Shah, T. (Tina), Sandhu, M.S. (Manjinder), Ricketts, S.L. (Sally), Boekholdt, S.M. (Matthijs), Wareham, N.J. (Nick), Khaw, K-T. (Kay-Tee), Kumari, M. (Meena), Kivimaki, M. (Mika), Marmot, M. (Michael), Asselbergs, F.W. (Folkert), Harst, P. (Pim) van der, Dullaart, R.P.F. (Robin), Navis, G. (Gerjan), Veldhuisen, D.J. (Dirk) van, Gilst, W.H. (Wiek) van, Thompson, J.F. (John), McCaskie, P. (Pamela), Palmer, C. (Cameron), Arca, M. (Marcello), Quagliarini, F. (Fabiana), Gaudio, C. (Carlo), Cambien, F. (François), Nicaud, V., Poirer, O. (Odette), Gudnason, V. (Vilmundur), Isaacs, A.J. (Aaron), Witteman, J.C.M. (Jacqueline), Tikka-Kleemola, P. (Päivi), Pencina, M. (Michael), Vasan, R.S. (Ramachandran Srini), D'Agostino, R.B. (Ralph), Ordovas, J.M. (Jose), Li, T.Y. (Tricia), Kakko, S. (Sakari), Kauma, H. (Heikki), Savolainen, M.J. (Markku), Kesäniemi, Y.A. (Antero), Sandhofer, A. (Anton), Paulweber, B. (Bernhard), Sorli, J.V. (Jose), Goto, A. (Akimoto), Yokoyama, S. (Shinji), Okumura, K. (Kenji), Horne, B.D. (Benjamin), Packard, C. (Chris), Freeman, D. (Dilys), Ford, I. (Ian), Sattar, N. (Naveed), McCormack, V. (Valerie), Lawlor, D.A. (Debbie), Ebrahim, S. (Shanil), Smith, A.V. (Davey), Kastelein, J.J.P. (John), Deanfield, J. (John), and Casas, J.P. (Juan)

Abstract

Background: Cholesteryl ester transfer protein (CETP) inhibitors raise high-density lipoprotein (HDL) cholesterol, but torcetrapib, the first-in-class inhibitor tested in a large outcome trial, caused an unexpected blood pressure elevation and increased cardiovascular events. Whether the hypertensive effect resulted from CETP inhibition or an off-target action of torcetrapib has been debated. We hypothesized that common single-nucleotide polymorphisms in the CETP gene could help distinguish mechanism-based from off-target actions of CETP inhibitors to inform on the validity of CETP as a therapeutic target. Methods and Results: We compared the effect of CETP single-nucleotide polymorphisms and torcetrapib treatment on lipid fractions, blood pressure, and electrolytes in up to 67 687 individuals from genetic studies and 17 911 from randomized trials. CETP single-nucleotide polymorphisms and torcetrapib treatment reduced CETP activity and had a directionally concordant effect on 8 lipid and lipoprotein traits (total, low-density lipoprotein, and HDL cholesterol; HDL2; HDL3; apolipoproteins A-I and B; and triglycerides), with the genetic effect on HDL cholesterol (0.13 mmol/L, 95% confidence interval [CI] 0.11 to 0.14 mmol/L) being consistent with that expected of a 10-mg dose of torcetrapib (0.13 mmol/L, 95% CI 0.10 to 0.15). In trials, 60 mg of torcetrapib elevated systolic and diastolic blood pressure by 4.47 mm Hg (95% CI 4.10 to 4.84 mm Hg) and 2.08 mm Hg (95% CI 1.84 to 2.31 mm Hg), respectively. However, the effect of CETP single-nucleotide polymorphisms on systolic blood pressure (0.16 mm Hg, 95% CI-0.28 to 0.60 mm Hg) and diastolic blood pressure (-0.04 mm Hg, 95% CI-0.36 to 0.28 mm Hg) was null and significantly different from that expected of 10 mg of torcetrapib. Conclusions: Discordance in the effects of CETP single-nucleotide polymorphisms and torcetrapib treatment on blood pressure despite the concordant effects on lipids indicates the hypertensive action

Published
2010
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38. Ankle brachial index combined with Framingham risk score to predict cardiovascular events and mortality - A meta-analysis

Author

Fowkes, F.G.R., Murray, G.D., Butcher, I., Heald, C.L., Lee, R.J., Chambless, L.E., Folsom, A.R., Hirsch, A.T., Dramaix, M., deBacker, G., Wautrecht, J.C., Kornitzer, M., Newman, A.B., Cushman, M., Sutton-Tyrrell, K., Lee, A.J., Price, J.F., D'Agostino, R.B., Murabito, J.M., Norman, P.E., Jamrozik, K., Curb, J.D., Masaki, K.H., Rodriquez, B.L., Dekker, J.M., Bouter, L.M., Heine, R.J., Nijpels, G., Stehouwer, C.D.A., Ferrucci, L., Stoffers, H.E., Hooi, J.D., Knottnerus, J.A., Ogren, M., Hedblad, B., Witteman, J.C., Breteler, M.M.B., Hunink, M.G.M., Hofman, A., Criqui, M.H., Langer, R.D., Fronek, A., Hiatt, W.R., Hamman, R., Resnick, H.E., Guralnik, J., McDermott, M.M., Fowkes, F.G.R., Murray, G.D., Butcher, I., Heald, C.L., Lee, R.J., Chambless, L.E., Folsom, A.R., Hirsch, A.T., Dramaix, M., deBacker, G., Wautrecht, J.C., Kornitzer, M., Newman, A.B., Cushman, M., Sutton-Tyrrell, K., Lee, A.J., Price, J.F., D'Agostino, R.B., Murabito, J.M., Norman, P.E., Jamrozik, K., Curb, J.D., Masaki, K.H., Rodriquez, B.L., Dekker, J.M., Bouter, L.M., Heine, R.J., Nijpels, G., Stehouwer, C.D.A., Ferrucci, L., Stoffers, H.E., Hooi, J.D., Knottnerus, J.A., Ogren, M., Hedblad, B., Witteman, J.C., Breteler, M.M.B., Hunink, M.G.M., Hofman, A., Criqui, M.H., Langer, R.D., Fronek, A., Hiatt, W.R., Hamman, R., Resnick, H.E., Guralnik, J., and McDermott, M.M.

Published
2008
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39. The Anglo Scandinavian Cardiac Outcomes Trial

Author

Mehlsen, J., D'Agostino, R.B., Chow, S.-C., Liu, J.-P., Sullivan, L.M., Massaro, J., Mehlsen, J., D'Agostino, R.B., Chow, S.-C., Liu, J.-P., Sullivan, L.M., and Massaro, J.

Published
2008

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