Browsing by Author "Emerging Risk Factors Collaboration"

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    C-reactive protein, fibrinogen, and cardiovascular disease prediction.
    (The New England journal of medicine, 2012-10) Emerging Risk Factors Collaboration; Kaptoge, Stephen; Di Angelantonio, Emanuele; Pennells, Lisa; Wood, Angela M; White, Ian R; Gao, Pei; Walker, Matthew; Thompson, Alexander; Sarwar, Nadeem; Caslake, Muriel; Butterworth, Adam S; Amouyel, Philippe; Assmann, Gerd; Bakker, Stephan JL; Barr, Elizabeth LM; Barrett-Connor, Elizabeth; Benjamin, Emelia J; Björkelund, Cecilia; Brenner, Hermann; Brunner, Eric; Clarke, Robert; Cooper, Jackie A; Cremer, Peter; Cushman, Mary; Dagenais, Gilles R; D'Agostino, Ralph B; Dankner, Rachel; Davey-Smith, George; Deeg, Dorly; Dekker, Jacqueline M; Engström, Gunnar; Folsom, Aaron R; Fowkes, F Gerry R; Gallacher, John; Gaziano, J Michael; Giampaoli, Simona; Gillum, Richard F; Hofman, Albert; Howard, Barbara V; Ingelsson, Erik; Iso, Hiroyasu; Jørgensen, Torben; Kiechl, Stefan; Kitamura, Akihiko; Kiyohara, Yutaka; Koenig, Wolfgang; Kromhout, Daan; Kuller, Lewis H; Lawlor, Debbie A; Meade, Tom W; Nissinen, Aulikki; Nordestgaard, Børge G; Onat, Altan; Panagiotakos, Demosthenes B; Psaty, Bruce M; Rodriguez, Beatriz; Rosengren, Annika; Salomaa, Veikko; Kauhanen, Jussi; Salonen, Jukka T; Shaffer, Jonathan A; Shea, Steven; Ford, Ian; Stehouwer, Coen DA; Strandberg, Timo E; Tipping, Robert W; Tosetto, Alberto; Wassertheil-Smoller, Sylvia; Wennberg, Patrik; Westendorp, Rudi G; Whincup, Peter H; Wilhelmsen, Lars; Woodward, Mark; Lowe, Gordon DO; Wareham, Nicholas J; Khaw, Kay-Tee; Sattar, Naveed; Packard, Chris J; Gudnason, Vilmundur; Ridker, Paul M; Pepys, Mark B; Thompson, Simon G; Danesh, John
    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.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.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 years.In a study of people without known cardiovascular disease, we estimated that under current treatment guidelines, assessment of the CRP or fibrinogen level in people at intermediate risk for a cardiovascular event could help prevent one additional event over a period of 10 years for every 400 to 500 people screened. (Funded by the British Heart Foundation and others.).
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    Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies.
    (European heart journal, 2019-02) Pennells, Lisa; Kaptoge, Stephen; Wood, Angela; Sweeting, Mike; Zhao, Xiaohui; White, Ian; Burgess, Stephen; Willeit, Peter; Bolton, Thomas; Moons, Karel GM; van der Schouw, Yvonne T; Selmer, Randi; Khaw, Kay-Tee; Gudnason, Vilmundur; Assmann, Gerd; Amouyel, Philippe; Salomaa, Veikko; Kivimaki, Mika; Nordestgaard, Børge G; Blaha, Michael J; Kuller, Lewis H; Brenner, Hermann; Gillum, Richard F; Meisinger, Christa; Ford, Ian; Knuiman, Matthew W; Rosengren, Annika; Lawlor, Debbie A; Völzke, Henry; Cooper, Cyrus; Marín Ibañez, Alejandro; Casiglia, Edoardo; Kauhanen, Jussi; Cooper, Jackie A; Rodriguez, Beatriz; Sundström, Johan; Barrett-Connor, Elizabeth; Dankner, Rachel; Nietert, Paul J; Davidson, Karina W; Wallace, Robert B; Blazer, Dan G; Björkelund, Cecilia; Donfrancesco, Chiara; Krumholz, Harlan M; Nissinen, Aulikki; Davis, Barry R; Coady, Sean; Whincup, Peter H; Jørgensen, Torben; Ducimetiere, Pierre; Trevisan, Maurizio; Engström, Gunnar; Crespo, Carlos J; Meade, Tom W; Visser, Marjolein; Kromhout, Daan; Kiechl, Stefan; Daimon, Makoto; Price, Jackie F; Gómez de la Cámara, Agustin; Wouter Jukema, J; Lamarche, Benoît; Onat, Altan; Simons, Leon A; Kavousi, Maryam; Ben-Shlomo, Yoav; Gallacher, John; Dekker, Jacqueline M; Arima, Hisatomi; Shara, Nawar; Tipping, Robert W; Roussel, Ronan; Brunner, Eric J; Koenig, Wolfgang; Sakurai, Masaru; Pavlovic, Jelena; Gansevoort, Ron T; Nagel, Dorothea; Goldbourt, Uri; Barr, Elizabeth LM; Palmieri, Luigi; Njølstad, Inger; Sato, Shinichi; Monique Verschuren, WM; Varghese, Cherian V; Graham, Ian; Onuma, Oyere; Greenland, Philip; Woodward, Mark; Ezzati, Majid; Psaty, Bruce M; Sattar, Naveed; Jackson, Rod; Ridker, Paul M; Cook, Nancy R; D'Agostino, Ralph B; Thompson, Simon G; Danesh, John; Di Angelantonio, Emanuele; Emerging Risk Factors Collaboration
    AIMS:There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after 'recalibration', a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied. METHODS AND RESULTS:Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at 'high' 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29-39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22-24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44-51 such individuals using original algorithms, in contrast to 37-39 individuals with recalibrated algorithms. CONCLUSION:Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need.