• Association of serum markers of oxidative stress with myocardial infarction and stroke: pooled results from four large European cohort studies.

      Xuan, Yang; Bobak, Martin; Anusruti, Ankita; Jansen, Eugène H J M; Pająk, Andrzej; Tamosiunas, Abdonas; Saum, Kai-Uwe; Holleczek, Bernd; Gao, Xin; Brenner, Hermann; Schöttker, Ben (2018-11-07)
      Oxidative stress contributes to endothelial dysfunction and is involved in the pathogenesis of myocardial infarction (MI) and stroke. However, associations of biomarkers of oxidative stress with MI and stroke have not yet been addressed in large cohort studies. A nested case-control design was applied in four population-based cohort studies from Germany, Czech Republic, Poland and Lithuania. Derivatives of reactive oxygen metabolites (d-ROMs) levels, as a proxy for the reactive oxygen species burden, and total thiol levels (TTL), as a proxy for the reductive capacity, were measured in baseline serum samples of 476 incident MI cases and 454 incident stroke cases as well as five controls per case individually matched by study center, age and sex. Statistical analyses were conducted with multi-variable adjusted conditional logistic regression models. d-ROMs levels were associated with both MI (odds ratio (OR), 1.21 [95% confidence interval (CI) 1.05-1.40] for 100 Carr units increase) and stroke (OR, 1.17 [95% CI 1.01-1.35] for 100 Carr units increase). TTL were only associated with stroke incidence (OR, 0.79 [95% CI 0.63-0.99] for quartiles 2-4 vs. quartile 1). The observed relationships were stronger with fatal than with non-fatal endpoints; association of TTL with fatal MI was statistically significant (OR, 0.69 [95% CI 0.51-0.93] for 100 μmol/L-increase). This pooled analysis of four large population-based cohorts suggests an important contribution of an imbalanced redox system to the etiology of mainly fatal MI and stroke events.
    • Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies.

      Pennells, Lisa; Kaptoge, Stephen; Wood, Angela; Sweeting, Mike; Zhao, Xiaohui; White, Ian; Burgess, Stephen; Willeit, Peter; Bolton, Thomas; Moons, Karel G M; 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 L M; Palmieri, Luigi; Njølstad, Inger; Sato, Shinichi; Monique Verschuren, W M; 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 (2019-02-14)
      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. 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. 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.