OBJECTIVES: This study sought to determine whether novel markers not involving ionizing radiation could predict coronary artery calcium (CAC) progression in a low-risk population. BACKGROUND: Increase in CAC scores over time (CAC progression) improves prediction of coronary heart disease (CHD) events. Due to radiation exposure, CAC measurement represents an undesirable method for repeated risk assessment, particularly in individuals with low predicted risk (Framingham Risk Score [FRS] <10%). METHODS: From 6,814 participants in MESA (Multi-Ethnic Study of Atherosclerosis), 2,620 individuals were classified as low risk for CHD events (FRS <10%) and had follow-up CAC measurement. In addition to traditional risk factors (RFs), various combinations of novel marker models were selected on the basis of data-driven, clinical, or backward stepwise selection techniques. RESULTS: Mean follow-up was 2.5 years. CAC progression occurred in 574 participants (22% overall; 214 of 1,830 with baseline CAC = 0 and 360 of 790 with baseline CAC >0). Addition of various combinations of novel markers to the base model (c statistic = 0.711) revealed improvements in discrimination of approximately only 0.005 each (c statistics 0.7158, 0.7160, and 0.7164) for the best-fit models. All 3 best-fit novel marker models calibrated well but were similar to the base model in predicting individual risk probabilities for CAC progression. The highest prevalence of CAC progression occurred in the highest compared with the lowest probability quartile groups (39.2% to 40.3% vs. 6.4% to 7.1%). CONCLUSIONS: In individuals at low predicted risk according to FRS, traditional risk factors predicted CAC progression in the short term with good discrimination and calibration. Prediction improved minimally when various novel markers were added to the model. Copyright Â
OBJECTIVES: This study sought to determine whether novel markers not involving ionizing radiation could predict coronary artery calcium (CAC) progression in a low-risk population. BACKGROUND: Increase in CAC scores over time (CAC progression) improves prediction of coronary heart disease (CHD) events. Due to radiation exposure, CAC measurement represents an undesirable method for repeated risk assessment, particularly in individuals with low predicted risk (Framingham Risk Score [FRS] <10%). METHODS: From 6,814 participants in MESA (Multi-Ethnic Study of Atherosclerosis), 2,620 individuals were classified as low risk for CHD events (FRS <10%) and had follow-up CAC measurement. In addition to traditional risk factors (RFs), various combinations of novel marker models were selected on the basis of data-driven, clinical, or backward stepwise selection techniques. RESULTS: Mean follow-up was 2.5 years. CAC progression occurred in 574 participants (22% overall; 214 of 1,830 with baseline CAC = 0 and 360 of 790 with baseline CAC >0). Addition of various combinations of novel markers to the base model (c statistic = 0.711) revealed improvements in discrimination of approximately only 0.005 each (c statistics 0.7158, 0.7160, and 0.7164) for the best-fit models. All 3 best-fit novel marker models calibrated well but were similar to the base model in predicting individual risk probabilities for CAC progression. The highest prevalence of CAC progression occurred in the highest compared with the lowest probability quartile groups (39.2% to 40.3% vs. 6.4% to 7.1%). CONCLUSIONS: In individuals at low predicted risk according to FRS, traditional risk factors predicted CAC progression in the short term with good discrimination and calibration. Prediction improved minimally when various novel markers were added to the model. Copyright Â
Authors: Michael G Shlipak; Linda F Fried; Mary Cushman; Teri A Manolio; Do Peterson; Catherine Stehman-Breen; Anthony Bleyer; Anne Newman; David Siscovick; Bruce Psaty Journal: JAMA Date: 2005-04-13 Impact factor: 56.272
Authors: Morteza Naghavi; Peter Libby; Erling Falk; S Ward Casscells; Silvio Litovsky; John Rumberger; Juan Jose Badimon; Christodoulos Stefanadis; Pedro Moreno; Gerard Pasterkamp; Zahi Fayad; Peter H Stone; Sergio Waxman; Paolo Raggi; Mohammad Madjid; Alireza Zarrabi; Allen Burke; Chun Yuan; Peter J Fitzgerald; David S Siscovick; Chris L de Korte; Masanori Aikawa; K E Juhani Airaksinen; Gerd Assmann; Christoph R Becker; James H Chesebro; Andrew Farb; Zorina S Galis; Chris Jackson; Ik-Kyung Jang; Wolfgang Koenig; Robert A Lodder; Keith March; Jasenka Demirovic; Mohamad Navab; Silvia G Priori; Mark D Rekhter; Raymond Bahr; Scott M Grundy; Roxana Mehran; Antonio Colombo; Eric Boerwinkle; Christie Ballantyne; William Insull; Robert S Schwartz; Robert Vogel; Patrick W Serruys; Goran K Hansson; David P Faxon; Sanjay Kaul; Helmut Drexler; Philip Greenland; James E Muller; Renu Virmani; Paul M Ridker; Douglas P Zipes; Prediman K Shah; James T Willerson Journal: Circulation Date: 2003-10-14 Impact factor: 29.690
Authors: Judith Hsia; Afifa Klouj; Anjana Prasad; Jeremy Burt; Lucile L Adams-Campbell; Barbara V Howard Journal: BMC Cardiovasc Disord Date: 2004-12-01 Impact factor: 2.298
Authors: Michael G Silverman; James R Harkness; Ron Blankstein; Matthew J Budoff; Arthur S Agatston; J Jeffrey Carr; Joao A Lima; Roger S Blumenthal; Khurram Nasir; Michael J Blaha Journal: JACC Cardiovasc Imaging Date: 2014-05
Authors: Joshua D Bundy; Jing Chen; Wei Yang; Matthew Budoff; Alan S Go; Juan E Grunwald; Radhakrishna R Kallem; Wendy S Post; Muredach P Reilly; Ana C Ricardo; Sylvia E Rosas; Xiaoming Zhang; Jiang He Journal: Atherosclerosis Date: 2018-02-10 Impact factor: 5.162
Authors: Dan K Kalra; Ran Heo; Valentina Valenti; Ryo Nakazato; James K Min Journal: Arterioscler Thromb Vasc Biol Date: 2014-04-10 Impact factor: 8.311
Authors: Mahmoud Al Rifai; Michael J Blaha; Vijay Nambi; Steven J C Shea; Erin D Michos; Roger S Blumenthal; Christie M Ballantyne; Moyses Szklo; Philip Greenland; Michael D Miedema; Khurram Nasir; Jerome I Rotter; Xiuqing Guo; Jie Yao; Wendy S Post; Salim S Virani Journal: Circulation Date: 2021-12-08 Impact factor: 29.690