Literature DB >> 20640227

Assessing the Incremental Role of Novel and Emerging Risk Factors.

Nancy R Cook1.   

Abstract

Many novel and emerging risk factors exhibit a significant association with cardiovascular disease, but have not been found to improve risk prediction. Statistical criteria used to evaluate such models and markers have largely relied on the receiver operating characteristic curve, which is an insensitive measure of improvement. Recently, new methods have been developed based on risk reclassification, or changes in risk strata following use of a new marker or model. Associated measures based on both calibration and discrimination have been proposed. This review describes previous methods used to evaluate models as well as the newly developed methods to evaluate clinical utility.

Entities:  

Year:  2010        PMID: 20640227      PMCID: PMC2904250          DOI: 10.1007/s12170-010-0084-x

Source DB:  PubMed          Journal:  Curr Cardiovasc Risk Rep        ISSN: 1932-9520


  35 in total

Review 1.  Sensitivity and specificity should be de-emphasized in diagnostic accuracy studies.

Authors:  Karel G M Moons; Frank E Harrell
Journal:  Acad Radiol       Date:  2003-06       Impact factor: 3.173

2.  Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation.

Authors:  R B D'Agostino; S Grundy; L M Sullivan; P Wilson
Journal:  JAMA       Date:  2001-07-11       Impact factor: 56.272

3.  A method of comparing the areas under receiver operating characteristic curves derived from the same cases.

Authors:  J A Hanley; B J McNeil
Journal:  Radiology       Date:  1983-09       Impact factor: 11.105

4.  Evaluating the yield of medical tests.

Authors:  F E Harrell; R M Califf; D B Pryor; K L Lee; R A Rosati
Journal:  JAMA       Date:  1982-05-14       Impact factor: 56.272

5.  Use and misuse of the receiver operating characteristic curve in risk prediction.

Authors:  Nancy R Cook
Journal:  Circulation       Date:  2007-02-20       Impact factor: 29.690

6.  Decision curve analysis: a novel method for evaluating prediction models.

Authors:  Andrew J Vickers; Elena B Elkin
Journal:  Med Decis Making       Date:  2006 Nov-Dec       Impact factor: 2.583

7.  A randomized trial of low-dose aspirin in the primary prevention of cardiovascular disease in women.

Authors:  Paul M Ridker; Nancy R Cook; I-Min Lee; David Gordon; J Michael Gaziano; Joann E Manson; Charles H Hennekens; Julie E Buring
Journal:  N Engl J Med       Date:  2005-03-07       Impact factor: 91.245

8.  Relationships between lipoprotein components and risk of myocardial infarction: age, gender and short versus longer follow-up periods in the Apolipoprotein MOrtality RISk study (AMORIS).

Authors:  I Holme; A H Aastveit; I Jungner; G Walldius
Journal:  J Intern Med       Date:  2008-02-21       Impact factor: 8.989

9.  Lipoprotein-associated phospholipase A2 and high-sensitivity C-reactive protein improve the stratification of ischemic stroke risk in the Atherosclerosis Risk in Communities (ARIC) study.

Authors:  Vijay Nambi; Ron C Hoogeveen; Lloyd Chambless; Yijuan Hu; Heejung Bang; Josef Coresh; Hanyu Ni; Eric Boerwinkle; Thomas Mosley; Richey Sharrett; Aaron R Folsom; Christie M Ballantyne
Journal:  Stroke       Date:  2008-12-18       Impact factor: 7.914

10.  Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures.

Authors:  Nancy R Cook; Paul M Ridker
Journal:  Ann Intern Med       Date:  2009-06-02       Impact factor: 25.391

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  19 in total

1.  HIV and aging: state of knowledge and areas of critical need for research. A report to the NIH Office of AIDS Research by the HIV and Aging Working Group.

Authors:  Kevin P High; Mark Brennan-Ing; David B Clifford; Mardge H Cohen; Judith Currier; Steven G Deeks; Sherry Deren; Rita B Effros; Kelly Gebo; Jörg J Goronzy; Amy C Justice; Alan Landay; Jules Levin; Paolo G Miotti; Robert J Munk; Heidi Nass; Charles R Rinaldo; Michael G Shlipak; Russell Tracy; Victor Valcour; David E Vance; Jeremy D Walston; Paul Volberding
Journal:  J Acquir Immune Defic Syndr       Date:  2012-07-01       Impact factor: 3.731

2.  Newly proposed electrocardiographic criteria for the diagnosis of left ventricular hypertrophy in a Chinese population.

Authors:  Qingmiao Shao; Lei Meng; Gary Tse; Abhishek C Sawant; Calista Zhuo Yi Chan; George Bazoukis; Adrian Baranchuk; Guangping Li; Tong Liu
Journal:  Ann Noninvasive Electrocardiol       Date:  2018-10-03       Impact factor: 1.468

Review 3.  Charting a roadmap for heart failure biomarker studies.

Authors:  Tariq Ahmad; Mona Fiuzat; Michael J Pencina; Nancy L Geller; Faiez Zannad; John G F Cleland; James V Snider; Stephan Blankenberg; Kirkwood F Adams; Rita F Redberg; Jae B Kim; Alice Mascette; Robert J Mentz; Christopher M O'Connor; G Michael Felker; James L Januzzi
Journal:  JACC Heart Fail       Date:  2014-06-11       Impact factor: 12.035

Review 4.  Novel biomarkers in chronic heart failure.

Authors:  Tariq Ahmad; Mona Fiuzat; G Michael Felker; Christopher O'Connor
Journal:  Nat Rev Cardiol       Date:  2012-03-27       Impact factor: 32.419

5.  Using repeated measures of sleep disturbances to predict future diagnosis-specific work disability: a cohort study.

Authors:  Paula Salo; Jussi Vahtera; Martica Hall; Naja Hulvej Rod; Marianna Virtanen; Jaana Pentti; Noora Sjösten; Tuula Oksanen; Mika Kivimäki
Journal:  Sleep       Date:  2012-04-01       Impact factor: 5.849

6.  Using additional information on working hours to predict coronary heart disease: a cohort study.

Authors:  Mika Kivimäki; G David Batty; Mark Hamer; Jane E Ferrie; Jussi Vahtera; Marianna Virtanen; Michael G Marmot; Archana Singh-Manoux; Martin J Shipley
Journal:  Ann Intern Med       Date:  2011-04-05       Impact factor: 25.391

7.  Discriminatory value of alanine aminotransferase for diabetes prediction: the Insulin Resistance Atherosclerosis Study.

Authors:  C Lorenzo; A J Hanley; M J Rewers; S M Haffner
Journal:  Diabet Med       Date:  2015-07-16       Impact factor: 4.359

Review 8.  Can Biomarkers Advance HIV Research and Care in the Antiretroviral Therapy Era?

Authors:  Amy C Justice; Kristine M Erlandson; Peter W Hunt; Alan Landay; Paolo Miotti; Russell P Tracy
Journal:  J Infect Dis       Date:  2018-01-30       Impact factor: 5.226

9.  Lipoprotein heterogeneity may help to detect individuals with insulin resistance.

Authors:  Carlos Lorenzo; Anthony J Hanley; Marian J Rewers; Andreas Festa; Steven M Haffner
Journal:  Diabetologia       Date:  2015-09-04       Impact factor: 10.122

10.  Predictive accuracy of the Veterans Aging Cohort Study index for mortality with HIV infection: a North American cross cohort analysis.

Authors:  Amy C Justice; Sharada P Modur; Janet P Tate; Keri N Althoff; Lisa P Jacobson; Kelly A Gebo; Mari M Kitahata; Michael A Horberg; John T Brooks; Kate Buchacz; Sean B Rourke; Anita Rachlis; Sonia Napravnik; Joseph Eron; James H Willig; Richard Moore; Gregory D Kirk; Ronald Bosch; Benigno Rodriguez; Robert S Hogg; Jennifer Thorne; James J Goedert; Marina Klein; John Gill; Steven Deeks; Timothy R Sterling; Kathryn Anastos; Stephen J Gange
Journal:  J Acquir Immune Defic Syndr       Date:  2013-02-01       Impact factor: 3.731

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