Assessment of improved prediction beyond traditional risk factors: When does a difference make a difference?

Circulation: Cardiovascular Genetics

Volumn 3, Issue 1, 2010, Pages 3-5

  Janssens, A Cecile J W ^a   Khoury, Muin J ^b  

^a ERASMUS MEDICAL CENTER   (Netherlands)

^b NATIONAL CENTER ON BIRTH DEFECTS AND DEVELOPMENTAL DISABILITIES   (United States)

Author keywords

Area under receiver operating characteristic curve; Cardiovascular disease; Editorial; Family history; Prediction; Reclassification; Risk assessment

Indexed keywords

C REACTIVE PROTEIN; CALCIUM;

ARTERY CALCIFICATION; CARDIOVASCULAR DISEASE; CARDIOVASCULAR RISK; CLINICAL PRACTICE; CORONARY ARTERY DISEASE; EDITORIAL; FAMILY HISTORY; GENETIC ASSOCIATION; GENOME ANALYSIS; HUMAN; MEDICAL DECISION MAKING; PREDICTION; PRIORITY JOURNAL; REFERENCE VALUE; RISK ASSESSMENT; SINGLE NUCLEOTIDE POLYMORPHISM; AREA UNDER THE CURVE; BIOLOGICAL MODEL; CALCINOSIS; CLASSIFICATION; GENETICS; NOTE; PREDICTION AND FORECASTING; RISK FACTOR;

AREA UNDER CURVE; CALCINOSIS; CARDIOVASCULAR DISEASES; CORONARY ARTERY DISEASE; HUMANS; MODELS, GENETIC; PREDICTIVE VALUE OF TESTS; RISK FACTORS;

EID: 77952478836     PISSN: 1942325X     EISSN: 19423268     Source Type: Journal    
DOI: 10.1161/CIRCGENETICS.110.938092     Document Type: Editorial

References (21)

1. Tzoulaki I, Liberopoulos G, Ioannidis JP. Assessment of claims of improved prediction beyond the Framingham risk score. J Am Med Assoc. 2009;302:2345-2352.
2. Manolio TA, Brooks LD, Collins FS. A HapMap harvest of insights into the genetics of common disease. J Clin Invest. 2008;118:1590-1605.
3. Berg AO, Baird MA, Botkin JR, Driscoll DA, Fishman PA, Guarino PD, Hiatt RA, Jarvik GP, Millon-Underwood S, Morgan TM, Mulvihill JJ, Pollin TI, Schimmel SR, Stefanek ME, Vollmer WM, Williams JK. National Institutes of Health state-of-the-science conference statement: family history and improving health. Ann Intern Med. 2009;151: 872-877.
4. Harrison TA, Hindorff LA, Kim H, Wines RC, Bowen DJ, McGrath BB, Edwards KL. Family history of diabetes as a potential public health tool. Am J Prev Med. 2003;24:152-159.
5. Wandeler G, Paccaud F, Vollenweider P, Waeber G, Mooser V, Bochud M. Strength of family history in predicting levels of blood pressure, plasma glucose and cholesterol. Public Health Genomics. 2009 [Epub ahead of print].
6. Yoon PW, Scheuner MT, Peterson-Oehlke KL, Gwinn M, Faucett A, Khoury MJ. Can family history be used as a tool for public health and preventive medicine? Genet Med. 2002;4:304-310.
7. Guttmacher AE, Collins FS, Carmona RH. The family history-more important than ever. N Engl J Med. 2004;351:2333-2336.
8. Valdez R, Yoon PW, Qureshi N, Fisk JD, Green R, Khoury MJ. Family history in public health practice: a genomic tool for disease prevention and health promotion. Ann Rev Public Health. 2010.
9. Scheuner MT, Setodji CM, Pankow JS, Blumenthal RS, Keeler E. General cardiovascular risk profile identifies advanced coronary artery calcium and is improved by family history: The Multi-Ethnic Study of Atherosclerosis. Circ Cardiovasc Genet. 2010;3:97-105.
10. Hlatky MA, Greenland P, Arnett DK, Ballantyne CM, Criqui MH, Elkind MS, Go AS, Harrell FE Jr, Hong Y, Howard BV, Howard VJ, Hsue PY, Kramer CM, McConnell JP, Normand SL, O'Donnell CJ, Smith SC Jr, Wilson PW. Criteria for evaluation of novel markers of cardiovascular risk: a scientific statement from the American Heart Association. Circulation. 2009;119:2408-2416.
11. Janes H, Pepe MS, Gu W. Assessing the value of risk predictions by using risk stratification tables. Ann Intern Med. 2008;149:751-760.
12. Cook NR. Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation. 2007;115:928-935.
13. Pepe MS, Janes HE. Gauging the performance of SNPs, biomarkers, and clinical factors for predicting risk of breast cancer. J Natl Cancer Inst. 2008;100:978-979.
14. Steyerberg EW, Vickers AJ, Cook NR, Gerds T, Gonen M, Obuchowski N, Pencina MJ, Kattan MW. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology. 2010;21:128-138.
15. Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27:157-172.
16. McGeechan K, Macaskill P, Irwig L, Liew G, Wong TY. Assessing new biomarkers and predictive models for use in clinical practice: a clinician's guide. Arch Intern Med. 2008;168:2304-2310.
17. Janssens AC, Van Duijn CM. Genome-based prediction of common diseases: methodological considerations for future research. Genome Med. 2009;1:20.
18. Lyssenko V, Almgren P, Anevski D, Orho-Melander M, Sjogren M, Saloranta C, Tuomi T, Groop L; the Botnia Study Group. Genetic prediction of future type 2 Diabetes. PLOS Med. 2005;2:e345.
19. Janssens ACJW, Gwinn M, Subramonia-Iyer S, Khoury MJ. Does genetic testing really improve the prediction of future type 2 diabetes? PLOS Medicine. 2006;3:e114.
20. Paynter NP, Chasman DI, Buring JE, Shiffman D, Cook NR, Ridker PM. Cardiovascular disease risk prediction with and without knowledge of genetic variation at chromosome 9p21.3. Ann Intern Med. 2009;150: 65-72.
21. Cook NR, Ridker PM. Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures. Ann Intern Med. 2009;150:795-802.