Individual Risk

Journal of Clinical Hypertension

Volumn 14, Issue 4, 2012, Pages 261-264

  Stern, Ralph H ^a  

^a UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BLOOD PRESSURE; HUMAN; HYPERTENSION; INDIVIDUAL RISK; MEDICAL DECISION MAKING; OUTCOME ASSESSMENT; PRIORITY JOURNAL; REVIEW; RISK FACTOR;

BIOLOGICAL MARKERS; HUMANS; MODELS, THEORETICAL; PREDICTIVE VALUE OF TESTS; PROBABILITY; PROGNOSIS; RISK ASSESSMENT;

EID: 84859419814     PISSN: 15246175     EISSN: 17517176     Source Type: Journal    
DOI: 10.1111/j.1751-7176.2012.00592.x     Document Type: Review

References (19)

1. Wilson P, Greenberg H. Interview of William Kannel, MD. Prog Cardiovasc Dis. 2010;53:4-9.
2. Truett J, Cornfield J, Kannel W. A multivariate analysis of the risk of coronary heart disease in framingham. J Chronic Dis. 1967;20:511-524.
3. American Heart Association. Coronary Risk Handbook: Estimating Risk of Coronary Heart Disease in Daily Practice. New York, NY: American Heart Association; 1973.
4. Lemeshow S, Klar J, Teres D. Outcome prediction for individual intensive care patients: useful, misused, or abused? Intensive Care Med. 1995;21:770-776.
5. Stern RH. The discordance of individual risk estimates and the reference class problem. arXiv:1001.2499v1[q-bio.QM]. Accessed January 30, 2012.
6. Gurm HS, Kaufman SR, Smith DE, et al. Different risk models predict markedly different probability of death for the same patient: implications of using risk models for individual patients. Eur Heart J. 2011;32(suppl 1):742.
7. Pepe M. Rejoinder to Nancy Cook's comment on "measures to summarize and compare the predictive capacity of markers." Int J Biostat. 2010; 6: Article 25. Accessed January 30, 2012.
8. Pepe MS. Problems with reclassification methods for evaluating prediction models. Am J Epidemiol. 2011;173:1327-1335.
9. Von Mises R. Probability, Statistics and Truth. New York, NY: Dover Publications, Inc; 1981: 17.
10. Mihaescu M, van Zitteren M, van Hoek M, et al. Improvement of risk prediction by genomic profiling: reclassicfication measures versus the area under the receiver operating characteristic curve. Am J Epidemiol. 2010;172:353-361.
11. Kannel WB, D'Agostino RB, Sullivan L, Wilson PWF. Concept and usefulness of cardiovascular risk profiles. Am Heart J. 2004;148:16-26.
12. Mihaescu R, van Hoek M, Sijbrands EJG, et al. Evaluation of risk prediction updates from commercial genome-wide scans. Genet Med. 2009;11:588-594.
13. Helfand M, Buckley DI, Freeman M, et al. Emerging risk factors for coronary heart disease: a summary of systematic reviews conducted for the U.S. Preventive services task force. Ann Intern Med. 2009;151:496-507.
14. O'Malley PG, Redberg RF. Risk refinement, reclassification, and treatment thresholds in primary prevention of cardiovascular disease incremental progress but significant gaps remain. Arch Intern Med. 2010;170:1602-1603.
15. McTiernan A, Kuniyuki A, Yasui Y, et al. Comparisons of two breast cancer risk estimates in women with a family history of breast cancer. Cancer Epidemol Biomarkers Prev. 1997;50:547-556.
16. Euhus DM, Leitch AM, Huth JF, Peters GN. Limitations of the Gail model in the specialized breast cancer risk assessment clinic. Breast J. 2002;8:23-27.
17. Pearson TA, Mensah GA, Alexander RW, et al. Markers of inflammation and cardiovascular disease, application to clinical and public health practice, a statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation. 2003;107:499-511.
18. Kooter AJ, Kostense PJ, Groenewold J, et al. Integrating information from novel risk factors with calculated risks the critical impact of risk factor prevalence. Circulation. 2011;124:741-745.
19. Feinstein AR. Multivariable Analysis an Introduction. New Haven, CT: Yale University Press; 1996:566.