Literature DB >> 22458749

Individual risk.

Ralph H Stern1.   

Abstract

Patients don't have an "individual risk" or unique probability of an outcome. Outside Mendelian inheritance, risks are conditional probabilities and differ as the risk factors included differ, at times substantially. This lack of reliability is an inherent limitation and is not resolved by including additional risk factors. Groups of like individuals need to be assembled to measure the probability of an outcome. Many groups, like any individual, can be identified, eg, groups of the same age, sex, race, or any combination of these attributes (or any others). That each of these groups may have different risk means there is no such thing as individual risk. This issue was identified by John Venn in 1866 and is known as the reference class problem. Models relate risk factors to outcomes in populations. The number calculated for an individual should not be reported as their individual or true risk, nor should it be used as the sole criterion for clinical decisions. Instead, Feinstein proposed relying on clinically important subgroups. An example would be utilizing an individual's blood pressure as the primary determinant of hypertension treatment decisions, not an unreliable individual risk estimate.
© 2012 Wiley Periodicals, Inc.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 22458749      PMCID: PMC8108880          DOI: 10.1111/j.1751-7176.2012.00592.x

Source DB:  PubMed          Journal:  J Clin Hypertens (Greenwich)        ISSN: 1524-6175            Impact factor:   3.738


  14 in total

1.  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.

Authors:  Thomas A Pearson; George A Mensah; R Wayne Alexander; Jeffrey L Anderson; Richard O Cannon; Michael Criqui; Yazid Y Fadl; Stephen P Fortmann; Yuling Hong; Gary L Myers; Nader Rifai; Sidney C Smith; Kathryn Taubert; Russell P Tracy; Frank Vinicor
Journal:  Circulation       Date:  2003-01-28       Impact factor: 29.690

2.  Comment: Measures to summarize and compare the predictive capacity of markers.

Authors:  Nancy R Cook
Journal:  Int J Biostat       Date:  2010-07-06       Impact factor: 0.968

3.  Improvement of risk prediction by genomic profiling: reclassification measures versus the area under the receiver operating characteristic curve.

Authors:  Raluca Mihaescu; Moniek van Zitteren; Mandy van Hoek; Eric J G Sijbrands; André G Uitterlinden; Jacqueline C M Witteman; Albert Hofman; M G Myriam Hunink; Cornelia M van Duijn; A Cecile J W Janssens
Journal:  Am J Epidemiol       Date:  2010-06-18       Impact factor: 4.897

4.  Interview of William Kannel, MD. Interview by Peter Wilson, Henry Greenberg.

Authors:  William Kannel
Journal:  Prog Cardiovasc Dis       Date:  2010 Jul-Aug       Impact factor: 8.194

5.  Risk refinement, reclassification, and treatment thresholds in primary prevention of cardiovascular disease: incremental progress but significant gaps remain.

Authors:  Patrick G O'Malley; Rita F Redberg
Journal:  Arch Intern Med       Date:  2010-09-27

6.  Integrating information from novel risk factors with calculated risks: the critical impact of risk factor prevalence.

Authors:  Albertus J Kooter; Piet J Kostense; Jan Groenewold; Abel Thijs; Naveed Sattar; Yvo M Smulders
Journal:  Circulation       Date:  2011-08-09       Impact factor: 29.690

7.  Limitations of the Gail model in the specialized breast cancer risk assessment clinic.

Authors:  David M Euhus; A Marilyn Leitch; James F Huth; George N Peters
Journal:  Breast J       Date:  2002 Jan-Feb       Impact factor: 2.431

8.  Outcome prediction for individual intensive care patients: useful, misused, or abused?

Authors:  S Lemeshow; J Klar; D Teres
Journal:  Intensive Care Med       Date:  1995-09       Impact factor: 17.440

Review 9.  Emerging risk factors for coronary heart disease: a summary of systematic reviews conducted for the U.S. Preventive Services Task Force.

Authors:  Mark Helfand; David I Buckley; Michele Freeman; Rongwei Fu; Kevin Rogers; Craig Fleming; Linda L Humphrey
Journal:  Ann Intern Med       Date:  2009-10-06       Impact factor: 25.391

10.  Concept and usefulness of cardiovascular risk profiles.

Authors:  William B Kannel; Ralph B D'Agostino; Lisa Sullivan; Peter W F Wilson
Journal:  Am Heart J       Date:  2004-07       Impact factor: 4.749

View more
  6 in total

Review 1.  Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects.

Authors:  David M Kent; Ewout Steyerberg; David van Klaveren
Journal:  BMJ       Date:  2018-12-10

2.  Using group data to treat individuals: understanding heterogeneous treatment effects in the age of precision medicine and patient-centred evidence.

Authors:  Issa J Dahabreh; Rodney Hayward; David M Kent
Journal:  Int J Epidemiol       Date:  2016-12-01       Impact factor: 7.196

3.  The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement: Explanation and Elaboration.

Authors:  David M Kent; David van Klaveren; Jessica K Paulus; Ralph D'Agostino; Steve Goodman; Rodney Hayward; John P A Ioannidis; Bray Patrick-Lake; Sally Morton; Michael Pencina; Gowri Raman; Joseph S Ross; Harry P Selker; Ravi Varadhan; Andrew Vickers; John B Wong; Ewout W Steyerberg
Journal:  Ann Intern Med       Date:  2019-11-12       Impact factor: 25.391

Review 4.  Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities.

Authors:  Jessica K Paulus; David M Kent
Journal:  NPJ Digit Med       Date:  2020-07-30

5.  Impact of sample size on the stability of risk scores from clinical prediction models: a case study in cardiovascular disease.

Authors:  Alexander Pate; Richard Emsley; Matthew Sperrin; Glen P Martin; Tjeerd van Staa
Journal:  Diagn Progn Res       Date:  2020-09-09

6.  The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement.

Authors:  David M Kent; Jessica K Paulus; David van Klaveren; Ralph D'Agostino; Steve Goodman; Rodney Hayward; John P A Ioannidis; Bray Patrick-Lake; Sally Morton; Michael Pencina; Gowri Raman; Joseph S Ross; Harry P Selker; Ravi Varadhan; Andrew Vickers; John B Wong; Ewout W Steyerberg
Journal:  Ann Intern Med       Date:  2019-11-12       Impact factor: 25.391

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.