title: Invited commentary: the importance of prevalence in the effectiveness of a (bio)marker.
abstract: Metrics such as relative hazards and relative risks do not account for the prevalence of a marker over time and its relation to whether and when an outcome occurs. Uncommon markers that have good predictive values and common markers that are poorly predictive may not be (clinically) useful in predicting disease and other health outcomes. Recent work by Little et al. (Am J Epidemiol. 2011;173(12):1380-1387) highlights the development of a new method that considers both factors in predicting outcomes. Measures that incorporate both marker prevalence and predictive values and therefore are measures of "effectiveness" may be broadly helpful in deciding which markers or exposures are useful in disease screening or should be targeted by health interventions.
authors.affiliation: Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
authors.forename: Arpita
authors.initials: A
authors.lastname: Ghosh
authors.forename: Philip E
authors.initials: PE
authors.lastname: Castle
mesh_terms: D015415:Biomarkers; D005260:Female; D006801:Humans; D008593:Menopause; D008597:Menstrual Cycle; D008875:Middle Aged; D011237:Predictive Value of Tests; D015995:Prevalence; D017584:Reproductive History
chemical_list: D015415:Biomarkers