title: Early-Phase Studies of Biomarkers: What Target Sensitivity and Specificity Values Might Confer Clinical Utility?
abstract: Many cancer biomarker research studies seek to develop markers that can accurately detect or predict future onset of disease. To design and evaluate these studies, one must specify the levels of accuracy sought. However, justified target levels are rarely available.
  
  
  
  We describe a way to calculate target levels of sensitivity and specificity for a biomarker intended to be applied in a defined clinical context. The calculation requires knowledge of the prevalence or incidence of cases in the clinical population and the ratio of benefit associated with the clinical consequences of a positive biomarker test in cases (true positive) to cost associated with a positive biomarker test in controls (false positive). Guidance is offered on soliciting the cost/benefit ratio. The calculations are based on the longstanding decision theory concept of providing a net benefit on average in the population, and they rely on some assumptions about uniformity of costs and benefits to those tested.
  
  
  
  Calculations are illustrated with 3 applications: predicting colon cancer recurrence in stage 1 patients; predicting interval breast cancer (between mammography screenings); and screening for ovarian cancer.
  
  
  
  It is feasible to specify target levels of biomarker performance that enable evaluation of the potential clinical impact of biomarkers in early-phase studies. Nevertheless, biomarkers meeting the criteria should still be tested rigorously in studies that measure the actual impact on patient outcomes of using the biomarker to make clinical decisions.
authors.affiliation: Biostatistics and Biomathematics Program, Public Health Sciences Division, mspepe@u.washington.edu.
authors.forename: Margaret S
authors.initials: MS
authors.lastname: Pepe
authors.affiliation: Vaccine and Infectious Disease Division, Public Health Sciences Division, and.
authors.forename: Holly
authors.initials: H
authors.lastname: Janes
authors.affiliation: Translational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA;
authors.forename: Christopher I
authors.initials: CI
authors.lastname: Li
authors.affiliation: Clinical Epidemiology, University of Amsterdam, Amsterdam, Netherlands;
authors.forename: Patrick M
authors.initials: PM
authors.lastname: Bossuyt
authors.affiliation: Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX;
authors.forename: Ziding
authors.initials: Z
authors.lastname: Feng
authors.affiliation: Department of Biostatistics, Institute of Medical Genetics, University of Copenhagen, Copenhagen, Denmark.
authors.forename: Jørgen
authors.initials: J
authors.lastname: Hilden
mesh_terms: D000368:Aged; D014408:Biomarkers, Tumor / Q000032:analysis*; D001943:Breast Neoplasms / Q000175:diagnosis*; D003110:Colonic Neoplasms / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008875:Middle Aged; D010051:Ovarian Neoplasms / Q000175:diagnosis*; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor