title: Identifying individuals at high risk of melanoma: a practical predictor of absolute risk.
abstract: OBJECTIVE
  We developed a model to estimate the 5-year absolute risk of melanoma to efficiently identify individuals at increased risk of melanoma for potential interventions.
  
  
  METHODS
  We used data from a case-control study with 718 non-Hispanic white patients with invasive cutaneous melanoma from melanoma clinics in Philadelphia, PA and San Francisco, CA; matched controls were 945 patients from outpatient clinics with similar catchment areas. All participants underwent extensive interviews and skin examinations. We selected easily obtained clinical characteristics and responses to simple questions for study in order to develop sex-specific relative risk models. These models were combined with incidence and mortality rates by United States geographic areas to develop estimates of the absolute risk of developing melanoma within 5 years.
  
  
  RESULTS
  Relative risk models yielded an attributable risk of 86% for men and 89% for women, using at most seven variables. Attributable risks did not vary by age, ultraviolet B flux or hours outdoors. The absolute individual risks varied widely, depending on age, other host characteristics, and geographic area. Individual absolute risk can be estimated using a program available online.
  
  
  CONCLUSIONS
  Our procedures allow for estimating the absolute risk of developing melanoma to assist in the identification of patients at high risk. Such high-risk individuals could undergo interventions including a complete skin examination, counseling to avoid sun exposures, regular self and professional surveillance, or participation in prevention trials. It is important to emphasize that these projections are not intended to identify current melanoma cases.
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. fearst@epndce.nci.nih.gov
authors.forename: Thomas R
authors.initials: TR
authors.lastname: Fears
authors.forename: DuPont
authors.initials: D
authors.lastname: Guerry
authors.forename: Ruth M
authors.initials: RM
authors.lastname: Pfeiffer
authors.forename: Richard W
authors.initials: RW
authors.lastname: Sagebiel
authors.forename: David E
authors.initials: DE
authors.lastname: Elder
authors.forename: Allan
authors.initials: A
authors.lastname: Halpern
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Holly
authors.forename: Patricia
authors.initials: P
authors.lastname: Hartge
authors.forename: Margaret A
authors.initials: MA
authors.lastname: Tucker
mesh_terms: D000328:Adult; D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D016022:Case-Control Studies; D005260:Female; D006630:Hispanic or Latino / Q000706:statistics & numerical data; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008297:Male; D008545:Melanoma / Q000453:epidemiology* / Q000209:etiology* / Q000401:mortality; D008875:Middle Aged; D015143:Philadelphia / Q000453:epidemiology; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors; D018426:SEER Program; D012495:San Francisco / Q000453:epidemiology; D012878:Skin Neoplasms / Q000453:epidemiology* / Q000209:etiology* / Q000401:mortality; D011795:Surveys and Questionnaires; D014481:United States / Q000453:epidemiology