title: Effects of mammography screening under different screening schedules: model estimates of potential benefits and harms.
abstract: BACKGROUND
  Despite trials of mammography and widespread use, optimal screening policy is controversial.
  
  
  OBJECTIVE
  To evaluate U.S. breast cancer screening strategies.
  
  
  METHODS
  6 models using common data elements.
  
  
  METHODS
  National data on age-specific incidence, competing mortality, mammography characteristics, and treatment effects.
  
  
  METHODS
  A contemporary population cohort.
  
  
  METHODS
  Lifetime.
  
  
  CONCLUSIONS
  Societal.
  
  
  METHODS
  20 screening strategies with varying initiation and cessation ages applied annually or biennially.
  
  
  METHODS
  Number of mammograms, reduction in deaths from breast cancer or life-years gained (vs. no screening), false-positive results, unnecessary biopsies, and overdiagnosis.
  
  
  RESULTS
  The 6 models produced consistent rankings of screening strategies. Screening biennially maintained an average of 81% (range across strategies and models, 67% to 99%) of the benefit of annual screening with almost half the number of false-positive results. Screening biennially from ages 50 to 69 years achieved a median 16.5% (range, 15% to 23%) reduction in breast cancer deaths versus no screening. Initiating biennial screening at age 40 years (vs. 50 years) reduced mortality by an additional 3% (range, 1% to 6%), consumed more resources, and yielded more false-positive results. Biennial screening after age 69 years yielded some additional mortality reduction in all models, but overdiagnosis increased most substantially at older ages.
  
  
  RESULTS
  Varying test sensitivity or treatment patterns did not change conclusions.
  
  
  CONCLUSIONS
  Results do not include morbidity from false-positive results, patient knowledge of earlier diagnosis, or unnecessary treatment.
  
  
  CONCLUSIONS
  Biennial screening achieves most of the benefit of annual screening with less harm. Decisions about the best strategy depend on program and individual objectives and the weight placed on benefits, harms, and resource considerations.
  
  
  BACKGROUND
  National Cancer Institute.
authors.affiliation: Georgetown University Medical Center and Lombardi Comprehensive Cancer Center, Washington, DC, USA. mandelbj@georgetown.edu
authors.forename: Jeanne S
authors.initials: JS
authors.lastname: Mandelblatt
authors.forename: Kathleen A
authors.initials: KA
authors.lastname: Cronin
authors.forename: Stephanie
authors.initials: S
authors.lastname: Bailey
authors.forename: Donald A
authors.initials: DA
authors.lastname: Berry
authors.forename: Harry J
authors.initials: HJ
authors.lastname: de Koning
authors.forename: Gerrit
authors.initials: G
authors.lastname: Draisma
authors.forename: Hui
authors.initials: H
authors.lastname: Huang
authors.forename: Sandra J
authors.initials: SJ
authors.lastname: Lee
authors.forename: Mark
authors.initials: M
authors.lastname: Munsell
authors.forename: Sylvia K
authors.initials: SK
authors.lastname: Plevritis
authors.forename: Peter
authors.initials: P
authors.lastname: Ravdin
authors.forename: Clyde B
authors.initials: CB
authors.lastname: Schechter
authors.forename: Bronislava
authors.initials: B
authors.lastname: Sigal
authors.forename: Michael A
authors.initials: MA
authors.lastname: Stoto
authors.forename: Natasha K
authors.initials: NK
authors.lastname: Stout
authors.forename: Nicolien T
authors.initials: NT
authors.lastname: van Ravesteyn
authors.forename: John
authors.initials: J
authors.lastname: Venier
authors.forename: Marvin
authors.initials: M
authors.lastname: Zelen
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Feuer
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000175:diagnosis / Q000453:epidemiology* / Q000401:mortality; D055088:Early Detection of Cancer; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008327:Mammography / Q000009:adverse effects / Q000191:economics; D008403:Mass Screening / Q000009:adverse effects / Q000191:economics / Q000379:methods*; D008875:Middle Aged; D015233:Models, Statistical; D012680:Sensitivity and Specificity; D013997:Time Factors