title: The contribution of mammography screening to breast cancer incidence trends in the United States: an updated age-period-cohort model.
abstract: BACKGROUND
  The impact of screening mammography on breast cancer incidence is difficult to disentangle from cohort- and age-related effects on incidence.
  
  
  METHODS
  We developed an age-period-cohort model of ductal carcinoma in situ (DCIS) and invasive breast cancer incidence in U.S. females using cancer registry data. Five functions were included in the model to estimate stage-specific effects for age, premenopausal birth cohorts, postmenopausal birth cohorts, period (for all years of diagnosis), and a mammography period effect limited to women ages ≥ 40 years after 1982. Incidence with and without the mammography period effect was calculated.
  
  
  RESULTS
  More recent birth cohorts have elevated underlying risk compared with earlier cohorts for both pre- and postmenopausal women. Comparing models with and without the mammography period effect showed that overall breast cancer incidence would have been 23.1% lower in the absence of mammography in 2010 (95% confidence intervals, 18.8-27.4), including 14.7% (9.5-19.3) lower for invasive breast cancer and 54.5% (47.4-59.6) lower for DCIS. Incidence of distant-staged breast cancer in 2010 would have been 29.0% (13.1-48.1) greater in the absence of mammography screening.
  
  
  CONCLUSIONS
  Mammography contributes to markedly elevated rates of DCIS and early-stage invasive cancers, but also contributes to substantial reductions in the incidence of metastatic breast cancer.
  
  
  CONCLUSIONS
  Mammography is an important tool for reducing the burden of breast cancer, but future work is needed to identify risk factors accounting for increasing underlying incidence and to distinguish between indolent and potentially lethal early-stage breast cancers that are detected via mammography.
authors: Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin. Department of Population Health Sciences, University of Wisconsin, Madison, Wisconsin. Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin.
authors: Ronald E
authors: RE
authors: Gangnon
authors: Department of Surgery and Vermont Cancer Center, University of Vermont, Burlington, Vermont.
authors: Brian L
authors: BL
authors: Sprague
authors: Department of Population Medicine, Harvard Medical School, Boston, Massachusetts.
authors: Natasha K
authors: NK
authors: Stout
authors: Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin. Department of Industrial and System Engineering, University of Wisconsin, Madison, Wisconsin.
authors: Oguz
authors: O
authors: Alagoz
authors: Oslo Center for Biostatistics and Epidemiology, Research Support Services, Oslo University Hospital, Oslo, Norway.
authors: Harald
authors: H
authors: Weedon-Fekjær
authors: Yale University School of Medicine, New Haven, Connecticut.
authors: Theodore R
authors: TR
authors: Holford
authors: Department of Population Health Sciences, University of Wisconsin, Madison, Wisconsin. Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin. trentham@wisc.edu.
authors: Amy
authors: A
authors: Trentham-Dietz
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000000981:diagnostic imaging / Q000453:epidemiology* / Q000473:pathology; D018270:Carcinoma, Ductal, Breast / Q000000981:diagnostic imaging / Q000453:epidemiology* / Q000473:pathology; D002285:Carcinoma, Intraductal, Noninfiltrating / Q000000981:diagnostic imaging / Q000453:epidemiology* / Q000473:pathology; D015331:Cohort Studies; D055088:Early Detection of Cancer; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008327:Mammography / Q000379:methods*; D008875:Middle Aged; D015233:Models, Statistical; D009367:Neoplasm Staging; D011379:Prognosis; D012307:Risk Factors; D018426:SEER Program; D013997:Time Factors; D014481:United States / Q000453:epidemiology; D055815:Young Adult