title: Using observational data to estimate an upper bound on the reduction in cancer mortality due to periodic screening.
abstract: BACKGROUND
  Because randomized cancer screening trials are very expensive, observational cancer screening studies can play an important role in the early phases of screening evaluation. Periodic screening evaluation (PSE) is a methodology for estimating the reduction in population cancer mortality from data on subjects who receive regularly scheduled screens. Although PSE does not require assumptions about natural history of cancer it requires other assumptions, particularly progressive detection - the assumption that once a cancer is detected by a screening test, it will always be detected by the screening test.
  
  
  METHODS
  We formulate a simple version of PSE and show that it leads to an upper bound on screening efficacy if the progressive detection assumption does not hold (and any effect of birth cohort is minimal) To determine if the upper bound is reasonable, for three randomized screening trials, we compared PSE estimates based only on screened subjects with PSE estimates based on all subjects.
  
  
  RESULTS
  In the three randomized screening trials, PSE estimates based on screened subjects gave fairly close results to PSE estimates based on all subjects.
  
  
  CONCLUSIONS
  PSE has promise for obtaining an upper bound on the reduction in population cancer mortality rates based on observational screening data. If the upper bound estimate is found to be small and any birth cohort effects are likely minimal, then a definitive randomized trial would not be warranted.
authors.affiliation: Biometry Research Group, Division of Cancer Prevention, National Cancer Institute, USA. sb16i@nih.gov
authors.forename: Stuart G
authors.initials: SG
authors.lastname: Baker
authors.forename: Diane
authors.initials: D
authors.lastname: Erwin
authors.forename: Barnett S
authors.initials: BS
authors.lastname: Kramer
authors.forename: Philip C
authors.initials: PC
authors.lastname: Prorok
mesh_terms: D000367:Age Factors; D001699:Biometry / Q000379:methods*; D001943:Breast Neoplasms / Q000175:diagnosis / Q000401:mortality; D015179:Colorectal Neoplasms / Q000401:mortality; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis / Q000401:mortality; D008910:Minnesota; D009369:Neoplasms / Q000175:diagnosis / Q000401:mortality*; D009518:New York; D016032:Randomized Controlled Trials as Topic; D015203:Reproducibility of Results; D016008:Statistical Distributions