title: Validation of Models Used to Inform Colorectal Cancer Screening Guidelines: Accuracy and Implications.
abstract: Microsimulation models synthesize evidence about disease processes and interventions, providing a method for predicting long-term benefits and harms of prevention, screening, and treatment strategies. Because models often require assumptions about unobservable processes, assessing a model's predictive accuracy is important.
  
  
  
  We validated 3 colorectal cancer (CRC) microsimulation models against outcomes from the United Kingdom Flexible Sigmoidoscopy Screening (UKFSS) Trial, a randomized controlled trial that examined the effectiveness of one-time flexible sigmoidoscopy screening to reduce CRC mortality. The models incorporate different assumptions about the time from adenoma initiation to development of preclinical and symptomatic CRC. Analyses compare model predictions to study estimates across a range of outcomes to provide insight into the accuracy of model assumptions.
  
  
  
  All 3 models accurately predicted the relative reduction in CRC mortality 10 years after screening (predicted hazard ratios, with 95% percentile intervals: 0.56 [0.44, 0.71], 0.63 [0.51, 0.75], 0.68 [0.53, 0.83]; estimated with 95% confidence interval: 0.56 [0.45, 0.69]). Two models with longer average preclinical duration accurately predicted the relative reduction in 10-year CRC incidence. Two models with longer mean sojourn time accurately predicted the number of screen-detected cancers. All 3 models predicted too many proximal adenomas among patients referred to colonoscopy.
  
  
  
  Model accuracy can only be established through external validation. Analyses such as these are therefore essential for any decision model. Results supported the assumptions that the average time from adenoma initiation to development of preclinical cancer is long (up to 25 years), and mean sojourn time is close to 4 years, suggesting the window for early detection and intervention by screening is relatively long. Variation in dwell time remains uncertain and could have important clinical and policy implications.
authors.affiliation: RAND Corporation, Santa Monica, CA, USA (CMR)
authors.forename: Carolyn M
authors.initials: CM
authors.lastname: Rutter
authors.affiliation: Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA, USA (ABK)
authors.forename: Amy B
authors.initials: AB
authors.lastname: Knudsen
authors.affiliation: Department of Biostatistics, University of Washington, Seattle, WA, USA (TLM)
authors.forename: Tracey L
authors.initials: TL
authors.lastname: Marsh
authors.affiliation: National Cancer Institute, Health Systems & Intervention Research Branch, Bethesda, MD, USA (VPD)
authors.forename: V Paul
authors.initials: VP
authors.lastname: Doria-Rose
authors.affiliation: Group Health Research Institute, Seattle, WA, USA (EJ, CP)
authors.forename: Eric
authors.initials: E
authors.lastname: Johnson
authors.affiliation: Group Health Research Institute, Seattle, WA, USA (EJ, CP)
authors.forename: Chester
authors.initials: C
authors.lastname: Pabiniak
authors.affiliation: Department of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN, USA (KMK)
authors.forename: Karen M
authors.initials: KM
authors.lastname: Kuntz
authors.affiliation: Department of Public Health, Erasmus MC, Rotterdam, Netherlands (MVB, IL)
authors.forename: Marjolein
authors.initials: M
authors.lastname: van Ballegooijen
authors.affiliation: Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA (AGZ)
authors.forename: Ann G
authors.initials: AG
authors.lastname: Zauber
authors.affiliation: Department of Public Health, Erasmus MC, Rotterdam, Netherlands (MVB, IL)
authors.forename: Iris
authors.initials: I
authors.lastname: Lansdorp-Vogelaar
mesh_terms: D015179:Colorectal Neoplasms / Q000175:diagnosis* / Q000401:mortality; D006801:Humans; D007258:Informed Consent; D008403:Mass Screening / Q000379:methods*; D008962:Models, Theoretical; D017410:Practice Guidelines as Topic; D006113:United Kingdom
keywords: colorectal cancer; discrete event simulation; gastroenterology; preventive medicine; simulation methods