Validation of Microsimulation Models against Alternative Model Predictions and Long-Term Colorectal Cancer Incidence and Mortality Outcomes of Randomized Controlled Trials

Jie-Bin Lew, Marjolein J. E. Greuter, Michael Caruana, Emily He, Joachim Worthington, D. James St John, Finlay A. Macrae, Eleonora Feletto, Veerle M. H. Coupé and Karen Canfell
Additional contact information
Jie-Bin Lew: Prince of Wales Clinical School, University of NSW, New South Wales, Australia
Marjolein J. E. Greuter: Department of Epidemiology and Biostatistics, VU University Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Michael Caruana: Prince of Wales Clinical School, University of NSW, New South Wales, Australia
Emily He: Prince of Wales Clinical School, University of NSW, New South Wales, Australia
Joachim Worthington: Cancer Research Division, Cancer Council NSW, New South Wales, Australia
D. James St John: Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Victoria, Australia
Finlay A. Macrae: Department of Colorectal Medicine and Genetics, and Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Victoria, Australia
Eleonora Feletto: Cancer Research Division, Cancer Council NSW, New South Wales, Australia
Veerle M. H. Coupé: Department of Epidemiology and Biostatistics, VU University Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Karen Canfell: School of Public Health, Sydney Medical School, University of Sydney, New South Wales, Australia

Medical Decision Making, 2020, vol. 40, issue 6, 815-829

Abstract: Background . This study aimed to assess the validity of 2 microsimulation models of colorectal cancer (CRC), Policy1-Bowel and ASCCA. Methods . The model-estimated CRC risk in population subgroups with different health statuses, “dwell time†(time from incident precancerous polyp to symptomatically detected CRC), and reduction in symptomatically detected CRC incidence after a one-time complete removal of polyps and/or undetected CRC were compared with published findings from 3 well-established models ( MISCAN, CRC-SPIN , and SimCRC ). Furthermore, 6 randomized controlled trials (RCTs) that provided screening using a guaiac fecal occult blood test (Funen trial, Burgundy trial, and Minnesota Colon Cancer Control Study [MCCCS]) or flexible sigmoidoscopy (NORCCAP, SCORE, and UKFSST) with long-term follow-up were simulated. Model-estimated long-term relative reductions of CRC incidence (RR inc ) and mortality (RR mort ) were compared with the RCTs’ findings. Results . The Policy1-Bowel and ASCCA estimates showed more similarities to CRC-SPIN and SimCRC . For example, overall dwell times estimated by Policy1-Bowel (24.0 years) and ASCCA (25.3) were comparable to CRC-SPIN (25.8) and SimCRC (25.2) but higher than MISCAN (10.6). In addition, ∼86% of Policy1-Bowel ’s and ∼74% of ASCCA ’s estimated RR inc and RR mort were consistent with the RCTs’ long-term follow-up findings. For example, at 17 to 18 years of follow-up, the MCCCS reported RR mort of 0.67 (95% confidence interval [CI], 0.51–0.83) and 0.79 (95% CI, 0.62–0.97) for the annual and biennial screening arm, respectively, and the UKFSST reported RR mort of 0.70 (95% CI, 0.62–0.79) for CRC at all sites and 0.54 (95% CI, 0.46–0.65) for distal CRC. The corresponding model estimates were 0.65, 0.74, 0.81, and 0.61, respectively, for Policy1-Bowel and 0.65, 0.70, 0.75, and 0.58, respectively, for ASCCA . Conclusion . Policy1-Bowel and ASCCA ’s estimates are largely consistent with the data included for comparisons, which indicates good model validity.

Keywords: ASCCA; colorectal cancer; microsimulation; Policy1-Bowel; population modelling; validation (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X20944869 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:40:y:2020:i:6:p:815-829

DOI: 10.1177/0272989X20944869

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().