Literature DB >> 32845232

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

Jie-Bin Lew1,2, Marjolein J E Greuter3, Michael Caruana1,2, Emily He1,2, Joachim Worthington2, D James St John4,5, Finlay A Macrae6, Eleonora Feletto2, Veerle M H Coupé3, Karen Canfell7,2.   

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 (RRinc) and mortality (RRmort) 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 RRinc and RRmort were consistent with the RCTs' long-term follow-up findings. For example, at 17 to 18 years of follow-up, the MCCCS reported RRmort 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 RRmort 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.

Entities:  

Keywords:  ASCCA; Policy1-Bowel; colorectal cancer; microsimulation; population modelling; validation

Mesh:

Year:  2020        PMID: 32845232     DOI: 10.1177/0272989X20944869

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  3 in total

1.  A progressive three-state model to estimate time to cancer: a likelihood-based approach.

Authors:  Eddymurphy U Akwiwu; Thomas Klausch; Henriette C Jodal; Beatriz Carvalho; Magnus Løberg; Mette Kalager; Johannes Berkhof; Veerle M H Coupé
Journal:  BMC Med Res Methodol       Date:  2022-06-27       Impact factor: 4.612

2.  Colorectal Cancer Screening within Colonoscopy Capacity Constraints: Can FIT-Based Programs Save More Lives by Trading off More Sensitive Test Cutoffs against Longer Screening Intervals?

Authors:  Ethna McFerran; James F O'Mahony; Steffie Naber; Linda Sharp; Ann G Zauber; Iris Lansdorp-Vogelaar; Frank Kee
Journal:  MDM Policy Pract       Date:  2022-05-07

3.  Prioritisation of colonoscopy services in colorectal cancer screening programmes to minimise impact of COVID-19 pandemic on predicted cancer burden: A comparative modelling study.

Authors:  Francine van Wifferen; Lucie de Jonge; Joachim Worthington; Marjolein J E Greuter; Jie-Bin Lew; Claude Nadeau; Rosita van den Puttelaar; Eleonora Feletto; Jean H E Yong; Iris Lansdorp-Vogelaar; Karen Canfell; Veerle M H Coupé
Journal:  J Med Screen       Date:  2021-12-03       Impact factor: 1.687

  3 in total

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