Evidence map›Paper›PMID 41484326›Full record

ArticlePharmacoEconomics2026

Developing and Calibrating a Colorectal Cancer Microsimulation Model for Northern Ireland.

Olivia Adair, Ethna McFerran, Mark Lawler, Luuk A van Duuren, Felicity Lamrock

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Article in PharmacoEconomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Olivia AdairSchool of Mathematics and Physics, Queen's University Belfast, Belfast, Northern Ireland, UK.ORCID http://orcid.org/0000-0002-1870-3818
Ethna McFerranSchool of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK.ORCID http://orcid.org/0000-0002-8918-7822
Mark LawlerSchool of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK.ORCID http://orcid.org/0000-0002-3930-8470
Luuk A van DuurenDepartment of Public Health, Erasmus University Medical Center, Rotterdam, Netherlands.ORCID http://orcid.org/0000-0002-6286-8062
Felicity LamrockSchool of Mathematics and Physics, Queen's University Belfast, Belfast, Northern Ireland, UK. f.lamrock@qub.ac.uk.ORCID http://orcid.org/0000-0002-8395-2415

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndividual-level microsimulation models are essential for evaluating colorectal cancer (CRC) screening programmes to capture the heterogeneity in disease progression. To ensure regional relevance, such models require detailed natural history structures and robust calibration to population-specific data. This study presents the development of the first CRC natural history microsimulation model tailored to Northern Ireland (NI) for evaluating the NI Bowel Cancer Screening Programme (NI BCSP).

methodThe model simulates individual trajectories from adenoma onset to CRC diagnosis. Eight natural history parameters were calibrated to sex-specific CRC incidence data, initially using empirical (frequentist) calibration and Approximate Bayesian Computation (ABC) rejection, followed by the ABC-Markov Chain Monte Carlo (ABC-MCMC) algorithm. Other parameters were informed by NI-specific data sources.

resultsThe frequentist and ABC rejection calibration approach's posterior distributions informed the prior distribution for the ABC-MCMC approach. ABC-MCMC was informative, yielding 55 parameter sets, but results were constrained by limited calibration targets and parameter identifiability.

conclusionThis is the first NI-specific CRC microsimulation model, providing a regionally tailored platform for evaluating screening strategies and supporting policy. Calibration was feasible in a data-limited context, but further refinement and additional targets are needed to improve parameter estimation.

Indexed as

Colorectal NeoplasmsEarly Detection of CancerAgedAlgorithmsBayes TheoremCalibrationComputer SimulationDisease ProgressionFemaleHumansIncidenceMaleMarkov ChainsMass ScreeningMiddle AgedMonte Carlo Method

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.