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Irish MOdelling of Diagnosis-related And Lead-time Overdiagnosis in Lung Cancer Screening (I-MODAL-Lung)

Principal Investigator
Name
Patrick Redmond
Degrees
MB BCh BAO PhD
Institution
Royal College of Surgeons in Ireland
Position Title
Associate Professor in General Practice
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-1442
Initial CDAS Request Approval
Sep 24, 2025
Title
Irish MOdelling of Diagnosis-related And Lead-time Overdiagnosis in Lung Cancer Screening (I-MODAL-Lung)
Summary
Lung cancer is the leading cause of cancer-related death in Ireland, but no national screening programme currently exists. Low-dose CT (LDCT) screening has been shown to reduce lung cancer mortality; however, it also introduces the risk of overdiagnosis—the detection of cancers that would not have become clinically significant. Existing estimates of overdiagnosis from trials such as the NLST are not directly transferable to the Irish population due to differences in smoking patterns, comorbidity profiles, and life expectancy.

The I-MODAL-Lung project aims to develop a robust, context-specific evidence base to inform the design of a proportionate, equitable LDCT screening programme for Ireland. We will use individual-level data from the NLST and NELSON trials to estimate age-, sex-, and histology-specific overdiagnosis rates adjusted for lead-time and competing mortality. These parameters will be embedded in an Irish-adapted MISCAN-Lung microsimulation model to simulate screening outcomes, including deaths averted, overdiagnosed cases, cost-effectiveness, and equity impacts across eligibility criteria and screening intervals.

The results will inform national screening policy and support broader European applications via open-access modelling tools and dashboards co-developed with the National Screening Service and international partners.
Aims

This project aims to generate robust, lead-time–adjusted estimates of overdiagnosis in low-dose CT (LDCT) lung cancer screening using individual-level data from the NLST and NELSON trials. We will apply harmonised Bayesian models to produce overdiagnosis parameters stratified by age, sex, and histology. These estimates will inform an Irish-calibrated MISCAN-Lung microsimulation model to evaluate the health, economic, and equity impacts of screening strategies based on age/pack-year and risk prediction (PLCOm2012) criteria. Outputs will include deaths averted, overdiagnosed cases, cost-effectiveness, and capacity requirements. The findings will support evidence-based decision-making for Ireland’s National Screening Service and provide transferable tools and parameters for EU implementation.

Collaborators

Prof Harry de Koning – Erasmus MC
Mr Koen de Nijs – Erasmus MC
Dr Hilary Robbins – IARC
Dr Patrick Redmond – RCSI University of Medicine and Health Sciences
Dr Donal Bailey – RCSI
Mr Seamus Cotter – RCSI
Dr Ben Jacob – RCSI
Dr Alan Smith – National Screening Service, HSE
Dr Theresa Redaniel – University of Bristol
Prof Nicole Rankin – University of Sydney