Chris Hyde

University of Exeter

Professor of Public Health and Clinical Epidemiology

NLST (Learn more about this study)

NLST-301

Apr 20, 2017

Clinical and cost effectiveness of lung cancer screening by low-dose CT

This project has been commissioned by the National Institute for Health Research (NIHR) Health Technology Assessment (HTA) programme (project number 14/151/07) for the UK National Screening Committee, to estimate the clinical effectiveness and cost-effectiveness of lung cancer screening by low-dose computed tomography (LDCT).

The two main components of the project are a systematic review and meta-analysis of randomized controlled trials (RCTs) of lung cancer screening with imaging technology (including LDCT and chest X-ray), and an economic evaluation (cost-utility analysis) of LDCT screening programs utilizing a Discrete Event Simulation (DES) model.

The relative benefits, costs and harms of lung cancer screening are most likely to be favorable when individuals at high risk for lung cancer are identified, although different studies have chosen varying criteria to select such high-risk individuals.

The National Lung Screening Trial (NLST) is the largest RCT identified evaluating LDCT, and due to its longitudinal design (repeated screens of patients) it has the potential to aid our understanding of how lung cancer develops, e.g., how long it takes for preclinical lung cancer to develop and to progress to later stages.

The DES model underlying the cost-utility analysis requires a well-founded model of the natural history of lung cancer, and the ability of LDCT to detect lung cancer at early stages, achieve a stage shift and a mortality benefit. Existing publications from NLST do not provide sufficient information to calibrate a natural history model, and so further data is requested.

To perform a natural history and effectiveness model calibration based on NLST data, using Bayesian Markov Chain Monte Carlo (MCMC) techniques. This natural history and effectiveness model will then underpin the DES model for the cost-utility analysis.

Specifically:
To estimate parameters for preclinical lung cancer incidence, indolent lung cancer development, preclinical lung cancer progression, clinical presentation and lung cancer mortality (the *natural history* model).
To estimate the sensitivity of LDCT- and chest X-ray-based screening programs, and any impact on stage-specific survival, in light of the estimated rate of indolent lung cancer development and the observed 20% reduction in lung cancer mortality (the *effectiveness* model).