UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

The value of blood-based measures of liver function and urate in lung cancer risk prediction: A cohort study and health economic analysis

Horsfall, Laura J; Clarke, Caroline S; Nazareth, Irwin; Ambler, Gareth; (2023) The value of blood-based measures of liver function and urate in lung cancer risk prediction: A cohort study and health economic analysis. Cancer Epidemiol , 84 , Article 102354. 10.1016/j.canep.2023.102354. Green open access

[thumbnail of 1-s2.0-S1877782123000346-main.pdf]
Preview
Text
1-s2.0-S1877782123000346-main.pdf - Published Version

Download (477kB) | Preview

Abstract

BACKGROUND: Several studies have reported associations between low-cost blood-based measurements and lung cancer but their role in risk prediction is unclear. We examined the value of expanding lung cancer risk models for targeting low-dose computed tomography (LDCT), including blood measurements of liver function and urate. METHODS: We analysed a cohort of 388,199 UK Biobank participants with 1873 events and calculated the c-index and fraction of new information (FNI) for models expanded to include combinations of blood measurements, lung function (forced expiratory volume in 1 s - FEV1), alcohol status and waist circumference. We calculated the hypothetical cost per lung cancer case detected by LDCT for different scenarios using a threshold of ≥ 1.51 % risk at 6 years. RESULTS: The c-index was 0.805 (95 %CI:0.794-0.816) for the model containing conventional predictors. Expanding to include blood measurements increased the c-index to 0.815 (95 %CI: 0.804-0.826;p < 0.0001;FNI:0.06). Expanding to include FEV1, alcohol status, and waist circumference increased the c-index to 0.811 (95 %CI: 0.800-0.822;p < 0.0001;FNI: 0.04). The c-index for the fully expanded model containing all variables was 0.819 (95 %CI:0.808-0.830;p < 0.0001;FNI:0.09). Model expansion had a greater impact on the c-index and FNI for people with a history of smoking cigarettes relative to the full cohort. Compared with the conventional risk model, the expanded models reduced the number of participants meeting the criteria for LDCT screening by 15-21 %, and lung cancer cases detected by 7-8 %. The additional cost per lung cancer case detected relative to the conventional model was £ 1018 for adding blood tests and £ 9775 for the fully expanded model. CONCLUSION: Blood measurements of liver function and urate made a modest improvement to lung cancer risk prediction compared with a model containing conventional risk factors. There was no evidence that model expansion would improve the cost per lung cancer case detected in UK healthcare settings.

Type: Article
Title: The value of blood-based measures of liver function and urate in lung cancer risk prediction: A cohort study and health economic analysis
Location: Netherlands
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.canep.2023.102354
Publisher version: https://doi.org/10.1016/j.canep.2023.102354
Language: English
Additional information: © 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Early detection, Epidemiology, Health economic evaluation, Low-dose computed tomography, Lung cancer, Screening, UK Biobank
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Primary Care and Population Health
URI: https://discovery.ucl.ac.uk/id/eprint/10167968
Downloads since deposit
56Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item