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Original research
Liverpool Lung Project lung cancer risk stratification model: calibration and prospective validation
  1. John K Field1,
  2. Daniel Vulkan2,
  3. Michael P A Davies1,
  4. Stephen W Duffy2,
  5. Rhian Gabe2
  1. 1Molecular and Clinical Cancer Medicine, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK
  2. 2Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK
  1. Correspondence to Dr John K Field, Molecular and Clinical Cancer Medicine, Faculty of Health and Life Sciences, University of Liverpool, Liverpool L69 3BX, UK; J.K.Field{at}liverpool.ac.uk

Abstract

Background Early detection of lung cancer saves lives, as demonstrated by the two largest published low-dose CT screening trials. Optimal implementation depends on our ability to identify those most at risk.

Methods Version 2 of the Liverpool Lung Project risk score (LLPv2) was developed from case-control data in Liverpool and further adapted when applied for selection of subjects for the UK Lung Screening Trial. The objective was to produce version 3 (LLPv3) of the model, by calibration to national figures for 2017. We validated both LLPv2 and LLPv3 using questionnaire data from 75 958 individuals, followed up for lung cancer over 5 years. We validated both discrimination, using receiver operating characteristic (ROC) analysis, and absolute incidence, by comparing deciles of predicted incidence with observed incidence. We calculated proportionate difference as the percentage excess or deficit of observed cancers compared with those predicted. We also carried out Hosmer-Lemeshow tests.

Results There were 599 lung cancers diagnosed over 5 years. The discrimination of both LLPv2 and LLPv3 was significant with an area under the ROC curve of 0.81 (95% CI 0.79 to 0.82). However, LLPv2 overestimated absolute risk in the population. The proportionate difference was −58.3% (95% CI −61.6% to −54.8%), that is, the actual number of cancers was only 42% of the number predicted.

In LLPv3, calibrated to national 2017 figures, the proportionate difference was −22.0% (95% CI −28.1% to −15.5%).

Conclusions While LLPv2 and LLPv3 have the same discriminatory power, LLPv3 improves the absolute lung cancer risk prediction and should be considered for use in further UK implementation studies.

  • imaging/CT MRI etc
  • lung cancer
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Footnotes

  • JKF and DV are joint first authors.

  • Contributors JF: trial conception and design, data interpretation and manuscript review. SWD: trial design, statistical analysis, data interpretation, manuscript review. DV: risk modelling, statistical analysis, data interpretation, manuscript review. MPAD and RG: data interpretation, manuscript review.

  • Funding Initial development of the LLP was funded by the Roy Castle Lung Cancer Foundation. The UKLS is funded by the Health Technology Assessment programme of the National Institute for Health Research. Michael Davies is a Roy Castle Lung Cancer Foundation Senior Research Fellow. Daniel Vulkan’s and Stephen Duffy’s contribution to this research was funded by the National Institute for Health Research (NIHR) Policy Research Programme, conducted through the Policy Research Unit in Cancer Awareness, Screening and Early Diagnosis, PR-PRU-1217-21601.

  • Disclaimer The funding source had no role in the design of our analyses, its interpretation, or the decision to submit the manuscript for publication. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

  • Competing interests JF: Speaker’s Bureau: AstraZenecaAdvisory Board: Epigenomics; NUCLEIX Ltd. AstraZeneca, iDNA. Grant Support: Janssen Research & Development, LLC. No competing interests from all other coauthors.

  • Patient consent for publication Not required.

  • Ethics approval Ethical approval for the study was given by Liverpool Central Research Ethics Committee in December 2010 (reference number 10/H1005/74).

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available upon reasonable request. We are committed, in principle, to data sharing with fellow researchers, and are currently drawing upoperating procedures for this. We anticipate that the data will be stored securely in Liverpool and reasonable requests for data for further research will be accommodated, subject to compliance with regulations, maintaining the integrity of information governance, and ensuring no loss of confidentiality on the part of the participants of the study. Requests that require considerable data manipulation and management on our part will need to be resourced by those requesting data.

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