Background Estimation of the clinical probability of malignancy in patients with pulmonary nodules will facilitate early diagnosis, determine optimum patient management strategies and reduce overall costs.
Methods Data from the UK Lung Cancer Screening trial were analysed. Multivariable logistic regression models were used to identify independent predictors and to develop a parsimonious model to estimate the probability of lung cancer in lung nodules detected at baseline and at 3-month and 12-month repeat screening.
Results Of 1994 participants who underwent CT scan, 1013 participants had a total of 5063 lung nodules and 52 (2.6%) of the participants developed lung cancer during a median follow-up of 4 years. Covariates that predict lung cancer in our model included female gender, asthma, bronchitis, asbestos exposure, history of cancer, early and late onset of family history of lung cancer, smoking duration, FVC, nodule type (pure ground-glass and part-solid) and volume as measured by semiautomated volumetry. The final model incorporating all predictors had excellent discrimination: area under the receiver operating characteristic curve (AUC 0.885, 95% CI 0.880 to 0.889). Internal validation suggested that the model will discriminate well when applied to new data (optimism-corrected AUC 0.882, 95% CI 0.848 to 0.907). The risk model had a good calibration (goodness-of-fit χ 8.13, p=0.42).
Conclusions Our model may be used in estimating the probability of lung cancer in nodules detected at baseline and at 3 months and 12 months from baseline, allowing more efficient stratification of follow-up in population-based lung cancer screening programmes.
Trial registration number 78513845.
- lung cancer
- CT Screening
- solitary pulmonary nodules
- risk prediction model
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Contributors MM and JF developed the concept and design of the probability of lung cancer in pulmonary nodules detected at baseline and associated repeat scans in the UKLS trial using nodule volumetry. AD provided expert advice on the radiological interpretation of the UKLS CT images. All of the authors contributed equally to developing and reviewing the manuscript.
Funding The study received funding from the National Institute for Health Research Health Technology Assessment (NIHR HTA) (reference number HTA 09/61/01).
Disclaimer The views and opinions expressed in this manuscript are those of the authors and do not necessarily reflect those of the Department of Health.
Competing interests JF reports grants from HTA, other from Epigenomics, other from Vision Gate, other from Nucleix and other from AstraZeneca, during the conduct of the study.
Patient consent for publication Not required.
Ethics approval The UKLS was approved by the National Information Governance Board, and ethical approval was given by the Liverpool Central Research Ethics Committee in 2010 (reference number 10/H1005/74).
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement We are committed, in principle, to data sharing with fellow researchers, and are currently drawing up operating 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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