Related Experiment Video For early detection
Updated: May 24, 2025
Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
Published on: October 13, 2023
Artificial intelligence for early detection of lung cancer in GPs' clinical notes: a retrospective observational
Martijn C Schut1, Torec T Luik2, Iacopo Vagliano3
1Department of Laboratory Medicine, Amsterdam University Medical Center (UMC) Vrije Universiteit Amsterdam, Amsterdam; Amsterdam Public Health, Amsterdam UMC, Amsterdam, the Netherlands.
Background:
The journey of >80% of patients diagnosed with lung cancer starts in general practice. About 75% of patients are diagnosed when it is at an advanced stage (3 or 4), leading to >80% mortality within 1 year at present. The long-term data in GP records might contain hidden information that could be used for earlier case finding of patients with cancer.
Aim:
To develop new prediction tools that improve the risk assessment for lung cancer.
Design And Setting:
Text analysis of electronic patient data using natural language processing and machine learning in the general practice files of four networks in the Netherlands.
Method:
Files of 525 526 patients were analysed, of whom 2386 were diagnosed with lung cancer. Diagnoses were validated by using the Dutch cancer registry, and both structured and free-text data were used to predict the diagnosis of lung cancer 5 months before diagnosis (4 months before referral).
Results:
The algorithm could facilitate earlier detection of lung cancer using routine general practice data. Discrimination, calibration, sensitivity, and specificity were established under various cut-off points of the prediction 5 months before diagnosis. Internal validation of the best model demonstrated an area under the curve of 0.88 (95% confidence interval [CI] = 0.86 to 0.89), which shrunk to 0.79 (95% CI = 0.78 to 0.80) during external validation. The desired sensitivity determines the number of patients to be referred to detect one patient with lung cancer.
Conclusion:
Artificial intelligence-based support enables earlier detection of lung cancer in general practice using readily available text in the patient files of GPs, but needs additional prospective clinical evaluation.
