Lung cancer is and remains one of the two most common types of cancer worldwide. Many people are affected in developing countries as well as in Europe and North America. The tumours are also responsible for most cancer-related deaths. Early detection is therefore important: this is the only way to maximise the chance of a cure.
The data has prompted more and more governments and healthcare systems to recommend screening procedures for people at high risk of bronchial carcinoma. This has also been the case in the UK since 2022. In this context, experts have been commissioned to develop a model that identifies those affected and thus avoids unnecessary CT scans.
The CanPredict (lung) predictive model was developed. It has been validated on over 19 million Britons receiving GP care in the National Health Service (NHS) and consists of statistical calculations that can predict individual lung cancer risk.
However, this specific model is currently only applicable to the UK population. This is due to the design of the healthcare model in the country and the data available there for large populations. The centralised system means that large amounts of detailed information are available. However, similar models are also conceivable for other countries.
The newly developed model was compared with existing scores or risk stratification models, using the same available NHS data. The result: CanPredict (lung) can predict the individual risk of lung cancer for every person in the UK healthcare system. However, this is only possible if data is already available, such as that collected during GP visits.
Although the model was developed for the British healthcare system, the study nevertheless shows that corresponding calculations can reliably predict the individual risk, provided the relevant data is available. As the model is based on various statistical calculations, it is important to collect the relevant information. Similar risk stratification options are also conceivable for other countries and other populations, so that early lung cancer detection can become simpler and more efficient.