New tool can spot those most at risk of developing lung cancer, say researchers

The CanPredict tool works by examining existing patient health records.

Lung cancer is the leading cause of cancer deaths worldwide (Alamy/PA)

Lives could be saved by a new tool that identifies those most at risk of developing lung cancer, according to researchers.

The CanPredict tool can spot those most at risk of developing the disease over the next decade and put them forward for screening tests earlier, researchers from the University of Oxford and the University of Nottingham said.

They created and tested CanPredict using the anonymised health records of more than 19 million adults from across the UK and hope it can save “time, money and, most importantly, lives”.

Lung cancer is the leading cause of cancer deaths worldwide and the second most common form of the disease, but early diagnosis has been shown to improve survival rates.

CanPredict has the potential to substantially reduce the burden on NHS staff, saving time, money and streamlining the administrative process for better patient experience

Dr Weiqi Liao, lead author

The researchers’ paper on “Predicting the future risk of lung cancer” was due to be published in the journal Lancet Respiratory Medicine on Wednesday.

Dr Weiqi Liao, lead author on the publication and a data scientist in the Nuffield Department of Primary Care Health Sciences at the University of Oxford, said: “Our tool, CanPredict, works by examining existing patient health records, so it could be run on a per GP surgery basis or nationally, automatically and objectively prioritising patients and alerting their GPs that they might benefit from further screening.

“Because of this, CanPredict has the potential to substantially reduce the burden on NHS staff, saving time, money and streamlining the administrative process for better patient experience.”

She said researchers used two separate sets of health record data to develop it: the QResearch database and the Clinical Practice Research Datalink (CPRD).

She added: “Using the QResearch database – which, in total, contains the anonymised health records of over 35 million patients, spanning all ethnicities and social groups across the UK – to identify 13 million people aged between 25 to 84 among whom 73,380 had a diagnosis of lung cancer.

“They then looked back through their health records to identify common factors which might be used to statistically predict their risk of developing the cancer.”

Factors such as smoking, age, ethnicity, body mass index, medical conditions and social deprivation were considered as part of the analysis, she said.

The tool was then tested using a separate set of anonymised GP health records, the CPRD.

We hope that this new validated risk tool will help better prioritise patients for screening and ultimately help spot lung cancer earlier when treatments are more likely to help

Professor Julia Hippisley-Cox, senior author

She added: “The researchers used the CPRD data, which contained data from an additional 2.54 million people’s anonymised health records, to see which people their new tool predicted were at the greatest risk of developing lung cancer, and then compared this to those who did go on to develop lung cancer.

“The new CanPredict tool correctly identified more people who went on to develop lung cancer and was more sensitive than current recommended methods of predicting risk, across five, six, and 10-year forecasts.”

Professor Julia Hippisley-Cox, senior author and professor of clinical epidemiology and general practice at the Nuffield Department of Primary Care Health Sciences, University of Oxford, said: “Improving early diagnosis of lung cancer is incredibly important both for the NHS but especially for patients and their families.

“We hope that this new validated risk tool will help better prioritise patients for screening and ultimately help spot lung cancer earlier when treatments are more likely to help.

“We’d like to thank the many thousands of GPs who have shared anonymised data for research without whom this would not have been possible.”