This site is intended for UK healthcare professionals
Medscape UK Univadis Logo
Medscape UK Univadis Logo

New Tool Predicts Risk of Developing Lung Cancer Within 10 Years

A tool that uses existing health records to predict a person's risk of developing lung cancer within 10 years has been developed by UK scientists.

Lung cancer is the third most common cancer in the UK. There are around 48,500 new lung cancer cases in the UK every year – more than 130 every day – accounting for 13% of all new cancer cases, according to Cancer Research UK.

Lyndsy Ambler, Cancer Research UK's senior strategic evidence manager, emphasised that: "Lung cancer still causes more deaths in the UK than any other cancer type."

Fergus Gleeson, professor of radiology, department of oncology at the University of Oxford and co-author of the study, highlighted that in the early stages of lung cancer there are "usually no obvious signs or symptoms, and it can go undetected for some time". 

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

Current methods to target screening relied on doctors recognising high-risk individuals or using tools based on using patient questionnaires to score risk and put those at highest forward, explained Professor Gleeson.

He added that the use of low-dose computerised tomography (CT) for lung cancer screening enabled early detection and treatment of the disease, which in turn improves people’s outcomes. "However, this type of screening isn't something we can do en masse for the population," he pointed out. "We need a way to target those at the greatest risk and put them forward for screening."

Identify Those For Screening

In September 2022 the UK National Screening Committee recommended using targeted lung cancer screening. However, the committee did not recommend which tools would best be used for targeting screening at people most at risk.

Now, a team of researchers from the University of Oxford and the University of Nottingham have developed a new tool, called 'CanPredict'. The tool is able "to identify the people most at risk of developing lung cancer over the next 10 years", and put them forward for screening tests earlier, "saving time, money and, most importantly, lives", claimed those behind the tool's development.

"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," explained Dr Weiqi Liao, data scientist in the Nuffield Department of Primary Care Health Sciences at the University of Oxford and lead author.

For the retrospective, population-based, cohortstudy, published in The Lancet Respiratory Medicine, the researchers set out to validate the CanPredict (lung) model for lung cancer screening in the UK and compare its performance against seven other risk prediction models.

They tested the tool using the anonymised health records of over 19 million adults from across the UK obtained from linked electronic health records from two English primary care databases – QResearch and Clinical Practice Research Datalink (CPRD) Gold. The primary study outcome was an incident diagnosis of lung cancer. 

Seven models for predicting lung cancer risk (Liverpool Lung Project [LLP]v2, LLPv3, Lung Cancer Risk Assessment Tool [LCRAT], Prostate, Lung, Colorectal, and Ovarian [PLCO]M2012, PLCOM2014, Pittsburgh, and Bach) were selected to compare their model performance with the CanPredict (lung) model using two approaches:

  • In ever-smokers aged 55–74 years – the population recommended for lung cancer screening in the UK
  • In the populations for each model determined by that model's eligibility criteria

Compared with the other lung cancer prediction models, the authors reported that the CanPredict (lung) model had the best performance in discrimination, calibration, and net benefit across three prediction horizons (5, 6, and 10 years) in the two approaches.

"The CanPredict (lung) model also had higher sensitivity than the current UK recommended models (LLPv2 and PLCOM2012), as it identified more lung cancer cases than those models by screening the same amount of individuals at high risk," they said.

Potential to Reduce NHS Burden and Improve Patient Experience

The new model had potential utility for risk stratification of the UK primary care population and selection of individuals at high risk of lung cancer for targeted screening, enthused the authors.

Dr Liao explained that since the new tool worked by examining existing patient health records 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".

Professor Hippisley-Cox said she hoped the validated risk tool would help "better prioritise patients for screening" and ultimately help spot lung cancer earlier when treatments were more likely to help. 

Dr Liao alluded that the tool had the potential to "substantially reduce the burden" on NHS staff, saving time, money, and streamlining the administrative process for a "better patient experience".

The researchers said that they planned to make the tool publicly available for use, subject to further funding for implementation in day-to-day practice, and to ensure Medicines and Healthcare Products Regulatory Agency (MHRA) medical device compliance.

The study was funded by Innovate UK, NIHR Biomedical Research Centre (Oxford), John Fell Oxford University Press Research Fund, Cancer Research UK, and the Oxford Wellcome Institutional Strategic Support Fund.