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Cambridge research shows breast cancer referral criteria miss up to 95% of women under 50 who develop breast cancer

Дата публикации: 21-08-2026 10:19:21

Cambridge tool would identify eight times as many women,

Основное содержимое страницы с новостью.

The method used to decide who should be referred by GPs for further breast cancer risk assessment and specialist care fails to pick up to 95 per cent of women under 50 who will go on to develop the disease in the next 10 years, research has shown.

An alternative and comprehensive risk assessment tool called BOADICEA, developed at the University of Cambridge with funding from Cancer Research UK, has been shown to identify eight times as many women in this age group who developed breast cancer, compared to the NICE (National Institute for Health and Care Excellence) criteria used by the NHS.

Mammograms are used by the NHS to screen for breast cancer. Picture: iStockMammograms are used by the NHS to screen for breast cancer. Picture: iStock

Breast cancer is the most common cancer and has steadily increased in the last few decades. It accounts for about one in four cases of cancers and 15 per cent of cancer deaths in women, and is one of the leading causes of death in women under 50.

Most women in England at higher risk of breast cancer are identified after being referred by their GP for further assessment and specialist care. GPs use family history, following criteria set out by NICE.

But researchers in Cambridge and The Institute of Cancer Research, London, found the NICE criteria fail to identify as many as 95 per cent of women under 50 who are at higher-than-average risk of breast cancer and 95 per cent of women who go on to develop breast cancer within 10 years.

They analysed data from 1,258 women aged under 50 years recruited to the Breast Cancer Now Generations Study between 2004 and 2011.

They compared NICE criteria with several risk assessment approaches using the BOADICEA risk model. BOADICEA, available via the CanRisk platform, combines factors such as family history, lifestyle, reproductive history and genetic information.

While previous studies have shown multifactorial risk models can identify more women at increased risk, this is the first study to directly evaluate this approach in a UK population-based cohort of women under 50.

Completing a risk assessment with the full BOADICEA model for all women aged under 50 would result in 26.5 per cent of women being categorised as at above-population level risk and referred for further assessment - and this would include 34.8 per cent of women under 50 who develop breast cancer within 10 years.

The current NICE criteria would result in just 1.4 per cent of women under 50 being referred for further assessment, which would include just 4.4 per cent of those women who develop breast cancer.

The researchers say a big reason for the disparity is that 73 per cent of women under 50 years who develop breast cancer within 10 years have no family history of breast cancer.

Dr Juliet Usher-Smith, from the Department of Public Health and Primary Care at Cambridge, the study’s senior author, said: “We need to get better at identifying women at highest risk of breast cancer so that we can intervene early, when there are more options for treating, or even preventing, their disease.

“The current NICE criteria used in general practice are missing up to 95 per cent of women under 50 who will go on to develop breast cancer. It’s time to look again at these criteria in the light of our findings.”

Changing the criteria would be far more resource intensive and lead to more referrals, including for many women who will not develop breast cancer.

Prof Montserrat Garcia-Closas, from The Institute of Cancer Research, London, said: “There will be a balance to strike: the NICE criteria are much easier to implement, but miss a large proportion of women at elevated risk. But a full risk assessment including genetic testing will place a heavy burden on resources.

“Ultimately, it will be a trade-off between the practical, resource, and cost implications of data collection and risk assessment, and the potential benefits and harms associated with accurate and inaccurate classification of women.”



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