What if all it took to understand your risk of one of the most common types of cancer was a computer program, a saliva sample and a questionnaire from your GP? 

That’s the promise of CanRisk. It’s an online platform our researchers built to turn a risk-calculating algorithm called BOADICEA into a powerful, easy-to-use tool doctors can use to identify people with a high risk of breast and ovarian cancer.

Currently, CanRisk is only recommended for genetics specialists, but research is beginning to uncover its wider potential. In August, an early study suggested that offering it to all women under 50 could help spot multiple times more women at increased risk of breast cancer than the guidelines doctors use today.

Those early signs suggest that CanRisk could help change how doctors diagnose, treat and even prevent breast cancer in younger women. For now, though, that’s all hypothetical. First, the team behind CanRisk need to work out how to adapt their specialist tool for everyday care.

The risks we can’t see

Overall, breast cancer is much more common in people over 50. That’s why all women aged 50 to 70 in the UK are invited for breast screening every three years. But age is far from the only risk factor, and the number of women under 50 being diagnosed with early-onset breast cancer is rising. 

One of the strongest indicators of increased breast cancer risk at younger ages is family history. So, UK guidelines also recommend that doctors refer younger women for regular screening if there’s a concerning pattern of cancer in their relatives, which may be linked to specific inherited gene changes.

Earlier breast cancer screening based on family history saves lives. But almost 3 in 4 women under 50 who are diagnosed with breast cancer don’t have a family history that might raise alarms. Under the current guidelines, their risk will probably only become clear after they develop breast cancer. Doctors don’t have the same opportunity to monitor them for early signs of the disease or take steps that could prevent it. 

The CanRisk programme is an opportunity to change that.

Back to BRCA

Like many stories about preventing cancer, this one goes back to the 1990s. That’s when Cancer Research UK scientists helped discover two tiny segments of DNA that changed the world’s understanding of cancer risk: BRCA1 and BRCA2. 

We all have these genes in our cells, where they help repair DNA damage before it becomes dangerous. A very small number of people are born with changes in BRCA1 or BRCA2 that stop them from working, raising the risk of certain cancers, including, as the name makes clear, BReast CAncer. 

Thanks to the discovery of BRCA genes, doctors can provide women with changes to them extra care, including earlier and more regular breast cancer screening. Today, Cancer Research UK-funded researchers are also working on new preventative drugs (including vaccines) to help lower the risk of BRCA-linked cancers without the need for surgery.

But BRCA’s impact actually goes further. Once scientists knew how much a single gene change could influence cancer risk, they could begin searching genetic data to find others. BRCA1 and BRCA2 have become lighthouses for researchers to navigate cancer risk by.

The rise of BOADICEA

Professor Antonis Antoniou and his team at the University of Cambridge are some of cancer risk’s most intrepid explorers. They launched BOADICEA as a web tool in 2008, initially to help identify which women with a family history of cancer were most likely to need BRCA testing.

Over time, as the Cambridge team and their international collaborators improved and updated the tool, they also helped uncover the role of many other genetic changes. 

“We’ve identified many more kinds of genes involved in cancer risk,” says Antoniou. “Some are rare changes like those to BRCA1 and BRCA2 that can cause a moderate or high risk on their own, but there are also more common variants that can have a joint effect if someone has lots of them.” 

Antoniou is also now a lead researcher on the Cancer Research UK-funded EMBRACE study, which began gathering data to understand the full range of risks associated with BRCA1 and BRCA2 changes all the way back in 1998. It’s since expanded to include other gene variants and is still helping researchers understand just how many other factors – environmental, lifestyle, biological, medical, hormonal and more – can come together to influence a person’s overall cancer risk. 

One way to think about this is by picturing each factor as a block in a tower-building game. As more blocks stack up, the structure becomes less stable, and the chances of it collapsing increase. Calculating risk is like measuring those chances, and that can get complicated quickly. To start, researchers need a huge amount of data to understand how much impact any particular block might have on the tower’s stability, and then they need to account for the fact that some of the blocks might only cause problems in certain combinations.

“We realised we needed a multifactorial risk model, using data from multiple sources, to provide much more powerful risk prediction by combining information from all these different risk factors together,” says Antoniou. 

That’s what BOADICEA has become. It’s essentially a calculator that can combine different risk factors and work out a person’s overall risk score for breast or ovarian cancer. In 2020, the team relaunched it through CanRisk, which is now a registered and approved medical device. 

CanRisk has now helped calculate more than 7.5 million cancer risk scores across 130 countries. Over that time, health economic analyses suggest it has helped prevent thousands of deaths from breast and ovarian cancer, and doctors have recently begun using it for prostate cancer, too.

To the frontlines

But that may only be scratching the surface of what CanRisk can do. So far, almost all the risk scores generated through the tool have been produced reactively – typically after people spoke to their doctors about their family history of cancer. Now the team are testing whether it can be used in frontline healthcare, to assess people’s cancer risk regardless of their family history, their background or their understanding of their DNA. 

“The vision here is to develop ways of doing proactive risk assessment at the population level,” says Antoniou, who stresses how this could help save lives and address health inequalities. “Because everyone gets the invite, you’re less likely to miss people who are high risk and may end up developing cancer.” 

In August 2026, a team of Antoniou’s colleagues published the results of one of the first studies evaluating that idea. Led by Dr Juliet Usher-Smith, they investigated how BOADICEA could be used as a proactive risk assessment tool using data from women under 50 who joined the Breast Cancer Now Generations Study between 2004 and 2011. 

The results make CanRisk’s potential clear. It flagged 26.5% of the women in this group as having a higher breast cancer risk and needing further testing. That subset included about a third (34.8%) of the women who went on to develop breast cancer within the following 10 years. 

By contrast, applying the current family history-based guidelines recommended by the National Institute for Health and Care Excellence (NICE) to the women in the study suggested that just 1.4% of them should be referred for further assessment. That included only 4.4% of those who developed breast cancer in the next decade.

This tells us a lot about how powerful CanRisk can be. If the NHS could smoothly swap it in for the current guidelines, it could help identify almost eight times as many women who later develop breast cancer. Those women could then be diagnosed earlier, when treatment is more likely to be effective, and in some cases their cancers could even be prevented.

And yet, even in this study, CanRisk missed most women who went on to develop breast cancer. There’s a lot more work to do to improve how we predict cancer risk. But alongside that, we also need to work out how to turn developments in researchers’ understanding of cancer risk into improvements in how doctors and health systems actually manage it. This study might show CanRisk’s potential, but it doesn’t tell us anything about how best to achieve it in the real world.

Predicting breast cancer risk in practice

In the UK today, CanRisk tests are offered to the small number of women who are referred to clinical genetics services because of their family history. Scaling that up to include all women in a specific age bracket could mean doing more CanRisk tests than have been done worldwide since the tool was launched six years ago. That would be a huge operational challenge on its own.

And, more than that, the August study suggests that using CanRisk in place of the current guidelines could mean more than 13 times as many younger women would be identified as having a high risk of breast cancer. It’s not clear if the UK’s current breast cancer screening programmes and genetics services could deal with such a big increase in referrals. 

“There will be a balance to strike,” says Professor Montserrat Garcia-Closas, who worked on the study at the Institute of Cancer Research in London. “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.” 

This is where the potential of a tool for helping tackle a specific problem meets the challenges of a health service that needs to balance lots of different priorities. If it’s not done correctly, implementing CanRisk could create more problems that it solves.  

“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,” says Garcia-Closas.

And with that, we’ve found the team’s next big research question: what’s the best way to make that trade-off?

Getting proactive

The CanRisk team are currently investigating how giving women under 50 proactive risk assessments could work in practice.

Their CanRisk-GP study, again led by Usher-Smith, who’s a GP herself, is well underway. A group of 40 to 50-year-old women registered with a small number of GPs across Cambridgeshire and Peterborough entered information about their personal risk factors using a new version of CanRisk called MyCanRisk. This, together with a saliva sample for genetic testing, was then used to complete a CanRisk assessment. 

Women identified as being at increased risk of developing breast cancer have now been advised to attend a GP appointment to discuss what steps they can take to reduce their risk. Where appropriate, they’re also being referred to specialist care. 

This is an early study, so it won’t answer every question about what proactive risk assessments can do to save lives from breast cancer. But it’s an important step in that direction. CanRisk-GP will help show if implementing CanRisk more widely is safe, equitable and cost-effective – and if being told their predicted cancer risk actually benefits women. 

“We need to find out if this is acceptable to women and if it works for clinicians,” says Antoniou. “What are the logistics and who’s going to take part?” 

The team are also running another trial called CanRisk-ClinGen, which is looking at women referred by their GP because they may have a higher breast cancer risk according to the current guidelines. It offers a full CanRisk assessment as soon as that referral happens, rather than waiting for a follow-up assessment about family history. From there, the researchers will see how CanRisk changes decisions, from the extra screening and treatments that might be offered to the lifestyle changes people choose to make.

From spotting risks to changing them

In a sense, CanRisk has been in development for close to 30 years. Even now, no one who’s worked on it would say it’s finished. With our funding, the team are continuing to comb through data on potential risk factors to make the tool more accurate, inclusive and personalised.

CanRisk is also benefitting from connections with the wider Cancer Data-Driven Detection (CD3) initiative, which Antoniou also leads. CD3 is bringing together vast and complex datasets, including electronic health records, screening data, and large population studies like UK Biobank and Our Future Health, to take researchers’ understanding of cancer risk further than ever before. With help from advanced data-analysing and pattern-finding AI systems, it’s setting out to reveal other cancer risk factors that we can’t yet see and make risk prediction work for everyone.

Through Antoniou, CD3 can also be traced back to BRCA. He was training to work in insurance when the genes’ discovery convinced him to apply statistics to cancer.

That was the start of a career dedicated to calculating risks. But the biggest thing Antoniou’s learned is that, on its own, calculating a risk isn’t enough to make a difference. Only 1% to 2% of all the risk prediction models scientists have devised for different diseases have ever become useful tools in clinics. The ones that make it have to go beyond numbers.