Hospital del Mar Research Institute Hospital del Mar Research Institute


18/11/2022 - General information

Personalised breast cancer screening could improve cancer survival and reduce overdiagnosis

A team of researchers from the Hospital del Mar Medical Research Institute has created a model for predicting individual breast cancer risk that could be used to create personalised breast cancer screening strategies.

The research, presented at the 13th European Breast Cancer Conference, could make breast screening programmes more effective and ultimately improve survival rates. It could also mean fewer people suffering from 'false positives' (when screening tests indicate cancer, but other tests show there is none) and 'overdiagnosis' (when people are diagnosed and treated for a cancer that is extremely slow growing and has not caused any problems in their lives).

The study used data from the Cancer Registry of Norway (Oslo) and involved a collaboration between researchers from the Norwegian Cancer Registry and the Hospital del Mar Medical Research Institute. Dr. Javier Louro, a researcher at the IMIM-Hospital del Mar and author of the study, says that "We are familiar with many of the factors that influence the risk of breast cancer. For example, getting older, having a family history of breast cancer and some types of benign breast disease can increase the risk. We can't do much about these risk factors, but we can use this information to predict breast cancer risk."

The research included data from nearly 50,000 women who participated in BreastScreen Norway between 2007 and 2020. BreastScreen Norway is a national programme that invites all women aged 50-69 to have a mammogram every two years. Screening programmes can help improve survival rates by ensuring that cancers are detected as early as possible.

The researchers used data on ten known risk factors to estimate individual women's risks of developing breast cancer over a four-year period. These included age, family history of breast cancer, previous benign breast disease, breast density (a measure of the glands and fibrous tissue in the breast), body mass index and alcohol consumption. They compared these risk factors in women with and without a diagnosis of breast cancer to assess the impact of each individual risk factor, develop the model and check whether the model was accurate overall.

From left to right: Marta Román, Javier Louro and Xavier Castells.

They found that the risk of developing breast cancer over a four-year period ranged from 0.22% for some people to 7.43% for others, with an average risk of 1.10%. The research also indicated that some factors were more important than previously thought, for example, the protective effect of how many hours of exercise a woman does per week. This is a factor that is not usually included in breast cancer risk prediction models.

Dr. Louro points out that "We have successfully developed and validated a model for estimating breast cancer risk in women participating in BreastScreen Norway, the national breast cancer screening programme in that country. Several breast cancer risk prediction models have already been developed, but we believe this is one of the first models designed to guide an individual's lifetime breast screening strategies using real data from a screening programme. It is also the first model developed using data from BreastScreen Norway.".

"Our model could be considered the key to designing personalised screening tests aimed at reducing the harm and increasing the benefits of mammograms. For example, someone at low risk could be offered a standard mammogram every three to four years instead of every two years. Someone at medium risk could be offered an advanced 3D mammogram every two years, while those at high risk could be offered a new screening mammogram or MRI every year. All these strategies are still theoretical and need to be studied to determine their effectiveness."

The researchers caution that their findings so far are based on one screening programme in a single country. The risk prediction technique now needs more work, including a similar study in a different setting or a computer simulation, to fully appreciate the impact of personalised breast screening.

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