The research, presented at the 13th European Congress of Breast Cancercould make breast screening programs more effective and ultimately improve survival rates.
It could also mean that fewer people suffer ‘false positives’ (when screening tests show cancer, but other tests show there isn’t) and ‘overdiagnosis’ (when people are diagnosed and treated for cancer that grows extremely slowly and hasn’t caused any problems in their lives).
The study used data from the Norwegian Cancer Registry (Oslo) and it was a collaboration between researchers from the Norwegian Cancer Registry and the Hospital del Mar Medical Research Institute in Barcelona.
“We know many of the factors that influence breast cancer risk. For example, getting older, having a family history of breast cancer, and some types of benign breast disease can increase your risk. We can’t do much about those risk factors, but we can use this information to predict breast cancer risk.” javier blond of the Hospital del Mar.
The research included data from around 50,000 women who participated in BreastScreen Norway between 2007 and 2020. BreastScreen Norway is a national program that invites all women between the ages of 50 and 69 to get a mammogram (a breast X-ray) every two years. Screening programs 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 use. 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 overall accurate.
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 (median) 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.
“We have successfully developed and validated a model to estimate breast cancer risk in women participating in BreastScreen Norway, the national breast cancer screening program in Norway. Several breast cancer risk prediction models have been created, but we believe this is one of the first models designed to guide breast screening strategies throughout a person’s lifetime using actual data from a screening program. ., says Louro.
It is also the first model developed using data from BreastScreen Norway.
“Our model could be considered key to designing personalized screening tests to reduce the harm and increase the benefits of mammography. For example, someone at low risk might be offered a standard mammogram every three to four years instead of every two years. Someone at medium risk may be offered an advanced 3D mammogram every two years, while people at high risk may be offered a new screening mammogram or MRI every year. All of these strategies are still theoretical and need to be studied with regard to their effectiveness.”
The researchers caution that their findings so far are based on a screening program in one country. The risk prediction technique now needs more work, such as a similar study in a different setting or a computer simulation, to understand the impact of personalized breast screening.
“We know that breast cancer screening programs are beneficial, but we also know that some people will experience potential harm from false positives or overdiagnosis. A screening program that is tailored to each person’s risk could reduce these harms and increase the benefits.” highlights Laura Biganzoli, co-president of the European Breast Cancer Congress and director of the Breast Center of Santo Stefano HospitalPrato, Italy.
“This research shows how we might identify people at high risk for breast cancer, but also how we might identify those at low risk. Therefore, is an important step towards personalized detectiona“, has added.