Researchers have created a model for predicting an individual’s breast cancer risk that could be used to create personalized breast cancer screening strategies, according to a new study published by Louro et al in the European Journal of Cancer. The research, also presented at the 13th European Breast Cancer Conference (Abstract 22), could make breast cancer screening programs more effective and ultimately improve survival rates. The findings also indicated personalized screening may lead to fewer false-positive results and overdiagnoses.
“We know about 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[s] can all increase the risk. We can’t do much about those risk factors, but we can use this information to predict the risk of [developing] breast cancer,” said first study author Javier Louro, PhD, a researcher at the Hospital del Mar Medical Research Institute.
The study included data from around 50,000 female patients who took part in BreastScreen Norway—a national program inviting individuals aged 50 to 69 years to have a mammogram every 2 years.
The researchers used data on 10 known risk factors to estimate the patients’ risks of developing breast cancer over a period of 4 years. These included age, family history of breast cancer, previous benign breast disease, breast density, body mass index, and alcohol consumption. They compared these risk factors in patients with and without a breast cancer diagnosis to assess the impact of each individual risk factor, to develop the model, and to check whether the model was broadly accurate.
Researchers found that the risk of developing breast cancer over a period of 4 years ranged from as low as 0.22% for some individuals up 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 amount of exercise a patient partakes in per week may determine whether the risk is greater or reduced. 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 [patients] participating in BreastScreen Norway…. Several breast cancer risk prediction models have been created, but we believe this is one of the first models designed to guide breast [cancer] screening strategies over a person’s lifetime using real data from a screening program. It is also the first model developed using data from BreastScreen Norway,” Dr. Louro highlighted. “Our model might be considered a key for designing personalized screening aimed at reducing the harms and increasing the benefits of mammographic screening. For example, someone with low risk might be offered screening with standard mammography every 3 or 4 years instead of [every] 2 years. Someone with medium risk might be offered screening with advanced [three-dimensional] mammography every 2 years, while those at a high risk might be offered a new screening test with mammography or magnetic resonance imaging every year. All of these strategies are still theoretical and should be studied with regard to their effectiveness.”
The researchers cautioned that their findings so far are based on a screening program in one country. The risk prediction technique now needs further work—such as a similar study in a different setting or using a computer simulation—to understand the impact of personalized breast cancer screening.
“We know that breast [cancer] screening programs are beneficial, but we also know that some people will experience potential harms caused by false positives or overdiagnos[e]s. A screening program that is tailored to each person’s risk could reduce these harms and increase the benefits,” stressed Laura Biganzoli, MD, Director of the Breast Center in the Department of Oncology at the Hospital of Prato and Co-Chair of the European Breast Cancer Conference, who was not involved in the study. “This research shows how we might be able to identify people with a high risk of breast cancer, but equally how we could identify those with a low risk. So it’s an important step toward personalized screening.”
Disclosure: For full disclosures of the study authors, visit ejcancer.com.The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.