Breast Neoplasms
Conditions
Keywords
Breast Neoplasms, Cancer Screening, Personalized Medicine, Mammographic Breast Density, Risk Assessment
Brief summary
The RIBBS study is a single-arm single-center study that aims to evaluate the effectiveness of a risk-based breast screening model using digital breast tomosynthesis (DBT) as the baseline test, quantitative individual breast density to guide supplemental ultrasound (US) imaging for dense breasts, and individual risk (calculated taking into account breast density) to guide the screening interval (annual or biennial). Invited 45-year-old women are differentiated into five different screening protocols (based on breast density and risk), and screened according to a personalized model until they turn 50 and return to routine screening. The only primary endpoint in this study is the cumulative incidence of advanced breast cancers (stage II and above). This endpoint will be evaluated at the end of the five-year intervention period and at 10 years. The results of the personalized screening model will be compared with those obtained from an observational cohort from a neighboring region in which a one-size-fits-all approach involving annual mammography for women aged 45-49 years is used. The comparison will be conducted with the hypothesis of superiority of the personalized screening model.
Detailed description
The incidence of breast cancer in women aged 45 to 49 is not much lower than in women aged 50 to 54. However, while the Italian Health System offers mammography screening to all women aged 50 to 69 every two years, women aged 45 to 49 are invited for annual mammography screening in only a few regions. Breast density, i.e. the amount of fibroglandular tissue, more present in young women, decreases the performance of mammography by reducing the detectability of breast cancer; consequently, breast cancer in women with dense breasts can often be found only when it is larger and thus at a more advanced stage. In addition, breast density is an independent risk for breast cancer. The RIBBS study was designed to use the first round of screening to identify women with dense breasts and those at increased risk of breast cancer, and use this information to tailor the subsequent screening protocol, including supplemental US imaging for women with dense breasts, and establishing the frequency of screening cycles according to risk category. The reference imaging is digital breast tomosynthesis, which has already demonstrated greater sensitivity than digital mammography in the standard screening age (50-69). Volumetric breast density (VBD) is calculated from DBT, and lifetime risk (LTR) is obtained from the Tyrer-Cuzick risk model which also includes breast drnsity as a risk factor. After the first round of screening, women are divided into five groups: women with non-dense breasts and low breast cancer risk are screened every two years with DBT alone; women with dense breasts and low breast cancer risk are screened every two years with DBT plus additional ultrasound (DBT+US); women with non-dense breasts and intermediate risk of breast cancer are screened annually with DBT alone; women with dense breasts and intermediate risk of breast cancer are screened annually with DBT+US; finally, high-risk women with a family history of breast cancer (w/wo hereditary factors) are monitored with annual MRI and tomosynthesis. Our study hypothesizes that a screening model stratified by breast density and risk is more effective and sustainable in reducing the incidence of advanced breast cancer than standard annual mammography screening.
Interventions
DIAGNOSTIC_TESTPersonalized screening protocol
At the first screening round (recruitment) all participating women had the same tests; * Two-view tomosynthesis of both breasts * Calculation of volumetric breast density (VBD) * Calculation of lifetime risk (LTR) using the Tyrer-Cuzick model At subsequent rounds: 1. Women with non-dense breasts and low breast cancer risk are re-screened only with DBT every 2 years; 2. Women with dense breasts and low breast cancer risk are re-screened with DBT+US every 2 years; 3. Women with non-dense breasts and intermediate breast cancer risk are re-screened only with DBT every year; 4. Women with dense breasts and intermediate breast cancer risk are re-screened with DBT+US every year; 5. Women at high risk of breast cancer associated with a family history of breast cancer (w/wo hereditary factors) undergo DBT and MRI every year.
Sponsors
Regione del Veneto (Italy)
Istituto Oncologico Veneto IRCCS
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
SCREENING
Masking
NONE
Eligibility
Sex/Gender
FEMALE
Age
45 Years to 45 Years
Healthy volunteers
Yes
Inclusion criteria
* Female * Aged 45 years old * Resident in the provinces of Padua and Rovigo (Italy) * Willing and able to give written informed consent * Willing and able to comply with scheduled visits, tests, and other procedures
Exclusion criteria
* Recent mammography * Personal history of breast carcinoma, either invasive or ductal carcinoma in situ (DCIS) * Known BRCA carrier or PALB2 or ≥50% risk * Psychiatric or other disorders that are not compatible with compliance to the protocol requirements and follow-up * Pregnant or breastfeeding * Unable to give informed consent * Current participation in another interventional breast screening trial
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Cumulative Incidence of Advanced Cancers | Up to 15 years | Percentage of breast cancer cases diagnosed at staged II or beyond, either during the entire screening period or thereafter. Advanced cancers occurring up to 10 years after the end of the screening intervention will be included |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Proportional Incidence of Interval Cancer | Up to 8 years | Number of women diagnosed with interval cancer (detected after a negative screening episode) divided by the expected number of breast cancer cases in the absence of screening |
| Total Assessment Rate | Up to 6 years | Number of women undergoing diagnostic evaluation per thousand women screened. Further breakdown into noninvasive and invasive assessment rates. |
| Surgical Referral Rate | Up to 6 years | Number of women referred to excisional biopsy or definitive surgical treatment per thousand women screened |
| Surgery Rate | Up to 6 years | Number of women undergoing excisional biopsy or definitive surgical treatment per thousand women screened |
| Benign Lesion Detection Rate | Up to 6 years | Number of women with any histologically diagnosed benign lesion per thousand women screened |
| Tumor-Stage Specific Detection Rate | Up to 6 years | Number of women with cancer detected by screening and classified by TNM tumor stage per thousand women screened |
| Regular Re-Screening Rate | Up to 6 years | Number of women who regularly undergo the specific screening protocol (within ± 3 months) between ages 45 and 49 per thousand women screened |
| Recall rate (RR) | Up to 6 years | Number of women recalled for further diagnostic evaluation per thousand women screened, also known as the BI-RADS abnormal interpretation rate |
| Cancer detection rate (CDR) | Up to 6 years | Number of cancers detected by screening test(s) per thousand women screened |
Other
| Measure | Time frame | Description |
|---|---|---|
| Impact of Breast Density Metrics on Personalization of Screening | Up to 8 years | This analysis compares the proportions of women with dense and non-dense breasts using various breast density metrics (Volumetric Breast Density, Area-Based Breast Density, BI-RADS category) to evaluate breast density stratification implications in personalized screening |
| Impact of Different Breast Density Metrics on Breast Cancer Risk Assessment | Up to 8 years | This analysis compares proportions of women classified as low, intermediate, and high risk using the Tyrer-Cuzick risk model when different breast density metrics are utilized. Examines implications of diverse density measures for risk stratification within personalized screening |
| Prevalence Analysis of Breast Cancer Subtypes | Up to 8 years | This analysis studies distribution of breast cancer subtypes (luminal A, luminal B, HER2-positive, basal-like) across the overall study population and when stratified by breast density and risk category. Analyzes subtype prevalence variations based on breast density and individual risk profilesand stratified by density and risk category. |
| Potential of Artificial Intelligence (AI) to Support Screening Personalization | Up to 8 years | Explores AI integration into personalized screening protocols. Assesses potential reduction in required readers for personalized protocols with double reading and workload reduction from AI's accurate classification of clearly negative exams. Evaluates benefits like cost savings, efficiency, resource utilization, radiologist productivity, and job satisfaction. Measures AI effectiveness in different subgroups based on breast density and risk categories |
| Cost and Organizational Impact Analysis | Up to 8 years | This analysis examines both the direct costs associated with implementing and operating the stratified screening program, as well as the economic feasibility and financial implications of adopting the personalized approach |
| Impact of Breast Cancer Risk Model on Personalization of Screening | Up to 8 years | This analysis compares the proportions of women categorized as low, intermediate, and high risk for breast cancer using different risk models (Tyrer-Cuzick, Gail, Boadicea) to assess risk stratification implications within personalized screening |
Countries
Italy
Outcome results
None listed