Contrast Enhancement Mammography vs MRI for the Surveillance of Women at High Risk of Breast Cancer: Con-trust Randomized Controlled Trial

Description and distribution of activities of each operating unit The project comprises six work packages (WPs) to ensure efficient project coordination, quality control and data collection for conducting the trial, breast cancer risk prediction using machine learning models, cost analysis, and evidence synthesis for guidelines development. In the Project Coordination WP, regular communication channels will be established, project management tools developed,and progress monitored to ensure compliance with ethical and regulatory requirements. The deliverables include ethics, safety, and administrative approval, electronic data collection and transfer tools, training materials for data management, progress reports, meeting agendas and minutes, budget and expenditure reports, and dissemination materials. The leading unit is AUSL-RE, and the WP is instrumental to all three aims. Administrative coordination of the trial accrual in the recruiting centers will be led by AUSL-RE and the centers in Southern Italy. The following centers have agreed to contribute: AOUI Verona, Policlinico S. Matteo Pavia, Irst-Meldola-Ausl Romagna, Policlinico S. Donato, Taormina, AOU Modena. The QualityControls WP ensures the quality control of CEM and MRI equipment used in the project and develops a tool to monitor the stability of CEM over time. The deliverables include quality control protocols, staff training materials, a consensus meeting of the radiologists and physicists, inspection and maintenance reports, a stability monitoring tool, and a database for collected data. The leading units are IOV and Messina; the WP contributes to Aims 1 and 2. The Machine Learning Models for BC Risk WP aims to develop machine learning models that can predict the risk of breast cancer using clinical and histopathological information and radiomic features. Deliverables include the machine learning models developed, documentation of their algorithms and validation results, and reports on their performance in predicting short-term breast cancer risk. The WP is led by Bari and all units will participate; it supports Aim 2. The Breast Density WP evaluates breast density using various automated software. The assessment of breast density will allow us to stratify the trial results. Deliverables include reports on the performance of different software tools, a database of breast density measurements, and an analysis of the impact of breast density on screening outcomes. The leading unit is IOV; the WP contributes to Aims 1 and 3 defining different scenarios for the introduction of CEM and MRI in different groups of women defined by breast density. The Radiation Dose WP aims to ensure that the radiation dose associated with CEM is within acceptable limits. Deliverables include a report on the radiation dose associated with CEM and recommendations for optimizing imaging protocols to minimize radiation exposure. The leading unit is AUSL-RE; the WP supports Aim 1 and will inform Aim 3 about the undesirable effects of the test. Finally, the HTA (health technology assessment) WP will assess the financial and organizational impact and explore the ethical, legal, and social issues of different scenarios of introducing CEM or MRI in the surveillance of high-risk non-mutated women. Deliverables are systematic reviews of the evidence integrated with Con-TRUST results and Evidence to Decision tables to be used by the Italian guideline initiative on breast cancer screening. The WP supports Aim 3 and is led by AUSLRE, with the contribution of other units.

Specific aim 1 The Con-Trust (CONtrast enhanced mammography Tailored Risk-Using Screening Trial) will include about 2200 high-risk women in the following centers: IOV of Padua, AUSL-IRCCS of Reggio Emilia, AOU of Messina, AUO of Bari, AOUI of Verona, Policlinico S. Matteo of Pavia, Policlinico San Donato Milanese, Irst-Meldola-Ausl Romagna, AOU of Modena. Women aged 30 to 65 years with a 5-year breast cancer (BC) risk \>5% will be contacted and informed about the study. The number of women enrolled in the dedicated surveillance programs at the participating centers, receiving a visit every 12 months, is expected to be adequate to reach the target sample size in less than 12 months, assuming a participation rate of less than 50%. Participants will be assessed using validated tools such as Tyrer-Cuzick IBIS, BOADICEA, BCSC or MyPeBS to determine their level of risk. All these tools rely on family and screening history, hormonal and reproductive history, breast density, and genetic information (BRCA1/2, TP53). In addition, MyPeBS includes a genomic risk score based on 313 single nucleotide polymorphisms and is available to women who previously participated in the MyPeBS study in Reggio Emilia. Women with known contraindication for MRI will undergo contrast-enhanced mammography (CEM) only, while those with known genetic mutation will receive the center-specific surveillance, usually MRI+DM. Finally, the remaining women (expected 1,400) will be randomized (700 per arm) to two rounds of CEM surveillance or to two rounds of MRI+DM surveillance. After 2 years, all women who were randomly assigned to receive either MRI or CEM, and who were eligible for both, will undergo the same exit test. This exit test is the standard test used for the surveillance of high-risk nonmutated women at each participating center. The co-primary endpoints are cumulative incidence of BC, including invasive BCs and ductal carcinoma in situ, interval, and screen-detected BCs, and cumulative recall-rate. The main analysis will only cover the subpopulation that was randomized. If the two techniques are equivalent, the predicted sample size will have 80% power to exclude a non-inferiority threshold of 2.5% higher incidence of BC, with 95% confidence. This would be equivalent to a reduction of less than one-third of cancers diagnosed early by the screening test. The cumulative incidence, based on an average risk of 7% at 5-years and a lead time of 4 years from the exit test, has been estimated at 8.4%, with 5.3% detected by screening at baseline and 3.1% occurring during follow-up based on results from the DENSE trial). Secondary endpoints include biopsy and false positive rate, positive predictive value, interval cancer rate, and cumulative incidence of advanced (T2+) cancers. The project involves two rounds of screening, with an interim analysis at 12 months (plus 3 months to include assessment of women positive at 12 months). The final analysis will be conducted at 24 months (plus 3 months) following the end of the project. The safety outcomes are mean glandular dose, adverse events, and reactions to contrast agents. Because eligible women have a high lifetime risk of BC, overdiagnosis is not considered a safety outcome. However, the entire study population will be considered for false-positive rates, glandular dose, and reactions to contrast agents. Subgroup analyses will be conducted based on key risk factors (age group, breast density, and risk level). Retrospective evaluation of images will allow estimation of the cancer detection rate of restricted imaging protocols such as unenhanced MRI (specifically, diffusion-weighted imaging) and MRI plus single medio-lateral oblique mammographic projection. The final study protocol will be defined with the active involvement of women and public health decision-makers.

Specific aim 2 Mammographic features, particularly breast density, are related to both BC risk and interval cancer incidence. Researchers are exploring ways to combine mammography and tomosynthesis data with standard variables to improve BC risk prediction. Limited studies on breast MRI or CEM suggest promising prognostic value and ability to predict BC. The Con-TRUST trial will have access to both mammographic and contrast-enhanced images for women participating in at least two rounds of screening. Accurate stratification of women according to their risk is critical for effective personalized screening. The potential benefits of screening are greatest for high-risk women, as they are more likely to develop breast cancer. However, the potential harms of screening are largely unrelated to the women\'s risk and are instead associated with false positives results or direct effects of the test. Therefore, stratifying the population according to individual risk can help optimize the balance between benefits and harms by recommending intensive and potentially risky screening strategies only to women with sufficiently high risk that the expected benefits outweigh the harms. The study will analyze images to extract numerical data on contrast, luminosity, texture indexes, and machine learning-derived features, as well as collect radiologist-defined characteristics such as the presence of calcification, visually assessed density, background enhancement, and other patterns. Several computational methods will be used to explore the ability to predict cancer characteristics along with clinical information: artificial intelligence methods as well traditional logistic models. The endpoint will be incidence of breast cancer, including invasive BCs and ductal carcinoma in situ. Sensitivity analyses will be conducted by limiting the clinical endpoint to invasive cancer and incident cancers, i.e. excluding prevalent cancer detected through imaging examinations made at the time of recruitment and excluding BRCA1/2 and P53 mutated women. The area under the curve at receiver operating characteristics analysis and its 95% confidence intervals (according to the exact binomial distribution) will be calculated, classifying women according to the model\'s predicted risk of BC and observing how the sensitivity and specificity of model classification vary at increasing thresholds of risk. All women included in the study who are randomized, assigned to CEM for contraindications to MRI, or mutated and following the standard practice will contribute to this aim.

Specific aim 3 To make evidence generation more usable for the health system and accelerate decision-making on the best allocation of CEM or MRI in the surveillance of high-risk women, the trial will include substudies on costs, feasibility, and organizationalimpact, and acceptability. The principles of HTA will guide this evaluation. Costs will be collected through an activity-based cost analysis, assessing the consumption of human and technological resources for activities that may differ between the two strategies. If non-inferiority is demonstrated, costs related to the two strategies will be projected in a budget impact analysis with a 5-year horizon. A cost-minimization analysis will also be conducted assuming equal effectiveness, considering both the public and individual perspectives, including costs and time spent by users. Organizational feasibility and impact will be assessed through interviews with key people, such as decision-makers, screening program coordinators, directors of imaging department, and professionals involved in the surveillance program. Women\'s preferences and values given to the considered outcomes will be collected through interviews and focus groups involving participants to investigate the acceptability of the two technologies and possible surveillance protocols. The process will be conducted with the advice of a user and stakeholder engagement board, which will include high-risk women, representatives of patient associations, public health system decision makers, and health professional representatives. Systematic reviews will integrate study results into the framework of existing knowledge on the use of CEM in women at high and intermediate risk of BC. The Steering committee of the Italian breast cancer screening guidelines adolpment project, coordinated by the Osservatorio Nazionale Screening, will prioritize relevant clinical questions and frame them as PICO

• Biopsy rate [Срок оценки: 12 months]
• Cumulative recall rate, [Срок оценки: 12 months]
• Cumulative incidence of BC [Срок оценки: 12 months]
• False-positive rate [Срок оценки: 12 months]
• Positive predictive value [Срок оценки: 12 months]
• Interval cancer [Срок оценки: 12 months]
• Cumulative incidence of advanced (T2+) cancers [Срок оценки: 12 months]
• Prevalence of exclusion conditions for MRI and CEM [Срок оценки: baseline]
• Cancer incidence. [Срок оценки: 12 months]
• Interval cancer [Срок оценки: 12 months]
• Advanced cancers (T2+) [Срок оценки: 12 months]
• Adverse events [Срок оценки: 12 months]