Trial Title:
Contrast Enhancement Mammography vs MRI for the Surveillance of Women at High Risk of Breast Cancer: Con-trust Randomized Controlled Trial
NCT ID:
NCT06629896
Condition:
Breast Cancer Screening and Diagnosis
Conditions: Official terms:
Breast Neoplasms
Conditions: Keywords:
breast cancer
screening
contrast enhanced mammography
magnetic resonance
Study type:
Interventional
Study phase:
N/A
Overall status:
Not yet recruiting
Study design:
Allocation:
Randomized
Intervention model:
Parallel Assignment
Intervention model description:
The study focus on the ability to early detect breast cancer. The study will compare
efficacy in reducing the incidence of BC in women who tested negative in the first
screening and cumulative recall rates over 2 screening rounds. All women will be followed
up for 2.5 years.
Primary purpose:
Screening
Masking:
Single (Outcomes Assessor)
Masking description:
Due to the nature of the intervention, it is not possible to blind the study arm to
patients or investigators. However, pathologic tumor size will be assessed blinded by
local pathologists, while radiologic tumor size, which initially cannot be assessed
blinded, will be examined independently by outside radiologists according to the
procedure described in Pattacini et al. 2022 [Pattacini P, Nitrosi A, Giorgi Rossi P,
Duffy SW, Iotti V, Ginocchi V, Ravaioli S, Vacondio R, Mancuso P, Ragazzi M, Campari C;
RETomo Working Group. A Randomized Trial Comparing Breast Cancer Incidence and Interval
Cancers after Tomosynthesis Plus Mammography versus Mammography Alone. Radiology. 2022
May;303(2):256-266]. This approach ensures an unbiased assessment of tumor size.
Intervention:
Intervention type:
Diagnostic Test
Intervention name:
Contrast Enhancement Mammography
Description:
In the experimental arm women will receive two rounds of CEM surveillance. After 2 years,
all women who were randomly assigned to receive either MRI or CEM will undergo the same
exit test. This exit test is the standard test used for the surveillance of high-risk non
mutated women at each participating center.
Arm group label:
CONtrast enhanced mammography
Intervention type:
Diagnostic Test
Intervention name:
magnetic resonance imaging (MRI) and digital mammography (DM)
Description:
women will receive two rounds of MRI+DM surveillance. After 2 years, all women who were
randomly assigned to receive either MRI or CEM 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.
Arm group label:
MRI
Summary:
Women at high risk of breast cancer (BC) should undergo annual magnetic resonance imaging
(MRI) and digital mammography (DM) from at least ages 35 to 60. While MRI is an expensive
and scarce resource, contrast-enhanced mammography (CEM) is a less costly and
time-consuming alternative that could be used to screen these women instead of MRI. The
Con-TRUST trial aims to randomize 1400 women in 10 centers to test whether CEM can be
used instead of MRI+DM for BC detection in high-risk women (>5%
5-year BC risk). The study will compare efficacy in reducing the incidence of BC in women
who tested negative in the first screening and cumulative recall rates over 2 screening
rounds. All women will be followed up for 2.5 years. Secondary outcomes include screening
performance, safety, and women's compliance. The trial results
will be integrated with the international literature and proposed for the development of
recommendations as part of the adolopment of European guidelines in Italy.
Detailed description:
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 (Population Intervention Comparator Outcome). Evidence from systematic
reviews on efficacy and safety, costs, and women's preferences will
be integrated with context-specific information from trial sub-studies on costs,
feasibility, organizational impact, and acceptability. The evidence will be summarized in
Summary of finding and Evidence to Decision tables, using the GRADE (Grading of
Recommendations Assessment, Development and Evaluation) methodology, and proposed for
developing recommendations to the Scientific Committee of the breast cancer screening
guideline adolopment of the European Guidelines.
Experimental design aim 1 High-risk women who are scheduled for a surveillance test will
be informed about the study through mail or phone. If willing, women can schedule an
appointment for detailed information and provide consent. Recruitment can also occur
during their first episode on-site. Validated risk assessment tools like Tyrer-Cuzick
IBIS, BOADICEA, Breast Cancer Screening Consortium, and Mammorisk will be used to assess
eligibility based on a 5% estimated risk of BC in the next five years. Algorithms will be
provided to calculate the risk. Exclusion criteria are pregnancy and non-comprehension of
information. After assessing eligibility for randomization, the investigator will assign
women directly to Contrast-Enhanced Mammography (CEM) if they have claustrophobia,
MRI-unsafe devices, intolerance to gadolinium, or are unable to enter the MRI gantry.
Women with a known intolerance to iodine contrast medium or known mutations in DNA repair
genes (BRCA1, BRCA2, TP53) will be assigned directly to MRI. MRI will be performed during
the indicated phase of the menstrual cycle (day 5-14) according to each
center's protocol. It will include T2W suppressed, post-contrast dynamic
imaging with MIP reconstruction, and diffusion-weighted imaging (DWI). MRI and Digital
Mammography (DM) will preferably be performed on the same day and interpreted together.
CEM, involving two views per breast, will also be conducted during the indicated
menstrual cycle phase (day 5-14) following the injection of contrast media, with the
first image acquired 2 minutes post-injection. The order of projection (MLO and CC for
each breast) will not affect the results. Experienced breast radiologists will interpret
the images locally. Ultrasound (US) second look will be considered based on local
protocols but only for specific cases. Women with positive or suspicious findings will be
recalled for further assessment, which may include ultrasound-guided core needle biopsy
(CNB) or stereotactic vacuum-assisted breast biopsy (VABB) depending on the easiest
imaging to localize the finding. Women with inconclusive CNB results will undergo VABB.
Those with malignancy or B3/B4 results on VABB will be discussed by a multidisciplinary
team. Short-term follow-up may be recommended in exceptional cases, usually after six
months. The study will include these screen-detected findings in the baseline outcomes.
Women with negative assessments will be referred to regular screening and actively
re-invited after 12 months. In the third screening round, all women in the randomized
sub-cohort will be rescreened using the standard test used for high-risk non-mutated
women at each center. Retrospective imaging reading, blinded to the outcome, will be
conducted to determine the accuracy of different imaging protocols, such as unenhanced
MRI (DWI-only with ADC maps; DWI plus T1-weighted plus T2-weighted sequences), MRI
abbreviated protocol, MRI plus single mediolateral oblique Mx projection, and reversed
hanging protocol for CEM. Breast density will be objectively assessed to conduct
sub-group analyses based on breast density categories. In addition, Aim 1 of the study
will include site visits for quality control of MRI and CEM equipment. This will ensure
that the imaging devices are functioning optimally and producing accurate results.
Furthermore, as part of the study, the radiation dose delivered by CEM and DM will be
accurately measured and recorded for the CEM and MRI+DM arms of the randomized
sub-cohort, respectively. This information will also be obtained for women who undergo
CEM alone or to MRI+DM in non-randomized cohorts. By collecting this data, the study aims
to assess the radiation exposure associated with CEM and evaluate its safety and
effectiveness as a screening method for high-risk women.
Experimental design aim 2 The objective of this experimental design is to develop a model
for predicting breast cancer (BC) risk during the study period. The design considers
multiple outcomes: 1) all cancers (including invasive and ductal carcinoma in situ
[DCIS], both prevalent and incident, and those detected by screening or as interval
cancers); 2) only incident cancers (excluding screendetected cancers that were positive
at the entry test); and 3) interval cancers. Sensitivity analyses excluding DCIS will be
conducted. The experimental design involves processing low-energy CEM images from the
randomized CEM arm and the observational cohort, as well as digital mammography (DM)
images from the randomized MRI+DM arm and the observational cohort. An artificial
intelligence (AI) software tool will be used to assess breast density and calculate a
breast cancer risk score. The goal is to refine or potentially replace existing breast
cancer risk models with this AI-based approach. Radiomics features will be extracted from
mammographic images using AI tools for risk assessment. Radiomics refers to
high-dimensional quantitative features extracted from medical images that capture
information about tumor heterogeneity, texture, shape, and other characteristics that are
not easily discernible to the naked eye. These features may include statistical measures
such as mean, standard deviation, skewness, and kurtosis of pixel intensities within the
breast region. Texture features, such as entropy, contrast, and homogeneity, will also be
extracted to quantify patterns and spatial relationships within the breast tissue. In
addition, shape-based features, such as compactness, circularity, and sphericity can be
computed to capture the geometric properties of lesions or regions of interest. These
features provide a rich set of data that can be used to improve risk prediction models.
To incorporate these radiomics features into risk prediction models, various machine
learning algorithms will be employed. These algorithms are able to learn patterns and
relationships within the data and make predictions based on the learned models. Various
machine learning models can be used, such as logistic regression, support vector machines
(SVM), random forests, or gradient boosting machines (GBM). Training and validation
datasets will be carefully constructed to ensure representativeness of the study
population and to capture the full spectrum of breast cancer risk. The datasets will
include cases from both the CEM and DM arms, as well as the observational cohort.
Variability among different imaging systems and technologists will be considered to
account potential sources of bias. During the model development process, the performance
of machine learning models will be evaluated using appropriate metrics, such as accuracy,
sensitivity, specificity, and the area under the receiver operating characteristic curve
(AUC). The AUC represents the ability of the model to discriminate between individuals
with and without breast cancer. It provides a comprehensive measure of the predictive
performance of the model across different risk thresholds. In addition, the performance
of AI-based risk assessment models will be compared with existing state-of-the-art breast
cancer risk models. This comparison will help determine the added value of radiomics
features and machine learning algorithms in improving risk prediction. Overall, the
combination of radiomics features extracted from mammography images and machine learning
models will enable the development of a more accurate and robust breast cancer risk
prediction model, potentially improving personalized screening strategies and optimizing
the balance between benefits and harms of screening.
Experimental design aim 3 Prior to the start of the project and before the protocol is
submitted to the ethics committee, a stakeholder committee will be established, composed
of representatives of high-risk women, patients' associations, public health
system decision-makers, and health professionals. This committee will play a crucial role
in assessing the relevance of the study outcomes to women's health and to the
health system in general. In addition, it will provide input into the review of
informational materials and women¿s outreach strategies. The stakeholder committee will
serve as an external advisory board for the study and will prioritize the clinical
questions framed as PICOs (Population Intervention Comparator Outcomes) that will guide
the systematic review of the use of contrast-enhanced mammography (CEM) and breast MRI in
the surveillance of high-risk women. The systematic review protocol will be registered in
the PROSPERO database, ensuring transparency and adherence to predefined methods. The
review will adopt the standard methods of the Cochrane Collaboration to ensure rigor and
minimize bias. The GRADE system will be used to assess the importance of outcomes and
certainty of evidence. This approach allows the quality and strength of the evidence to
be assessed, helping to formulate reliable conclusions. To examine the economic evidence,
the NICE methodological checklist for economic studies will be used to assess
applicability and methodological limitations. If the study results support equal
effectiveness between the two surveillance strategies, a cost minimization analysis will
be conducted. This analysis will consider both the direct costs incurred by the
healthcare system and the time spent by women participating in the surveillance. To
explore the organizational impact of the two surveillance strategies, interviews will be
conducted with decision makers at the hospital and local health authority levels,
screening program coordinators, directors of diagnostic imaging department, and
professionals involved in the surveillance program. These interviews will provide
insights into the practical implications and potential challenges associated with
implementing the different strategies within the existing healthcare infrastructure. The
acceptability of the two technologies and potential surveillance strategies will be
investigated through interviews with participating women and focus groups. Face-to-face
discussions with women will gather their perspectives and experiences, helping them to
understand their preferences and concerns. Data extracted from the systematic review and
information gathered through the interviews and focus groups will be summarized in
summary tables of findings using the electronic online tool GRADEpro. These tables will
present a concise and structured overview of the evidence, facilitating interpretation
and synthesis of the results. In addition, Evidence to Decision Tables will be developed
for submission to the Scientific Technical Committee of the Italian Breast Cancer
Screening Guidelines Development Project, which contributes to the European
recommendations on breast cancer screening. These tables will help consider and
potentially include PICOs in the guidelines, ensuring the formulation of evidence-based
recommendations. By involving stakeholders, conducting systematic reviews, evaluating
economic aspects, assessing organizational impact, and investigating acceptability, the
study aims to generate comprehensive evidence that can inform decision making and guide
the best allocation of resources between CEM and MRI in the surveillance of high-risk
women.
Hypothesis and significance International guidelines recommend annual MRI, usually in
combination with digital mammography (DM), for women with a known BRCA1/2 mutation and
those with a similarly high risk of BC. This is due to its higher sensitivity, as
demonstrated by several multicentre studies, including one conducted in Italy. It is
estimated that 1 to 3% of females aged 40 to 70 years, depending on the model used, can
be classified with a mutated-like risk of BC and may benefit from surveillance by MRI.
Breast MRI has been shown to reduce interval cancer in women with extremely dense
breasts, and has been suggested as potential supplemental screening for women with dense
breasts. However, MRI is a limited resource, expensive, and burdened by specific
contraindications, such as claustrophobia and unsafe medical devices for MRI. As a
result, many women at high risk for BC do not receive adequate surveillance. A very
recent meta-analysis, which included more than 10,000 patients, showed that
contrast-enhanced mammography (CEM) has a high accuracy in detecting BC, similar to that
of MRI. CEM is already preferred over MRI for preoperative assessment by European
Commission guidelines, and smaller studies on screening with CEM of high-risk women are
underway (e.g., SCEMAM in the USA, and CESM in high and intermediate-risk women, which
just concluded recruitment at IOV, Padua, one of the centers participating in this
proposal). However, no study has compared MRI and CEM for downstream consequences of
screening. The techniques use different contrast agents (CAs) that exhibit the same
two-compartment intravascular-interstitial biodistribution. The gadolinium-based CAs used
in MRI, apart from rare allergic reactions, are of concern for long-term accumulation in
tissues when considering the high cumulative doses reached in annual screening programs,
including the brain. In contrast, iodine-based CAs can cause nephropathy. CEM provides a
radiation dose comparable to that of DM but offers both morphological evaluation (similar
to standard DM) and functional evaluation (similar to MRI), simultaneously. Morphological
evaluation allows for the detection of calcification-associated lesions, such as ductal
carcinoma in situ, with less neoangiogenesis and the possibility of false negatives with
MRI, especially in women who underwent thoracic radiotherapy. Moreover, CEM is estimated
to cost less than one-third of MRI. Given its comparable efficacy and safety, as well as
much lower costs and resource consumption, a non-inferiority study design aimed to
investigate whether CEM can be used as an alternative to MRI+DM for early detection of BC
in high-risk women with >5% BC risk in the next 5 years.
Criteria for eligibility:
Criteria:
Inclusion Criteria:
- Women at high risk of developing breast cancer already in care at participating
centers or new referral for early diagnosis programs, aged between 35 and 60 years,
with an estimated risk of breast cancer in the next 5 years >=5%.
To estimate the 5-year risk, centers may use one of the following models and criteria:
- Tyrer Cuzick IBIS: criterion >10% at 10 years;
- BOADICEA: criterion >10% at 10 years;
- BCSC: criterion >10% at 10 years (if possible switch to Tyrer-Cuzick if >=2
relatives with breast or ovarian cancer);
- MyPeBS (Mammorisk): woman included at very high risk in the MyPeBS study and who has
completed the active follow-up period;
- Women with previous chest irradiation for radiotherapy
Exclusion Criteria:
-
- Previous breast cancer;
- Pregnancy;
- Bilateral mastectomy;
- Psychiatric or other disorders not compatible with compliance with the protocol and
follow-up requirements;
- Women who do not intend or cannot be followed for at least 2.5 years;
- Women are unable to understand the information or to express a truly informed
consent or non-consent to participation.
Gender:
Female
Minimum age:
35 Years
Maximum age:
60 Years
Healthy volunteers:
No
Locations:
Facility:
Name:
Istituto in tecnologie avanzate e modelli assistenziali in oncologia - AUSL-IRCCS Reggio Emilia
Address:
City:
Reggio Emilia
Zip:
42122
Country:
Italy
Start date:
January 7, 2025
Completion date:
January 7, 2030
Lead sponsor:
Agency:
Azienda Unità Sanitaria Locale Reggio Emilia
Agency class:
Other
Collaborator:
Agency:
Istituto Oncologico Veneto I.O.V. - I.R.C.C.S.
Agency class:
Other
Collaborator:
Agency:
Azienda Ospedaliera Universitaria (AOU) Messina
Agency class:
Other
Collaborator:
Agency:
Azienda Ospedaliera Universitaria (AOU) Bari
Agency class:
Other
Collaborator:
Agency:
Azienda Ospedaliera Universitaria Integrata Verona
Agency class:
Other
Collaborator:
Agency:
Fondazione IRCCS Policlinico San Matteo di Pavia
Agency class:
Other
Collaborator:
Agency:
Azienda Ospedaliero-Universitaria di Modena
Agency class:
Other
Collaborator:
Agency:
Azienda USL della Romagna
Agency class:
Other
Collaborator:
Agency:
Fondazione IRCCS Istituto Nazionale dei Tumori, Milano
Agency class:
Other
Source:
Azienda Unità Sanitaria Locale Reggio Emilia
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT06629896
https://www.nice.org.uk/guidance/cg164/ifp/chapter/Early-detection-of-breast-cancer-by-surveillance
https://gdt.gradepro.org/app/handbook/handbook.html
https://www.nice.org.uk/process/pmg6/resources/the-guidelines-manual-appendices-bi-2549703709/chapter/appendix-g-methodology-checklist-economic-evaluations
