Breast Cancer, Chemotherapy Effect, Recurrence, Local Neoplasm, Risk Factors, Triple Negative Breast Cancer
Conditions
Brief summary
INTRODUCTION Breast cancer (BC) is the leading cause of cancer-related death in women. Since the early 1980s, the implementation of screening programs has reduced the number of patients diagnosed with locally advanced breast cancer. Currently, the treatment for these patients involves initial neoadjuvant chemotherapy (NACT) followed by surgical treatment. In recent years, NACT has also been used for highly chemoresponsive tumors such as triple-negative (TN) and HER2-positive (HER2+) breast cancer. The widespread use of NACT has led to additional benefits, including downstaging of breast and axillary neoplasms, resulting in reduced morbidity; improved cosmetic outcomes due to increased use of conservative interventions; and personalized adjuvant chemotherapy treatment. Several studies have shown that response to chemotherapy predicts better systemic outcomes. Complete pathological response (pCR), defined as the absence of invasive neoplastic residue in the surgical specimen, has been predictive of better distant outcomes. Limited evidence exists regarding other predictive factors for distant outcomes. Given the significant impact of disease recurrence on patient prognosis, efforts have been made to understand the factors contributing to recurrence and to predict which patients are more prone to relapse. In this context, the term Early Disease Recurrence (EDR) has been coined to define the occurrence of disease recurrence, both locally and distantly, within 3 years after completing treatment. In recent years, the potential of radiomic analysis in aiding diagnostic and therapeutic decision-making processes in BC has been demonstrated. Specifically, radiomic features obtained from Magnetic Resonance Imaging (MRI) images appear capable of predicting tumor receptor status, differentiating tumor subtypes, and predicting response to NACT. Although the role of radiomics in predicting recurrence has been investigated, research is still in its early stages, and there are variations in technology and methodology for extracting radiomic features. Additionally, to date, no studies have evaluated the feasibility and reliability of using radiomic models combined with clinical and radiological variables to predict disease recurrence in BC patients undergoing NACT.
Interventions
DIAGNOSTIC_TESTMRI
Breast MRI
Sponsors
Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Study design
Observational model
CASE_ONLY
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
FEMALE
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Histological diagnosis of locally advanced Luminal or HER2+ or Triple-negative breast cancer (cT2, T3, T4 N0 or any T N1, N2, N3, M0), clinical stage of disease from I to III. * Patient undergoing neoadjuvant chemotherapy treatment from January 1, 2014, to June 30, 2021. * Age \> 18 years * Availability of clinical data, staging MRI diagnostic images (for the radiomic sub-study), and biomolecular data.
Exclusion criteria
* Previous or synchronous history of systemic malignancies. * History of ipsilateral or contralateral breast neoplasia. * Evidence of metastatic disease (Stage IV). * Neoadjuvant treatment with hormone therapy. * Patients with unavailable or low-quality MRI images that did not allow lesion identification (for the radiomic study only).
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Description of molecular subtypes | 7 years | Frequency of molecular subtypes (Her2 positive, hormone receptor-positive/Her2 negative, Triple Negative) in the considered cases |
| Association between radiomic features and risk of recurrence | 7 years | Association between radiomic features extracted from pre-operative MRI and the onset of disease recurrence within 3 years from the end of neoadjuvant treatment |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Association between chemotherapy and neoplastic characteristics | 7 years | Evaluate whether clinical features (divided into: age assessed in years, menopausal status divided into menopausal or fertile age), radiological features such as initial extent of disease and lymph node involvement at diagnosis) and biomolecular features (such as histotype: divided into ductal, lobular or nonspecial type, grading, hormone receptor status) influence response to neoadjuvant chemotherapy Translated with DeepL.com (free version) |
| Evaluation of radiological response | 7 years | Frequency of radiological response according to molecular subtype, treatment, type of imaging examination used, and initial staging. |
| Frequency of complete pathological response | 7 years | Frequency of complete pathological response according to molecular subtype, treatment, and initial staging. |
| Description of surgical treatment according to the cancer characteristics | 7 years | Frequency of surgical procedures based on radiological response, molecular subtypes, and initial staging. |
| Description of adjuvant treatments | 7 years | Frequency of adjuvant therapies based on neoadjuvant treatment, molecular subtypes, and initial staging. |
| Evaluation of oncological outcomes | 7 years | Disease-free survival (DFS) measured from the start of neoadjuvant therapy to the first evidence of disease recurrence or death, whichever occurs first. |
| Assessment of risk of recurrence using models | 7 years | Accuracy of pure models (radiomic/clinical/radiological) and combined models in predicting disease recurrence within 3 years from the end of neoadjuvant treatment |
Countries
Italy
Contacts
Primary ContactAlessandra Fabi
Backup ContactAntonio Franco
Outcome results
None listed