Validation of a Prognostic Method for Assessing the Risk of Distant Metastasis in Early-stage Breast Cancer
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Validation of Prognostic tool.
- Who it may be relevant to
- Registry conditions: Breast Cancer Early Stage Breast Cancer (Stage 1-3). Basic parameters: from 18 years · Female.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Italy
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Dissecting the Role of miR-3916 and miR3613-5p in Breast Cancer and Developing a Metastases Predictor PORTENT Algorithm
Overview
This is a multicenter, observational validation study designed to evaluate the prognostic performance of the PORTENT algorithm in patients with early-stage breast cancer. The model integrates clinicopathological variables and the expression levels of two small non-coding RNAs (miR-3916 and miR-3613-5p) to estimate individual risk of developing distant metastases. The primary objective is to assess the discriminatory ability of the PORTENT algorithm for predicting distant metastasis at predefined time points after diagnosis.
Detailed description
This multicenter retrospective observational study aims to clinically validate the PORTENT prognostic algorithm for predicting the risk of distant metastases in women with early-stage breast cancer. Female patients with Stage I-III disease from three independent cohorts with available residual tumor tissue and follow-up data will be included.
The primary endpoint of the study is the discriminatory performance of the PORTENT algorithm, assessed by the area under the receiver operating characteristic curve (AUC) for the prediction of distant metastases at 5 and 10 years from diagnosis.
The algorithm integrates established clinicopathological prognostic factors (tumor stage, histological grade, and Ki67-MIB1) with the expression levels of miR-3916 and miR-3613-5p. MicroRNA expression and target protein expression will be evaluated using RT-qPCR and immunohistochemistry.
Secondary and exploratory analyses will include model calibration assessed using calibration curves and the Integrated Calibration Index (ICI), as well as survival analyses (overall survival, progression-free survival, and metastasis-free survival) performed using Cox proportional hazards models.
Interventions
- Diagnostic test Validation of Prognostic tool
Collection of Clinical History: Clinical data, including medical history, clinicopathological features (e.g., age, histology, receptor and nodal status), and follow-up information (presence or absence of metastasis, patient vital status), will be collected and entered into a dedicated platform by. Follow-up updates are scheduled by Month 48 of the project (December 31, 2025) to ensure timely and accurate patient outcome data. Laboratory Analysis: Residual tumor sections prepared by the Patholog
Primary outcome measures
- Discriminatory Performance of the Prognostic Algorithm (AUC) for Prediction of Distant Metastasis Within 5 Years From Diagnosis [Time frame: 5 years from diagnosis; interim analysis at March 2027.]
- Discriminatory Performance of the Prognostic Algorithm (AUC) for Prediction of Distant Metastasis Within 10 Years From Diagnosis [Time frame: 10 years from diagnosis; final analysis after completion of 10-year follow-up for all participants (expected by 2029).]
Secondary outcome measures (8)
- Calibration of the Prognostic Model at 5 Years (Integrated Calibration Index) [Time frame: 5 years from diagnosis; interim analysis at March 2027.]
- Calibration of the Prognostic Model at 10 Years (Integrated Calibration Index) [Time frame: 10 years from diagnosis; final analysis after completion of 10-year follow-up (expected by 2029).]
- Difference in Discriminatory Performance Between Prognostic Models (ΔAUC) at 5 Years [Time frame: 5 years from diagnosis; interim analysis at March 2027.]
- Difference in Discriminatory Performance Between Prognostic Models (ΔAUC) at 10 Years [Time frame: 10 years from diagnosis; final analysis after completion of 10-year follow-up (expected by 2029).]
- Classification Performance of the Prognostic Algorithm at 10 Years (Sensitivity, Specificity, PPV, NPV) [Time frame: 10 years from diagnosis; final analysis after completion of 10-year follow-up (expected by 2029).]
- Association Between miR-3916 and miR-3613-5p Expression and Overall Survival [Time frame: Up to 10 years from diagnosis; final analysis after completion of follow-up (expected by 2029).]
- Prognostic Algorithm Performance Within PAM50 Molecular Subgroups [Time frame: 5 and 10 years from diagnosis; final analysis after completion of follow-up (expected by 2029).]
- Analytical Validity of miRNA Expression Assessment [Time frame: Data collection and analysis completed by March 2027.]
Eligibility criteria
Inclusion criteria
- Stage I-III breast cancer
- Residual tumor tissue available
- Written informed consent
Exclusion criteria
- Age <18
- Stage IV at diagnosis
- Refusal or inability to provide informed consent
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Other
Study locations
Italy · 1 center
- Fondazione Casa Sollievo della Sofferenza IRCCS — San Giovanni Rotondo
Publications
- Fontana A, Barbano R, Pasculli B, Mazza T, Palumbo O, Binda E, Trivieri N, Mencarelli G, Laurenzana I, Lamorte D, De Luca L, Caivano A, Biagini T, Rendina M, Lo Mele A, Prencipe G, Bravaccini S, Murgo R, Ciuffreda L, Morritti M, Valori VM, Di Lisa FS, Vici P, Castelvetere M, Carella M, Graziano P, Maiello E, Copetti M, Esteller M, Parrella P. Development of a microRNA-based prognostic model for ac PMID 41024243
Identifiers
NCT: NCT07372261 · PORTENT