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This is a clinical prospective, no-Profit, Interventional, Premarket Medical Device "early phase", multicentre, single-arm study, based on collecting data on predictive biomarkers of mCRC patients, integrate them with the results of the retrospective evaluation of outcomes and profiles of historical mCRC patients previously treated in the Oncology Units, in order to evaluate the efficacy of the best administered treatment. Results from the retrospective evaluation, will serve to build an AI-based profile capable to identify "good" or "poor" responders to therapy and to support the clinician towards the best treatment option. AI is a software based on algorithm defined as Medical Device Class IIa.
This is a clinical prospective, no-Profit, Interventional, Premarket Medical Device "early phase", multicentre, single-arm study, based on collecting data on predictive biomarkers of mCRC patients, integrate them with the results of the retrospective evaluation of outcomes and profiles of historical mCRC patients previously treated in the Oncology Units, in order to evaluate the efficacy of the best administered treatment. Results from the retrospective evaluation, will serve to build an AI-based profile capable to identify "good" or "poor" responders to therapy and to support the clinician towards the best treatment option. Following the first disease progression (PD), 2nd line therapy will be at Investigator's choice. The drugs under investigation are those commonly employed in mCRC patients as per usual standard of care. Artificial Intelligence (AI) is a software based on algorithm defined as Medical Device Class IIa.
The REVERT clinical trial is study, inserted within a wider European Project. The clinical study will take advantage of the results of the retrospective evaluation of mCRC patients' outcomes and profiles, aimed at evaluate the efficacy of treatment strategies, that will performed during the early activities of the European Project. In such retrospective analysis AI and Machine Learning (ML) will be instructed and used to derive predictive clinical data, after having analysed all possible variables including known mutational, biochemical and clinical features of samples from mCRC patients historically treated in the Oncology Units participating to the project and stored in partner Biobanks. AI and ML methodologies are based on Support Vector Machines and combine Multiple Kernel Learning and Random Optimization, incorporating already available large databases with new, potential prognostic/predictive biomarkers (e.g., gene mutations, epigenetic changes, gene expression profiling signatures). The emerging results will be used to help the choice of the best combinatorial therapy, for every prospectively enrolled mCRC patient. Sex and gender differences, also according to sidedness, will be analysed to evaluate their impact on survival and quality of life (QoL) in patients with mCRC.
Study length is planned to be about 24 months (12 months recruitment + 12 months of follow-up). The end of study is defined as the time when all enrolled patients will have experienced evidence of disease progression or will be out of treatment as per protocol, toxicity, medical decision or patient's withdrawal.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| All subjects | Other | mCRC subjects with WT (wild type) and RAS (matated) |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI | Device | The aim of using AI software to support physicians in choosing the most effective treatment. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Progression Free Survival (PFS) | Progression Free Survival (PFS), including PFS1 and PFS2, defined as the time from enrolment to the first documentation of objective disease progression or death due to any cause, whichever occurs first. | through study completion, an average of 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Overall survival (OS) | The time from enrolment to the date of death due to any cause. For patients still alive at the time of analysis, the OS time will be censored on the last date the patients were known to be alive. | through study completion, an average of 1 year |
| Response Rate (RR) |
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Inclusion Criteria:
Signed and dated Informed Consent.
Age ≥ 18 years at time of Informed Consent.
Histologically- or cytologically-confirmed mCRC.
Assessed tumour EGFR pathway mutational status (K-RAS, N-RAS), BRAF, HER-2 neu, MSI.
Sufficient amount of representative tumour specimen (primary or metastatic, archival or newly obtained for confirmatory central laboratory testing of BRAF and KRAS mutational status.
Dihydropyrimidine dehydrogenase (DPD) before 5-FU infusion.
Eligibility to receive bevacizumab, cetuximab or panitumumab per locally approved label with regard to tumour RAS status.
Recurrence of disease after primary radical surgery and adjuvant therapy carried out > 6 months prior the present trial.
Evidence of measurable or evaluable non-measurable disease as per RECIST, v1.1
ECOG PS of 0 or 1.
Adequate bone marrow function characterized by the following at screening:
Adequate renal function characterized by serum creatinine ≤ 1.5 × upper limit of normal (ULN), or creatinine clearance ≥ 50 mL/min.
Adequate hepatic function characterized by the following:
Female patients are either postmenopausal for at least 1 year, surgically sterile for at least 6 weeks, or must agree to take appropriate precautions to avoid pregnancy.
Males must agree to take appropriate precautions to avoid fathering a child from screening through follow-up.
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Mario Roselli, PI | Medical Oncology Unit, Department of Oncohematology, Policlinico Tor Vergata | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Scienze della Salute Università degli Studi di Firenze | Florence | 50121 | Italy | |||
| Unità Oncologia Medica Dipartimento di Discipline Chirurgiche, Oncologiche e Stomatologiche |
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| ID | Term |
|---|---|
| D003110 | Colonic Neoplasms |
| ID | Term |
|---|---|
| D015179 | Colorectal Neoplasms |
| D007414 | Intestinal Neoplasms |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
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Patients, male and female, age ≥18 years, with WT (wild type) and RAS mutated (mut) affected by mCRC.
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The percentage of patients, relative to the total of enrolled subjects, achieving a complete (CR) or partial (PR) response, according to RECIST 1.1 criteria, during the phases of treatment. |
| through study completion, an average of 1 year |
| Early Tumour Shrinkage (ETS) | As the percentage of patients, relative to the total of the enrolled subjects, achieving a >20% decrease in the sum of diameters of RECIST target lesions. | through study completion, an average of 1 year |
| Quality of Life (QoL) | measured using the EORTC QLQ-C30 questionnaire | through study completion, an average of 1 year |
| Palermo |
| 90127 |
| Italy |
| Medical Oncology Unit, Department of Oncohematology, Policlinico Tor Vergata | Roma | 00133 | Italy |
| "Grigore T. Popa" University of Medicine and Pharmacy of Iași | Iași | Iaşi | 700115 | Romania |
| Regional Institute of Oncology | Iași | Iaşi | 700483 | Romania |
| Hospital General Universitario Santa Lucía | Cartagena | Murcia | 30202 | Spain |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D004066 | Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D003108 | Colonic Diseases |
| D007410 | Intestinal Diseases |