- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06114589
A Study to Develop Molecular Integrated Predictive Models of Breast Radio-toxicity (Precise-RTox) ((Precise-RTox))
November 2, 2023 updated by: Centro di Riferimento Oncologico - Aviano
An Observational Study to Develop Molecular Integrated Predictive Models of Breast Radio-toxicity (Precise-RTox)
Breast radiation treatment is burdened by acute and chronic toxicities, in most cases mild.
However, considering the excellent life expectancy of patients with breast cancer, maintaining a low toxicity profile is of primary importance in order to guarantee a satisfactory quality of life.
The definition of the molecular and genetic variables related to radiotoxicity and their integration into predictive molecular signatures may allow the risk of toxicity to be individualized.
This would provide the clinician with a useful tool in order to personalize the radiation treatment, thus being able to choose the best technique or schedule for each patient.
Study Overview
Status
Recruiting
Conditions
Detailed Description
Breast radiation treatment is burdened by acute and chronic toxicities, in most cases mild.
However, considering the excellent life expectancy of patients with breast cancer, maintaining a low toxicity profile is of primary importance in order to guarantee a satisfactory quality of life.
Currently there are numerous predictive models of toxicity (Normal Tissue Complication Probability, NTCP) which are based on dosimetric and sometimes also clinical data.
To date, they do not include individual genetic variability.
However, it is believed that inter-individual variability may be responsible for up to 40% of actinic toxicity.
Multiparametric models that consider genetics, dose and clinical aspects probably better reflect the complexity of radiotoxicity than models that rely on a single parameter and it is possible to integrate such parameters using a machine learning approach.
The definition of the molecular and genetic variables related to radiotoxicity and their integration into predictive molecular signatures would therefore allow the risk to be individualized.
This would provide the clinician with a useful tool in order to personalize the radiation treatment, thus being able to choose the best technique or schedule for each patient.
Study Type
Observational
Enrollment (Estimated)
420
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Lorenzo Vinante, MD
- Phone Number: +390434659855
- Email: lorenzo.vinante@cro.it
Study Locations
-
-
Pordenone
-
Aviano, Pordenone, Italy, 33081
- Recruiting
- Centro di Riferimento Oncologico (CRO) di Aviano - IRCCS
-
Contact:
- Lorenzo Vinante, MD
- Phone Number: +390434659855
- Email: lorenzo.vinante@cro.it
-
Principal Investigator:
- Lorenzo Vinante, MD
-
Principal Investigator:
- Barbara Belletti, PhD
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
N/A
Sampling Method
Non-Probability Sample
Study Population
Women with distant non-metastatic breast cancer candidated to radiotherapy after conservative surgery
Description
Inclusion Criteria:
- Age ≥18 years;
- Ability to express appropriate informed consent to treatment;
- Distant nonmetastatic breast cancer;
- Histology: infiltrating NST(no special type)/lobular carcinoma or ductal carcinoma in situ;
- Stage: pTis; pT1-3 pN1-3 M0;
- Hormone receptors, HER-2 status: Any;
- Breast-conserving surgery. Both the sentinel lymph node biopsy and axillary lymphadenectomy. Negative surgical margins.
- Candidates for postoperative radiation treatment.
Exclusion Criteria:
- Refusal of radiotherapy treatment (i.e., absence of signed informed consent);
- Previous radiation therapy at the same site;
- Concomitant chemotherapy with anthracyclines or taxanes;
- Inability to maintain treatment position;
- Partial breast radiotherapy (PBI);
- Male breast cancer;
- Mastectomy surgery.
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Generation of a predictive model for actinic fibrosis.
Time Frame: up to 2 years after start of treatment
|
Identification of a predictive model of actinic fibrosis in the breast, with sensitivity of at least 75% and specificity of 90%.
Fibrosis is defined as grade ≥2 (CTCAE v 4.0) or skin induration as grade ≥2 defined according to CTCAE v 4.0 .
|
up to 2 years after start of treatment
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Generation of a predictive model for acute skin toxicity
Time Frame: up to 2 years after start of treatment
|
Sensitivity of a model combining different variables to predict acute skin toxicity defined according to CTCAE scale v4.0 as dermatitis grade ≥2 or ulceration of the skin of grade ≥2
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for late skin toxicity
Time Frame: up to 2 years after start of treatment
|
Sensitivity of a model combining different variables to predict late skin toxicity defined according to CTCAE scale v4.0 as grade 2 telangiectasia or grade 2 hyperpigmentation
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for acute pain
Time Frame: up to 2 years after start of treatment
|
Sensitivity of a model combining different variables to predict acute pain of grade ≥2 defined according to CTCAE scale v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for chronic pain
Time Frame: up to 2 years after start of treatment
|
Sensitivity of a model combining different variables to predict chronic pain grade ≥2 defined according to CTCAE scale v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for fatigue
Time Frame: up to 2 years after start of treatment
|
Sensitivity of a model combining different variables to predict fatigue of grade ≥2 defined according to CTCAE scale v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for lymphedema
Time Frame: up to 2 years after start of treatment
|
Sensitivity of a model combining different variables to predict ipsilateral limb lymphedema of grade ≥2 defined according to CTCAE v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for hypothyroidism
Time Frame: up to 2 years after start of treatment
|
Sensitivity of a model combining different variables to predict hypothyroidism of grade ≥2 defined according to CTCAE v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for contra-lateral breast cancer
Time Frame: up to 2 years after start of treatment
|
Sensitivity of a model combining different variables to predict secondary neoplasia to the contra-lateral breast according to CTCAE v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for cardiotoxicity
Time Frame: up to 2 years after start of treatment
|
Sensitivity of a model combining different variables to predict grade ≥2 cardiovascular events defined according to CTCAE v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for aesthetic outcome
Time Frame: up to 2 years after start of treatment
|
Sensitivity of a model combining different variables to predict aesthetic outcome defined as fair/poor, according to Harvard score
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for acute skin toxicity
Time Frame: up to 2 years after start of treatment
|
Specificity of a model combining different variables to predict acute skin toxicity defined according to CTCAE scale v4.0 as dermatitis grade ≥2 or ulceration of the skin of grade ≥2
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for late skin toxicity
Time Frame: up to 2 years after start of treatment
|
Specificity of a model combining different variables to predict late skin toxicity defined according to CTCAE scale v4.0 as grade 2 telangiectasia or grade 2 hyperpigmentation
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for acute pain
Time Frame: up to 2 years after start of treatment
|
Specificity of a model combining different variables to predict acute pain of grade ≥2 defined according to CTCAE scale v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for chronic pain
Time Frame: up to 2 years after start of treatment
|
Specificity of a model combining different variables to predict chronic pain of grade ≥2 defined according to CTCAE scale v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for fatigue
Time Frame: up to 2 years after start of treatment
|
Specificity of a model combining different variables to predict fatigue of grade ≥2 defined according to CTCAE scale v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for lymphedema
Time Frame: up to 2 years after start of treatment
|
Specificity of a model combining different variables to predict ipsilateral limb lymphedema of grade ≥2 defined according to CTCAE v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for hypothyroidism
Time Frame: up to 2 years after start of treatment
|
Specificity of a model combining different variables to predict hypothyroidism of grade ≥2 defined according to CTCAE v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for contra-lateral breast cancer
Time Frame: up to 2 years after start of treatment
|
Specificity of a model combining different variables to predict secondary neoplasia to the contra-lateral breast according to CTCAE v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for cardiotoxicity
Time Frame: up to 2 years after start of treatment
|
Specificity of a model combining different variables to predict grade ≥2 cardiovascular events defined according to CTCAE v4.0
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for aesthetic outcome
Time Frame: up to 2 years after start of treatment
|
Specificity of a model combining different variables to predict aesthetic outcome defined as fair/poor, according to Harvard score
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for cardiotoxicity
Time Frame: up to 2 years after start of treatment
|
Sensitivity of a model combining different variables to predict cardiotoxicity defined as reduction at echocardiography of Global Longitudinal Strain (GLS) ≥10% compared to baseline
|
up to 2 years after start of treatment
|
|
Generation of a predictive model for cardiotoxicity
Time Frame: up to 2 years after start of treatment
|
Specificity of a model combining different variables to predict cardiotoxicity defined as reduction at echocardiography of Global Longitudinal Strain (GLS) ≥10% compared to baseline
|
up to 2 years after start of treatment
|
|
Comparison between toxicity risk in treatment plans using protons or photons
Time Frame: up to 2 years after start of treatment
|
Difference in frequency of high risk toxicity between treatment plans using protons or photons
|
up to 2 years after start of treatment
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Investigators
- Principal Investigator: Lorenzo Vinante, MD, Centro di Riferimento Oncologico di Aviano (CRO) - IRCCS
- Principal Investigator: Barbara Belletti, PhD, Centro di Riferimento Oncologico di Aviano (CRO) - IRCCS
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
August 25, 2022
Primary Completion (Estimated)
June 30, 2026
Study Completion (Estimated)
June 30, 2026
Study Registration Dates
First Submitted
October 27, 2023
First Submitted That Met QC Criteria
October 27, 2023
First Posted (Actual)
November 2, 2023
Study Record Updates
Last Update Posted (Actual)
November 7, 2023
Last Update Submitted That Met QC Criteria
November 2, 2023
Last Verified
November 1, 2023
More Information
Terms related to this study
Other Study ID Numbers
- CRO-2022-29
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
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