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

Study Locations

    • Pordenone
      • Aviano, Pordenone, Italy, 33081
        • Recruiting
        • Centro di Riferimento Oncologico (CRO) di Aviano - IRCCS
        • Contact:
        • 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

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Subscribe