A Study to Develop Molecular Integrated Predictive Models of Breast Radio-toxicity (Precise-RTox)

Last updated: November 2, 2023
Sponsor: Centro di Riferimento Oncologico - Aviano
Overall Status: Active - Recruiting

Phase

N/A

Condition

Breast Cancer

Cancer

Treatment

N/A

Clinical Study ID

NCT06114589
CRO-2022-29
  • Ages > 18
  • Female

Study Summary

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.

Eligibility Criteria

Inclusion

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 insitu;
  • Stage: pTis; pT1-3 pN1-3 M0;
  • Hormone receptors, HER-2 status: Any;
  • Breast-conserving surgery. Both the sentinel lymph node biopsy and axillarylymphadenectomy. Negative surgical margins.
  • Candidates for postoperative radiation treatment.

Exclusion

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 Design

Total Participants: 420
Study Start date:
August 25, 2022
Estimated Completion Date:
June 30, 2026

Study 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.

Connect with a study center

  • Centro di Riferimento Oncologico (CRO) di Aviano - IRCCS

    Aviano, Pordenone 33081
    Italy

    Active - Recruiting

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