Actively Recruiting

Age: 18Years +
FEMALE
ID07305727

Developing a Radiomic MRI Model Predictive of Response to Concomitant Chemoradiotherapy in Locally Advanced Cervical Cancer A Prognostic, Retrospective, Open-label, Multicenter Clinical Cohort Study

Led by Centre Hospitalier Universitaire de Nīmes · Updated on 2026-01-07

120

Participants Needed

1

Research Sites

21 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

Researchers are investigating a predictive model using radiomic data from pelvic MRI scans to understand the response to combined radiotherapy and chemotherapy in women with locally advanced cervical cancer. This approach aims to predict treatment outcomes early, helping to identify patients who may benefit from alternative therapies. The study focuses on patients with cervical cancer stages IB to IVA, who have undergone chemoradiotherapy, addressing the variability in treatment responses and recurrence rates. The study uses clinical and biological data from the EPICOL cohort, which includes patients treated with chemoradiotherapy at specialized cancer centers. Radiomic analysis is applied to MRI images taken before and after treatment to develop a model predicting progression-free survival and overall survival. This observational cohort study is retrospective, open-label, and involves multiple centers, aiming to validate radiomic markers as prognostic tools. Participants will have their clinical history, MRI images, biopsy samples, and follow-up data reviewed, including at least two years of post-treatment monitoring. Researchers will assess correlations between radiomic features and immune markers such as PD-L1 expression and tumor-infiltrating lymphocytes. The primary outcome is progression-free survival assessed at 24 months, with additional analysis of overall survival and biomarker associations. The study contributes to understanding cervical cancer prognosis and potential personalized treatment strategies.

CONDITIONS

Brief Title

A Radiomic MRI Predictive Model for Response to Concomitant Chemoradiotherapy in Locally Advanced Cervical Cancer

Who Can Participate

Age: 18Years +
FEMALE

Eligibility Criteria

Eligible

You may qualify if you...

  • Patients treated with exclusive radio-chemotherapy for locally advanced cervical cancer (stage Ib-IVb according to the FIGO classification).
  • Patients with a minimum of 2 years of post-treatment follow-up.
  • Patients for whom the initial biopsy specimen (prior to treatment) is available.
  • Patients who have not expressed their opposition to participating in the study.
  • Patients who are affiliated with or beneficiaries of a health insurance plan.
Not Eligible

You will not qualify if you...

  • Patients under judicial protection, guardianship, or curatorship

AI-Screening

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Your Study Journey

Screening

Duration - 2 to 4 weeks

Participants are screened for eligibility to participate in the trial.

Diagnostic Evaluation

Duration - Time of treatment and imaging assessments

Participants undergo pelvic MRI scans before and after chemoradiotherapy to collect radiomic data for developing a predictive model.

2 MRI visits (before and after treatment)

Long-term Monitoring

Duration - At least 24 months

Participants are followed for at least 2 years after treatment to assess progression-free and overall survival and correlate imaging data with biological markers.

Trial Site Locations

Total: 1 location

1

Nimes University Hospital

Nîmes, Gard, France, 30029

Actively Recruiting

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Research Team

F

Frédéric FITENI, Professor

A

Anissa MEGZARI

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

0

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Published Research Related To This Trial

Could follow-up different modalities play a role in asymptomatic cervical cancer relapses diagnosis? An Italian multicenter retrospective analysis.

P Zola, L Fuso, S Mazzola...

https://pubmed.ncbi.nlm.nih.gov/17868785

Radiomics-based prediction of two-year clinical outcome in locally advanced cervical cancer patients undergoing neoadjuvant chemoradiotherapy.

Rosa Autorino, Benedetta Gui, Giulia Panza...

https://pubmed.ncbi.nlm.nih.gov/35325372