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Developing a Radiomic MRI Predictive Model for Response to Concomitant Chemoradiotherapy in Locally Advanced Cervical Cancer.

NCT ID: NCT07305727

Last Updated: 2025-12-26

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

120 participants

Study Classification

OBSERVATIONAL

Study Start Date

2026-01-01

Study Completion Date

2026-12-31

Brief Summary

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Cervical cancer is the fourth most common cancer in women worldwide, with approximately 604,000 new cases in 2020.Treatment for locally advanced cervical cancer is based on a combination of radiotherapy and chemotherapy. The response to concomitant chemoradiotherapy vary from one woman to another. Predicting the response to these treatments would allow early consideration of alternative therapies for patients identified as less responsive to standard treatments. A 5-year recurrence-free survival is approximately 79% for stages IB and IIA and 59% for stages III and IVA, with approximately 36% of local failures despite chemoradiotherapy. In a few studies,the radiomic MRI approach in locally advanced cervical cancers has shown to be prognostic for locoregional recurrence or survival but these models still need to be explored and validated.The EPICOL cohort, a clinical-biological cohort of 136 patients treated with chemoradiotherapy for locally advanced cervical cancer at the Montpellier Cancer Institute or Nîmes University Hospital, will be used to develop a predictive model of response to chemoradiotherapy based on radiomic data from pelvic MRIs before and after treatment.

Detailed Description

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Cervical cancer is an invasive cancer that develops from the squamous epithelium of the cervix. Worldwide, cervical cancer is the fourth most common cancer in women, with approximately 604,000 new cases in 2020.Treatment for locally advanced cervical cancer (FIGO stage IB3 to IVA) is based on a combination of radiotherapy and chemotherapy (cisplatin 40 mg/m2 x5 or 6 or carboplatin area under the curve 2 if cisplatin is contraindicated). Responses to concomitant chemoradiotherapy remain highly heterogeneous from one woman to another, and predicting the response to these treatments would allow early consideration of alternative therapies for patients identified as less responsive to standard treatments. Indeed, 5-year recurrence-free survival is approximately 79% for stages IB and IIA and 59% for stages III and IVA, with approximately 36% of local failures despite chemoradiotherapy.

The radiomic MRI approach in locally advanced cervical cancers has shown in a few studies to be prognostic for locoregional recurrence or survival. However, these models still need to be explored and validated before they can be implemented in routine clinical practice.

The EPICOL cohort is a clinical-biological cohort of 136 patients treated with chemoradiotherapy for locally advanced cervical cancer at the Montpellier Cancer Institute or Nîmes University Hospital.

We propose to develop a predictive model of response to chemoradiotherapy based on radiomic data from pelvic MRIs before and after treatment from the EPICOL cohort.

Conditions

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Uterine Cervical Neoplasms Cervical Cancer by FIGO Stage 2018

Keywords

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cancer cervix survival modeling radiomic models

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* 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.

Exclusion Criteria

* Patients under judicial protection, guardianship, or curatorship
Minimum Eligible Age

18 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

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Centre Hospitalier Universitaire de Nīmes

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Nimes University Hospital

Nîmes, Gard, France

Site Status RECRUITING

Countries

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France

Central Contacts

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Frédéric FITENI, Professor

Role: CONTACT

Phone: +334.34.03.46.69

Email: [email protected]

Anissa MEGZARI

Role: CONTACT

Phone: 0466684236

Email: [email protected]

References

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Pang SS, Murphy M, Markham MJ. Current Management of Locally Advanced and Metastatic Cervical Cancer in the United States. JCO Oncol Pract. 2022 Jun;18(6):417-422. doi: 10.1200/OP.21.00795. Epub 2022 Mar 14.

Reference Type BACKGROUND
PMID: 35286157 (View on PubMed)

Zola P, Fuso L, Mazzola S, Piovano E, Perotto S, Gadducci A, Galletto L, Landoni F, Maggino T, Raspagliesi F, Sartori E, Scambia G. Could follow-up different modalities play a role in asymptomatic cervical cancer relapses diagnosis? An Italian multicenter retrospective analysis. Gynecol Oncol. 2007 Oct;107(1 Suppl 1):S150-4. doi: 10.1016/j.ygyno.2007.07.028. Epub 2007 Sep 14.

Reference Type BACKGROUND
PMID: 17868785 (View on PubMed)

Autorino R, Gui B, Panza G, Boldrini L, Cusumano D, Russo L, Nardangeli A, Persiani S, Campitelli M, Ferrandina G, Macchia G, Valentini V, Gambacorta MA, Manfredi R. Radiomics-based prediction of two-year clinical outcome in locally advanced cervical cancer patients undergoing neoadjuvant chemoradiotherapy. Radiol Med. 2022 May;127(5):498-506. doi: 10.1007/s11547-022-01482-9. Epub 2022 Mar 24.

Reference Type BACKGROUND
PMID: 35325372 (View on PubMed)

Bizzarri N, Russo L, Dolciami M, Zormpas-Petridis K, Boldrini L, Querleu D, Ferrandina G, Pedone Anchora L, Gui B, Sala E, Scambia G. Radiomics systematic review in cervical cancer: gynecological oncologists' perspective. Int J Gynecol Cancer. 2023 Oct 2;33(10):1522-1541. doi: 10.1136/ijgc-2023-004589.

Reference Type BACKGROUND
PMID: 37714669 (View on PubMed)

Halle MK, Hodneland E, Wagner-Larsen KS, Lura NG, Fasmer KE, Berg HF, Stokowy T, Srivastava A, Forsse D, Hoivik EA, Woie K, Bertelsen BI, Krakstad C, Haldorsen IS. Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer. Sci Rep. 2024 May 17;14(1):11339. doi: 10.1038/s41598-024-61271-4.

Reference Type BACKGROUND
PMID: 38760387 (View on PubMed)

Li H, Zhu M, Jian L, Bi F, Zhang X, Fang C, Wang Y, Wang J, Wu N, Yu X. Radiomic Score as a Potential Imaging Biomarker for Predicting Survival in Patients With Cervical Cancer. Front Oncol. 2021 Aug 16;11:706043. doi: 10.3389/fonc.2021.706043. eCollection 2021.

Reference Type BACKGROUND
PMID: 34485139 (View on PubMed)

Other Identifiers

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SIRIC/2024/FF01

Identifier Type: -

Identifier Source: org_study_id