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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.
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.
The aim is to develop a predictive model of response to chemoradiotherapy based on radiomic data from pelvic MRIs before and after treatment from the EPICOL cohort.
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| Measure | Description | Time Frame |
|---|---|---|
| Prognostic role of a magnetic resonance imaging radiomic model on progression-free survival in patients treated for locally advanced cervical cancer. | Time from diagnosis to death from any cause or progression (according to RECIST v1.1 criteria) at 24 months of follow-up. | Month 24 |
| Measure | Description | Time Frame |
|---|---|---|
| Prognostic role of an magnetic resonance imaging radiomic model on overall survival in patients treated for locally advanced cervical cancer. | Time between treatment initiation and death from any cause at 24 months of follow-up. | Month 24 |
| Correlation between the radiomic magnetic imaging radiomic model and Programmed cell Death protein 1 (PD-L1) expression. |
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Inclusion Criteria:
Exclusion Criteria:
Human beings who possess a uterus with a cervix.
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For this study, data from 120 patients for whom we have MRI data from the EPICOL cohort (136 patients included) will be used.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Frédéric FITENI, Professor | Contact | +334.34.03.46.69 | frederic.fiteni@chu-nimes.fr | |
| Anissa MEGZARI | Contact | 0466684236 | drc@chu-nimes.fr |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Nimes University Hospital | Recruiting | Nîmes | Gard | 30029 | France |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35286157 | Background | 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. | |
| 17868785 | Background | 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. |
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| ID | Term |
|---|---|
| D002583 | Uterine Cervical Neoplasms |
| D009369 | Neoplasms |
| ID | Term |
|---|---|
| D014594 | Uterine Neoplasms |
| D005833 | Genital Neoplasms, Female |
| D014565 | Urogenital Neoplasms |
| D009371 | Neoplasms by Site |
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Collection of Programmed cell Death protein 1 (PD-L1) expression levels from biopsies from the EPICOL cohort. |
| Month 24 |
| Correlation between the radiomic magnetic resonance imaging model and tumor-infiltrating lymphocytes (TILs). | Collection of tumor-infiltrating lymphocyte (TIL) expression levels in biopsies from the EPICOL cohort. | Month 24 |
| 35325372 | Background | 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. |
| 37714669 | Background | 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. |
| 38760387 | Background | 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. |
| 34485139 | Background | 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. |
| D002577 |
| Uterine Cervical Diseases |
| D014591 | Uterine Diseases |
| D005831 | Genital Diseases, Female |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D000091662 | Genital Diseases |