SUCCOR Risk: Design and Validation of a Recurrence Prediction Index for Early-Stage Cervical Cancer.

Female; Humans; Hysterectomy/methods; Prognosis; Recurrence; Retrospective Studies; Risk Assessment; Neoplasm Recurrence, Local/diagnosis; Neoplasm Recurrence, Local/pathology; Neoplasm Staging; Uterine Cervical Neoplasms/diagnosis; Uterine Cervical Neoplasms/pathology; Uterine Cervical Neoplasms/surgery; Hysterectomy; Neoplasm Recurrence, Local; Uterine Cervical Neoplasms; Surgery; Oncology

Abstract :

[en] [en] OBJECTIVE: Based on the SUCCOR study database, our primary objective was to identify the independent clinical pathological variables associated with the risk of relapse in patients with stage IB1 cervical cancer who underwent a radical hysterectomy. Our secondary goal was to design and validate a risk predictive index (RPI) for classifying patients depending on the risk of recurrence. METHODS: Overall, 1116 women were included from January 2013 to December 2014. We randomly divided our sample into two cohorts: discovery and validation cohorts. The test group was used to identify the independent variables associated with relapse, and with these variables, we designed our RPI. The index was applied to calculate a relapse risk score for each participant in the validation group. RESULTS: A previous cone biopsy was the most significant independent variable that lowered the rate of relapse (odds ratio [OR] 0.31, 95% confidence interval [CI] 0.17-0.60). Additionally, patients with a tumor diameter >2 cm on preoperative imaging assessment (OR 2.15, 95% CI 1.33-3.5) and operated by the minimally invasive approach (OR 1.61, 95% CI 1.00-2.57) were more likely to have a recurrence. Based on these findings, patients in the validation cohort were classified according to the RPI of low, medium, or high risk of relapse, with rates of 3.4%, 9.8%, and 21.3% observed in each group, respectively. With a median follow-up of 58 months, the 5-year disease-free survival rates were 97.2% for the low-risk group, 88.0% for the medium-risk group, and 80.5% for the high-risk group (p < 0.001). CONCLUSION: Previous conization to radical hysterectomy was the most powerful protective variable of relapse. Our risk predictor index was validated to identify patients at risk of recurrence.

Disciplines :

Oncology

Author, co-author :

Manzour, Nabil ; Department of Gynecology, Clinica Universidad de Navarra, Pamplona, Spain

Chiva, Luis ; Department of Gynecology, Clinica Universidad de Navarra, Pamplona, Spain. lchiva@unav.es

Chacón, Enrique ; Department of Gynecology, Clinica Universidad de Navarra, Pamplona, Spain

Martin-Calvo, Nerea ; Department of Preventive Medicine and Public Health, Universidad de Navarra, Pamplona, Spain

Boria, Felix ; Department of Gynecology, Clínica Universidad de Navarra, Madrid, Spain

Minguez, José A ; Department of Gynecology, Clinica Universidad de Navarra, Pamplona, Spain

Alcazar, Juan L ; Department of Gynecology, Clinica Universidad de Navarra, Pamplona, Spain

SUCCOR Study Group

Other collaborator :

Goffin, Frédéric ; Centre Hospitalier Universitaire de Liège - CHU > > Service de gynécologie-obstétrique (CHR) ; Member of the Succor Study Group

Language :

English

Title :

SUCCOR Risk: Design and Validation of a Recurrence Prediction Index for Early-Stage Cervical Cancer.

Publication date :

August 2022

Journal title :

Annals of Surgical Oncology

ISSN :

1068-9265

eISSN :

1534-4681

Publisher :

Springer Science and Business Media Deutschland GmbH, United States

Volume :

Issue :

Pages :

4819 - 4829

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://link.springer.com/content/pdf/10.1245/s10434-022-11671-5.pdf

Funders :

UNAV - Universidad de Navarra

Funding text :

The authors thank all members of the Gynecologic Oncologic Team at the Clínica Universidad de Navarra. They would especially like to thank Dr. Matías Jurado, Dr. Antonio Gil, Dr. Antonio González-Martín, Yessica Rodríguez, MD, and Salim Manzour for their invaluable support and help in the elaboration of this project. In addition, the authors would like to thank the ESGO and its members—without them it would not have been possible to carry out the SUCCOR project and this subsequent study. On behalf of the SUCCOR study Group : Vanna Zanagnolo, Denis Querleu, Mihai Căpîlna, Anna Fagotti, Ali Kucukmetin, Constantijne Mom, Galina Chakalova, Shamistan Aliyev, Mario Malzoni, Fabrice Narducci, Octavio Arencibia, Francesci Raspagliesi, Tayfun Toptas, David Cibula, Dilyara Kaidarova, Mehmet Meydanli, Mariana Tavares, Dmytro Golub, Anna Perrone, Robert Poka, Dimitrios Tsolakidis, Goran Vujić, Marcin Jedryka, Petra Zusterzeel, Jogchum Beltman, Frédéric Goffin, Dimitros Haidopoulos, Herman Haller, Robert Jach, Iryna Yezhova, Igor Berlev, Margarida Bernardino, Rasiah Bharathan, Maximilian Lanner, Vladyslav Sukhin, Jean G. Feron, Robert Fruscio, Kersti Kukk, Jordi Ponce, Nabil Abdalla, Özgür Akbayir, Sedat Akgöl, Elif Aksahin, Shamistan Aliyev, Maria Alonso-Espias, Igor Aluloski, Claudia Andrade, Nikola Badzakov, Rosa Barrachina, Giorgio Bogani, Eduard-Aexandru Bonci, Hélène Bonsang-Kitzis,Cosima Brucker, Laura Cárdenas, Andrea Casajuana, Pere Cavalle, Jorge Cea, Benito Chiofalo, Gloria Cordeiro, Pluvio Coronado, Maria Cuadra, Javier Díez, Teresa Diniz da Costa, Santiago Domingo, Lukas Dostalek, Fuat Demirkiran, Diego Erasun, Mathias Fehr, Sergi Fernandez-Gonzalez, Annamaria Ferrero, Soledad Fidalgo, Gabriel Fiol, Khadra Galaal, José García, Gerhard Gebauer, Fabio Ghezzi, Juan Gilabert, Nana Gomes, Elisabete Gonçalves, Virginia Gonzalez, Frederic Grandjean, Miriam Guijarro, Frédéric Guyon, Jolien Haesen, Gines Hernandez- Cortes, Sofía Herrero, Imre Pete, Ioannis Kalogiannidis, Erbil Karaman, Andreas Kavallaris, Lukasz Klasa, Ioannis Kotsopoulos, Stefan Kovachev, Meelis Leht, Arantxa Lekuona, Mathieu Luyckx, Michael Mallmann, Gemma Mancebo, Aljosa Mandic, Tiermes Marina, Victor Martin, María Belén Martín- Salamanca, Alejandra Martinez, Gesine Meili, Gustavo Mendinhos, Liliana Mereu, Milena Mitrovic, Sara Morales, Enrique Moratalla, Bibiana Morillas, Eva Myriokefalitaki, Maja PakižImre, Stamatios Petousis, Laurentiu Pirtea, Natalia Povolotskaya, Sonia Prader, Alfonso Quesada, Mikulás Redecha, Fernando Roldan, Philip Rolland, Reeli Saaron, Cosmin-Paul Sarac, Jens-Peter Scharf, Špela Smrkolj, Rita Sousa, Artem Stepanyan, Vladimír Študent, Carmen Tauste, Hans Trum, Taner Turan, Manuela Undurraga, Arno Uppin, Alicia Vázquez, Ignace Vergote, George Vorgias and Ignacio Zapardiel.

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since 25 November 2023

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