Estimation risk of lymph nodal invasion in patients with early-stage cervical cancer: Cervical cancer application

Frontiers in Oncology

Oncology

Vincent Balaya¹  Benedetta Guani²  Patrice Mathevet³  Anis Feki⁴  Thomas Gaillard⁵  Fabrice Lecuru⁶  Xavier Paoletti⁷  Ly-Ann Teo-Fortin⁸  Marie Plante⁹ 

[1] Department of Gynecology and Obstetrics, FOCH Hospital, Suresnes, France;Department of Gynecology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland;Department of Gynecology, Hopital Fribourgeois (HFR), Fribourg, Switzerland;Faculty of Biology and Medicine, University of Fribourg, Fribourg, Switzerland;Department of Gynecology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland;Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland;Department of Gynecology, Hopital Fribourgeois (HFR), Fribourg, Switzerland;Faculty of Biology and Medicine, University of Fribourg, Fribourg, Switzerland;Department of Gynecology, Institut Curie, Paris, France;Department of Gynecology, Institut Curie, Paris, France;Department of Medicine, University of Paris, Paris, France;Department of Statistics, Institut Curie, Paris, France;Faculty of Medicine, Laval University of Quebec, Quebec, QC, Canada;Faculty of Medicine, Laval University of Quebec, Quebec, QC, Canada;Division of Gynecologic Oncology, Centre Hospitalier Universitaire (CHU) de Quebec, L’Hôtel-Dieu de Quebec, Quebec, QC, Canada;

关键词: cervical cancer;    lymph nodal status;    early-stage cervical cancer;    cervical cancer web application;    gynecological cancer;   

DOI  :  10.3389/fonc.2022.935628

 received in 2022-05-04, accepted in 2022-07-12,  发布年份 2022

来源: Frontiers

【 摘 要 】

IntroductionLymph node status is a major prognostic factor in early-stage cervical cancer. Predicting the risk of lymph node metastasis is essential for optimal therapeutic management. The aim of the study was to develop a web-based application to predict the risk of lymph node metastasis in patients with early-stage (IA1 with positive lymph vascular space invasion, IA2 and IB1) cervical cancer.Materials and methodsWe performed a secondary analysis of data from two prospective multicenter trials, Senticol 1 and 2 pooled together in the training dataset. The histological risk factors were included in a multivariate logistic regression model in order to determine the most suitable prediction model. An internal validation of the chosen prediction model was then carried out by a cross validation of the ‘leave one out cross validation’ type. The prediction model was implemented in an interactive online application of the ‘Shinyapp’ type. Finally, an external validation was performed with a retrospective cohort from L’Hôtel-Dieu de Québec in Canada.ResultsThree hundred twenty-one patients participating in Senticol 1 and 2 were included in our training analysis. Among these patients, 280 did not present lymph node invasion (87.2%), 13 presented isolated tumor cells (4%), 11 presented micrometastases (3.4%) and 17 macrometastases (5.3%). Tumor size, presence of lymph-vascular space invasion and stromal invasion were included in the prediction model. The Receiver Operating Characteristic (ROC) Curve from this model had an area under the curve (AUC) of 0.79 (95% CI [0.69– 0.90]). The AUC from the cross validation was 0.65. The external validation on the Canadian cohort confirmed a good discrimination of the model with an AUC of 0.83.DiscussionThis is the first study of a prediction score for lymph node involvement in early-stage cervical cancer that includes internal and external validation. The web application is a simple, practical, and modern method of using this prediction score to assist in clinical management.

【 授权许可】

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Copyright © 2022 Guani, Gaillard, Teo-Fortin, Balaya, Feki, Paoletti, Mathevet, Plante and Lecuru