ENDORISK-2: A personalized Bayesian network for preoperative risk stratification in endometrial cancer, integrating molecular classification and preoperative myometrial invasion assessment

Background ENDORISK is a Bayesian network that can assist in preoperative risk estimation of lymph node metastasis (LNM) risk in endometrial cancer (EC) with consistent performance in external validations. To reflect state of the art care, ENDORISK was optimized by integrating molecular classificati...

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Detalles Bibliográficos
Autores: Lombaers, Marike, Reijnen, Casper, Sprik, Ally, Bretová, Petra, Grube, Marcel, Vrede, Stephanie, Berg, Hege, Asberger, Jasmin, Colas, Eva, Hausnerova, Jitka, Huvila, Jutta, Gil Moreno, Antonio, Matias-Guiu, Xavier, Simons, Michiel, Snijders, Marc, Visser, Nicole, Kommoss, Stefan, Weinberger, Vit, Amant, Frederic, Bronsert, Peter, Haldorsen, Ingfrid, Koskas, Martin, Krakstad, Camilla, Küsters Vandevelde, Heidi, Mancebo, Gemma, van der Putten, Louis, de la Calle, Irene, Lucas, Peter, Hommersom, Arjen, Pijnenborg, Johanna
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10459.1/469209
Acceso en línea:https://doi.org/10.1016/j.ejca.2025.116058
https://hdl.handle.net/10459.1/469209
http://hdl.handle.net/10459.1/469209
Access Level:acceso abierto
Palabra clave:Bayesian network
Endometrial cancer
Lymph node metastasis
Molecular classification
Myometrial invasion
Risk estimation
Descripción
Sumario:Background ENDORISK is a Bayesian network that can assist in preoperative risk estimation of lymph node metastasis (LNM) risk in endometrial cancer (EC) with consistent performance in external validations. To reflect state of the art care, ENDORISK was optimized by integrating molecular classification and preoperative assessment of myometrial invasion (MI). Methods Variables for POLE, MSI, and preoperative assessment of MI, either by expert transvaginal ultrasound or pelvic magnetic resonance imaging (MRI), were added to develop ENDORISK-2. The p53 biomarker, part of the molecular classification, was already included in ENDORISK. External validation of ENDORISK-2 for LNM prediction was performed in two independent cohorts from: Brno (CZ), (n = 581) and Tübingen (DE), (n = 247). Findings ENDORISK-2 yielded AUCs of 0·85 (95 % CI 0·80–0·90) (CZ) and 0·86 (95 % CI 0·77–0·96) (DE) for predicting LNM. In patients with low-grade histology, 83 % (CZ) and 89 % (DE) were estimated having less than 10 % risk of LNM, with false negative rates (FNR) of 4·3 % (CZ) and 2·2 % (DE). The previously defined set of minimally required variables, i.e.: preoperative tumor grade, three of the four immunohistochemical (IHC) markers, and one clinical marker, could be interchanged with the new variables, with comparable validation metrics, including AUC values of 0·79–0·87 for LNM prediction. Interpretation. Incorporation of molecular data and preoperative MI improved the flexibility of ENDORISK with comparable diagnostic accuracy for estimating LNM as when based on low-cost immunohistochemical biomarkers. In addition, the high diagnostic accuracy in patients with low-grade EC demonstrates how ENDORISK-2 could aid clinicians in identifying patients in whom surgical lymph node assessment may safely be omitted. These results underline its power for clinical use in both high and low resource countries.

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