ENDORISK-2: A personalized Bayesian network for preoperative risk stratification in endometrial cancer, integrating molecular classification and preoperative myometrial invasion assessment
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F65269705%3A_____%2F25%3A00082875" target="_blank" >RIV/65269705:_____/25:00082875 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14110/25:00142810
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S095980492500944X" target="_blank" >https://www.sciencedirect.com/science/article/pii/S095980492500944X</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ejca.2025.116058" target="_blank" >10.1016/j.ejca.2025.116058</a>
Alternative languages
Result language
angličtina
Original language name
ENDORISK-2: A personalized Bayesian network for preoperative risk stratification in endometrial cancer, integrating molecular classification and preoperative myometrial invasion assessment
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30204 - Oncology
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
European Journal of Cancer
ISSN
0959-8049
e-ISSN
1879-0852
Volume of the periodical
231
Issue of the periodical within the volume
2025
Country of publishing house
GB - UNITED KINGDOM
Number of pages
10
Pages from-to
116058
UT code for WoS article
001609063800001
EID of the result in the Scopus database
2-s2.0-105020939885