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

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/00216224:14110/25:00142810

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30204 - Oncology

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

European Journal of Cancer

ISSN

0959-8049

e-ISSN

1879-0852

Svazek periodika

231

Číslo periodika v rámci svazku

2025

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

10

Strana od-do

116058

Kód UT WoS článku

001609063800001

EID výsledku v databázi Scopus

2-s2.0-105020939885