Bretová Petra, Ndukwe Munachiso Iheme, Laco Jan, Vošmiková Hana, Rešlová Taťána, Pohanková Denisa, Balcarová Klára, Haviger Jiří, Havigerová Jana Marie, Sirák Igor
Department of Obstetrics and Gynecology, Charles University, Faculty of Medicine in Hradec Kralove, Hradec Kralove, Czech Republic.
Department of Oncology and Radiotherapy, University Hospital Hradec Kralove, Hradec Kralove, Czech Republic.
BMC Cancer. 2025 Aug 11;25(1):1302. doi: 10.1186/s12885-025-14741-5.
The study aimed to evaluate the impact of integrating molecular classification with imaging-based preoperative staging on risk stratification prediction in endometrial cancer patients in accordance with ESGO/ESTRO/ESP (European Society of Gynaecological Oncology/European Society for Radiotherapy and Oncology/European Society of Pathology) 2021 guidelines.
A retrospective cohort of 143 endometrial cancer patients was analyzed to assess changes in preoperative risk stratification after incorporating molecular classification into clinical evaluation. Preoperative clinical staging was primarily based on transvaginal ultrasound imaging. The overall agreement between preoperative risk group estimates (with/without molecular classification) and final postoperative outcomes was assessed using weighted Cohen's Kappa, with bootstrap 95% confidence intervals and quadratic weights.
The addition of molecular classification significantly improved preoperative risk stratification accuracy (from 59.4 to 73.4%), particularly for patients post-operatively classified as high-risk. Kappa values indicated an improvement in overall agreement between preoperative and postoperative risk stratification following the addition of molecular classification, from 0.551 (95% CI: 0.430-0.671) to 0.767 (95% CI: 0.675-0.849). The non-overlapping confidence intervals indicated statistical significance. Preoperative assessment without molecular input tended to underestimate risk stratification. However, 26.6% of patients remained misclassified due to other factors, mostly within the intermediate and high-intermediate risk groups.
Incorporating molecular classification enhances preoperative risk stratification and has the potential to tailor surgical treatment. Further validation through prospective multicentric studies is needed to support our findings.
本研究旨在根据欧洲妇科肿瘤学会/欧洲放射治疗与肿瘤学会/欧洲病理学会（ESGO/ESTRO/ESP）2021年指南，评估将分子分类与基于影像的术前分期相结合对子宫内膜癌患者风险分层预测的影响。
对143例子宫内膜癌患者的回顾性队列进行分析，以评估将分子分类纳入临床评估后术前风险分层的变化。术前临床分期主要基于经阴道超声成像。使用加权科恩kappa系数、自抽样95%置信区间和二次权重评估术前风险组估计（有/无分子分类）与最终术后结果之间的总体一致性。
增加分子分类显著提高了术前风险分层的准确性（从59.4%提高到73.4%），尤其是对于术后被分类为高危的患者。kappa值表明，增加分子分类后，术前和术后风险分层之间的总体一致性有所改善，从0.551（95%CI：0.430-0.671）提高到0.767（95%CI：0.675-0.849）。不重叠的置信区间表明具有统计学意义。没有分子输入的术前评估往往低估风险分层。然而，26.6%的患者由于其他因素仍被错误分类，主要在中风险和高中风险组内。
纳入分子分类可增强术前风险分层，并有可能调整手术治疗方案。需要通过前瞻性多中心研究进行进一步验证，以支持我们的研究结果。
