Lou Yaochen, Jiang Feng, Du Yan, Guan Jun
Department of Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China.
Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China.
Front Oncol. 2024 Sep 6;14:1442127. doi: 10.3389/fonc.2024.1442127. eCollection 2024.
To establish a nomogram based on presurgical predictors of concurrent endometrial cancer (EC) for patients diagnosed with endometrial atypical hyperplasia before definitive surgery (preoperative-EAH) to improve the risk stratification and clinical application.
Preoperative-EAH patients who underwent hysterectomy in a tertiary hospital from January 2020 to December 2022 were retrospectively analyzed. Independent predictors from the multivariate logistic regression model were used to establish a nomogram, and bootstrap resampling was used for internal validation.
Of 370 preoperative-EAH patients, 23.4% were diagnosed with EC after definitive surgery (final-EC). Multivariate analyses found three independent predictors of final EC: human epididymis protein 4 (HE4) ≥43.50 pmol/L [odds ratio (OR) = 3.70; 95% confidence intervals (CI) = 2.06-6.67], body mass index (BMI) ≥ 28 kg/m (OR = 2.05; 95% CI = 1.14-3.69), and postmenopausal status, particularly at postmenopausal time ≥5 years (OR = 5.84, 95% CI = 2.51-13.55), which were used to establish a nomogram model. The bootstrap-corrected C-index of the nomogram was 0.733 (95% CI = 0.68-0.79), which was significantly higher than that of each individual factor. The calibration curve and decision curve showed good consistency and clinical net benefit of the model. At the maximum Youden index, 49.4% (43/87) of women in the high-risk group defined by nomogram had concurrent EC, versus 16.6% in the low-risk group (< 0.001).
The nomogram based on HE4, menopausal status, and BMI was found with an improved predictive value to stratify preoperative-EAH patients at high risk of concurrent EC for better clinical management.
为确诊为子宫内膜非典型增生且即将接受确定性手术（术前子宫内膜非典型增生，preoperative-EAH）的患者建立基于同期子宫内膜癌（EC）术前预测指标的列线图，以改善风险分层和临床应用。
回顾性分析2020年1月至2022年12月在一家三级医院接受子宫切除术的术前-EAH患者。使用多因素逻辑回归模型中的独立预测指标建立列线图，并采用自抽样法进行内部验证。
在370例术前-EAH患者中，23.4%在确定性手术后被诊断为EC（最终EC）。多因素分析发现最终EC的三个独立预测指标：人附睾蛋白4（HE4）≥43.50 pmol/L[比值比（OR）=3.70；95%置信区间（CI）=2.06-6.67]、体重指数（BMI）≥28 kg/m²（OR = 2.05；95% CI = 1.14-3.69）以及绝经状态，尤其是绝经时间≥5年（OR = 5.84，95% CI = 2.51-13.55），并据此建立列线图模型。列线图的自抽样校正C指数为0.733（95% CI = 0.68-0.79），显著高于各单一因素。校准曲线和决策曲线显示该模型具有良好的一致性和临床净效益。在最大约登指数时，列线图定义的高危组中49.4%（43/87）的女性患有同期EC，而低危组为16.6%（P<0.001）。
基于HE4、绝经状态和BMI的列线图对术前-EAH患者同期EC的高危分层具有更高的预测价值，有助于更好地进行临床管理。
