Construction and validation of a nomogram prediction model for risk stratification of early-stage endometrial cancer

ZHU Yuanyi; FANG Yongkun; GUAN Jian; XU Li; ZHENG Haoyu; XIANG Ke; ZHANG Wei

doi:10.3969/j.issn.1004-3594.2026.08.002

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Medical Journal of the Chinese People Armed Police Forces ›› 2026, Vol. 37 ›› Issue (8) : 655-663. DOI: 10.3969/j.issn.1004-3594.2026.08.002

ORIGINAL ARTICLES

Construction and validation of a nomogram prediction model for risk stratification of early-stage endometrial cancer

ZHU Yuanyi, FANG Yongkun, GUAN Jian, XU Li, ZHENG Haoyu, XIANG Ke, ZHANG Wei

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Abstract

Objective To investigate the clinical value of a nomogram model based on clinical indicators and multi-sequence MRI features in predicting the risk stratification of early-stage endometrial cancer(EC). Methods A retrospective analysis was conducted on the clinical and MRI data of 150 patients diagnosed with early-stage EC in Sichuan Provincial Corps Hospital of Chinese People's Armed Police Force from July 2014 to July 2025. The patients were randomly divided into a training set and a test one at a 7:3 ratio. The differences in clinical indicators and MRI features between the low-risk and non-low-risk groups in the training set were illustrated. Logistic regression analysis was employed on the variables in the training set to identify the predictors, which were then used to construct a nomogram model. The predictive performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. Results A total of 105 patients were assigned to the training set, and 45 to the test one. Tumor location, anteroposterior diameter, uterine corner involvement, relative ADC value ratio of tumor to myometrium, arterial phase enhancement zone between the intima and muscularis, and arterial phase lesion edge enhancement were identified as predictors for non-low-risk early-stage EC in the training set. The area under the ROC curve (AUC) for the nomogram model constructed from these six factors was 0.979 (0.957,1.000) for the training set and 0.934 (0.867,1.000) for the test one respectively. The calibration curves demonstrated good fit in both sets, and the decision curve analysis indicated favorable clinical utility of the nomogram. Conclusions The nomogram constructed using clinical indicators and MRI features exhibits high accuracy in predicting the risk stratification of early-stage EC and holds significant value in guiding clinical treatment decisions.

Key words

endometrial carcinoma / magnetic resonance imaging / nomogram / prediction / level of risk

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ZHU Yuanyi, FANG Yongkun, GUAN Jian, XU Li, ZHENG Haoyu, XIANG Ke, ZHANG Wei. Construction and validation of a nomogram prediction model for risk stratification of early-stage endometrial cancer[J]. Medical Journal of the Chinese People Armed Police Forces. 2026, 37(8): 655-663 https://doi.org/10.3969/j.issn.1004-3594.2026.08.002

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