Evidence map›Paper›PMID 42630439›Full record

ArticleAmerican journal of translational research2026

Predictive value of deep myometrial invasion for lymph node metastasis in low-grade endometrioid carcinoma and its implications for surgical decision-making.

Li Zhao, Yanhua Zhang, Xiaowen Feng, Jia Wang, Qijing Wang, Shuai Li, Tao Zhang, Ruijin Wu

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Article in American journal of translational research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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8 authors.

Li ZhaoDepartment of Gynecology, Women's Hospital School of Medicine Zhejiang University Hangzhou 310006, Zhejiang, China.
Yanhua ZhangDepartment of Gynecology, Women's Hospital School of Medicine Zhejiang University Hangzhou 310006, Zhejiang, China.
Xiaowen FengSchool of Medicine Zhejiang University Hangzhou 310006, Zhejiang, China.
Jia WangSchool of Medicine Zhejiang University Hangzhou 310006, Zhejiang, China.
Qijing WangDepartment of Gynecology, Women's Hospital School of Medicine Zhejiang University Hangzhou 310006, Zhejiang, China.
Shuai LiDepartment of Laboratory, Women's Hospital School of Medicine Zhejiang University Hangzhou 310006, Zhejiang, China.
Tao ZhangDepartment of Gynecology, Women's Hospital School of Medicine Zhejiang University Hangzhou 310006, Zhejiang, China.
Ruijin WuDepartment of Gynecology, Women's Hospital School of Medicine Zhejiang University Hangzhou 310006, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the predictive value of deep myometrial invasion (DMI) for lymph node metastasis (LNM) in low-grade endometrioid carcinoma (LGEC) and its implications for surgical decision-making.

methodsA retrospective cohort study was conducted on 212 patients with pathologically confirmed LGEC (G1/G2) who underwent surgical treatment at Women's Hospital, School of Medicine, Zhejiang University between January 2018 and December 2023. Clinicopathological variables were analyzed using univariate and multivariate logistic regression to identify independent risk factors for LNM. The predictive performance of DMI and other significant variables was assessed by sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and receiver operating characteristic (ROC) curves. A combined predictive model incorporating all independent factors was developed and internally validated using calibration curves and the Hosmer-Lemeshow test. External validation was performed in an independent cohort of 54 patients.

resultsLNM occurred in 9.4% (20/212) of patients. Multivariate analysis identified DMI ≥50% (OR=3.58, 95% CI: 1.23-10.41, P=0.019), cervical stromal invasion (CSI; OR=5.24, 95% CI: 1.47-18.73, P=0.011), and elevated preoperative CA125 >35 U/ml (OR=4.14, 95% CI: 1.42-12.07, P=0.009) as independent predictors. The combined model achieved a sensitivity of 90% and an NPV of 99% for LNM prediction; external validation yielded an NPV of 97.44%, confirming its robustness for identifying low-risk patients. Patients with DMI were more likely to undergo laparotomy than those with superficial invasion (50.0% vs. 18.3%, P<0.001) and more frequently received postoperative adjuvant therapy (52.1% vs. 12.8%, P<0.001).

conclusionDMI, CSI, and elevated CA125 are independent risk factors for LNM in LGEC. The high sensitivity and NPV of the combined predictive model support a selective lymphadenectomy strategy to avoid overtreatment in low-risk patients, while DMI also informs surgical approach selection and adjuvant therapy decisions.

Indexed as

deep myometrial invasionLow-grade endometrioid carcinomalymph node metastasispredictive valuesurgical decision-making

Identifiers

PMID42630439
PMCPMC13494388

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.