ArticleAmerican journal of translational research2026
Clinical significance of MIF in predicting lymph node metastasis and immune-inflammatory characteristics in endometrial cancer: a retrospective study of 361 patients.
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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Abstract
backgroundMacrophage migration inhibitory factor (MIF) contributes to the progression of diverse malignancies. However, its expression and relation with systemic immune-inflammatory characteristics in predicting lymph node metastasis (LNM) in endometrial cancer (EC) remains unclear.
objectiveThe current study evaluates the association between MIF-related inflammatory features and LNM, and establishes a preoperative model for predicting LNM in EC.
methodsThe current study enrolled 361 EC patients, and their clinical characteristics, hematologic parameters, tumor biomarkers, inflammatory indices, imaging features, and preoperative pathological findings were collected. MIF expression and relevant immune-inflammatory indicators were analyzed for their correlations with LNM. Independent predictors were identified using multivariable logistic regression. Model performance was assessed using ROC curves, calibration plots, and decision curve analysis (DCA).
resultsAmong the 361 patients, LNM occurred in 51 patients (15.8%). Patients with LNM had significantly higher levels of CA125, HE4, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and larger tumor diameter. Myometrial invasion ≥1/2, cervical stromal involvement, and non-endometrioid histology were all significantly more frequent in the LNM group. Multivariate logistic regression identified high MIF expression, SII (per 100 units), myometrial invasion ≥50%, LVSI, and high-grade histology as independent predictors of LNM. The nomogram demonstrated excellent discriminatory performance, good calibration, and favorable clinical utility on decision curve analysis.
conclusionTumor MIF expression is an independent predictor of LNM in EC. Incorporation of MIF into a clinically grounded prediction model may enhance preoperative risk stratification of EC.
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