ArticleAnnals of surgical oncology2026
Nomogram Based on Pan-Immune Inflammation Value and Clinicopathological Parameters for Predicting the Recurrence of Endometrial Cancer and Providing Postoperative Prognostic Management.
Article in Annals of surgical oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Association of Preoperative Pan-Immune-Inflammation Value with Adverse Pathology and Oncological Outcomes Following Radical Prostatectomy: A Single-Center Retrospective Study.International journal of medical sciences · 2026Article
- Pretreatment Pan-Immune-Inflammation Value and Corrected Prognostic Nutritional Index for 24-Month Recurrence Risk Stratification After Neoadjuvant Chemotherapy and Surgery in Stage III Endometrial Cancer.International journal of women's health · 2026Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundEvaluation of preoperative pan-immune inflammation value (PIV) combined with clinicopathological parameters in predicting postoperative recurrence of endometrial cancer (EC) and development of a prognostic model for optimized recurrence risk assessment.
methodsThis retrospective study analyzed a training cohort of 1,275 patients and a validation cohort of 656 patients. Prognostic factors associated with recurrence-free survival (RFS) were identified through univariate and multivariate Cox regression analyses, and a nomogram model was subsequently constructed. The discriminative ability and accuracy of the model were evaluated by using the C-index, area under the curve (AUC), and calibration curve. Patients were stratified into low-risk and high-risk groups based on nomogram, and the clinical utility of the model was validated through Kaplan-Meier survival analysis, providing a robust foundation for clinical decision-making.
resultsCox regression analysis revealed that age (P = 0.012), International Federation of Gynecology and Obstetrics (FIGO) stage (P < 0.001), Ca125 (P = 0.012), lymphovascular space invasion (LVSI) (P = 0.007), myometrial invasion (P < 0.001), histological type (P < 0.001), p53 expression (P = 0.001), adjuvant therapy (P < 0.001), and PIV (P < 0.001) were independent prognostic factors for RFS in EC. We developed a predictive model integrating clinicopathological parameters and PIV, which demonstrated superior performance in predicting 1-, 3-, and 5-year RFS compared with single-indicator models and other conventional models.
conclusionsThis nomogram demonstrates high predictive accuracy for RFS in EC patients, offering a robust tool to guide personalized therapeutic strategies in clinical practice.
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