ArticleCancer medicine2023
Construction of refined staging classification systems integrating FIGO/T-categories and corpus uterine invasion for non-metastatic cervical cancer.
Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Machine learning and deep learning to improve overall survival prediction in cervical cancer patients.Translational cancer research · 2025Article
- Article
- The silent spread: exploring diverse metastatic pathways in high-grade serous ovarian cancer.Frontiers in medicine · 2025Review
- Construction of refined staging classification systems integrating FIGO/T-categories and corpus uterine invasion for non-metastatic cervical cancer.Cancer medicine · 2023Article
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10 authors.
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Abstract
backgroundTo investigate the prognostic value of corpus uterine invasion (CUI) in cervical cancer (CC), and determine the necessity to incorporate it for staging.
methodsA total of 809 cases of biopsy-proven, non-metastatic CC were identified from an academic cancer center. Recursive partitioning analysis (RPA) method was used to develop the refined staging systems with respect to overall survival (OS). Internal validation was performed by using calibration curve with 1000 bootstrap resampling. Performances of the RPA-refined stages were compared against the conventional FIGO 2018 and 9th edition TNM-stage classifications by the receiver operating characteristic curve (ROC) and decision curve analysis (DCA).
resultsWe identified that CUI was independently prognostic for death and relapse in our cohort. RPA modeling using a two-tiered stratification by CUI (positive and negative) and FIGO/T-categories divided CC into three risk groupings (FIGO I'-III'/T1'-3'), with 5-year OS of 90.8%, 82.1%, and 68.5% for proposed FIGO stage I'-III', respectively (p ≤ 0.003 for all pairwise comparisons), and 89.7%, 78.8%, and 68.0% for proposed T1'-3', respectively (p < 0.001 for all pairwise comparisons). The RPA-refined staging systems were well validated with RPA-predicted OS rates showed optimal agreement with actual observed survivals. Additionally, the RPA-refined stages outperformed the conventional FIGO/TNM-stage with significantly higher accuracy of survival prediction (AUC: RPA-FIGO vs. FIGO, 0.663 [95% CI 0.629-0.695] vs. 0.638 [0.604-0.671], p = 0.047; RPA-T vs. T, 0.661 [0.627-0.694] vs. 0.627 [0.592-0.660], p = 0.036).
conclusionCUI affects the survival outcomes in patients with CC. Disease extended to corpus uterine should be classified as stage III/T3.
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