ArticleFrontiers in oncology2023
Increases prognostic value of clinical-pathological nomogram in patients with esophageal squamous cell carcinoma.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Age of onset by temporal and spatial changes and prognostic value for esophageal cancer.Chinese medical journal · 2026Article
- Protective Effect of Glutathione Supplementation On Mouse Ovarian Tissue Vitrification and Autologous Transplantation.Reproductive sciences (Thousand Oaks, Calif.) · 2026Article
- A reciprocal interaction between L-lysine andiMetaOmics · 2025Article
- Interactions between cancer-associated fibroblasts and the extracellular matrix in oesophageal cancer.Matrix biology : journal of the International Society for Matrix Biology · 2025Review
- A dynamic nomogram for predicting abdominal lymph node recurrence in patients with esophageal carcinoma.Scientific reports · 2025Article
- Prognostic value of FDX1, the cuprotosis key gene, and its prediction models across imaging modalities and histology.BMC cancer · 2024Article
- UPP1 promotes lung adenocarcinoma progression through the induction of an immunosuppressive microenvironment.Nature communications · 2024Article
- Prognostic value of immunosuppression scores in patients with esophageal squamous cell carcinoma: a multicenter study.Frontiers in immunology · 2024Article
- Nomogram incorporating potent inflammatory indicators for overall survival estimation of patients with primary oral squamous cell carcinoma.Frontiers in oncology · 2023Article
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Authors and funding
26 authors.
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Abstract
Background: This study was intended to construct a brand new prognostic nomogram after combine clinical and pathological characteristics to increases prognostic value in patients with esophageal squamous cell carcinoma. Methods: A total of 1,634 patients were included. Subsequently, the tumor tissues of all patients were prepared into tissue microarrays. AIPATHWELL software was employed to explore tissue microarrays and calculate the tumor-stroma ratio. X-tile was adopted to find the optimal cut-off value. Univariate and multivariate Cox analyses were used to screen out remarkable characteristics for constructing the nomogram in the total populations. A novel prognostic nomogram with clinical and pathological characteristics was constructed on the basis of the training cohort (n=1,144). What's more performance was validated in the validation cohort (n=490). Clinical-pathological nomogram were assessed by concordance index, time-dependent receiver operating characteristic, calibration curve and decision curve analysis. Results: The patients can divide into two groups with cut-off value of 69.78 for the tumor-stroma ratio. It is noteworthy that the survival difference was noticeable ( Conclusions: As evidently revealed by the research findings, tumor-stroma ratio is an independent prognostic factor in patients with esophageal squamous cell carcinoma. The clinical-pathological nomogram has an incremental value compared TNM stage in predicting overall survival.
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