ArticleBMC cancer2018
Nomograms for predicting risk of locoregional recurrence and distant metastases for esophageal cancer patients after radical esophagectomy.
Article in BMC cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Perineural Invasion Is a Significant Indicator of High Malignant Degree and Poor Prognosis in Esophageal Cancer: A Systematic Review and Meta-Analysis.Frontiers in oncology · 2022Pooled it
- Machine learning models predict overall survival and progression free survival of non-surgical esophageal cancer patients with chemoradiotherapy based on CT image radiomics signatures.Radiation oncology (London, England) · 2022Trial
- Eight-year patient survival following multidisciplinary management for two recurrences of esophageal cancer: case report and literature review.International journal of surgery case reports · 2026Article
- Machine learning combined with CT-based radiomics predicts the prognosis of oesophageal squamous cell carcinoma.Insights into imaging · 2025Article
- CT-radiomics combined with inflammatory indicators for prediction of progression free survival of resectable esophageal squamous cell carcinoma.Scientific reports · 2025Article
- Impact of Lymphatic and Venous Invasion Patterns on Postoperative Prognosis and Distant Metastasis in Esophageal Squamous Cell Carcinoma After Preoperative Chemotherapy.Annals of surgical oncology · 2025Article
- Identification and Validation of MYADM as a Novel Prognostic Marker Related to EMT in ESCC.Journal of Cancer · 2024Article
- Microscopic venous invasion is a predictor of prognosis in patients with esophageal squamous cell carcinoma undergoing ineffective neoadjuvant chemotherapy and surgery.Esophagus : official journal of the Japan Esophageal Society · 2023Article
- A new prognostic model of esophageal squamous cell carcinoma based on Cloud-least squares support vector machine.Journal of thoracic disease · 2023Article
- Review
- The role of vascular invasion and lymphatic invasion in predicting recurrent thoracic oesophageal squamous cell carcinoma.World journal of surgical oncology · 2022Article
- A Prognostic Model Based on mRNA Expression Analysis of Esophageal Squamous Cell Carcinoma.Frontiers in bioengineering and biotechnology · 2022Article
- Article
- Prognostic nomograms and risk-stratifying systems for predicting survival in patients with resected pT2-4aN0M0 esophageal carcinoma.Journal of thoracic disease · 2021Article
- Prediction of Locoregional Recurrence-Free Survival of Oesophageal Squamous Cell Carcinoma After Chemoradiotherapy Based on an Enhanced CT-Based Radiomics Model.Frontiers in oncology · 2021Article
- Recurrence risk stratification based on a competing-risks nomogram to identify patients with esophageal cancer who may benefit from postoperative radiotherapy.Therapeutic advances in medical oncology · 2021Article
- Established and Validated Novel Nomogram for Predicting Prognosis of Post-Mastectomy pN0-1 Breast Cancer without Adjuvant Radiotherapy.Cancer management and research · 2021Article
- Focus on patients with early esophageal cancer-a prognostic nomogram.Translational cancer research · 2020Article
- Nomograms Predict Survival Advantages of Gleason Score 3+4 Over 4+3 for Prostate Cancer: A SEER-Based Study.Frontiers in oncology · 2019Article
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5 authors.
Funding
Abstract
backgroundThe aim of this study was to develop nomograms for predicting the risk of locoregional recurrence or distant metastasis in esophageal cancer patients who were treated with esophagectomy and regional lymphadenectomy.
methodsThe clinicopathologic data of 408 esophageal cancer patients after esophagectomy and regional lymphadenectomy were analyzed in this study. Univariate and multivariate COX regression analyses were used to test the association between the clinicopathologic data and the risk of locoregional recurrence or distant metastasis. The nomograms were built from the COX regression model.
resultsUnivariate analyses revealed that tumor length, tumor width, T-staging and perineural invasion(PNI) were significantly associated with locoregional recurrence, and that tumor length, tumor width, differentiation, T-staging, N-staging, lymph vascular space invasion(LVSI), PNI and adjuvant chemotherapy were significantly associated with distant metastasis. Multivariate analyses revealed that tumor length, tumor width and T-staging were predictors of risk of locoregional recurrence, and that differentiation, N-staging, LVSI and PNI were predictors of risk of distant metastasis. Two nomograms were constructed for a visual explanation of these two COX regression models. The bias-corrected curve showed no significant departure from the ideal curve in these two nomograms.
conclusionsTwo nomograms were developed and validated to predict the risk of locoregional recurrence and distant metastasis in esophageal cancer patients after radical esophagectomy. The calculation outcome will help oncologists to choose adjuvant treatment regimens.
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