ArticleBMC cancer2025
Enhanced prognosis prediction model in esophageal cancer via lymph node assessment post-neoadjuvant.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Recurrent laryngeal nerve lymph nodes status prediction after neoadjuvant therapy for thoracic esophageal squamous cell carcinoma.Insights into imaging · 2026Article
- Dissection of lymph node on longevity in breast and colorectal operation.Bioinformation · 2026Article
- Residual disease subtyping predicts survival and guides adjuvant immunotherapy in esophageal squamous cell carcinoma after neoadjuvant chemoimmunotherapy.Frontiers in immunology · 2026Article
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11 authors.
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Abstract
Develop an improved lymph node evaluation system for prognosis prediction in esophageal squamous cell carcinoma (ESCC) patients receiving neoadjuvant therapy.
methodsStudied 282 ESCC patients who underwent neoadjuvant chemoradiotherapy (NCRT) and surgery. Evaluated lymph node factors like number, size, location, and intra-nodal cancer status. Developed and validated a prognostic model using these factors.
resultsCases with a clearance of 17-30 lymph nodes during surgery showed improved overall survival (OS) compared to those with fewer than 17 or more than 30 cleared nodes. Patients with a lower tumor regression grade of lymph nodes (LN-TRG) experienced improved OS and recurrence-free survival (RFS). Patients with LN extracapsular invasion had worse OS and RFS. Abdominal lymph nodes showed the highest ratio of residual cancer, highest hazard ratio (HR), and the largest number and proportion of positive cases. The five most relevant factors for prognosis, as revealed by Lasso regression and Cox univariate analysis, were LN-TRG, LN total tumor diameter, the clearance of 17-30 lymph nodes, the proportion of positive lymph nodes, and LN extracapsular invasion. The predictive model, based on these factors, achieved good risk stratification for OS and RFS (AUC = 0.705, 0.679), surpassing pathology N (pN) staging.
conclusionA comprehensive lymph node assessment using a predictive model enables improved prognosis prediction and risk stratification compared to pN staging for patients undergoing neoadjuvant therapy. This approach contributes to the accurate evaluation of clinical prognosis and assists in guiding treatment strategies.
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