ArticleUnited European gastroenterology journal2021
Lymphovascular invasion quantification could improve risk prediction of lymph node metastases in patients with submucosal (T1b) esophageal adenocarcinoma.
Article in United European gastroenterology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Article
- Accuracy of machine learning in detecting lymph node metastasis of esophageal cancer: a systematic review and meta-analysis.Translational cancer research · 2026Article
- Evolving challenges in the management of early esophageal adenocarcinoma: from clinical staging to molecular insights.World journal of surgical oncology · 2026Review
- Imaging biomarkers to stratify lymph node metastases in abdominal CT - Is radiomics superior to dual-energy material decomposition?European journal of radiology open · 2023Article
- Lymphovascular invasion quantification could improve risk prediction of lymph node metastases in patients with submucosal (T1b) esophageal adenocarcinoma.United European gastroenterology journal · 2021Article
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31 authors.
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Abstract
aimTo quantify lymphovascular invasion (LVI) and to assess the prognostic value in patients with pT1b esophageal adenocarcinoma.
methodsIn this nationwide, retrospective cohort study, patients were included if they were treated with surgery or endoscopic resection for pT1b esophageal adenocarcinoma. Primary endpoint was the presence of metastases, lymph node metastases, or distant metastases, in surgical resection specimens or during follow-up. A prediction model to identify risk factors for metastases was developed and internally validated.
results248 patients were included. LVI was distributed as follows: no LVI (n = 196; 79.0%), 1 LVI focus (n = 16; 6.5%), 2-3 LVI foci (n = 21; 8.5%) and ≥4 LVI foci (n = 15; 6.0%). Seventy-eight patients had metastases. The risk of metastases was increased for tumors with 2-3 LVI foci [subdistribution hazard ratio (SHR) 3.39, 95% confidence interval (CI) 2.10-5.47] and ≥4 LVI foci (SHR 3.81, 95% CI 2.37-6.10). The prediction model demonstrated a good discriminative ability (c-statistic 0.81).
conclusionThe risk of metastases is higher when more LVI foci are present. Quantification of LVI could be useful for a more precise risk estimation of metastases. This model needs to be externally validated before implementation into clinical practice.
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