Literature DB >> 28802729

Predictors of pathologic upstaging in early esophageal adenocarcinoma: Results from the national cancer database.

Craig S Brown1, Natalie Gwilliam2, Alex Kyrillos3, Waseem Lutfi3, Brittany Lapin3, Ki Wan Kim4, Seth B Krantz4, John A Howington4, Katherine Yao4, Michael B Ujiki5.   

Abstract

BACKGROUND: Upstaging in early esophageal adenocarcinoma (EAC) patients happens at a high rate and has implications for treatment. We sought to identify risk factors predicting upstaging. STUDY
DESIGN: The National Cancer Database (2010-2013) was queried for all patients with clinical T1/T2 and N0 EAC who underwent esophagectomy without neoadjuvant therapy. Logistic regression models were developed to investigate risk factors for upstaging.
RESULTS: A total of 1120 patients were included. Pathologic upstaging occurred in 21.3% (n = 239). After adjustment, risk of upstaging increased with tumor size (tumor size 1-3 cm, OR 4.57,95% CI 2.58-8.10, tumor size >3 cm, OR 10.57, 95% CI 5.77-19.35, as compared to tumors <1 cm) as well as with positive margins (OR 4.13, 95% CI 2.17-7.87) and > than 10 lymph nodes examined (OR 1.85, 95% CI 1.29-2.63), while facility volume was not significant. Odds of upstaging increased linearly with number of lymph nodes examined (OR 1.02 per node).
CONCLUSION: Our data underscore the importance of tumor size as a predictor for upstaging and of completing a thorough lymph node dissection for staging purposes.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Esophageal adenocarcinoma; National cancer database; Staging; Upstaging

Mesh:

Year:  2017        PMID: 28802729     DOI: 10.1016/j.amjsurg.2017.07.015

Source DB:  PubMed          Journal:  Am J Surg        ISSN: 0002-9610            Impact factor:   2.565


  7 in total

1.  High Mean Corpuscular Volume as a Predictor of Poor Overall Survival in Patients with Esophageal Cancer Receiving Concurrent Chemoradiotherapy.

Authors:  Ke-Jie Li; Wen-Yue Gu; Xiao-Fang Xia; Ping Zhang; Chang-Lin Zou; Zheng-Hua Fei
Journal:  Cancer Manag Res       Date:  2020-08-20       Impact factor: 3.989

2.  Identification of potential key genes in esophageal adenocarcinoma using bioinformatics.

Authors:  Zhiyu Dong; Junwen Wang; Haiqin Zhang; Tingting Zhan; Ying Chen; Shuchang Xu
Journal:  Exp Ther Med       Date:  2019-09-05       Impact factor: 2.447

3.  Prognostic value of tumor length and diameter for esophageal squamous cell cancer patients treated with definitive (chemo)radiotherapy: Potential indicators for nonsurgical T staging.

Authors:  Hongyao Xu; Shengxi Wu; Hesan Luo; Chuyun Chen; Lianxing Lin; Hecheng Huang; Renliang Xue
Journal:  Cancer Med       Date:  2019-09-04       Impact factor: 4.452

4.  Identification of Molecular Biomarkers and Key Pathways for Esophageal Carcinoma (EsC): A Bioinformatics Approach.

Authors:  Md Rakibul Islam; Mohammad Khursheed Alam; Bikash Kumar Paul; Deepika Koundal; Atef Zaguia; Kawsar Ahmed
Journal:  Biomed Res Int       Date:  2022-01-12       Impact factor: 3.411

5.  High Mean Corpuscular Volume Predicts Poor Outcome for Patients With Gastroesophageal Adenocarcinoma.

Authors:  Gerd Jomrich; Marlene Hollenstein; Max John; Robin Ristl; Matthias Paireder; Ivan Kristo; Reza Asari; Sebastian F Schoppmann
Journal:  Ann Surg Oncol       Date:  2019-01-31       Impact factor: 5.344

6.  Predicting lymph node metastases with endoscopic resection in cT2N0M0 oesophageal cancer: A systematic review and meta-analysis.

Authors:  Ali Al-Kaabi; Rachel S van der Post; Jonathan Huising; Camiel Rosman; Iris D Nagtegaal; Peter D Siersema
Journal:  United European Gastroenterol J       Date:  2019-09-25       Impact factor: 4.623

7.  Modeling the impact of delaying surgery for early esophageal cancer in the era of COVID-19.

Authors:  Maren E Shipe; Jordan J Baechle; Stephen A Deppen; Erin A Gillaspie; Eric L Grogan
Journal:  Surg Endosc       Date:  2020-11-02       Impact factor: 4.584

  7 in total

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