Literature DB >> 31442498

Precision Surgical Therapy for Adenocarcinoma of the Esophagus and Esophagogastric Junction.

Thomas W Rice1, Min Lu2, Hemant Ishwaran2, Eugene H Blackstone3.   

Abstract

INTRODUCTION: To facilitate the initial clinical decision regarding whether to use esophagectomy alone or neoadjuvant therapy in surgical care for individual patients with adenocarcinoma of the esophagus and esophagogastric junction-information not available from randomized trials-a machine-learning analysis was performed using worldwide real-world data on patients undergoing different therapies for this rare adenocarcinoma.
METHODS: Using random forest technology in a sequential analysis, we (1) identified eligibility for each of four therapies among 13,365 patients: esophagectomy alone (n = 6649), neoadjuvant therapy (n = 4706), esophagectomy and adjuvant therapy (n = 998), and neoadjuvant and adjuvant therapy (n = 1022); (2) performed survival analyses incorporating interactions of patient and cancer characteristics with therapy; (3) determined optimal therapy as that predicted to maximize lifetime within 10 years (restricted mean survival time; RMST) for each patient; and (4) compared lifetime gained from optimal versus actual therapies.
RESULTS: Actual therapy was optimal in 61% of those receiving esophagectomy alone; neoadjuvant therapy was optimal for 36% receiving neoadjuvant therapy. Many patients were predicted to benefit from postoperative adjuvant therapy. Total RMST for actual therapy received was 58,825 years. Had patients received optimal therapy, total RMST was predicted to be 62,982 years, a 7% gain.
CONCLUSIONS: Average treatment effect for adenocarcinoma of the esophagus yields only crude evidence-based therapy guidelines. However, patient response to therapy is widely variable, and survival after data-driven predicted optimal therapy often differs from actual therapy received. Therapy must address an individual patient's cancer and clinical characteristics to provide precision surgical therapy for adenocarcinoma of the esophagus and esophagogastric junction.
Copyright © 2019 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Artificial intelligence; Machine learning; Real-world data; Survival analysis

Mesh:

Year:  2019        PMID: 31442498      PMCID: PMC6876319          DOI: 10.1016/j.jtho.2019.08.004

Source DB:  PubMed          Journal:  J Thorac Oncol        ISSN: 1556-0864            Impact factor:   15.609


  41 in total

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Authors:  T W Rice; T E M R Lerut; M B Orringer; L-Q Chen; W L Hofstetter; B M Smithers; V W Rusch; J van Lanschot; K N Chen; A R Davies; X B D'Journo; K A Kesler; J D Luketich; M K Ferguson; J V Räsänen; R van Hillegersberg; W Fang; L Durand; W H Allum; I Cecconello; R J Cerfolio; M Pera; S M Griffin; R Burger; J-F Liu; M S Allen; S Law; T J Watson; G E Darling; W J Scott; A Duranceau; C E Denlinger; P H Schipper; H Ishwaran; C Apperson-Hansen; L M DiPaola; M E Semple; E H Blackstone
Journal:  Dis Esophagus       Date:  2016-10       Impact factor: 3.429

2.  Adjuvant chemotherapy following trimodality therapy for esophageal carcinoma-Is the evidence sufficient?

Authors:  Scott M Atay; Mariela Blum; Boris Sepesi
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3.  Cancer of the Esophagus and Esophagogastric Junction: An Eighth Edition Staging Primer.

Authors:  Thomas W Rice; Hemant Ishwaran; Mark K Ferguson; Eugene H Blackstone; Peter Goldstraw
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4.  Disparities in survival after trimodality therapy for esophageal adenocarcinoma.

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Journal:  Dis Esophagus       Date:  2018-09-01       Impact factor: 3.429

5.  Recommendations for pathologic staging (pTNM) of cancer of the esophagus and esophagogastric junction for the 8th edition AJCC/UICC staging manuals.

Authors:  T W Rice; H Ishwaran; W L Hofstetter; D P Kelsen; C Apperson-Hansen; E H Blackstone
Journal:  Dis Esophagus       Date:  2016-11       Impact factor: 3.429

6.  Recommendations for clinical staging (cTNM) of cancer of the esophagus and esophagogastric junction for the 8th edition AJCC/UICC staging manuals.

Authors:  Thomas W Rice; Hemant Ishwaran; Eugene H Blackstone; Wayne L Hofstetter; David P Kelsen; Carolyn Apperson-Hansen
Journal:  Dis Esophagus       Date:  2016-11       Impact factor: 3.429

7.  Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods.

Authors:  Min Lu; Saad Sadiq; Daniel J Feaster; Hemant Ishwaran
Journal:  J Comput Graph Stat       Date:  2018-02-01       Impact factor: 2.302

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Authors:  T Glatz; P Bronsert; M Schäfer; B Kulemann; G Marjanovic; O Sick; U T Hopt; K Zirlik; F Makowiec; J Hoeppner
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Authors:  Sheraz R Markar; Caroline Gronnier; Arnaud Pasquer; Alain Duhamel; Hélène Beal; Jérémie Théreaux; Johan Gagnière; Gil Lebreton; Cécile Brigand; Bernard Meunier; Denis Collet; Christophe Mariette
Journal:  Eur J Cancer       Date:  2016-01-23       Impact factor: 9.162

10.  Biomarker-Driven Therapy in Metastatic Gastric and Esophageal Cancer: Real-Life Clinical Experience.

Authors:  Ofer Purim; Alexander Beny; Moshe Inbar; Katerina Shulman; Baruch Brenner; Elizabeth Dudnik; Felix Bokstein; Mark Temper; Dror Limon; Diana Matceyevsky; David Sarid; Amiel Segal; Valeriya Semenisty; Ronen Brenner; Tamar Peretz; Efraim Idelevich; Sharon Pelles-Avraham; Amichay Meirovitz; Arie Figer; Kenneth Russell; Andreas Voss; Addie Dvir; Lior Soussan-Gutman; Ayala Hubert
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4.  Myeloid-Derived Suppressor Cells in Immune Microenvironment Promote Progression of Esophagogastric Junction Adenocarcinoma.

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Journal:  Front Oncol       Date:  2021-03-29       Impact factor: 6.244

Review 5.  Recent advances in multidisciplinary therapy for adenocarcinoma of the esophagus and esophagogastric junction.

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Journal:  World J Gastroenterol       Date:  2022-08-21       Impact factor: 5.374

6.  Global research trends of artificial intelligence applied in esophageal carcinoma: A bibliometric analysis (2000-2022) via CiteSpace and VOSviewer.

Authors:  Jia-Xin Tu; Xue-Ting Lin; Hui-Qing Ye; Shan-Lan Yang; Li-Fang Deng; Ruo-Ling Zhu; Lei Wu; Xiao-Qiang Zhang
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Review 7.  Artificial intelligence-assisted esophageal cancer management: Now and future.

Authors:  Yu-Hang Zhang; Lin-Jie Guo; Xiang-Lei Yuan; Bing Hu
Journal:  World J Gastroenterol       Date:  2020-09-21       Impact factor: 5.742

  7 in total

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