Evidence map›Paper›PMID 31442498›Full record

ArticleJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer2019

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

Thomas W Rice, Min Lu, Hemant Ishwaran, Eugene H Blackstone, Worldwide Esophageal Cancer Collaboration Investigators

Abstract read
In one paragraph

Article in Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 28 citations in OpenAlex.

  1. Adjuvant Therapy after Esophagectomy for Esophageal Cancer: Who Needs It?: Multi-institution Worldwide Observational Study.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024
    Article
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  3. Article
  4. Review
  5. [Technical innovations and future perspectives].Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen · 2022
    Review
  6. A scoping review of artificial intelligence applications in thoracic surgery.European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery · 2022
    Article
  7. Article
  8. Article
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Thomas W RiceDepartment of Thoracic and Cardiovascular Surgery, Cleveland Clinic, Cleveland, Ohio.
Min LuDepartment of Public Health Sciences, Division of Biostatistics, University of Miami, Coral Gables, Florida.
Hemant IshwaranDepartment of Public Health Sciences, Division of Biostatistics, University of Miami, Coral Gables, Florida.
Eugene H BlackstoneDepartment of Thoracic and Cardiovascular Surgery, Cleveland Clinic, Cleveland, Ohio; Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio. Electronic address: blackse@ccf.org.
Worldwide Esophageal Cancer Collaboration Investigators
Cleveland Clinic · USUniversity of Miami · US

Funding

Clinical and Translational Science Collaborative of ClevelandUL1TR000439 · NCATS · CASE WESTERN RESERVE UNIVERSITY · PI KONSTAN, MICHAEL W. · 2012 to 2016
$50.0M
Miami Clinical and Translational Science InstituteUL1TR002736 · NCATS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CARRASQUILLO, OLVEEN, KOBETZ, ERIN N · 2018 to 2022
$23.2M
NextGen Random ForestsR01GM125072 · NIGMS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI ISHWARAN, HEMANT · 2017 to 2020
$1.4M
NCATS NIH HHS UL1 TR000439NCATS NIH HHS UL1 TR002736NIGMS NIH HHS R01 GM125072
6 · The paper itself

Abstract

introductionTo 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.

methodsUsing 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.

resultsActual 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.

conclusionsAverage 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.

Indexed as

AdenocarcinomaAgedEsophageal NeoplasmsEsophagogastric JunctionHumansMachine LearningSurvival AnalysisArtificial intelligenceMachine learningReal-world dataSurvival analysis

Identifiers

PMID31442498
PMCPMC6876319
OpenAlexW2969631706

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.