Evidence map›Paper›PMID 33145093›Full record

ReviewJournal of thoracic disease2020

Role of precision imaging in esophageal cancer.

Sherif B Elsherif, Sonia Andreou, Mayur Virarkar, Erik Soule, Dheeraj Reddy Gopireddy, Priya R Bhosale, Chandana Lall

Abstract readReview
In one paragraph

Review in Journal of thoracic disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
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

16 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Imaging in Esophageal Cancer: A Comprehensive Review.The Indian journal of radiology & imaging · 2025
    Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. An In Vivo Study ofBioMed research international · 2022
    Article
  15. Article
  16. Article
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

7 authors.

Sherif B ElsherifDepartment of Radiology, University of Florida College of Medicine, Jacksonville, FL, USA.
Sonia AndreouDepartment of Radiology, University of Florida College of Medicine, Jacksonville, FL, USA.
Mayur VirarkarDepartment of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Erik SouleDepartment of Radiology, University of Florida College of Medicine, Jacksonville, FL, USA.
Dheeraj Reddy GopireddyDepartment of Radiology, University of Florida College of Medicine, Jacksonville, FL, USA.
Priya R BhosaleDepartment of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Chandana LallDepartment of Radiology, University of Florida College of Medicine, Jacksonville, FL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Esophageal cancer is a major cause of morbidity and mortality worldwide. Recent advancements in the management of esophageal cancer have allowed for earlier detection, improved ability to monitor progression, and superior treatment options. These innovations allow treatment teams to formulate more customized management plans and have led to an increase in patient survival rates. For example, in order for the most effective management plan to be constructed, accurate staging must be performed to determine tumor resectability. This article reviews the multimodality imaging approach involved in making a diagnosis, staging, evaluating treatment response and detecting recurrence in esophageal cancer.

Indexed as

endoscopic ultrasonographyesophageal adenocarcinoma (EAC)Esophageal canceresophageal squamous cell carcinoma (ESCC)MRI

Identifiers

PMID33145093
PMCPMC7578477

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.