Evidence map›Paper›PMID 31360303›Full record

ArticleOncotarget2019

Prognostic immune markers for recurrence and survival in locally advanced esophageal adenocarcinoma.

Laila Babar, Juliann E Kosovec, Vida Jahangiri, Nobel Chowdhury, Ping Zheng, Ashten N Omstead, Madison S Salvitti, Matthew A Smith, Ajay Goel, Ronan J Kelly and 2 more

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 22% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Cross-talk of mFrontiers in immunology · 2025
    Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. The immune landscape of esophageal cancer.Cancer communications (London, England) · 2019
    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

12 authors at 4 institutions in 1 country.

Laila BabarEsophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Juliann E KosovecEsophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Vida JahangiriEsophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Nobel ChowdhuryEsophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Ping ZhengEsophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Ashten N OmsteadEsophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Madison S SalvittiEsophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Matthew A SmithEsophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Ajay GoelBeckman Research Institute, City of Hope Comprehensive Cancer Center, Monrovia, CA, USA.
Ronan J KellyDepartment of Hematology and Oncology, Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX, USA.
Blair A JobeEsophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Ali H ZaidiEsophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Allegheny Health Network · USLung Institute · USBaylor University Medical Center · USBeckman Research Institute

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Treatment options and risk stratification for esophageal adenocarcinomas (EAC) currently rely on pathological criteria such as tumor staging. However, with advancement in immune modulated treatments, there is a need for accurate predictive biomarkers that will help identify high-risk patients and provide novel therapeutic targets. Hence, we analyzed as prognostic classifiers a host of histopathological parameters in conjunction with novel immune biomarkers. Specifically, gene expression levels for CXCL9, IDO1, LAG3, and TIM3 were established in treatment naïve samples. Additionally, PD-L1 and CD8 positivity was determined by immunohistochemical staining. Based on our finding, a Cox model consisting of pathological complete response (CR), LAG3, and CXCL9 provided improved predictability for disease-free survival (DFS) compared to CR alone, and it demonstrated statistical significance for predictability of recurrence (p=0.0001). Likewise, for overall survival (OS), a Cox model constituted of TIM3, CR, and IDO1 performed better than CR alone, and it demonstrated statistical significance for predictability of survival (p = 0.0004). TIM3 was identified as the best predictor for OS (HR=4.43, p=0.0023). In conclusion, given the paucity of treatment options for EAC, evaluation of these biomarkers early in the disease course will lead to better risk stratification of patients and much needed alternatives for improved therapy.

Indexed as

CXCL9esophageal adenocarcinomaIDO1LAG3TIM3

Identifiers

PMID31360303
PMCPMC6642049
OpenAlexW2997905415

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.