Evidence map›Paper›PMID 31817531›Full record

ArticleCancers2019

Prognostic Immune Cell Profiling of Malignant Pleural Effusion Patients by Computerized Immunohistochemical and Transcriptional Analysis.

Chengguang Wu, Fabian Mairinger, Ruben Casanova, Aashil A Batavia, Anne-Laure Leblond, Alex Soltermann

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Observational
  4. Article
  5. Review
  6. Review
  7. Article
  8. 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

6 authors at 2 institutions in 2 countries.

Chengguang WuInstitute of Pathology and Molecular Pathology, University Hospital Zurich, CH-8091 Zurich, Switzerland.
Fabian MairingerInstitute of Pathology, University Hospital Essen, D-45147 Essen, Germany.
Ruben CasanovaInstitute of Pathology and Molecular Pathology, University Hospital Zurich, CH-8091 Zurich, Switzerland.
Aashil A BataviaInstitute of Pathology and Molecular Pathology, University Hospital Zurich, CH-8091 Zurich, Switzerland.
Anne-Laure LeblondInstitute of Pathology and Molecular Pathology, University Hospital Zurich, CH-8091 Zurich, Switzerland.
Alex SoltermannInstitute of Pathology and Molecular Pathology, University Hospital Zurich, CH-8091 Zurich, Switzerland.
University Hospital of Zurich · CHEssen University Hospital · DE

Funding

China Scholarship Council 201506240116Swiss Cancer League F-87701-31-01Swiss National Science Foundation SystemsX M-87704-01-02
6 · The paper itself

Abstract

Malignant pleural effusion (MPE) is a severe condition of advanced tumors without effective therapy. We used digitalized immunohistochemical and transcriptional approaches to investigate the prognostic influence of immune cells and expression variance of associated immunomodulatory molecules in MPE. Cytology tissue microarrays were constructed from MPE cell blocks of 155 patients with five tumor entities. Immune cells lineage markers were quantified by computational cytopathology on immunohistochemistry. mRNA expression analysis of nine lineage markers and 17 immunomodulators was performed by NanoString. Immunohistochemically quantified high B cells to leukocytes ratio (hazard ratio (HR) = 0.70,

Indexed as

cytopathologydigitalized image analysisimmune profilingimmunomodulatormalignant pleural effusionsprognosis

Identifiers

PMID31817531
PMCPMC6966627
OpenAlexW2993694859

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.