Evidence map›Paper›PMID 30350175›Full record

ReviewDer Pathologe2018

[Prognostic significance of immune cell infiltrates in tumor pathology].

D-C Wagner, W Roth

Abstract readReview
PubMed Publisher
In one paragraph

Review in Der Pathologe, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Treatment-induced changes of lymphocyte subsets in patients with adenoid cystic carcinoma of the head and neck.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2019
    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

2 authors.

D-C WagnerInstitut für Pathologie, Universitätsmedizin der Johannes Gutenberg-Universität Mainz, Langenbeckstr. 1, 55131, Mainz, Deutschland. daniel-christoph.wagner@unimedizin-mainz.de.
W RothInstitut für Pathologie, Universitätsmedizin der Johannes Gutenberg-Universität Mainz, Langenbeckstr. 1, 55131, Mainz, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe quantity, distribution, activation status, cytokine profile, and spatial distribution of tumor-infiltrating immune cells have prognostic value and may be predictive of response to immunotherapies.

objectivesA survey of relevant immune cell populations including their prognostic significance in the most common types of tumors.

methodsNonsystematic assessment and a discussion of studies that were conducted to estimate the prognostic significance of certain immune cell subsets and the methodical approaches used.

resultsFor many tumor entities, prognostically favorable and unfavorable immune cell populations can be differentiated. However, nonspecific cell markers that may partly summarize antithetic immune cell subsets can be employed. Differences in sampling procedures and the determination of cut-off levels further limit the comparability of the studies carried out so far.

conclusionThe phenotypic and functional heterogeneity of tumor-infiltrating immune cells requires the use of cell subset-specific antibodies and antibody combinations. Furthermore, harmonized assessment routines, validation studies, and meta-analyses are important prerequisites for potential diagnostic implementation.

Indexed as

Lymphocytes, Tumor-InfiltratingNeoplasmsBiomarkersHumansPrognosisBiomarkersCancerImmune systemImmunohistochemistryLeukocytesPrognostic factors

Identifiers

What OpenQuestion holds

Textmetadata
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.