Evidence map›Paper›PMID 25806294›Full record

ReviewTranslational lung cancer research2014

Prognostic markers in lung cancer: is it ready for prime time?

Chang-Qi Zhu, Ming-Sound Tsao

Abstract readReview
In one paragraph

Review in Translational lung cancer research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. A novel 12-gene signature as independent prognostic model in stage IA and IB lung squamous cell carcinoma patients.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2021
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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.

Chang-Qi Zhu1 Princess Margaret Cancer Centre, University Health Network and 2 Department of Laboratory Medicine and Pathobiology, University of Toronto, Ontario, Canada.
Ming-Sound Tsao1 Princess Margaret Cancer Centre, University Health Network and 2 Department of Laboratory Medicine and Pathobiology, University of Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-small cell lung cancer (NSCLC) is a heterogeneity disease and to date, specific clinical factors and tumor stage are established as prognostic markers. Nevertheless, prognosis within stage may vary significantly. During the last 3 decades, genes/proteins that drive tumor initiation and progression, such as oncogenes and tumor suppressor genes have been studied as additional potential prognostic markers. The protein markers as evaluated by immunohistochemistry (IHC) have previously dominated these studies. However, with the development of high-throughput techniques to interrogate genome wide genetic or gene expression changes, DNA (copy number and mutation) and RNA (mRNA and microRNA) based markers have more recently been studied as prognostic markers. Largely due to the heterogeneity and complexity of NSCLC, single gene markers including KRAS mutation has not been validated as strong prognostic markers. In contrast, several gene expression signatures representing mRNA levels of multiple genes have been developed and validated in multiple microarray datasets of independent patient cohorts. The salient features of these gene signatures and their potential value to predict benefit from adjuvant chemotherapy is discussed.

Indexed as

expression signatureimmunohistochemistry (IHC)multi-gene markersPrognostic markerproteomics

Identifiers

PMID25806294
PMCPMC4367687

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.