Evidence map›Paper›PMID 28790845›Full record

ReviewOncoTargets and therapy2017

Clinical efficacy evaluation of tyrosine kinase inhibitors for non-adenocarcinoma lung cancer patients harboring EGFR-sensitizing mutations.

Xinyu Song, Zhehai Wang

Open access · goldAbstract readReview
In one paragraph

Review in OncoTargets and therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. 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 at 2 institutions in 2 countries.

Xinyu SongSchool of Medicine and Life Sciences, University of Jinan-Shandong Academy of Medical Sciences.
Zhehai WangShandong Cancer Hospital Affiliated to Shandong University, Jinan, Shandong, People's Republic of China.
Academy of Medical Sciences · GBShandong Tumor Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) as a standard therapy have been used in EGFR-mutated adenocarcinoma of non-small-cell lung cancer (NSCLC) patients in recent years. But in current randomized prospective clinical trials, due to few cases of non-adenocarcinoma patients having been found, the efficacy of TKIs for EGFR-mutated non-adenocarcinoma and the relationship with clinicopathological characteristics remained debatable. The results of retrospective studies showed that the frequency of EGFR mutation was significantly associated with nationality, gender, smoking history, and histology type. Being female, never-smoker and adenocarcinoma had a higher mutation rate. Furthermore, the EGFR mutation rate and efficacies of TKIs in adenocarcinoma were higher than those in non-adenocarcinoma. And in non-adenocarcinoma, the EGFR mutation rate and efficacies of TKIs in adenosquamous cell carcinoma were higher than those in squamous cell carcinoma or in large-cell lung carcinoma. In conclusion, it may be necessary to conduct a large sample prospective study to understand the clinicopathological characteristics of non-adenocarcinomas and to evaluate the efficacy of EGFR TKI and/or chemotherapy for EGFR-mutated non-adenocarcinoma NSCLC. So we searched relevant articles between the year 2010 and 2016 through the major indexed literature database PubMed by searching the keywords such as EGFR mutation, Tyrosine kinase inhibitors, and Non-adenocarcinoma.

Indexed as

EGFR mutationnon-adenocarcinomatyrosine kinase inhibitors

Identifiers

PMID28790845
PMCPMC5488763
OpenAlexW2641340660

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.