Evidence map›Paper›PMID 26767046›Full record

ArticleThoracic cancer2014

Tumor MET expression profile predicts the outcome of non-small cell lung cancer patients receiving epidermal growth factor receptor tyrosine kinase inhibitors.

Hyun Chang, Xianglan Zhang, Byoung Chul Cho, Hee Jin Park, Joo-Hang Kim

Open access · bronzeAbstract read
In one paragraph

Article in Thoracic cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 24% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

5 authors at 2 institutions in 2 countries.

Hyun ChangDivision of Hematology and Medical Oncology, Department of Internal Medicine, International St. Mary's Hospital Incheon, Korea; Department of Internal Medicine, Yonsei University College of Medicine Seoul, Korea.
Xianglan ZhangDepartment of Pathology, Yanbian University Hospital Yanji, China.
Byoung Chul ChoDepartment of Internal Medicine, Yonsei University College of Medicine Seoul, Korea.
Hee Jin ParkDepartment of Pathology, Yonsei University College of Medicine Seoul, Korea.
Joo-Hang KimDepartment of Internal Medicine, Yonsei University College of Medicine Seoul, Korea.
Yonsei University · KRYanbian University Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study assesses whether MET expression in tumor tissue is associated with an increased sensitivity to epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) in non-small-cell lung cancer (NSCLC) patients.

methodsThis retrospective study included 69 NSCLC participants with available tumor tissue and data on treatment response and survival. MET and hepatocyte growth factor expression in tumor tissue were evaluated by immunohistochemistry.

resultsPositive tMET expression correlated with a shorter progression-free survival (PFS; P = 0.003) and overall survival (OS; P = 0.05). Positive pY1234/1235 expression was significantly associated with a longer PFS (P = 0.031) and OS (P = 0.012). In multivariable analyses, tMET and pY1234/1235 expression were independent factors for PFS and OS, respectively. (tMET, PFS; P = 0.02, OS; P = 0.0007 and pY1234/1234, PFS; P = 0.01, OS; P = 0.004).

conclusionsThis study suggests that total and phosphorylated MET expression in tumor tissue is potentially useful for the selection of NSCLC patients who are likely to benefit from EGFR-TKIs, irrespective of their EGFR status.

Indexed as

Epidermal growth factor receptorMETnon-small cell lung cancertyrosine kinase inhibitor

Identifiers

PMID26767046
PMCPMC4704337
OpenAlexW2148519330

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.