Evidence map›Paper›PMID 28423587›Full record

SynthesisOncotarget2017

The correlation between programmed death-ligand 1 expression and driver gene mutations in NSCLC.

Haitao Yang, Huijuan Chen, Shuimei Luo, Lina Li, Sijing Zhou, Ruifen Shen, Heng Lin, Xianhe Xie

Open access · diamondAbstract readMeta-Analysis
In one paragraph

Synthesis in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
4.1field-weighted citation impact, top 6% 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

21 citing papers in PubMed, 32 citations in OpenAlex.

  1. Review
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  3. Article
  4. Review
  5. AnFrontiers in immunology · 2022
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  10. Molecular profile of non-small cell lung cancer in northeastern Brazil.Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia · 2019
    Article
  11. Article
  12. Review
  13. Article
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  15. Synchronous Presence ofWorld journal of oncology · 2018
    Article
  16. Correlation ofOncotarget · 2018
    Article
  17. Review
  18. Review
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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

8 authors at 2 institutions in 1 country.

Haitao YangDepartment of Chemotherapy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, China.
Huijuan ChenDepartment of Chemotherapy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, China.
Shuimei LuoDepartment of Chemotherapy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, China.
Lina LiDepartment of Chemotherapy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, China.
Sijing ZhouDepartment of Chemotherapy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, China.
Ruifen ShenDepartment of Chemotherapy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, China.
Heng LinDepartment of Chemotherapy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, China.
Xianhe XieDepartment of Chemotherapy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, China.
First Affiliated Hospital of Fujian Medical University · CNFujian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to evaluate the correlation between positive PD-L1 expression and driver gene mutations in NSCLC and to seek preliminary evidence in favor of the strategy of PD-L1 inhibitors plus targeted agents.

resultsThe overall analyses revealed that positive PD-L1 expression had a significant relationship with KRAS status (RR = 1.26; 95% CI, 1.06-1.50, P = 0.010), but no correlation with clinical characteristics (gender, smoking status, histological types), driver gene status (EGFR, ALK) and overall survival (OS): male versus female (RR = 1.16; 95% CI, 0.95-1.42; P = 0.15), never smoking versus former/current smoking (RR = 0.79; 95% CI, 0.56-1.11; P = 0.17), adenocarcinoma versus non-adenocarcinoma (RR = 0.94; 95% CI, 0.63-1.41; P = 0.77), EGFR mutation versus EGFR wild type (RR = 0.74; 95% CI, 0.52-1.06; P = 0.10), ALK positive versus ALK negative (RR = 1.02; 95% CI, 0.75-1.38; P = 0.91), OS of positive PD-L1 expression versus that of negative PD-L1 expression (HR = 1.31, 95% CI, 0.90-1.90; P = 0.15), respectively. Noteworthily, subgroup analyses exhibited that in Chinese cohort studies, positive PD-L1 expression was significantly correlated with OS (HR = 1.75, 95% CI, 1.36-2.24, P < 0.0001); and in the studies using PD-L1 monoclonal antibodies (McAbs), positive PD-L1 expression was significantly correlated with KRAS mutation (RR = 1.32, 95% CI, 1.06-1.65, P = 0.01) and EGFR mutation (RR = 0.51, 95% CI, 0.28-0.93, P = 0.03). MATERIALS AND

methodsAfter thoroughly searching PubMed, EMBASE and Cochrane Library databases, 11 relevant studies incorporating 3128 cases were identified. The pooled data were analyzed via Review manager 5.3 software.

conclusionsPD-L1 inhibitors probably was a potential promising option to manage advanced NSCLC harboring KRAS mutation.

Indexed as

MutationAnaplastic Lymphoma KinaseAsian PeopleB7-H1 AntigenCarcinoma, Non-Small-Cell LungChinaDisease-Free SurvivalErbB ReceptorsFemaleGene Expression Regulation, NeoplasticHumansLung NeoplasmsMaleProto-Oncogene Proteins p21(ras)Receptor Protein-Tyrosine KinasesALK protein, humanAnaplastic Lymphoma KinaseB7-H1 AntigenCD274 protein, humanEGFR protein, humanErbB ReceptorsKRAS protein, humanProto-Oncogene Proteins p21(ras)Receptor Protein-Tyrosine KinasesALKEGFRKRASNSCLCPD-L1

Identifiers

PMID28423587
PMCPMC5410323
OpenAlexW2590374339

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.