Evidence map›Paper›PMID 28860576›Full record

SynthesisScientific reports2017

PD-L1 expression in lung cancer and its correlation with driver mutations: a meta-analysis.

Minghui Zhang, Guoliang Li, Yanbo Wang, Yan Wang, Shu Zhao, Pu Haihong, Hongli Zhao, Yan Wang

2 registry-linked trialsOpen access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 145 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
145citing papers in PubMed, 5 pooled it
11.5field-weighted citation impact, top 1% 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.

NCT04250727 nacompletednot on this mapstarted 2021, after this paper: background citation

Switching to a Non-tobacco-based Oral Nicotine Product Among Adult Cigarette Smokers: Exploring the Roles of Product Characteristics and User History

TypeinterventionalSponsorYale UniversityRan2021 to 2022Enrolled30ConditionsTobacco Use Disorder, Oral Nicotine Pouch Use, Smoking Behaviors, Harm ReductionArmsZYN
NCT04276025 completednot on this map

Relationship Between Histopathological Features, Mutation Status, 18F-FDG PET/CT Radiomic Imaging Parameters as Well as Clinical Outcome in Patients With Treatment-naïve Non-small Cell Lung Cancer

TypeobservationalSponsorKlinikum Bayreuth GmbHRan2016 to 2020Enrolled2,000ConditionsNSCLCArmsClinical routine F18-FDG-PET/CT, molecular pathology and clinical outcome
3 · Its place in the literature

Who cites it

145 citing papers in PubMed, 5 syntheses or guidelines pooled it, 232 citations in OpenAlex.

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  10. PD-L1 expression scoring using artificial intelligence algorithms in non-small cell lung cancer harbouring ROS1 fusions: potential clinical-biological significance.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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85 more citing papers are in PubMed but not listed here.

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 3 institutions in 1 country.

Minghui ZhangDepartment of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150081, Heilongjiang, China.
Guoliang LiDepartment of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150040, Heilongjiang, China.
Yanbo WangDepartment of Surgical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150081, Heilongjiang, China. wangyan11lou@163.com.
Yan WangDepartment of Medical Oncology, Heilongjiang Provincial Hospital, Harbin, 150030, Heilongjiang, China.
Shu ZhaoDepartment of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150081, Heilongjiang, China.
Pu HaihongDepartment of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150081, Heilongjiang, China.
Hongli ZhaoDepartment of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150081, Heilongjiang, China.
Yan WangDepartment of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150081, Heilongjiang, China.
Harbin Medical University · CNThird Affiliated Hospital of Harbin Medical University · CNSecond Affiliated Hospital of Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although many studies have addressed the prognostic value of programmed cell death-ligand 1 (PD-L1) expression in lung cancer, the results remain controversial. A systematic search of the PubMed, EMBASE, and Cochrane Library databases was performed to identify the correlation between PD-L1 expression and driver mutations and overall survival (OS). This meta-analysis enrolled a total of 11,444 patients for 47 studies, and the pooled results showed that increased PD-L1 expression was associated with poor prognosis (HR = 1.40, 95% CI: 1.19-1.65, P < 0.001). In subgroup analysis stratified according to histology types, the pooled results demonstrated that increased PD-L1 expression was an unfavorable prognostic factor for non-small cell lung cancer (NSCLC) (HR = 1.26, 95% CI: 1.05-1.52, P = 0.01) and pulmonary lymphoepithelioma-like carcinoma (LELC) (HR = 3.04, 95% CI: 1.19-7.77, P = 0.02), rather than small cell lung cancer (SCLC) (HR = 0.62, 95% CI: 0.27-1.39, P = 0.24). The pooled ORs indicated that PD-L1 expression was associated with gender, smoking status, histology, differentiation, tumour size, lymph nodal metastasis, TNM stage and EGFR mutation. However, PD-L1 expression was not correlated with ALK rearrangement and KRAS mutations.

Indexed as

Biomarkers, TumorGene ExpressionGenetic Predisposition to DiseaseMutationB7-H1 AntigenGenetic Association StudiesHumansLung NeoplasmsNeoplasm GradingNeoplasm MetastasisNeoplasm StagingOdds RatioPrognosisPublication BiasB7-H1 AntigenBiomarkers, TumorCD274 protein, human

Identifiers

PMID28860576
PMCPMC5578960
OpenAlexW2748992739

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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.