Evidence map›Paper›PMID 34766737›Full record

ArticleCancer reports (Hoboken, N.J.)2022

The number of brain metastases predicts the survival of non-small cell lung cancer patients with EGFR mutation status.

Jun Shao, Jingwei Li, Lujia Song, Qiuyao He, Yuxuan Wu, Linhui Li, Dan Liu, Chengdi Wang, Weimin Li

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer reports (Hoboken, N.J.), 2022. 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
0.6field-weighted citation impact, top 30% 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, 6 citations in OpenAlex.

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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

9 authors at 1 institution in 1 country.

Jun ShaoDepartment of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China.
Jingwei LiDepartment of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China.
Lujia SongDepartment of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China.
Qiuyao HeDepartment of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China.
Yuxuan WuDepartment of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China.
Linhui LiDepartment of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China.
Dan LiuDepartment of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China.
Chengdi WangDepartment of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China.ORCID 0000-0002-5284-2889
Weimin LiDepartment of Respiratory and Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan, China.ORCID 0000-0003-0985-0311
Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer is the common cause of cancer-related deaths throughout the world, and brain is a frequent metastatic site of lung cancer.

aimThis research sought to evaluate the impact of the number of brain metastases in prognosticating non-small cell lung cancer (NSCLC) patients accounting to the role of epidermal growth factor receptor (EGFR) mutations. METHODS AND

resultsNSCLC patients with brain metastases diagnosed/treated in West China Hospital, Sichuan University between 2009 and 2017 were identified retrospectively. Kaplan-Meier approach was adopted to estimate OS. And we performed univariate and multivariate Cox proportional hazards regression analyses of characteristics related to overall survival (OS) in both EGFR-mutated and wild-type cohorts. In total, this study included 611 eligible NSCLC patients with brain metastases. Extracranial metastases and chemotherapy were independent prognostic factors of OS in both cohorts. As the disease progressed, EGFR-mutated patients had brain metastasis significantly earlier (P < .0001), but they also had notably better survival outcomes than wild-type patients (P < .0001). And the number of brain metastases impacted the survival incidence in the progression significantly in both EGFR-mutated and wild-type groups (P = .0087/.037, respectively).

conclusionThe number of brain metastases was a prognostic factor for lung cancer patients either with EGFR mutations or with wild-type EGFR, with larger number indicating more unfavorble clinical outcomes. Patients with EGFR mutations had a better survival.

Indexed as

Brain NeoplasmsCarcinoma, Non-Small-Cell LungLung NeoplasmsErbB ReceptorsHumansMutationRetrospective StudiesEGFR protein, humanErbB ReceptorsEGFR mutationlung cancernumber of brain metastasessurvival

Identifiers

PMID34766737
PMCPMC9458511
OpenAlexW3211406726

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.