Evidence map›Paper›PMID 30588016›Full record

ArticleOncoTargets and therapy2018

Curative effectiveness and safety of osimertinib in the treatment for non-small-cell lung cancer: a meta-analysis of the experimental evidence.

Peng Chen, Fuchao Chen, Jiexin Lei, Benhong Zhou

Abstract read
In one paragraph

Article in OncoTargets and therapy, 2018. 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
–field-weighted citation impact
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.

  1. Article
  2. 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

4 authors.

Peng ChenDepartment of Pharmacy, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, People's Republic of China, benhongzh@whu.edu.cn.
Fuchao ChenDepartment of Pharmacy, Dongfeng Hospital, Hubei University of Medicine, Shiyan, Hubei 442008, People's Republic of China.
Jiexin LeiDepartment of Endocrinology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, People's Republic of China.
Benhong ZhouDepartment of Pharmacy, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, People's Republic of China, benhongzh@whu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOsimertinib is an EGFR-TKI that is selective for both EGFR-TKI-sensitizing and T790M resistance mutations in patients with non-small-cell lung cancer (NSCLC). The purpose of this study was conducting a meta-analysis to evaluate the clinical efficacy and safety of osimertinib in the treatment for NSCLC.

methodsUsing "osimertinib" as a keyword combined with "non-small-cell lung cancer" and "randomized controlled trial" as medical subject headings, the following electronic databases were searched: PubMed, EMBASE, Cochrane Library, and China National Knowledge Infrastructure. After data extraction and quality assessment of the included randomized controlled trials, the RevMan 5.3 software and R meta package were applied for meta-analysis of objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and safety.

resultsTen studies met our criteria and were included in the meta-analysis, with a total of 3,260 participants. The meta-analysis showed that osimertinib therapy was superior to the control therapy alone in ORR (combined RR=1.53, 95% CI: 0.87-2.71,

conclusionOur study showed that osimertinib demonstrated a significant improvement in the ORR, DCR, PFS, and OS with tolerable adverse effects for NSCLC patients. However, because of some clear limitations (heterogeneity and publication bias), these results should be interpreted with caution.

Indexed as

efficacymeta-analysisNSCLCosimertinibsafetysurvival

Identifiers

PMID30588016
PMCPMC6296202

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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.