Evidence map›Paper›PMID 26904218›Full record

ArticleJournal of thoracic disease2016

Targeted drugs for unselected patients with advanced non-small-cell lung cancer: a network meta-analysis.

Miaomiao Sheng, Yueguang Zhao, Fang Wang, Shanshan Li, Xiaojie Wang, Tao Shou, Ying Luo, Wenru Tang

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. [Relationship between ID1 and EGFR-TKI Resistance 
in Non-small Cell Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2016
    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

8 authors.

Miaomiao Sheng1 Laboratory of Molecular Genetics of Aging & Tumor, Medical Faculty, Kunming University of Science and Technology, Kunming 650500, China ; 2 First People's Hospital of Yunnan Province, Kunming 650032, China.
Yueguang Zhao1 Laboratory of Molecular Genetics of Aging & Tumor, Medical Faculty, Kunming University of Science and Technology, Kunming 650500, China ; 2 First People's Hospital of Yunnan Province, Kunming 650032, China.
Fang Wang1 Laboratory of Molecular Genetics of Aging & Tumor, Medical Faculty, Kunming University of Science and Technology, Kunming 650500, China ; 2 First People's Hospital of Yunnan Province, Kunming 650032, China.
Shanshan Li1 Laboratory of Molecular Genetics of Aging & Tumor, Medical Faculty, Kunming University of Science and Technology, Kunming 650500, China ; 2 First People's Hospital of Yunnan Province, Kunming 650032, China.
Xiaojie Wang1 Laboratory of Molecular Genetics of Aging & Tumor, Medical Faculty, Kunming University of Science and Technology, Kunming 650500, China ; 2 First People's Hospital of Yunnan Province, Kunming 650032, China.
Tao Shou1 Laboratory of Molecular Genetics of Aging & Tumor, Medical Faculty, Kunming University of Science and Technology, Kunming 650500, China ; 2 First People's Hospital of Yunnan Province, Kunming 650032, China.
Ying Luo1 Laboratory of Molecular Genetics of Aging & Tumor, Medical Faculty, Kunming University of Science and Technology, Kunming 650500, China ; 2 First People's Hospital of Yunnan Province, Kunming 650032, China.
Wenru Tang1 Laboratory of Molecular Genetics of Aging & Tumor, Medical Faculty, Kunming University of Science and Technology, Kunming 650500, China ; 2 First People's Hospital of Yunnan Province, Kunming 650032, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrently, targeted therapy has shown encouraging treatment benefits in selected patients with advanced non-small cell lung cancer (NSCLC). However, the comparative benefits of targeted drugs and chemotherapy (CT) treatments in unselected patients are not clear. We therefore conduct a network meta-analysis to assess the relative efficacy and safety of these regimens.

methodsPubMed, EMBASE, Cochrane Library and abstracts from major scientific meetings were searched for eligible literatures. The odds ratio (OR) for objective response rate (ORR) and safety was used for pooling effect sizes. Bayesian network meta-analysis was conducted to calculate the efficacy and safety of all included treatments. All tests of statistical significance were two sided.

resultsA total of 13,060 patients from 24 randomized controlled trials (RCT) were assessed. The targeted agents included bevacizumab (Bev), gefitinib (Gef), erlotinib (Erl) and cetuximab (Cet). Network meta-analysis showed that Bev + CT had a statistically significantly higher incidence of ORR relative to the other six different treatments, including placebo (OR =6.47; 95% CI, 3.85-10.29), Erl (OR =2.81; 95% CI, 2.08-3.70), CT (OR =1.92; 95% CI, 1.61-2.28), Gef (OR =1.40; 95% CI, 1.10-1.75), Erl + CT (OR =1.46; 95% CI, 1.17-1.80) and Gef + CT (OR =1.75; 95% CI, 1.36-2.22), whereas placebo and Erl were associated with statistically significantly lower incidence of ORR. Trend analyses of rank probability revealed that Bev + CT had the highest probability of being the best treatment arm in term of ORR, followed by Cet + CT. Meanwhile, Cet + CT showed significant severer rash and thrombocytopenia compared with Bev + CT. Gef was probable to be the rank 3 for ORR but was associated with relatively low risk for grade ≥3 toxicities.

conclusionsOur study suggested that Bev + CT may offer better ORR in the treatment of unselected patients with advanced NSCLC. Future studies will be needed to investigate whether the increase of ORR with targeted drugs would be translated into survival benefits.

Indexed as

efficacynetwork meta-analysisnon-small cell lung cancer (NSCLC)Targeted drugs

Identifiers

PMID26904218
PMCPMC4740157

What OpenQuestion holds

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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.