Evidence map›Paper›PMID 27009843›Full record

ArticleOncotarget2016

Analysis of ultra-deep targeted sequencing reveals mutation burden is associated with gender and clinical outcome in lung adenocarcinoma.

Dakai Xiao, Hui Pan, Fuqiang Li, Kui Wu, Xin Zhang, Jianxing He

Abstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 4 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

53 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

6 authors.

Dakai XiaoDepartment of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Hui PanDepartment of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Fuqiang LiBGI-Shenzhen, Shenzhen, China.
Kui WuBGI-Shenzhen, Shenzhen, China.
Xin ZhangDepartment of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Jianxing HeDepartment of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gender-associated difference in incidence and clinical outcomes of lung cancer have been established, but the biological mechanisms underlying these gender-associated differences are less studied. Recently we have characterized the genomic landscape of lung adenocarcinoma derived from Chinese population (Reference [1]). In this study we evaluated the clinical significance of mutation burden in lung adenocarcinoma and found that the male tumors harbored statistically greater burden of genetic alterations than female counterparts (Male median 3 (range 0-34) vs female median = 2 (0-24), male to female ratio = 1.636, 95% CI = 1.343-1.992) after adjustment of age at surgery, stage, smoking status. Kaplan-Meier survival analysis revealed that greater burden of genetic alterations was associated with worse overall survival. Moreover, multivariable analysis demonstrated mutation burden was an independent prognostic factor for the patients. Taken together, our analysis demonstrated gender disparity of mutation burden and their prognostic value in lung adenocarcinoma. This gender difference in mutation burden might provide an explanation for the distinct difference in the clinical outcomes between sexes in lung adenocarcinoma.

Indexed as

MutationSex CharacteristicsAdenocarcinomaAdenocarcinoma of LungAdultAgedDNA Mutational AnalysisFemaleHigh-Throughput Nucleotide SequencingHumansKaplan-Meier EstimateLung NeoplasmsMaleMiddle Agedlung adenocarcinomamutation burdentargeted NGS sequencing

Identifiers

PMID27009843
PMCPMC5008406

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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.