Evidence map›Paper›PMID 24535778›Full record

SynthesisTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2014

TERT rs2736100 polymorphism contributes to lung cancer risk: a meta-analysis including 49,869 cases and 73,464 controls.

Wei Nie, Yuansheng Zang, Jiquan Chen, Qingyu Xiu

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Article
  4. Article
  5. 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.

Wei NieDepartment of Respiratory Medicine, Shanghai Changzheng Hospital, Second Military Medical University, 415 Fengyang Road, Shanghai, 200003, China.
Yuansheng Zang
Jiquan Chen
Qingyu Xiu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Some studies investigated the association of TERT rs2736100 polymorphism with lung cancer (LC). But the results were not consistent. We performed a meta-analysis to examine the association between rs2736100 and LC. Databases including PubMed, EMBASE, Wanfang, and China National Knowledge Infrastructure (CNKI) were searched. Data were extracted, and pooled odds ratios (ORs) with 95 % confidence intervals (CIs) were calculated. A total of 19 studies including 49,869 cases and 73,464 controls were involved in this meta-analysis. Overall, a significant association between TERT rs2736100 polymorphism and LC risk was observed (OR=1.23, 95 % CI 1.18-1.28, P<0.00001). This polymorphism was also significantly associated with LC risk in Asians (OR=1.27, 95 % CI 1.22-1.33, P<0.00001), Caucasians (OR=1.14, 95 % CI 1.10-1.18, P<0.00001), female patients (OR=1.37, 95 % CI 1.24-1.51, P<0.00001), male patients (OR=1.23, 95 % CI 1.15-1.31, P<0.00001), adenocarcinoma patients (OR=1.35, 95 % CI 1.28-1.41, P<0.00001), squamous cell carcinoma patients (OR=1.13, 95 % CI 1.04-1.21, P=0.002), small cell lung cancer patients (OR=1.09, 95 % CI 1.03-1.16, P=0.004), current smokers (OR=1.22, 95 % CI 1.17-1.27, P<0.00001), former smokers (OR=1.14, 95 % CI 1.08-1.21, P<0.0001), and never smokers (OR=1.37, 95 % CI 1.31-1.43, P<0.00001), respectively. This meta-analysis suggested that TERT rs2736100 polymorphism was a risk factor for LC.

Indexed as

Genetic Predisposition to DiseasePolymorphism, GeneticFemaleHumansLung NeoplasmsMalePublication BiasRiskSmokingTelomeraseTelomeraseTERT protein, human

Identifiers

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.