Differences in the risk association of TERT rs2736098 (C > T) with lung cancer between Caucasian and Asian populations: A meta-analysis.

Xiaozheng Wu, Wen Li, Ran Ding, Hongguan Jiao, Yihui Chai, Yunzhi Chen

Abstract readMeta-Analysis

In one paragraph

Synthesis in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Xiaozheng WuDepartment of Preclinical Medicine, Guizhou University of Traditional ChineseMedicine, Guiyang, 550025, China.

Wen LiDepartment of Preclinical Medicine, Guizhou University of Traditional ChineseMedicine, Guiyang, 550025, China.

Ran DingDepartment of Preclinical Medicine, Guizhou University of Traditional ChineseMedicine, Guiyang, 550025, China.

Hongguan JiaoDepartment of Information Engineering, Guizhou University of Traditional Chinese, Guiyang, China.

Yihui ChaiDepartment of Preclinical Medicine, Guizhou University of Traditional ChineseMedicine, Guiyang, 550025, China.

Yunzhi ChenDepartment of Preclinical Medicine, Guizhou University of Traditional ChineseMedicine, Guiyang, 550025, China. chenyunzhi270@gzy.edu.cn.

Funding

Academic New Seedling Project of Guizhou University of Traditional Chinese Medicine Guike Cooperative Academic New Seedling [2023]-22Guizhou Provincial Basic Research Program(Natural Science) Qiankehe Foundation-ZK[2023]General 411

6 · The paper itself

Abstract

The T allele variant of TERT rs2736098 has been associated with an increased risk of lung cancer (LC), yet various studies have yielded inconsistent findings. The purpose of this study is to verify the association between the rs2736098 variant and LC risk, as well as to investigate the differences in this association across different ethnic groups (Caucasians and Asians), various LC subtypes, and distinct smoking statuses. A computer search was conducted for literatures published up to December 20, 2024, in PubMed, Embase, Web of Science, and MEDLINE databases. Data were analyzed using RevMan 5.3, while sensitivity analysis and publication bias were assessed using Stata 14.0. The stability of the results was evaluated with TSA software Registration number: CRD420251030755. The T allele variant of rs2736098 was associated with an increased risk of LC ([OR] = 1.22, 95%CI [1.18, 1.27]), and this association was observed in both Caucasians ([OR] = 1.17, 95%CI [1.14, 1.20]) and Asians ([OR] = 1.26, 95%CI [1.19, 1.34]), with a stronger association in Asians than in Caucasians (Subgroup differences: P = 0.03, I

Indexed as

Asian PeopleGenetic Predisposition to DiseaseLung NeoplasmsPolymorphism, Single NucleotideTelomeraseWhite PeopleAllelesHumansRisk FactorsSmokingTelomeraseTERT protein, humanLung cancerMeta-Analysisrs2736098TERT

Identifiers

PMID41286209

DOI10.1038/s41598-025-25536-w

PMCPMC12644772

What Socratic holds

Textmetadata

LicenceCC BY-NC-ND

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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 Socratic graph.