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Prognostic Value of TGF-β in Lung Cancer: Systematic Review and Meta-analysis

Overview
Journal BMC Cancer
Publisher Biomed Central
Specialty Oncology
Date 2019 Jul 17
PMID 31307405
Citations 44
Authors
Affiliations
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Abstract

Background: Lung cancer is the most important cause of cancer-related deaths worldwide and the overall survival of patients with non-small cell lung cancer has not improved. Transforming growth factor beta or TGF-β is a polypeptide member of the transforming growth factor beta superfamily of cytokines, while far fewer clinical studies addressing the association between TGF-β expression and the disease prognosis have been reported up to now. Therefore, our meta-analysis aims to determine the prognostic significance of TGF-β expression in lung cancer patients.

Methods: PubMed, EMBASE, the Web of Science and China National Knowledge Infrastructure (CNKI) databases were searched for full-text literature citations. We applied the hazard ratio (HR) with 95% confidence interval (CI) as the appropriate summarized statistics. Q-test and I statistic were used to estimate the level of heterogeneity. The publication bias was detected by Begg's test and Egger's test.

Results: Eight eligible studies involving 579 patients were selected for this meta-analysis. The combined HR for the eight eligible studies was 2.17 (95% CI: 1.71-2.77, P < 0.00001) and heterogeneity of overall prognosis was relatively low (I = 14.2%, P = 0.319). We further undertook the subgroup analysis including assessment of the association between TGF-β expression and pathology of the lung cancer, treatment and quantity of sample in studies. All the results revealed that a significantly high TGF-β expression in patients was an indicator of poor survival. Neither Begg's test nor Egger's test found publication bias in any analysis.

Conclusions: The present evidence indicates that TGF-β expression can significantly predict the worse prognosis in patients with lung cancer. The findings of our meta-analysis may be confirmed in the future by the use of more updated review pooling and additional relevant investigations.

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