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Posted by on Jun 13, 2015 in Lung cancer | 0 comments

In a nutshell

The authors evaluated the relationship between the levels of a protein called TIMP-2 and overall survival in patients with non-small cell lung cancer (NSCLC). 

Some background

NSCLC is the most common type of lung cancer. Survival rates in NSCLC are poor despite recent developments in its treatment. Early diagnosis is important to achieve better patient outcome.

Biomarkers are naturally occurring substances or measurements that are associated with a disease and often used for predicting the outcome or progression of a disease. TIMP-2 is a protein known to stop the growth of lung cancer cells and may be an important biomarker in NSCLC. However, based on previously studies, the link between increased TIMP-2 levels and NSCLC outcomes remain controversial. Therefore, the value of TIMP-2 as a biomarker for NSCLC needs to be reassessed.

Methods & findings

The authors examined the correlation between TIMP-2 levels and survival in NSCLC patients.

The study included 399 patients with NSCLC, from 5 studies. The average age of the patients was 55-62 years. The average follow-up time of the studies was 25-35.5 months. TIMP-2 levels were measured in patients’ tumor samples or blood samples. Overall survival time was also measured.

The results suggest that high levels of TIMP-2 are linked with better patient outcome. Overall, the risk of death was reduced by 43% in patients with high levels of TIMP-2.

The bottom line

The authors concluded that increased levels of TIMP-2 were linked with improved overall survival in NSCLC. They suggest that measuring TIMP-2 could be useful for predicting patient outcome.

The fine print

The 5 studies were carried out in Asian patients. Therefore, it is not known whether results would be similar for other races.

Published By :

PLOS ONE

Date :

Apr 23, 2015

Original Title :

Prognostic Value of Tissue Inhibitor of Metalloproteinase-2 Expression in Patients with Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis.

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