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Gut. 2010 Mar;59(3):341-7. doi: 10.1136/gut.2009.188946. Epub 2009 Oct 15.

Visceral fat area is an independent predictive biomarker of outcome after first-line bevacizumab-based treatment in metastatic colorectal cancer.

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1
Department of Radiology, Georges-Francois Leclerc Cancer Cente, Dijon, France.

Abstract

BACKGROUND:

Adipose tissue releases angiogenic factors that may promote tumour growth.

OBJECTIVE:

To determine whether body mass index (BMI), subcutaneous fat area (SFA) and visceral fat area (VFA) are associated with outcomes in patients given first-line bevacizumab-based treatment for metastatic colorectal cancer (MCC). Patients CT was used to measure SFA and VFA in 120 patients with MCC who received bevacizumab-based treatment (bevacizumab group, n=80) or chemotherapy alone (chemotherapy group, n=40) as first-line treatment. Associations linking BMI, SFA and VFA to tumour response, time-to-progression (TTP) and overall survival (OS) were evaluated.

RESULTS:

In the bevacizumab group, median follow-up lasted for 24 months (3-70). BMI, SFA and VFA values above the median (ie, high BMI, high VFA and high SFA) were significantly associated with absence of a response. TTP was shorter in patients with high BMI (9 vs 12 months; p=0.01) or high VFA (9 vs 14 months; p=0.0008). High VFA was associated with shorter OS (p=0.0493). By multivariate analysis, high VFA was independently associated with response, TTP and OS (HR=7.18, p=0.008, HR=5.79, p=0.005 and HR=2.88, p=0.027, respectively). In the chemotherapy group, median follow-up lasted for 30 months (4-84). BMI, SFA and VFA were not associated with response, TTP or OS. In the whole population, interaction between VFA and bevacizumab administration was significant for response (OR=3.31, p=0.005) and TTP (HR=1.64, p=0.022), thereby confirming the results.

CONCLUSION:

This study provides the first evidence that high VFA independently predicts a poorer outcome in patients given first-line bevacizumab-based treatment for MCC. However, this predictive biomarker needs to be validated in a different dataset.

PMID:
19837679
DOI:
10.1136/gut.2009.188946
[Indexed for MEDLINE]
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