Literature DB >> 24680585

Measurements of adiposity as clinical biomarkers for first-line bevacizumab-based chemotherapy in epithelial ovarian cancer.

Katrina N Slaughter1, Theresa Thai2, Shayla Penaroza2, Doris M Benbrook2, Elangovan Thavathiru2, Kai Ding2, Tina Nelson2, D Scott McMeekin2, Kathleen N Moore2.   

Abstract

OBJECTIVE: There is a lack of reliable indicators to predict who will benefit most from anti-angiogenic therapy, such as bevacizumab. Recognizing obesity is associated with increased levels of VEGF, the main target of bevacizumab, we sought to assess if adiposity, measured in terms of BMI, subcutaneous fat area (SFA), and visceral fat area (VFA) was prognostic.
METHODS: Reviewed 46 patients with advanced EOC who received primary treatment with bevacizumab-based chemotherapy (N=21) or chemotherapy alone (N=25) for whom complete records, CT prior to the first cycle of chemo, and serum were available. CT was used to measure SFA and VFA by radiologists blinded to outcomes. ELISA was used to measure serum levels of VEGF and angiopoietin-2 in the bevacizumab group.
RESULTS: BMI, SFA, and VFA were dichotomized using the median and categorized as "high" or "low". In the bevacizumab group median PFS was shorter for patients with high BMI (9.8 vs. 24.7months, p=0.03), while in the chemotherapy group median PFS was similar between high and low BMI (17.6 vs. 11.9months, p=0.19). In the bevacizumab group patients with a high BMI had higher median levels of VEGF and angiopoietin-2, 371.9 vs. 191.4pg/ml (p=0.05) and 45.9 vs. 16.6pg/ml (p=0.09) respectively. On multivariate analysis neither BMI, SFA, nor VFA were associated with PFS (p=0.13, p=0.86, p=0.16 respectively) or OS (p=0.14, p=0.93, p=0.28 respectively) in the chemotherapy group. However, in the bevacizumab group BMI was significantly associated with PFS (p=0.02); accounting for confounders adjusted HR for high vs. low BMI was 5.16 (95% CI 1.31-20.24). Additionally in the bevacizumab group SFA was significantly associated with OS (p=0.03); accounting for confounders adjusted HR for high vs. low SFA was 3.58 (95% CI 1.12-11.43).
CONCLUSION: Results provide the first evidence in EOC that patients with high levels of adiposity may not derive benefit from bevacizumab and that measurements of adiposity are likely to be a useful biomarker.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Angiogenesis; Clinical biomarker; Subcutaneous fat; Visceral fat

Mesh:

Substances:

Year:  2014        PMID: 24680585     DOI: 10.1016/j.ygyno.2014.01.031

Source DB:  PubMed          Journal:  Gynecol Oncol        ISSN: 0090-8258            Impact factor:   5.482


  23 in total

Review 1.  Impact of obesity on chemotherapy management and outcomes in women with gynecologic malignancies.

Authors:  Neil S Horowitz; Alexi A Wright
Journal:  Gynecol Oncol       Date:  2015-04-12       Impact factor: 5.482

2.  Anthropometer3D: Automatic Multi-Slice Segmentation Software for the Measurement of Anthropometric Parameters from CT of PET/CT.

Authors:  Pierre Decazes; David Tonnelet; Pierre Vera; Isabelle Gardin
Journal:  J Digit Imaging       Date:  2019-04       Impact factor: 4.056

Review 3.  Metabolic risk factors and mechanisms of disease in epithelial ovarian cancer: A review.

Authors:  Eric R Craig; Angelina I Londoño; Lyse A Norian; Rebecca C Arend
Journal:  Gynecol Oncol       Date:  2016-10-15       Impact factor: 5.482

Review 4.  Bevacizumab: a review of its use in advanced cancer.

Authors:  Gillian M Keating
Journal:  Drugs       Date:  2014-10       Impact factor: 9.546

5.  Quantitative measurement of adiposity using CT images to predict the benefit of bevacizumab-based chemotherapy in epithelial ovarian cancer patients.

Authors:  Yunzhi Wang; Theresa Thai; Kathleen Moore; Kai Ding; Scott McMeekin; Hong Liu; Bin Zheng
Journal:  Oncol Lett       Date:  2016-05-31       Impact factor: 2.967

Review 6.  Bevacizumab use in the frontline, maintenance and recurrent settings for ovarian cancer.

Authors:  Carolyn E Haunschild; Krishnansu S Tewari
Journal:  Future Oncol       Date:  2019-11-20       Impact factor: 3.404

7.  A two-step convolutional neural network based computer-aided detection scheme for automatically segmenting adipose tissue volume depicting on CT images.

Authors:  Yunzhi Wang; Yuchen Qiu; Theresa Thai; Kathleen Moore; Hong Liu; Bin Zheng
Journal:  Comput Methods Programs Biomed       Date:  2017-03-21       Impact factor: 5.428

8.  Measurements of adiposity as prognostic biomarkers for survival with anti-angiogenic treatment in epithelial ovarian cancer: An NRG Oncology/Gynecologic Oncology Group ancillary data analysis of GOG 218.

Authors:  K N Slaughter Wade; M F Brady; T Thai; Y Wang; B Zheng; R Salani; K S Tewari; H J Gray; J N Bakkum-Gamez; R A Burger; K N Moore; M A Bookman
Journal:  Gynecol Oncol       Date:  2019-08-10       Impact factor: 5.482

Review 9.  A weighty problem: metabolic perturbations and the obesity-cancer link.

Authors:  Ciara H O'Flanagan; Laura W Bowers; Stephen D Hursting
Journal:  Horm Mol Biol Clin Investig       Date:  2015-08

10.  Obesity Contributes to Ovarian Cancer Metastatic Success through Increased Lipogenesis, Enhanced Vascularity, and Decreased Infiltration of M1 Macrophages.

Authors:  Yueying Liu; Matthew N Metzinger; Kyle A Lewellen; Stephanie N Cripps; Kyle D Carey; Elizabeth I Harper; Zonggao Shi; Laura Tarwater; Annie Grisoli; Eric Lee; Ania Slusarz; Jing Yang; Elizabeth A Loughran; Kaitlyn Conley; Jeff J Johnson; Yuliya Klymenko; Lana Bruney; Zhong Liang; Norman J Dovichi; Bentley Cheatham; W Matthew Leevy; M Sharon Stack
Journal:  Cancer Res       Date:  2015-11-16       Impact factor: 12.701

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.