Correlation of Imaging and Plasma Based Biomarkers to Predict Response to Bevacizumab in Epithelial Ovarian Cancer (EOC)
Open accessAbstract
Purpose Increasing measures of adiposity have been correlated with poor oncologic outcomes and a lack of response to anti-angiogenic therapies. Limited data exists on the impact of subcutaneous fat density (SFD) and visceral fat density (VFD) on oncologic outcomes. This ancillary analysis of GOG-218, evaluates whether imaging markers of adiposity were predictive biomarkers for bevacizumab (bev) use in epithelial ovarian cancer (EOC).Patients and methods There were 1249 patients (67%) from GOG-218 with imaging measurements. SFD and VFD were calculated utilizing Hounsfield units (HU). Proportional hazards models were used to assess the association between SFD and VFD with overall survival (OS).Results Increased SFD and VFD showed an increased HR for death (HR per 1-SD increase 1.12, 95% CI:1.05-1.19 p = 0.0009 and 1.13, 95% CI: 1.05-1.20 p = 0.0006 respectively). In the predictive analysis for response to bev, high VFD showed an increased hazard for death in the placebo group (HR per 1-SD increase 1.22, 95% CI: 1.09-1.37; p = 0.025). However, in the bev group there was no effect seen (HR per 1-SD increase: 1.01, 95% CI: 0.90-1.14) Median OS was 45 vs 47 months in the VFD low groups and 36 vs 42 months in the VFD high groups on placebo versus bev, respectively.Conclusion High VFD and SFD have a negative prognostic impact on patients with EOC. High VFD appears to be a predictive marker of bev response and patients with high VFD may be more likely to benefit from initial treatment with bev.
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Unlike for PARP inhibitors, there are no clinically approved biomarkers to predict responses of women with ovarian cancer to the anti-angiogenic bevacizumab.
“Unlike for PARPis, there are no clinically approved biomarkers to predict responses of women with ovarian cancer to the anti-angiogenic bevacizumab, although numerous studies have focused on this area (Buechel et al., 2021; Gao et al., 2021; Hsu et al., 2021).”
From Three-dimensional modelling of ovarian cancer: from cell lines to organoids for discovery and personalized medicine (2022) · cites this paper as Buechel et al., 2021
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References 30 · Cited by 17
- Authors
- Buechel, M. E., Enserro, D., Burger, R. A., Brady, M. F., Wade, K., Secord, A. A., Nixon, A. B., Mirniaharikandehei, S., Liu, H., Zheng, B., O'Malley, D. M., Gray, H., Tewari, K. S., Mannel, R. S., Birrer, M. J., & Moore, K. N.
- Affiliations
- OU Health Stephenson Cancer Center (US)
- Roswell Park Comprehensive Cancer Center (US)
- University of Pennsylvania (US)
- Ochsner Medical Center (US)
- Duke University (US)
- University of Oklahoma (US)
- University of Washington (US)
- University of California, Irvine (US)
- University of Alabama at Birmingham (US)
- Corresponding author
- Buechel, Megan E.
- Enserro, Danielle
- Burger, Robert A.
- Brady, Mark F.
- Wade, Katrina
- Secord, Angeles Alvarez
- Nixon, Andrew B.
- Mirniaharikandehei, Seyedehnafiseh
- Liu, Hong
- Zheng, Bin
- Gray, Heidi
- Tewari, Krishnansu S.
- Mannel, Robert S.
- Birrer, Michael J.
- Moore, Kathleen N.
- ORCID
- Venue
- Gynecologic Oncology
- Publisher
- Elsevier BV
- Published
- 2021-05
- Volume
- 161
- Issue
- 2
- Pages
- 382-388
- ISSN
- 0090-8258 (ISSN-L)
- PMC
- PMC8327185
- OpenAlex
- W3135115077
- Cited by
- 17
- References
- 30
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 2 · 2023: 1 · 2022: 6 · 2021: 1 · 2020: 1
- FWCI
- 2.16
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Gynecologic Oncology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Funders
- National Cancer Institute
- University of Oklahoma Stephenson Cancer Center
- Topics
- Health Sciences › Medicine › Reproductive Medicine › Ovarian cancer diagnosis and treatment
- Health Sciences › Medicine › Oncology › Cancer Risks and Factors
- Health Sciences › Medicine › Oncology › Inflammatory Biomarkers in Disease Prognosis
- Keywords
- epithelial ovarian cancer, bevacizumab, adiposity, predictive biomarkers, overall survival, CT imaging biomarkers, Hounsfield units
- MeSH terms
- Bevacizumab, Antineoplastic Agents, Immunological, Carcinoma, Ovarian Epithelial, Adult, Aged, Double-Blind Method, Female, Humans, Middle Aged, Ovarian Neoplasms, Tomography, X-Ray Computed, Biomarkers, Tumor, Survival Analysis, Treatment Outcome, Subcutaneous Fat, Intra-Abdominal Fat, Adiposity
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