scholarly journals Treatment Decisions and Survival in Ovarian Cancer

2018 ◽  
Author(s):  
Hugo de Seabra Martins Nunes ◽  
Alexandra Mayer ◽  
Ana Francisca Jorge ◽  
Teresa Margarida Cunha ◽  
Ana Opinião ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Treatment Decisions

How does 18f-FDG PET-CT scan affect clinical judgment and change treatment decisions in patients with epithelial ovarian cancer?

2010 ◽  
Vol 28 (15_suppl) ◽  
pp. 5053-5053
Author(s):  
F. Selcukbiricik ◽  
M. Ozguroglu ◽  
M. A. Ozturk ◽  
N. Ozgur ◽  
H. Turna ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Ct Scan ◽  
Epithelial Ovarian Cancer ◽  
Clinical Judgment ◽  
Fdg Pet ◽  
Treatment Decisions ◽  
Pet Ct ◽  
18F Fdg ◽  
Fdg Pet Ct ◽  
Pet Ct Scan

Staging early ovarian cancer: Impact on treatment decisions

2010 ◽  
Vol 46 (5) ◽  
pp. 856-858
Author(s):  
Ralph S. Freedman
Keyword(s):  
Ovarian Cancer ◽  
Treatment Decisions ◽  
Early Ovarian Cancer ◽  
Impact On Treatment

scholarly journals Organoids and epithelial ovarian cancer ‑ a future tool for personalized treatment decisions?

2021 ◽  
Vol 16 (2) ◽  
Author(s):  
Yagmur Sisman ◽  
Tine Schnack ◽  
Estrid Høgdall ◽  
Claus Høgdall
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Treatment Decisions ◽  
Personalized Treatment

Timing of referral to genetic counseling among women with gynecologic or breast cancer.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 1545-1545
Author(s):  
Amy J Bregar ◽  
Terri Febbraro ◽  
Katina Robison ◽  
Jennifer Scalia Wilbur ◽  
Jessica Kent Laprise ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Genetic Counseling ◽  
Cancer Patients ◽  
Early Stage ◽  
Treatment Decisions ◽  
Genetic Evaluation ◽  
Early Stage Breast Cancer ◽  
Breast Cancer Patients ◽  
Late Stages

1545 Background: The National Comprehensive Cancer Network (NCCN) has established guidelines delineating appropriate candidates for genetic counseling. While genetic predisposition is responsible for a small percentage of cancer, genetic referral at diagnosis may effect treatment decisions. We aim to determine factors associated with timing of referral in women with breast and gynecologic cancers. Methods: Patients from an academic women’s oncology program were identified who met a subset of NCCN referral criteria for genetic evaluation between 2004-2010 (ovarian cancer at any age, breast cancer ≤ 50 years of age, or uterine cancer < 50 years of age). A retrospective chart review was conducted. Statistics were analyzed using SAS v. 9.2 (SAS Institute, Cary, NC); categorical variables were compared by chi-square or Fisher's exact test and continuous variables were compared by ANOVA. The study was approved by the hospital Institutional Review Board. Results: 820 women with cancer (26% uterine, 38% breast, 35% ovarian) were included. The overall referral rate was 22%; more breast than gynecologic cancer patients were referred (34% vs. 28%, p<0.0001). Breast cancer patients were more often referred at diagnosis compared to women with uterine (p<0.0001) and ovarian cancer (p=0.007). Early stage breast cancer patients were more often referred at diagnosis compared to women with late stages (p=0.03). Among ovarian cancer patients, those with late stages were more often referred at diagnosis compared to women with early stages (p=0.02). Age at diagnosis, family history, and parity were not associated with timing of referral. Among women with breast cancer, 26% of referred patients had a prophylactic contralateral mastectomy compared to 8% of those not referred (p<0.0001). Conclusions: Genetic counseling is underutilized in breast and gynecologic malignancies. The timing of referral varies widely and genetic counseling may impact treatment decisions. Breast cancer diagnosis, early stage breast cancer, and late stage ovarian cancer are associated with earlier referral for genetic evaluation. Further research is needed to determine additional factors that may increase referral rates and impact timing of referral.

scholarly journals Treatment decisions in advanced ovarian cancer

1989 ◽  
Vol 60 (2) ◽  
pp. 155-156 ◽  
Author(s):  
MM Cody ◽  
ML Slevin
Keyword(s):  
Ovarian Cancer ◽  
Advanced Ovarian Cancer ◽  
Treatment Decisions

Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team

2017 ◽  
Vol 27 (2) ◽  
pp. 382-389 ◽  
Author(s):  
Signe Frahm Bjørn ◽  
Tine Henrichsen Schnack ◽  
Henrik Lajer ◽  
Ib Jarle Christensen ◽  
Lene Lundvall ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Multidisciplinary Team ◽  
Treatment Decisions ◽  
Cancer Surgery ◽  
Advanced Technology ◽  
Patients With Cancer ◽  
Primary Surgery ◽  
Primary Debulking Surgery ◽  
Gynecology And Obstetrics ◽  
Wide Range

ObjectiveProper planning of intervention and care of ovarian cancer surgery is of outmost importance and involves a wide range of personnel at the departments involved. The aim of this study is to evaluate the introduction of an ovarian surgery classification (COVA) system for facilitating multidisciplinary team (MDT) decisions.Materials and MethodsFour hundred eighteen women diagnosed with ovarian cancers (n = 351) or borderline tumors (n = 66) were selected for primary debulking surgery from January 2008 to July 2013. At an MDT meeting, women were allocated into 3 groups named “pre-COVA” 1 to 3 classifying the expected extent of the primary surgery and need for postoperative care. On the basis of the operative procedures performed, women were allocated into 1 of the 3 corresponding COVA 1 to 3 groups. The outcome measure was the predictive value of the pre-COVA score compared with the actual COVA performed.ResultsThe MDT meeting allocated 213 women (51%) to pre-COVA 1, 136 (33%) to pre-COVA 2, and 52 (12%) to pre-COVA 3. At the end of surgery, 168 (40%) were classified as COVA 1, 158 (38%) were classified as COVA 2, and 28 (7%) were classified as COVA 3. Traced individually, 212 (51%) patients were correctly preclassified at the MDT meeting and distributed into 110 (52%) COVA 1, 71 (52%) COVA 2, and 17 (32%) COVA 3. Analyzing the subgroup of patients with cancer, 164 (47%) were correctly preclassified. Regarding the International Federation of Gynecology and Obstetrics (FIGO) stages, the pre-COVA classification predicted the actual COVA group in 79 (49%) FIGO stages I to IIIB and in 85 (45%) FIGO stages IIIC to IV.ConclusionsThe COVA classification system is a simple and useful tool in the MDT setting where specialists make treatment decisions based on advanced technology. The use of pre-COVA classification facilitates well-organized patient care–relevant procedures to be undertaken. Pre-COVA accurately predicts the final COVA in 51% classified women.

scholarly journals PARP inhibitors in ovarian cancer: Clinical evidence for informed treatment decisions

2015 ◽  
Vol 113 (S1) ◽  
pp. S10-S16 ◽  
Author(s):  
Jonathan A Ledermann ◽  
Fatima El-Khouly
Keyword(s):  
Ovarian Cancer ◽  
Clinical Evidence ◽  
Treatment Decisions ◽  
Parp Inhibitors ◽  
Informed Treatment

Impact of extended cycles of chemotherapy on survival outcome in recurrent epithelial ovarian cancer

2020 ◽  
Vol 159 ◽  
pp. 346-347
Author(s):  
W.Y. Hwang ◽  
S.I. Kim ◽  
M. Lee ◽  
K. Kim ◽  
J.H. No ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Survival Outcome
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