Rebecca S. Kristeleit, MD, PhD, on Relapsed Ovarian Cancer: Rucaparib vs Chemotherapy
SGO 2021 Virtual Annual Meeting on Womens Cancer
Rebecca S. Kristeleit, MD, PhD, of the University College London and UCL Cancer Institute, discusses efficacy and safety results from the phase III ARIEL4 study, which showed that rucaparib improved progression-free survival vs standard-of-care chemotherapy in patients with BRCA-mutated, platinum-resistant, or platinum-sensitive relapsed ovarian cancer (ID #10191).
The ASCO Post Staff
Eric Pujade-Lauraine, MD, PhD, of Hôpital Hôtel-Dieu, discusses results from the PAOLA-1ENGOT-ov25 trial on the use of homologous recombination–repair mutation gene panels and whether they can predict the efficacy of olaparib plus bevacizumab in first-line maintenance therapy for patients with ovarian cancer (ID# 10224).
The ASCO Post Staff
Lauren Thomaier, MD, of the University of Minnesota, discusses the genetic variants found to be associated with an increase in chemotherapy-induced neuropathy symptoms in a cohort of gynecologic cancer survivors. Combining these variants with clinical characteristics may provide an important treatment tool (ID# 10253).
The ASCO Post Staff
Dana M. Roque, MD, of the University of Maryland Medical Center, discusses phase II results showing that weekly ixabepilone plus biweekly bevacizumab may improve overall response rate as well as progression-free and overall survival for women with platinum-resistant or -refractory ovarian, fallopian tube, and primary peritoneal cancers, a population in need of treatment choices.
The ASCO Post Staff
Charles N. Landen, MD, of the University of Virginia, discusses results from the first clinical trial in ovarian cancer to demonstrate that neither a BRCA1/2 mutation nor a homologous recombination deficiency improves sensitivity to a therapeutic PD-L1 blockade in patients receiving atezolizumab vs placebo combined with carboplatin, paclitaxel, and bevacizumab for newly diagnosed disease (ID #10240).
The ASCO Post Staff
Brittany A. Davidson, MD, of Duke University, discusses the development and validation of the GO-POP model (Gynecologic Oncology Predictor of Postoperative opioid use), an individualized patient-centered predictive tool designed to help avoid overprescribing pain medications (ID# 10253).
