Eric Pujade-Lauraine, MD, PhD, on First-Line Maintenance Therapy in Ovarian Cancer
SGO 2021 Virtual Annual Meeting on Womens Cancer
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
Vicky Makker, MD, of Memorial Sloan Kettering Cancer Center, discusses phase III findings showing that lenvatinib plus pembrolizumab may improve overall and progression-free survival, as well as overall response rate, compared with treatment of physician’s choice for advanced endometrial cancer. These results were achieved regardless of mismatch repair status following platinum-based chemotherapy (ID #10191).
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
Shannon N. Westin, MD, of The University of Texas MD Anderson Cancer Center, discusses phase II results from the ENPAC trial, which showed the combination of enzalutamide, paclitaxel, and carboplatin yielded promising clinical outcomes in chemotherapy-naive advanced or recurrent endometrioid cancer (ID # 10244).
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).