Bradley J. Monk, MD: I want to finish our conversation by pivoting away from the NCCN [National Comprehensive Cancer Network] Guidelines and talking about what’s new and evolving. A paper that Jonathan Ledermann and I presented at SGO [Society of Gynecologic Oncology Annual Meeting on Women’s Cancer] is a paper called JAVELIN OVARIAN 100. I think all of you are aware that there are 3 established ways to make checkpoint inhibitors better. One is added to chemotherapy. And JAVELIN OVARIAN 100 addresses that. I’m going to go next to you, Katie Moore. The second way is to add an anti-VEGF to a checkpoint inhibitor. The third way is to add a CTLA4, another checkpoint inhibitor. We don’t have a lot of data on that, although NRG Oncology’s NIVO [nivolumab] vs NIVO-IPI [nivolumab-ipilimumab] study was just published.
JAVELIN OVARIAN 100 was presented at SGO. Quite frankly, it was a study that to me was very disappointing because, as you know, we can add chemotherapy to checkpoint inhibitor in triple-negative breast cancer, in lung cancer, in lots of opportunities. We just decided to do it in ovarian cancer. I get it; It was a ready, shoot, aim approach, rather than aiming before we took on this massive endeavor. But there were 998 patients on carboplatin-paclitaxel, and then we added avelumab to it, either avelumab in the maintenance phase—because that’s really what we believe in, maintenance—or with chemotherapy and in maintenance.
The study was stopped by the Data Safety Monitoring Board. In the maintenance arm, the hazard ratio, when you add checkpoint inhibitor and maintenance, avelumab did not overlap 1, but it was on the wrong side. It was a hazard ratio of 1.43, with a 95% confidence interval of 1.05 and 1.95. So it suggested—didn’t test the hypothesis but suggested—that maintenance checkpoint inhibitor was harmful after response to chemotherapy. That was surprising. When it was added to chemotherapy and maintenance, there was a hazard ratio of 1.14. We took a deep dive into the biomarkers, and some of the biomarkers were presented here, PD-L1 expression specifically, and there was no real signal. And PD-L1 expression measurements are complicated. You can either measure the immune cells or the tumor cells. About a quarter of the immune cells were positive, about a quarter of the tumor cells were positive, and there was a lot of overlap in the immune cells and the tumor cells. And 9% were negative. So it wasn’t helpful. We’re doing RNA-seq [RNA-sequencing] and other biomarkers. We’ll probably have those for you at the IGCS [International Gynecologic Cancer Society], Tom Krivak, where you’re the program chair. So that was disappointing.
Transcript edited for clarity.