Jbain, it was here. I've quoted the relevant remarks and the link is below, from Dec. 2015 conf. call.
GZ is George Zavoico
GZ: ”Re: SUNRISE, there have been a couple of interesting & unfortunate events with some other companies where OS in the placebo arm of a trial has been much longer than expected. What are you seeing in that regard, because SUNRISE has been going on now for about 2 years now. What kind of advances have you seen in the SOC that might either make us more confident, or maybe a little bit more worried, about the possibility of having a surprise like that?” Steve King: I can start off and maybe Joe can add in, but when we designed the SUNRISE study we did take into account the variability that had been seen in the docetaxel studies that had been reported up to that point. I don’t think we’ve seen any really significant variations from that as over time as more readouts have come. So, that’s one thing that we did take into account, that we were toward the upper end of what have been previously reported for docetaxel. Secondly, when we powered the study, in the Ph2 study we saw about a 4mos. difference in median OS, and the SUNRISE study was designed to really show a statistical difference even at 2mos; we built in some powering assumptions we think will give us some opportunity there should be arms behave in a way that was little bit unexpected. So, we’ve tried to hedge against that going into the stage design and we think we’re in good shape and now it’s just a matter of getting the readouts - we’re little under 2yrs right now from when we started to study, so at this point there’s really nothing more we can learn from the ongoing operations of the SUNRISE trial itself. Joe Shan: George, obviously it's a very dynamic field right now. As Steve mentioned, we tried to make the SUNRISE design in such a way that it's as homogenous as practical. We obviously have some stratification criteria built in and some preplanned, subgroup analyses that are going to be pre-specified. Probably the biggest change in the landscape since we started enrollment is the approval of checkpoint inhibitors in this space, and we probably have patients that have received checkpoint therapy, and if there's an imbalance between the 2 arms of the study the subgroup analysis should account for that. But, it’s something that’s really impossible to predict how the changing SOC is going to effect the results of the control arms - this is why we have to run double-blind. Probably one predictor would be if we reach the number of interim events necessary to trigger the interim analyses, and the general projections that can give us some a little bit of confidence that these aren't too different than what we have previously seen.
Market Data 
Markets 
AI
