Alan Bryce, MD: Dr Heath, as the audience processes this data, again, it’s hard to differentiate among these drugs. Is there real-world data to help [with a] comparative analysis of these AR [androgen receptor] inhibitors that might help the clinician think about these 3 drugs and [guide] treatment selection?

Elisabeth Heath, MD, FACP: That’s a great question, and we’re seeing in our field more reporting of these real-world data. You could [take a] hard line and ask, what kind of value? As a practicing clinician I value this because it gives a different feel of how people interpret the data. Long have we known of level 1 data that we go, yeah, that’s the right answer on the test, but then you go into your clinic and realize, that is hard to translate on any given day, for any particular patient. When you do look at these large data sets, you see what your colleagues are doing. One of them was reported at ASCO GU [American Society of Clinical Oncology Genitourinary Symposium], using a registry of sorts. This is the DEAR study [NCT05362149] [from which Daniel George, MD] was able to report the real-world use of darolutamide vs enzalutamide vs apalutamide. They looked at this precision-point, specialty urology–based registry and at a retrospective observational chart review. It could have multiple limitations, but the data showed that darolutamide, when you’re looking at specific end points that Dr Zhang was mentioning—such as staying on treatment for that duration before metastasis occurs or that you have a lower discontinuation rate because of an adverse event—that with both end points, it favored darolutamide. It’s in a way in line with what has been reported, not just initially, but also long-term. Some of the post hoc…[reporting], I just say, well this is good; it means people are taking the data as is. I think the experience is perhaps mimicking what we’re seeing in practice, for those of us who use multiple compounds.

Another registry was also reported, and this was not necessarily from registry, but it’s from 9 UK [United Kingdom] sites looking at this. It was the RECORD study, so it’s real-world data based out of the UK. This is interesting because it’s the same look at outcomes. Here though, [it’s] specifically looking at darolutamide, and kind of looking at it from a doubling-time standpoint. To echo what Dr Posadas was saying, I think those of us who have patients that are doubling time, 6 months and higher, we tend to get less nervous. We’re like, OK, I think everything’s OK, but the minute you’re having the pretreatment doubling time of less than 6 months, we’re starting to worry. Perhaps in today’s world, a PSMA PET [prostate-specific membrane antigen positron emission tomography scan] might show more than 1 lonely retroperitoneal lymph node. The data shows activity in both settings; it’s certainly very good, and it’s not even reached in terms of their end point of PFS [progression-free survival], in the greater than 6 months [area]. However you cut the data, it’s showing favorable results ... had done a recent comparison, and this is where we get a little stuck—yes, we shouldn’t compare any of these, they’re all stand-alone, big, well-designed studies, and they all have their own limitations—but she actually reported an indirect comparison of these 3 agents, in this particular group of nonmetastatic CRPC [castration-resistant prostate cancer]. They used a method known as matching-adjusted indirect comparison. This is where I say, boy oh boy, am I glad there are smart statisticians out there who can come up with such innovation to help us. It’s a very intriguing paper; I encourage everyone to take a peek at it. When you’re looking at what is reported, and at least matching up the data-set points, whether it’s AEs [adverse events] or some of their end points, and doing the best you can to indirectly compare them, if you look at darolutamide, it’s showing less falls, less fracture, less rash. So is that potentially fraught with limitations? Of course, but in practice, [you’re] doing it in your head. It’s a little bit of mental gymnastics in your head. Would this help me? Well, it’s a nice piece of data that I would integrate with what Dr Zhang had mentioned, but at the end of the day, you’re going to pick your drug based on the potential adverse events. That might be worse for one patient with a set of comorbidities vs another. If somebody is already kind of weebly-wobbly and you’re worried about that person falling, they’re already on phosphonates, and you’re like, oh no, it’s an ice storm in Michigan, you might think twice about the selection. If you have somebody with poorly controlled hypertension, you might think twice about the selection. I think the good news here is, our colleagues as well as ourselves are integrating the data in a way that I think we expect, and when you take a brief snapshot, you can say that perhaps one is favoring the other. But if that doesn’t fit for your patient, that is OK, you have other options.

Transcript edited for clarity.