In Real-World Analyses, Apalutamide Delivers Quicker Responses in Prostate Cancer
Benjamin Lowentritt, MD, discussed findings from real-world analyses looking at enzalutamide or abiraterone vs apalutamide in patients with metastatic castration-sensitive prostate cancer.
PC-3 human prostate cancer cells: © heitipaves - stock.adobe.com
While several agents exist for the treatment of metastatic castration-sensitive prostate cancer (mCSPC), little research exist comparing these drugs head-to-head. Two real-world analyses published in the Journal of Clinical Oncology sought to close this gap.
“It is a good problem to have. But when we have multiple different options, all of which are studied under their own trials, and their own specific sets of criteria,[they] are similar but hard to compare between, and we still are left with this question of, is there an option that may be somewhat better than another?” said Benjamin Lowentritt, MD, in an interview with Targeted OncologyTM.
The first study aimed to compare the rates of 90% decrease in prostate-specific antigen levels (PSA90) at 6 months among patients with newly diagnosed mCSPC who were treatment-naive to next-generation androgen receptor signaling inhibitors (ARSIs) and were initiated on either apalutamide (Erleada) or enzalutamide (Xtandi).1
A total of 332 patients were identified in the apalutamide group and 383 patients in the enzalutamide group.By 6 months after the index date, 81.0% of patients in the apalutamide group and 75.2% of patients in the enzalutamide group had at least 1 PSA test. A significantly higher proportion of patients in the apalutamide group achieved a PSA90 response by 6 months compared with the enzalutamide group (62.8% vs 49.6%; P =.004).The median time to achieve PSA90 response was 3.5 months for the apalutamide group and 6.1 months for the enzalutamide group.
The second study had a similar goal of comparing PSA90 rates by 6 months; however, patients were treated with apalutamide or abiraterone acetate (Zytiga). Patients still had newly diagnosed mCSPC who were treatment-naive to next-generation ARSIs.2
A total of 356 patients were identified in the apalutamide group and 324 patients in the abiraterone group.By 6 months after the index date, 82.0% of patients in the apalutamide group and 73.5% of patients in the abiraterone group had at least 1 PSA test. A significantly higher proportion of patients in the apalutamide group achieved a PSA90 response by 6 months compared to the abiraterone group (62.2% vs 41.6%; P <.001).The median time to achieve PSA90 response was 3.6 months for the apalutamide group and 10.3 months for the abiraterone group.
In the interview, Lowentritt, medical director of the Prostate Cancer Care Program at Chesapeake Urology Associates, discussed these studies and their implications for prostate cancer treatment practices.
Benjamin Lowentritt, MD
Targeted Oncology: What are some of the unmet needs among patients in the population that these studies focused on?
Lowentritt: We have this wealth of opportunity and almost [an] excess of options for patients that have advanced prostate cancer that are presenting with metastatic castrate-sensitive disease. It is a good problem to have. But when we have multiple different options, all of which are studied under their own trials, and their own very specific sets of criteria,[they] are similar, but hard to compare between, and we still are left with this question of, is there an option that may be somewhat better than another?
The use of real-world evidence is trying to answer some of those questions. We are unlikely to get head-to-head trials that look to compare 2 of these medications. But this is a 1 of several looks that we have done have some real-world evidence data to try to get to a question of, are there differences in the in the experience that we are seeing for how [patients]are responding to some of these different options?
Has any previous research identified that specific agents are more effective in specific patient demographics or for certain biomarkers?
Not specifically looking at answering those questions like, is there a marker that might differentiate who is better for one vs the other? [It is] one of the levels of investigation that I think should happen in the future. But no, unfortunately, we have not seen that kind of evaluation done.
The narrative around these treatments is often that they are similar. And these are not the only 2 agents; there are others in the space. The idea is [that] they all wrote work roughly the same, and therefore should have roughly the same outcomes. I think we are seeing that that just is not necessarily true. Now, I do not know why that is. Maybe this is not purely a matter of drug effect. It may be better persistence on therapy, maybe there is more tolerance, maybe for some reason, there is an access issue that is better for 1 vs another. This data set does not answer the question as to why there is this difference. All it says is that there is a difference. And I do think further evaluation of the datasets and the patients can help us determine that.
It should be noted that this is not the first look we have had at this type of data and even as the data set has grown, and as we have refined it, as far as what questions we are able to answer and how detailed we can get. Some of these findings have remained consistent throughout as time goes on. This is more and more powerful information to suggest some real differences.
What was the methodology of these studies? How did you collect the data?
These studies looked at a dataset from a number of larger community-based urology practices that treat advanced prostate cancer and was a data that was extracted from electronic medical records [EMR], and then matched with claims-based data as well. We were able to pull out more than just straight EMR data but also see from a claims system tovalidate the patients who are in the disease state where we think they are and maybe try to answer some of the limitations we typically have with pure EMR-based data extractions.
We set a number of criteria to establish definitions of what it meant to be newly diagnosed, what it meant to be de novo metastatic, which meant they had to have the have the diagnosis of metastases within a quick timeframe of their first diagnosis of prostate cancer. Then,[patients starting] on therapy had to have a certain amount of information [before starting]. Then, we had to have at least 12 months of follow-up data with at least 1 or 2 PSA [tests]subsequent to their diagnosis, so we were able to see the level of decline and track those patients and determine, at least, their initial response. We followed them out until they either switched to a different medication, or there was some other event that would be considered progression.
Could you summarize your findings?
[In the first study, patients] were closely matched. We had over 300 patients in each group. What we were able to see is that the PSA90, roughly 63% of people in the apalutamide arm did achieve a PSA90, whereas about 50% of patients in the enzalutamide arm achieved that. There was the separation in how quickly patients were achieving a PSA90. We have shown in multiple looks at similar data that those differences seem to persist even as both groups continue to grow a little bit, that there do appear to be in these real-world datasets, more patients are responding to achieving a PSA90 with apalutamide.
[The second study also included patients with] de novo metastatic castration-sensitive prostate cancer patients that [were] being treated with their first-line therapy of [androgen deprivation therapy (ADT)] plus apalutamide or ADT plus abiraterone and prednisone.
It is also the dataset from community urology groups and matched claims-based data. We were able to then track and see the PSA decline. Again, [the arms were]similarly matched, over 300 patients in each arm. What we saw was that in this dataset, about 62% of the apalutamide patients achieved a PSA90 in the first 6 months. A little under 42% achieved a PSA90 in the abiraterone and prednisone [arm].
This is also data that mirrors some of the prior work that we have done with this group.We are seeing this consistent difference between the PSA90 response and these patients. It should be said that it says this is talking about the depth of response, but also in a quick timeframe, because this is in the first 6 months. So, that is a measure that has been validated as an important measure of early efficacy and a predictor of long-term survival measures in other trials. It is something that I think is an important piece of information for [physicians] to understand when they are trying to figure out the best option for patients.
Based on these findings, would you consider any implications for physicians when they are seeing patients with this disease state and presenting at this point?
I think there is still a lot of discretion to the individual physician when they are making these decisions. For many of us, there may be particular medical reasons, comorbid conditions, drug-drug interactions, but often, those differences do not exist.I think the availability of real-world evidence like this is helping [physicians] distinguish when they are choosing an option that might be best for their patient. Certainly, this is not to the level of a placebo-controlled, double-blinded, prospective trial. But we are probably never going to have that level of data to answer some of these questions. I think it is helpful for [physicians] to understand that this data is out there and certainly may help in making treatment decisions.
What is the importance of sourcing data from community practices in real-world analyses like these?
Community sites may be involved in research, and so their patients may have access to this. Typically, patients that are included in clinical trials are often a narrow part of the overall patient community and do not always reflect what we see in the community. Sometimes they are international, sometimes they are lacking in racial or ethnic backgrounds.When we look at this [data], we are looking at community practices across the country that have the makeup of what we would expect to see in the community. There tends to be a higher number of minorities, of people with different diverse backgrounds and races in these datasets, higher than what we see in in many of the clinical trials. I think it is important to be able to say, this is a real-world dataset, this is real-world evidence.
There are certainly limitations to what we can expect from that because it is not as controlled as a clinical trial. But with the emergence of electronic medical records, with the emergence of specific kinds of discrete data points that we can now extract, and frankly, with more sophistication of these statistical models and ability to compare groups, we are getting closer to being able to say that the data is on par with much of what we could get prospectively. We will never get there fully because there is always the potential for data to get a little bit off when we are not looking at it in a prospective manner. But this is not your typical historical, retrospective chart pull review that we have seen in the past. This is able to build models and pull out a number of different data points, so there is no risk of cherry picking or certain practices that might make the data less valid. It is getting us closer and closer to that gold standard of data. I think because of that, it is much more powerful and is helping create more feedback for the provider who is just trying to make the best decision in their community.
