Chapters Transcript Video Less Bench, More Bedside - Prostate Cancer Biomarkers for Clinicians Jeffrey Tosoian, MD, MPH Uh, thank you, Chad and thank you all so much for, for having me today. It's Um, you know, really exciting. It's you have such an awesome, awesome group there. I think I've, you know, more, more friends on faculty there than. Than anywhere other than maybe the places I trained and have been. So it's it's awesome to be joining you and uh lucky to call a lot of your friends. I appreciate the opportunity. I will go ahead and share my screen. And we can go into presenter mode, if we're looking OK, I will, we'll go ahead and get started, um, as Chad very kindly mentioned, um, you know, I am now on, on faculty at Vanderbilt since 2021, um, after having been at at Hopkins in Michigan and, um, you know, really developed an interest in Answer early detection biomarkers, um, and so I'm looking forward to talking with you today about prostate cancer biomarker testing really with a focus on the clinical side of things, um, and how we can help to use these tests to, to help our practice. And so my disclosures are listed here. This includes uh my role, as you see, as a co-founder and adviser to LinxDX which commercializes the the my prostate score 2.0, uh, which, which I will discuss. And so I'll start with an overview of biomarkers and. Just wanted to make sure that chat wasn't for me, um, with an overview of biomarkers, why we use them, how we can meaningfully interpret them clinically, and we'll talk about currently available biomarkers and proceed to bring their use together with MRI. So we hear about these all the time and have to ask what really is a biomarker. We'll define that as a characteristic that importantly is objectively measured as an indicator of normal or pathologic processes. So in our setting, we'll be talking about these tests as an indicator of clinically significant prostate cancer. And why do we use biomarkers in the setting of prostate cancer? Here we have the NCCN algorithm, only to reinforce that PSA is, of course, our first line test for prostate cancer screening. Yet we know the limitations of PSA as an isolated screening test. It's expressed by prosthetic epithelial cells, not cancer cells, so it lacks specificity for cancer, can be elevated due to a number of benign conditions. And under that traditional screening pathway in which patients with an elevated PSA underwent biopsy. The European trial taught us that 88% of biopsies performed for elevated PSA ultimately proved to be unnecessary, and that's an unacceptably high rate by by any measure. And so in response to that, guidelines have begun to suggest the use of MRI or biomarker tests to better define the probability of clinically significant cancers prior to proceeding to biopsy. And so when we ask, how do we look at these biomarkers, the CDC has laid out a framework to characterize them across three domains. Analytic validity takes place in the lab and is ultimately to ensure that a test is measuring what it aims to measure. Clinical utility asks whether the use of the test changes clinical decision making and improves outcomes, and we'll focus on clinical validity, which asks if the test is able to detect a difference between cases and non-cases. Validity is basically synonymous with terms like accuracy or diagnostic performance. And so we largely measure validity with these 4 metrics that are likely familiar to all. I will give a quick refresher on these um terms just to provide some context for our discussion today. And so, one important point is that all of these measures are, are always by definition, relative to a threshold value that categorize. result as positive or negative. And so when someone will often casually say, oh, PSA has a sensitivity of As for example, they're actually, because again, these measures are always in reference to A threshold value. And so with that established, this next point is something that really helped these terms to make sense to me, and that is that sensitivity and specificity are really not easily interpreted in the context of an individual patient. These are measures that make sense when we apply them to a population, whether that's our overall clinic, or even from a legislative standpoint, the overall population. On the other hand, NPV and PPV can be interpreted to an individual patient and do make sense in that regard. Another point is that sensitivity and specificity are measures inherent to a specific test, so they really should not vary too widely depending on the study population. On the other hand, predictive values we know are dependent on how prevalent the outcome is in the study population. So you want to make sure that the patient demographics are consistent with the, the study cohort, if you are referencing as when when relaying info to your patients. And so I will quickly go through these terms kind of more as a didactic. Um, sensitivity in three words, positivity in disease. It's the proportion of patients that test positive among those with the disease. In this case, grade group 2 and above prostate cancer. And so, a highly sensitive test, if negative, can therefore be used to rule out the disease. And this is where we get that mnemonic snout, saying a sensitive test with a negative result rules out. And so, looking at our standard framework where patients with a positive test would proceed to biopsy, and those with a negative test would defer biopsy, question becomes clinically, what does sensitivity really tell us in practice? And that is that if you use a given test in, let's say every patient that walks through your door with an elevated PSA, the sensitivity of that test will tell you the proportion of significant cancers that will be detected relative to if you had biopsied every patient. And so we can take this from from none other than than Doctor Rich, who joins us and says here, when I think about using a test in my entire practice or the overall population, I value high sensitivity. And when we ask why, They tell us, because if I use a test with 95% sensitivity in all of my patients to rule out a biopsy, that means I'll still detect 95% of the high grade disease I would have detected if I, I biopsied everyone. And, and that's right on. Um, and so, moving on to specificity here in three words. Again, these are just some things that have helped me to Have a working understanding of these terms. Negativity in health, so specificity is the proportion that will test negative among those without the disease. And so, a highly specific test when positive, is used to confidently rule in disease. And that's where the other mnemonic comes from, spin, a highly specific test with a positive result, rules in disease. And so in our context, specificity actually has a very clear clinical translation. Again, if we apply the test to an overall population, specificity tells us the proportion of unnecessary biopsies that will be avoided through using the test. And so bringing these two terms together, Chad correctly tells us that if he uses a test with 95% sensitivity and 40% specificity to decide who needs a biopsy, They'll then capture 95% of those significant cancers and avoid 40% of those unnecessary biopsies. And this is the, the trade-off that have made these tools like biomarkers and, and MRI um you know, viewed positively for, for clinical practice. Thankfully, NPV and PPV are are far more intuitive measures. They're interpretable on the level of the individual patient and therefore more useful in in counseling. This does come with the, the caveat that predictive values are dependent on the prevalence of the disease in the tested population. And so we need to ensure that the patient fits the profile of patients in the, in the studies used to calculate NPV and PPV. And so in, in very brief, as this is more familiar to all of us, NPV ultimately tells us the likelihood that a biopsy would in fact be negative or grade group 1 disease in a patient with a negative test. So if test A has 95% NPV, Mr. Smith has a negative test, if he undergoes biopsy, there's a 95% chance that it will not detect clinically significant cancer. And finally, PPV similarly intuitive, if test A has 60% PPV and the patient has a positive test, there's a 60% chance the biopsy will yield significant disease. And so, we'll take that summary with us as we look through the published data. As mentioned, sensitivity and specificity in form at the population level are clinical outcomes of cancers detected and unnecessary biopsies avoided respectively, NPV and PPV can inform the individual patient's risks, so long as their characteristics are aligned with the study cohort where those values were calculated. And so, let's talk about the currently available blood and urine-based biomarkers. We've established now that biomarkers like MRI are proposed for use in patients with a confirmed elevated PSA prior to biopsy, and the most recent NCCN guidelines now include 8 validated markers, up from 6 last year. And each of these, you know, really have been well validated to improve upon PSA and PSA based risk calculators like the PCPTRC or the PCBG um for detection of clinically significant disease. And we'll go over each of the, the available tests briefly in terms of their content and some of the clinical data based on our approach from a couple of, of recent reviews. And that was, that approach was simply to include validation studies that were performed in the appropriate clinical population. Those that reported on the outcome of clinically significant cancer, and those in which the sensitivity and specificity were reported, or they were able to be calculated from the, the raw data provided. And so here's a summary slide of those markers, which we'll come back to again. And I will, you know, move, move rather efficiently through these to ensure we have some time to chat, but obviously happy to come back at, at any point later. And so we'll first look at the 4K score test. It's one of the blood-based markers includes total PSA and 3 additional PSA related markers. The markers are combined with clinical factors. algorithm ultimately provide if they had. If you were to undergo a prostate biopsy. And we're of course. Just look broadly at the, at the data here, and we'll see a common theme arising across these markers. Here we can see that for the 4K score test across several testing cohorts, the sensitivity for significant disease is consistently 90% or higher, with similarly high NPVs and the specificity values ranging from 19 to 47%. And so, based on these data, as, as we discussed, application of this test to a clinical population would detect 90 to 96% of significant cancers relative to if every patient had undergone a biopsy, while avoiding roughly 20 to 50% of unnecessary biopsies. And here is the score report for the 4K test, providing the patient's individualized risk of detecting significant cancer, and also indicating that validated threshold for this test, which is 7.5%. Prostate Health index or Phi is another blood-based assay. It combines PSA in a mathematical equation with free and pro PSA to provide a risk score for prostate cancer. It does not include clinical factors, and again, we see that sensitivity values consistently range from 90% upwards with specificity spanning 12 to 40%. And even though, you know, there are certainly sufficient data for clinically significant disease, the, the phi score report on last check does actually still just provide the risk of overall cancer um as categorized based on some of the, the earlier data. So there's, there's some room for improvement in, in that score report. Uh, the, the ISO PSA test is a blood-based assay that partitions PSA and free PSA in a two-phase reagent system. The result is, is this test parameter K. and this is admittedly, to me, not the, the most intuitive of, of the tests, but, you know, the result can be converted to a more intuitive percentage risk of significant disease. Personalized to each given patient. And these data similarly reveal high sensitivity with specificity values in the 40% range. Stockholm 3 test was one of the new additions this year. It includes PSA, 4 other serum proteins, as well as several single nucleotide polymorphisms or snips, as well as clinical data to provide a percentage risk of significant disease. And since this was added to our guidelines after we had performed these reviews, this is not an exhaustive list of of those data, but similarly, we see sensitivity in the 90% range and specificity approximating 33%. I think we're we're seeing a trend emerging here. Um, the, the score report here does show an individualized risk percentage. We'll move on to the, the urine-based markers. The select MDX test is based on post-DRE urine, combines clinical factors with RNA expression of two cancer-related genes, HOC C6 and DLX1. The the validated cut point for select appears to sacrifice some sensitivity in favor of specificity, making it a little bit of an outlier in terms of performance data, but for the most part, we do see these sensitivity values in the high 80s to 90s. This score report now more simply categorizes patients as low or elevated risk and provides the the predictive risk values associated with each of those categories. The XODX test is another urine-based test. This does not require a DRE prior to obtaining the urine, which, you know, it was the, the first of the tests to offer that and, you know, really set the platform in that regard, which was huge to a lot of providers, particularly during the time of COVID. And so, um, this test measures 3 RNA transcripts in urinary exosomes to provide a risk score that's associated with significant cancer on biopsy. And here we see the, the exo data in the initial biopsy setting, revealing similarly 92 to 93% sensitivity, specificity approximating 30%. Well, in the repeat biopsy, we do see a slight reduction in the sensitivity to, to 82% at that same validated threshold. The EO score report provides a number from 0 to 100 and informs as to whether the, the patient is above or below the, the cutoff value for higher risk of high grade disease. The original, my prostate score was a post-DRE urine test. It combined two urinary markers with, with serum PSA to again provide the percentage risk of significant disease. And we did see across initial and repeat biopsies uh settings, very high sensitivity and and modest specificity largely in the 30 to 33% range. And that provides us a summary of where we stood uh a few years back. So, allow me to take us back to around 2020 and When our, our biomarker armamentarium was a little more abbreviated, and I wanna just share briefly how we came to develop the, the MPS 2 test. And so at that time, around 2020, the good news was we, we did have several biomarkers proven to improve upon PSA and risk calculators. Um, you know, a lot of positivity. The dolphins drafted Tua, things were, things were looking up there in Miami. Yet, you know, there appeared to be a glass ceiling on the performance of these biomarkers for detecting clinically significant disease. And at that time, I was, was a fellow at Michigan working with with the rule Chenayan as as Chad had mentioned. And we hypothesized that this was because biomarkers contained in these tests were those that had been discovered via efforts to distinguish cancer from non-cancer. And that was certainly a big improvement over PSA though we had learned over the last 10 to 15 years that higher grade cancers were really what we needed to detect, something that's now more more second nature in the field. And so our goal, and some work supported by the PCF and the, the NCI's EDRN. was to develop a test to improve detection of those higher grade cancers really through two mechanisms. First was identifying and incorporating novel markers that were specifically overexpressed in high grade cancers relative to low grade cancers, so. Enabling us to distinguish ideally between high grade and low grade disease, which, as you'd imagine could be useful in the diagnostic setting but also particularly useful in active surveillance, which I often joke is where where biomarkers go to die because as we've seen, not many biomarkers have been particularly useful in in that setting, a very homogeneous population. And second was simply by including more informative markers in one single test. And so, there's a fun way to illustrate this. I like to think of prostate cancer biomarkers in terms of generations. Our first generation test, PSA was specific for prostate, but not for cancer. Then came along the 2nd generation, which included the majority of biomarkers. That are included in the essays we just reviewed. They represented a large improvement to PSA through that biologic link to prostate cancer. And so our goal was to uncover a third generation of biomarkers specific for high grade disease and incorporate this into a new test. And so that was the framework for what became the MPS2 test. I will provide a, a very abbreviated version of that work done over the last several years, as, you know, I think it provides some helpful biologic rationale as to why the test could be particularly informative in certain settings. And so we started with discovery of novel markers by measuring nearly 60,000 markers across benign tissue, low grade tissue, and higher grade cancers. And we specifically identified markers that were overexpressed. In those higher grade cancers compared to grade group 1 disease, we took the candidate markers identified in that step, confirmed those that could be successfully measured in urine, and derived a model to optimize detection of clinically significant disease, which included 18 of those candidate genes. The testing approach, or the, the locked-in model was then assessed in an external population. This was carried out by statisticians actually here at at Fred Hutch, um, and was completely blinded to to the other investigators. One important point is that knowing that clinical data are not always available or reliable, we developed 3 models ranging from one that Included only those biomarkers to one that included biomarkers, plus our more standard clinical data as well. Prostate volume so that the test could be flexible based on the, the available data um clinically. And so these are the 18 markers included in the, in the validated test. It includes the tempers toward fusion, which was discovered in in Ruh's lab and has greater than 99% specificity for, for cancer in tissue, as well as 4 of the markers that are uniquely associated with high grade disease and several associated with prostate cancer. And so here I'll briefly show the validation cohort, only to emphasize to the point I made earlier, that these are patients that are proposed for biomarker testing with a moderately elevated PSA. Another point to make is that the new test was able to be directly compared to two of the existing biomarker tests, Phi and the original MPS. And so here we see that in that blinded validation under an approach that maintained 95% sensitivity. In patients undergoing an initial biopsy, MPS2 would have allowed for avoidance of 35 to 42% of unnecessary biopsies, which was an additional 5 to 27% relative to the existing options shown here, including 5 to 15% relative to to Phi and MPS. So a, a modest but clinically meaningful improvement seen there. In men with a prior negative biopsy, the test performance really did stand out. So you can see the, the really significant reduction in unnecessary biopsies afforded by MPS2 relative to these other tests. And this does also make sense biologically because we know, you know, the majority of existing biomarker tests, including those shown here, do maintain some level of reliance on PSA and PSA related markers. We know that PSA is, is actually Particularly poor at indicating the need for, for repeat biopsy in these men who have already been referred once due to an elevated PSA and undergone a biopsy. And so by, by using the 17 non-PSA markers of cancer, MPS2 was, was able to rule out repeat biopsy in approximately half the patients that traditionally would have undergone biopsy. Notably, the, the sensitivity and negative predictive value for grade group 3 and higher cancer were both 99%, which told us that the, the rare cases of a false negative test were almost exclusively grade group 2 disease and that those higher grade cancers were, were almost never missed. And so while that performance was strong, it was performed in urine obtained after DRE and much to the delight of patients and certainly our, our residents, uh, DRE has been de-emphasized in both the guidelines and practice. And so we needed to, to validate the test in non-DRE urine. And I'm just going to move through this particularly quickly. We were able to do that. Uh, and published that earlier this year, um, you know, notable, just to see the, the difference in overlap of PSA between. You know, insignificant or benign biopsies to those with significant disease. You can see here PSA values as we know, largely overlap. When we looked at MPS2, you see a 2 to 3-fold difference in those median values between those with and without significant disease. And so that was again, highly encouraging. The findings in this cohort largely reflected those of the of the post-DRE cohort, with upwards of a third of biopsies able to be avoided at a high sensitivity testing threshold. Similarly, in the repeat biopsy, we saw just really strong performance, you know, comparatively to the PCPT risk calculator. And so to come full circle on our, our now 8 biomarkers available, here is the, the MPS 2 score report showing the, the patient's personalized risk of significant cancer on biopsy. And so, you know, we are really hopeful it can be a useful addition to, to clinical practice. Um, it certainly appears to compare favorably to, to some of the existing tests and particularly in that repeat biopsy setting. And I'll mention, you know, without giving too much away, um, we now have data in around 300 patients in the active surveillance setting uh that our, our oncology fellow Cam Britton will be presenting at SUO. And right now, the data are suggestive that the test, you know, really could replace the need for surveillance biopsy in that setting. Um, with that similar level of accuracy to what we're seeing in the, the diagnostic setting. Um, and so, you know, we know that surveillance remains a, a really tough arena to differentiate among these patients. We have, you know, good evidence, including, uh, a really great recent paper from Sanaj and the team. Uh, showing that tissue-based biomarkers don't appear to be the answer there, largely because they failed to account for the, the multifocality of what is a multifocal disease. And so we'll continue to, to follow the data, but are are hopeful that the tests can have an impact across all these settings. And so getting back to the big picture of the biomarkers in general, I see that we're at 7:34, 4:34 local time. And so I'll aim to wrap up here in the next 5 or so minutes to leave some time for questions. Um, but we can conclude based on the published data that the high sensitivity and NPV of biomarkers really do suggest that they're well suited for an initial rule out testing. These assays will direct us toward biopsy in the vast majority of men that do have clinically significant disease while avoiding upwards of a third of biopsies in unnecessary biopsies in those without. And so that's, that's the state of things in terms of diagnostic biomarkers. Here's a summary table of the markers highlighting some of the, just the practical considerations that I think make a test more clinically useful, but these really are all strong tests that have been well, well validated. And so, I'll, I'll wrap up here with a few words on bringing these, these tests together with MRI. It's worth making a few points. Um, you know, first, when we look at meta-analysis of MRI at predominantly academic expert centers, We do see a strong pooled negative predictive value of around 91%. On the other hand, as many of you probably know, and is often pointed out, the NPV across these, these expert sites did reach as low as 63% at some sites, which really just highlights that variability of the, the rule out value of MRI depending on where that is performed and reviewed. To go a step further, data from the group at Stanford looked at the range of NPV observed within individual, among individual radiologists in their group, found this reached as low as 40% in the, the lowest performing radiologist, an overall NPV of 76%. And, and that is consistent with the findings of the, the music registry up in Michigan, which found 77% NPV across academic and community settings. And so the point to make there is simply that, you know, it's not that MRI is not phenomenal, particularly at our Miami Vanderbilt Hopkins Cents, but it's ultimately, you know, still, uh, has some subjectivity and that has some implications in the community. And so when we look at the, the strengths and weaknesses of biomarkers and MRI in terms of performance, I think it's, it's very clear how well these tools complement each other. Biomarkers have that really impressive rule out ability that MRI can, can lack at many centers, um, but MRI offers PPV that biomarkers cannot, and the ability to target image or target lesions on imaging and actually improve detection of significant disease. You know, I do with, with caveats stated, I think that biomarkers do offer some practical advantages shown here that depending on the setting or the specific patient could make them more sensible as a starting point. And so bringing. Together, asking, you know, what, what is optimal, what, what do I think is optimal? Um, you know, I really do think that at sites where the NPV of MRI is known and is sufficiently high, it's, it's very reasonable to use as a, as a first line test and, you know, in many cases the only test. I think it's worth mentioning that in settings where it's not well established, the, the strong rule out performance of biomarkers and some of those practical advantages may favor their, their first line use. And so, ultimately, I do think the, the most pragmatic approach to screening is, is like the one shown here. Patients with an elevated PSA undergo biomarker testing. Those with a positive test proceed to MRI. Positive MRI merits targeted biopsy with or without systematic biopsy as more data continue to emerge. On that front, a negative MRI can be used to rule out biopsy or combined with the biomarker result or PSA density to individualize that decision for system systematic biopsy. And so we do have a good template for this from the Finished ProScreen trial. That trial, you know, really followed that exact approach. Men with an elevated PSA underwent 4K testing. Those with a positive 4K proceeded to MRI. Men with a positive MRI underwent targeted biopsy only in this case, and those with a negative MRI, those that were higher risk based on PSA density, did undergo systematic biopsy. And I'll I'll cut right to the chase and you know, we can compare the first round of screening in procre using this approach to the first round of the ERSPC, which of course is the large European trial that that taught us a great deal. And you know, the limitations of both notwithstanding, this really does illustrate the progress made in the field over the past 20 to 30 years. Um, and how this approach of biomarker testing followed by MRI can answer those those criticisms from a previous, previous era with a sevenfold reduction in patients undergoing biopsy, eightfold reduction in overdiagnosis of low grade disease, and essentially preserved detection of significant cancers. So to conclude, with contemporary screening is focused on clinically significant disease, the majority of patients with elevated PSA really should be undergoing MRI or biomarker testing prior to biopsy. We saw how these tools really complement each other well, supporting a role for potentially sequential testing. Biomarkers do offer some performance and really practical advantages that could make them better suited as a first line test to identify patients than for pre-biopsy MRI which I think plays to the strengths of, of both tests. And so in terms of our work presented, so many people here to thank, and I really do want to thank all of you for the opportunity to speak with you all today. Here's our Euro crew on the left, and I know you all are, are pretty cozy with the Stanley Cup these days, but it did visit our, our cancer center, which was nice. And so really appreciate you all and happy to take any questions. Thanks, Jeff. That was a really amazing talk and a tour de force of a very complex topic, which kudos for even getting this done in such a short period of time. I wish we had a whole hour or more. Um, I know we've discussed at meetings about, you know, the role of race in detection, and I was just curious, for like, for example, that my prostate score weighs heavily on the temper er as part of the biomarker, and that's, you know, more predictive it seems in European or Caucasian populations. And I was just curious when applying these tests to a predominantly black population. Um, if there are concerns about the performance, uh, I know people do validation studies in black populations, but given that, you know, some of these biomarkers are more predictive in, in European populations, just curious your thoughts on those and how we can improve on that given the burden of prostate cancer in black men. Yeah, absolutely. And I apologize. I think they're, uh, emptying the, the dumpster here right next to me. So, hopefully, you're still able to hear me. But, um, yes, absolutely. Um, that, you know, as, as I think you know, was, was one of our major aims was to ensure that, you know, given the, the molecular differences in prostate cancer by race, um, you know, there is Reason to believe that there could be differences in performance of these molecular markers. Um, you know, we know, uh, Adam Murphy at Northwestern recently showed some decreased performance of MRI in black men, and so this is, you know, critical to, to address. Um, we are, we are gathering additional data to specifically answer that question in black men right now, um, and also gathering the resources to if the test does not perform equally well in black men to be able to develop and independently validate, uh, a test that, that does perform as well. Um, the preliminary data or really it's the data based on the, the first. MPS test showed that at a, you know, at that same clinical threshold, the sensitivity was equivalent and even slightly improved in black men, but there was a, a modest reduction in, in specificity. And so, you know, that, of course, as, as we talked about brings into question the, you know, how, how many biopsies are being ruled out. And so, you know, I do feel comfortable. Again, just based on preliminary data that, you know, we're not, we're, we're hopefully not, and preliminary data show as much sacrificing any sensitivity, um, you know, which is where risk really comes in. But there could be some, some trade-off with these, these current tests, um, in terms of clinical usefulness and ruling out biopsies, but I know many of the groups are looking at that and I can tell you with certainty, that's something that That we're looking at with MPS2. Awesome, thanks so much, man. I think we have time for one more question, Laura, Bob, I have a question. Go ahead, sorry. All right, so, um, thank you for the talk. Uh, this is Ali, one of the, uh, faculty members. I work mainly at the VA and most of the patients I see in clinic are patients who had the PSA and MRI when they come to see me. And there was this meta-analysis that was published in JAMA in March 2024 but I think the Harvard Group which combined the yield of PSA density and, uh, MRI findings, uh, MRI pirates finding. It has very high negative protected value when you have a normal, uh, PSA density and the Pyri 3 region for example. Um, do you see, um, any role of biomarker in, in that situation where you have like y 3 but normal PSA because to me that that high negative predictive value is, is reassuring for, for us to avoid such biopsies. Yeah, absolutely. No, it's a, it's a great question, and, you know, I, I do. I think that, you know, and this is why, you know, part of why I, I do think for those practical reasons that it, it may make sense to, to get biomarkers more as a first line test there. That's also considering, you know, cost and, and some other practical factors. Um, you know, you're absolutely right that a lot of centers have found that PSA density can be that, you know, kind of tiebreaker in the setting of an equivocal MRI. Um, I know that, you know, several others have, have not found it to, to work well in, in that role or as well. Um, you know, there's that literature that shows that there's really not a A clear and certainly not a biologically, um, you know, rational cutoff for PSA density, but rather it is a, a pretty consistent increase in risk with the increase in PSA density. And so, all to say, you know, I think it's the onus is on, you know, biomarkers to potentially show that they, they do offer. Information beyond what PSA density offers. Um, you know, I think for the first MPS test, we, we actually had published exactly that showing a, a pretty significant improvement with, um with MPS relative to PSA density, though there are data, you know, similarly, as you mentioned, showing that PSA density can, can do the trick there. Um, and so if, you know, you're finding that, that seems to work well clinically, you know, I don't think the, the data exists right now to make a, a particularly strong case to, to add biomarkers, um, unless, you know, certainly if that PSA density is, is also in that equivocal range, you know, in the 0.1 to 0.2 range, um, and you think it could, could inform. Uh, next steps for for a given patient. Uh, so just, just a final question. So how, how do you do it when you see a patient with a PSA and MRI? Do you, where do you use the biomarkers? Yeah, so, no, great question. If, if patients already have an MRI, um, you know, it's, it's rare that I will, you know, again, particularly, largely practice in, in Nashville where thankfully, I, I spent a lot of time at our VA too, um, but our data appear to be pretty strong for MRI, um, you know, it's, it's not often that I, I will. Then add a biomarker on top of of that MRI if they're already coming in with, with an MRI. All right. Thank you. Awesome. Yeah, thank you. Well, thanks again, Jeff and uh enjoy the rest of your meeting there in Seattle. Uh, thanks so much for giving this awesome talk. Um we have our sub talk up next, so I appreciate you being here. Appreciate you all. Thank you so much and feel free to, to shoot me an email with any questions. Take care, guys. Published September 18, 2025 Created by
