Ladies and gentlemen, thank you for standing by and welcome to the Myriere Genetic GeneSight Clinical Data Call. During the presentation, all participants will be in a listen only mode. Afterwards, we will conduct a question and answer session. As a reminder, this conference is being recorded today, Friday, January 4, 2019. I would now like to turn the conference over to Scott Gleason, VP, Investor Relations.
Please go ahead.
Thank you, David. Good afternoon and welcome to the Myriad Genetics GeneSight clinical data call. My name is Scott Gleeson. I'm the SVP of Investor Relations and Corporate Strategy. Presenting for Myriad today will be Mark Capone, President and Chief Executive Officer and Doctor.
Brian DeCarra, our Executive Vice President of Clinical Development. This call can be heard live via webcast@myriad.com. The call is being recorded and will be archived in the Investors section of our website. In addition, there will be a slide presentation pertaining to today's call on the Investors section of our website, which will be filed following the call on Form 8 ks. Please note that some of the information presented today may contain projections or other forward looking statements regarding future events or the future financial performance of the company.
These statements are based on management's current expectations and any actual events or results may differ materially and adversely from these expectations for a variety of reasons. We refer you to the documents the company files from time to time with the Securities and Exchange Commission, specifically the company's annual report on Form 10 ks, its quarterly reports on Form 10 Q and its current reports on Form 8 ks. These documents identify important risk factors that could cause the actual results to differ materially from those contained in our projections or other forward looking statements. With that, I'm pleased to turn the call over to Mark.
Thanks, Scott. First, I want to apologize to investors for hosting a call on a Friday afternoon. However, we were notified yesterday that the online version of the publication of the guided study would become available this morning, and we thought it was important to provide a comprehensive review of the data that will be submitted in our reimbursement dossier prior to the JPMorgan Healthcare Conference next week. On today's call, I will start by discussing the landscape for depression studies, and Brian will review the details of the entire GeneSight dossier. Clinical studies assessing a patient's depressive symptoms are, by definition, subjective.
The tool utilized for decades in clinical studies and endorsed by the FDA is the 17 question survey called the Hamilton Depression Scale or HAM D17. This questionnaire evaluates symptoms associated with depression, and the answers are added together producing a score that ranges from 0 to 52. Patients with scores between 0 and 7 are considered normal. Scores between 814 are considered mildly depressed, scores between 1418 are moderately depressed, scores between 19 22 severely depressed and above 22 are considered very severely depressed. Based upon changes in these scores from baseline to a typical 8 week follow-up visit, 3 endpoints are calculated.
These include symptom improvement, defined as the percent change in HAM D17 scores response rates, defined as the percentage of patients whose HAM D17 scores decreased by greater than 50% from baseline and remission rates defined as the percentage of patients with HAM D17 scores decreased to 7 or below. Remission is viewed as the most important endpoint for patients, physicians and payers because these patients are considered back to normal. In fact, the APA guidelines expressly state that the goal of treatment is remission. Additionally, from a payer perspective, every patient who achieves remission saves a health plan approximately $20,000 per year in total costs, and response and remission data is included in calculating heated scores used in rating insurance plans. Not surprisingly, pharmaceutical studies for antidepressants demonstrate inconsistent results given the somewhat subjective nature of the MD-seventeen questionnaire.
In a review of the registration studies submitted to the FDA for 40 approved antidepressants, no drugs have been approved based upon superiority to an active drug control arm, and comparator arms used are always placebo. Even then, only 13% of FDA approved drugs show statistical significance in remission, 30% show statistical significance in response and 70% show statistical significance in symptom improvement. In fact, in the ProzacTac geriatric registration study, Prozac demonstrated significance over placebo in response and remission endpoints, but only approach significance in symptom improvement. It is worth noting that remission is particularly difficult to achieve for treatment resistant depressed patients that have failed previous medications. The largest study designed to evaluate remission rates was called STAR*D study, which enrolled over 4,000 participants.
A subset of these patients had previous treatment failures similar to those in the guided study and in those patients, the remission rates were between 13% 13.7%, which was on par with remission rates seen in the guided study. The study also noted that in this subset of patients, those that achieved response but not remission had relapse rates close to 80%. The authors of the study concluded that response without remission is even more precarious as given the high probability of relapse and called for all reasonable efforts to be made to assist participants in reaching remission and for the continuation of careful clinical monitoring beyond the time of remission or response. It is also helpful to understand the magnitude of improvement in remission rates seen in other clinical studies. To illustrate this, we evaluate the data for the 2 most recent FDA approved therapeutics for major depressive disorder, velozodone with the brand name of Vibrid and boritoxetine with the brand name of Trintellix.
Neither of these drugs achieved a statistically significant improvement in remission rates when compared to placebo. In addition, the magnitude of the improvement in remission rates was consistent with the guided study despite the fact that these drugs were compared to placebo rather than to an optimal active drug arm. It is also interesting to note that fortoroxetine had a lower remission rate than placebo in one of its studies. With that overview of the unique aspects of depression in clinical studies, I would now like to turn the call over to Brian DeCaro, the architect of the guided study, to review the entirety of the clinical data on GeneSight.
Thanks, Mark. I'm pleased to provide a review of the existing clinical utility studies on GeneSight prior to the guided study. As a reminder, these previous studies demonstrate that GeneSight improves outcomes in patients relative to standard of care therapy and were sufficient for Medicare to render a positive coverage decision for the test. The largest of these studies, the LaCrosse study, was an open label study evaluating how GeneSight impacted depressive symptoms relative to standard of care therapy in 165 patients with major depressive disorder who had failed at least one line of pharmacological treatment. The study found that at week 8, GeneSight patients saw a 70% greater improvement in depressive symptoms.
This was a highly statistically significant result. Additionally, patients in the GeneSight arm saw greater than 2x the response rates and almost 3x as many physicians in the GeneSight group felt their patients were highly satisfied with their care. The second study supporting GeneSight was the HAM study, which was again an open label study evaluating the ability GeneSight to improve depressive symptoms relative to a treatment as usual arm. This study found a 4 fold improvement in depressive symptoms at week age, which is again highly statistically significant. Finally, the PINE REST study was a Phase II study to provide information essential to the design of the much larger guided study.
The study evaluated changes in depressive symptoms over a 10 week period. While not designed to provide a statistically significant result given the relatively low number of patients, patients in the GeneSight guided arm saw 2x the remission and response rates of patients in the treatment as usual arm. Additionally, the study demonstrated the ability of GeneSight to stratify patient outcomes based upon whether patients entering the study were on red medications. The study demonstrated that those who were on red medications had substantially worse outcomes compared to those who entered on green or yellow medications. While these three studies provided a solid foundation of clinical evidence, we believe a large prospective study would ensure the broadest commercial coverage.
After extensive consultation with managed care stakeholders, we designed the guided study to answer specific questions identified by these payers. The now published GeneSight guided study is the largest prospective pharmacogenetics study for depression ever conducted And I would like to provide a review of this groundbreaking study and some new data that was published this morning. The GeneSight randomized controlled trial evaluated approximately 1200 patients with moderate to severe major depressive disorder who had failed at least one prior line of medication. In order to be enrolled in the study, patients were assessed by local raters as having a least moderate depressive symptoms with a score of greater than or equal to 11 on the QIDC16 symptom scale at screening. After enrolling, patients were subsequently screened by blinded central raters using the HAM D17 questionnaire to definitively identify patients having moderate to very severe symptoms, and these patients were the basis of the primary analysis.
The study included over 60 sites with the nation's leading academic institutions, including key members of the National Network of Depression Centers. Patients were randomized into a GeneSight guided arm or a treatment as usual arm. Both the central raters and the patients were blinded as to treatment arm to eliminate any bias. The study evaluated all three endpoints relative to HAMV-seventeen scores, including remission, response and symptom improvement. After week 8, the patients were unblinded and the study continues for a total of 24 weeks.
Overall, the design and rigor of the study was similar to studies conducted for a pharmaceutical seeking approval from the FDA. On the next slide, you can see the study enrollment and randomization data. A total of 2,004 patients were screened for eligibility criteria and 1398 were randomized on a one to one basis into either the treatment as usual or GeneSight guided arms of the study. There were no significant differences in dropout rates between the two arms over either the blinded period or the open label period of the study. The next slide shows an example of a GeneSight report.
As a reminder, the GeneSight report places medications into green, use as directed yellow, moderate gene drug interaction or red, significant gene drug interaction. Patients on green medications do not require medication changes, whereas those on yellow or red medications should have a dose and or medication change. As expected, there was no measurable GeneSight benefit in patients that entered the study on green medications. There was benefit in patients that entered on yellow medications and significant benefit for patients that entered on red, red medications. The next slide shows the results for the three outcomes of remission response and symptom improvement over the 8 week blinded period of the study.
Importantly, the GeneSight guided arm performed better in all three endpoints, showing a highly statistically significant improvement in remission and response rates and an improvement in symptoms that was approaching statistical significance. Overall, GeneSight led to a 50% improvement in remission rates, a 30% improvement in response rates and an 11% improvement in symptoms relative to the treatment as usual arm. This is the first time to our knowledge that a technology has demonstrated a statistically significant improvement in overall outcomes relative to an optimized active drug arm for depression. The next slide shows the durability of results. Importantly, all three key endpoints of remission, rates, response rates and symptom improvement continue to improve over the 24 week timeframe and remission rates more than doubled between week 8 week 24 in the GeneSight guided arm.
This finding has been well received by payers that wanted assurance that the GeneSight benefits are enduring. Additional analyses were performed on the 21% of patients that entered the study on RED, genetically incongruent medications who should benefit the most from GeneSight testing. Note that in the treatment as usual arm without the benefit of the GeneSight report, the percent of patients on red medications actually increased over the 8 week study period, demonstrating that physicians were unable to improve congruence using a trial and error approach. However, in the GeneSci arm, 57% of patients were switched from red medications, significantly improving congruence. There were 3 factors that contributed to the 43% of patients who remained on RED medications in the GeneSci arm.
First, switching was not required in the protocol. 2nd, physicians were naive to GeneSight. And third, patients were blinded to the fact that they were taking red medications. Because some patients remain on red medications and some were switched, we were able to do a separate analysis comparing these 2 patient groups. When comparing these 2 patient groups, the patients have switched from RED medications experience remission rates that were 153% higher, response rates that were 71% higher and symptom improvement that was 59% higher.
All of these results were highly statistically significant. These impressive results have been very impactful for physicians because it establishes a new standard of care where patients on a red medication must be identified and their medications modified. This switching analysis has also been an important point in our peer discussions as utilization management programs can focus on switching patients from red medications, which would deliver clinical results even better than those in the guided study. The next slide shows secondary endpoint analyses from the study for all three endpoints using 3 different depression instruments for the intent to treat population. The intent to treat population represents a total of 12.99 patient at week 8 compared to the study population of 1167 patients at the same time frame.
The difference is that the intent to treat population included all enrolled patients, while the per protocol population excluded those patients that were entered in the study based upon the QIDC16 assessment at individual sites, but were subsequently found to be only mildly depressed by the blinded central raters using the Hamby 17 questionnaire. Many consider the intense treat population as the most relevant since it reflects real world practice and is often the population used for FDA registration studies by pharmaceutical companies. Beyond the HAM D17 score assessments by the blinded central raters, patients also received a QIDC16 assessment by raters co located with the treating clinicians who were unblinded and a PHQ-nine patient self assessment. The local rater assessment of the QID C16 instrument was designed to be used for enrollment, but was also being evaluated as a potentially more cost effective endpoint for future studies. While the QUITC16 endpoints evaluated by site raters correlated with the HAM B17 endpoints evaluated by blind essential raters, they did not validate as an alternative endpoint.
The PHQ-nine instrument was included because it is used by payers in HEDIS evaluations. It is highly encouraging to see that the GeneSight guided arm showed better numerical outcomes across all three endpoints in every depression assessment instrument. Additionally, in the endpoints used by the FDA and payers, 4 out of the 6 achieved statistical significance and the other 2 approached significance of P values of 0.07. Also, every endpoint demonstrated statistical significance in at least one of the depression instruments, including symptom improvement. Lastly, it is interesting to note that the statistical significance of the HAM D17 endpoints actually improved when the mildly depressed patients were included in the study.
The robustness and breadth of these results provide even further evidence that gene site guided therapy provides superior outcomes for treatment resistant depressed patients. An additional analysis was performed based upon other observations noted during the manuscript review process. The per protocol analysis was diluted by the 30% of patients that entered the study on green medications only and who were not expected to benefit from GeneSight. As an important additional analysis, an important additional analysis was performed on the intent to treat patient cohort that excluded these patients. This data will be featured in an upcoming additional publication.
Comparing the GeneSight and TAU arms and the patients entering on yellow or red medications, all three endpoints were statistically significant with a 70% increase in remission, a 42% improvement in response rates and a 23% improvement in symptoms. This analysis clearly demonstrates that GeneSight improves outcomes for the 70% of patients taking medications that require modification based upon their genetic profile. Given the size of this study and the diversity of sites, we believe this reflects the real world reality in the United States. Having a tool that can improve outcomes for some of the 70% of treatment resistant depressed patients is a major advance in addressing the growing mental health crisis. Now I would like to discuss the IMPACT study, which compared GeneSci outcomes between primary care physicians and psychiatrists.
First, it is important to understand that the goal of the IMPACT study was to answer a question unique to Medicare regarding a primary care physician's ability to use GeneSight effectively. Since the Medicare coverage decision was based upon studies conducted by psychiatrists, we were asked to provide some more supporting evidence for use by primary care physicians. In the United States, approximately 60% of treatment resistant depression patients are seen by a primary care physician. The study was performed in cooperation with the Canadian Centre For Addiction and Mental Health and was an open label study where all patients received GeneSight reports. The primary endpoint in the study was change in the back depression inventory or BDI over 8 weeks.
The BDI is a questionnaire based assessment of depressive symptoms similar to the HAM D17 and the 3 endpoints of remission, response and symptom improvement were assessed. The study enrolled 18 71 patients treated by either psychiatrists or primary care physicians with no significant patient demographic differences between the 2 physician groups. Importantly, the data showed that both physician groups did well using GeneSight, while primary care physicians performed even better. Primary care physicians saw 63% greater remission rates, 35% greater response rates and 27% greater symptom improvement versus psychiatrists with all endpoints highly statistically significant. These results were partly attributed to the fact that the primary care physicians had higher compliance rates with the GeneSight test results.
Now that the guided impact studies are published, we will be filing a formal reconsideration request to Medicare to evaluate expanding the local coverage decision to include primary care physicians. Next, I would like to discuss the health economic data supporting the GeneSight test. Our 2 prior health economic studies included the Medco Prescription Drug Study and the Union Health Service Health Care Utilization Study. The Medco study evaluated real world prescription claims data for 2,168 patients receiving GeneSight compared to 10,880 patients receiving treatment as usual over a 1 year period. The study found that patients receiving GeneSight saved on average $10.36 in total prescription drug costs comprised of $3.21 from CNS medications $7.14 from non CNS medications compared to patients that did not receive GeneSight.
This result was highly statistically significant with a p value of 0.007. Additionally, patients in the GeneSight group saw an increase in medication adherence of 17% and reduced polypharmacy. In the Union Health Service study on healthcare utilization sorry, the Union Health Service study on healthcare utilization was a 1 year retrospective study of 96 patients with major depressive disorder. The study found that patients on red medications had 67 percent more general medical visits and 69% more total healthcare visits, both of which were statistically significant. Based upon these higher inpatient and outpatient visits, patients on RED medications had health care service costs
that were
$5,188 higher than patients on genetically optimal medications. Consequently, total healthcare savings for all patients in the UHF study translated to $15.56 for patients using GeneSight. Furthermore, patients on red medications have 4 times as many disability claims and greater than 20 additional workplace absences relative to the green or yellow been patients. These changes were also statistically significant and if applied to an employer would lead to $7.75 in incremental annual cost savings per patient. When combined, the Medco study and the Union Health Service study translate into $3,367 in 1st year savings or a 28 week payback period for a self insured employer plan, which now comprise over half of privately insured patients.
To further strengthen our health economic data, an outside consulting group conducted a study in conjunction with OptumHealth to determine how GeneSight impacted total healthcare spending in the Optum claims database. The study evaluated 683 patients, of which 205 had GeneSight and 478 received treatment as usual therapy. The study included patients who had failed at least one prior round of medication and evaluated spending over a 12 month period after GeneSight testing to compare costs. The study found that patients in the GeneSight cohort had 17,627 dollars in total costs compared to $23,132 in costs in the treatment of usual arm, representing total cost savings of $5,505 This was highly statistically significant even after adjusting for pretest differences between the two arms. When evaluating the subset of patients with major depressive disorder, patients who received GeneSight had total cost of $18,741 compared to $24,971 in the treatment as usual arm, representing total cost savings of $6,050 Again, this result was highly statistically significant after controlling for pretest differences.
As with the Medco and Union Health Service studies, there was a significant reduction in total medication spend, but the largest component of total cost savings came from healthcare service utilization savings. With a $2,000 test price, this means a commercial payer would realize a 17 week payback for depressed patients and even a shorter payback for the self insured plans because these savings exclude productivity improvements. One important factor with GeneSight is that direct medical cost savings will not be the only consideration for payers. Another consideration is the impact to the quality assessment instrument called Healthcare Effectiveness Data and Information Set or HEDIS scores. Behavioral health is an important component of HEDIS scores and for depression, the key metrics utilized are remission and response measures.
Commercial payer plans pay close attention to these scores given they are a component of a plan's overall rating used by customers to evaluate the quality of the plan. Also, the behavioral health metrics within HEDIS could be used in the future to determine star ratings for health insurance plans. Plans with higher star ratings get higher reimbursement from Medicare Advantage and plans with consistently low ratings can be excluded from participation. We believe GeneSight's ability to positively impact remission response rates and their impact on HEDIS scores will be another value consideration when commercial insurers evaluate the test. I would now like to turn the
call back over to Mark. Thanks, Brian.
I would like to provide a summary from what was presented today and discuss the next steps in the commercialization of GeneSight. First, the guided study is the 5th positive study demonstrating the impact GeneSight has on improving outcomes for depressed patients. Guided is the largest prospective pharmacogenomic study ever and the first to produce Level 1 outcomes evidence compared to active drug rather than placebo. In the guided study, GeneSight showed a 50% improvement in response, which was highly statistically significant 30% improvement in remission, which was highly statistically significant and an 11% improvement in symptoms, which was approaching significance. When patients entering the study on green medications were excluded, all endpoints reached statistical significance with a 70% increase in remission, a 42% improvement in response rates and a 23% improvement in symptoms.
In addition, the benefits from GeneSight were durable continued to improve throughout the 24 week time frame for the study with remission rates more than doubling to 31%, response rates increasing to 44% and symptoms improving by 43%. Further analysis showed that patients switching from red medications compared to those that did not switch experienced remission rates that were 153% higher, response rates that were 71 percent higher and symptom improvement that was 59% higher, and all of these results were highly statistically significant. Also, the IMPACT study showed that primary care physicians using GeneSight can realize excellent outcomes for patients that exceeded those generated by psychiatrists. Finally, multiple health economic studies utilizing real world cost data have shown that GeneSight saves the health care system significant costs and generates a highly attractive payback for payers. In summary, we believe this reimbursement dossier is the most compelling ever generated by Myriad in our 27 year history.
Consequently, we will immediately send this dossier to commercial payers, representing more than 60% of covered lives. Typically, commercial insurers will review their medical policy decisions concerning mental health policies at set times throughout the year, but we will request out of cycle reviews for those scheduled later in the year. In addition, we will immediately submit the impact and guided data to Medicare along with a request to expand the LCD to include primary care physicians. Also, we are actively working with key opinion leaders to publish a number of additional papers based upon the guided study, including the analysis with green patients excluded. When supported by reimbursement, we will begin our launch into the primary care market, which represents more than 60% of the depression market, which will also include a significant direct to patient awareness campaign.
The majority of our current sample volume that exceeds 300,000 tests per year is ordered by psychiatrists. So a primary care launch will represent the potential for a substantial inflection in volume. In conclusion, we are extremely excited about the future for GeneSight and believe with additional reimbursement over the coming months, it will emerge as one of the largest tests in the molecular diagnostic industry and will transform the financial performance of the company. With that, I am pleased to turn the call back over to Scott for Q and A.
Thanks, Mark. David, we are now ready to begin our Q and A session. In order to ensure broad participation in today's Q and A session, we are asking participants to please ask only one question and one follow-up. Operator, we are now ready for the Q and A portion of the call.
Thank you, sir. Our first question comes from the line of Patrick Donnelly, Goldman Sachs. Your line is
open. Great. Thanks, guys. Mark, maybe just
to start, pretty broad publication here. Can you just talk through how this publication is going to change the conversation with payers now that it's out there, what your guys' approach is going to be?
Yes. Thanks, Patrick, and Happy New Year. I think one of the things that's important is that the data in this publication is identical to the data that's already been shown to payers. So in fact, in the room today with us is the Managed Care team. After this call is over, we'll be reviewing our progress and submission of all this dossier to payers.
But the content of that dossier has already been reviewed with payers. The only incremental data in the manuscript that payers had not previously seen were the secondary analyses that Brian went through for the ITT population. And in fact, all that data is very supportive of the data that they've already seen, and that is that in every case, GeneSight was numerically better than the treatment as usual arm. In the 6 endpoints used by the FDA and payers, That GeneSight was statistically significant in 4 of those and had P values of 0.07 in the other 2. And so while that's new data, it's clearly very supportive of everything they've seen.
So I think that's the important thing is that this isn't new and that was purposeful because we wanted payers exposed to all of this beforehand. So as a result of that and in those payer discussions, we know payers were very, very responsive to this data. They were very interested in this data and responded very well, and we're particularly focused on the remission and response data. As we noted before in our discussions, those payers really had little to no questions at all about symptom improvements. They were very much focused on remission and response, and they've never seen data whereby remission and response were statistically significantly improved when compared to an active drug arm.
So that was very exciting to them, which is why they had told us, please do not wait for this to be in print. We would like this dossier submitted immediately upon acceptance of the publication, which is why the managed care team will be doing that in the coming days. So I think that's where we stand. We know there's high receptivity. One reason that they are so focused on this, I think there's some very important data that we mentioned upfront, even for these treatment resistant depressed patients, remission rates are quite low, as Brian noted, as we noted that STAR*D was only 13%.
But what's also very important to note is that even when patients responded in the STAR D study, so these are patients that have more than a 50% reduction in their depressive symptoms, 80% of those patients relapsed. And that's why payers have been so focused on remission because they know that's their only real chance to decrease their costs and that's why they've been so focused on the 24 week data because they want to make sure that there isn't some relapse that occurred after the study. And so that's why they were so excited about it and everything in this manuscript is supportive of the information that they've already seen.
Okay. And then maybe just a quick follow-up. Can you just expand a little bit just on the process to get more formalized in the treatment guidelines? It's obviously been really impactful in the historic diagnostic test getting into guidelines really causes that inflection higher. So can you talk through any conversations you've had and then the process that you guys are kind of approaching
to get involved there? Yes. There is I think one of the differences that we face in the neuroscience area is that guidelines are generally updated maybe every decade or longer. As you know, Patrick, in most of the other disease states and in fact, personalized medicine has largely been focused on the oncology area. And in that case, we have NCCN guidelines that are addressed on at least a yearly basis, and so they're very much up to date.
That's just not the true in from an APA perspective, those guidelines, it's over 10 years. And so as a result of that, payers have historically not relied on guidelines to make decisions. So for example, there are antidepressants that have been approved by the FDA that have never been featured in the APA guidelines. So payers are actually quite used to having to make decisions in the absence of APA guidelines given the fact that they're so typically out of date. There are a couple of other bodies that do guidelines on a more frequent basis, and we're in discussions with those bodies that are looking at their depression and pharmacogenomic guidelines.
So I think there's the opportunity for some of those other guidelines to be updated quicker. But I think given the fact that payers are used to having to make decisions without updated guidelines, I think that's what we anticipate in the upcoming discussions.
Our next question comes from the line of Sung Ji Nam with BTIG. Your line is open.
Hi. Thanks for taking the questions and I was curious as to the durability of GeneSight over the 6 month period. You talked about that being kind of the industry standard metric, measuring it over 6 months. Is there a further value in kind of looking at the durability beyond that point or was curious about that?
Yes, this is Brian here. Again, the standard pharmaceutical FDA approval studies are 8 weeks. Some of them are actually shorter to 6 weeks. So the normal period. We definitely heard feedback from payers that they wanted us to go longer, which is why we designed this open label period out to 6 months so that we could show that the patients sustained their remission and as we also saw that we even doubled remission rates over that period of time.
I think that we've also seen impacts of GeneSight longer term in both the Medco study, which was a 1 year study and retrospectively in some of our long term studies like UHF, which is also a 1 effort where we've been seeing those financial impacts over a longer sustained period. So I do think we have significant data and over time, we will have even longer term data following that. As we work with payers, as you saw with the Optum data, that also was a 1 year prospective effort where we saw those significant health care savings. So we expect to see this even further than the 1 year period.
Great. That's helpful. And then, Mark, when you talk about next steps and pursuing additional papers supporting GeneSight, I'm sorry, additional publications. Was curious as to whether or not you're looking to explore kind of new aspects of the study of previous studies or new segment cohorts. Just curious as to what this would entail in terms of what you're looking at and how you expect to further expand your studies related to this
product? Yes. I think there's a variety of additional areas where we have key opinion leaders that are quite interested in all this data and areas where they would like to do some additional publications. I think a good reference point, we've talked about STAR*D a couple of times this afternoon already, I think at the end, STAR*D had over 100 publications that resulted from that singular study. And so we actually already have put together, along with our scientific advisory board, a list of additional studies that people would love to publish on, and we're prioritizing those and working through those.
One of the ones we already mentioned, of course, was the analysis where you exclude patients that were never expected to benefit from GeneSight, which is the green patients. And of course, we disclosed that data already, and that will be headed towards a publication. We already have some additional data on things like side effects for patients that were on RET medications, and that was actually mentioned in the manuscript that there was a significant difference for patients that switched from red medications from a side effect standpoint. So there's just a whole long list of things like that, that people would like to look at. One of the other things I can mention because it's working its way to a poster is MD6.
There are opinion leaders that believe that MD6 is a more sensitive approach to looking at outcomes compared to MD17, and that data looks exciting, and of course, we'll make that available then in poster and manuscript form. So yes, I think you should just look for a long series of additional publications answering yet other questions that key opinion leaders are interested in pursuing over the coming years.
This is Brian. I'd just add 2 other points to that just real briefly. One on the follow on from guided deeper analyses, we've also have seen in sub analyses that we've put in or putting in posters that the over 65 for Medicare population had even larger magnitude benefits, although the whole population had a benefit. And so that's important again with the early data that Medicare already had and made their positive coverage decision before. But also about future studies, after 5 positive studies, all that showed that GeneSight is prospectively better than treatment as usual against an active drug arm, we've had a lot of payers say, why are we waiting for our patients to fail?
We should actually use this for patients who have never been on medications and moving into that treatment naive phase for patients as well. So that's a future area for us to go into as well.
Our next question comes from Bill Quirk with Piper Jaffray. Your line is open.
Great. Thanks. Good afternoon, everybody. First question for me, Mark, is with respect to the sub analysis or maybe some
of the data that
the payers haven't seen, have they been aware within the guided study that within the guided treatment side of it that obviously there's a number of physicians who didn't follow the recommendations from GeneSight and is that in the discussion at all the discussion at all regarding reimbursement? Is there potential like compliance elements that the physicians would have to follow to trigger reimbursement or I just getting ahead of myself here at this point?
No, that's and Happy New Year, Bill. That's an excellent question. In fact, Brian and I happen to both be in a meeting with a payer where this particular issue came up. So that data is actually extraordinarily important to payers and exciting to payers. So just to review that, what was fascinating about this study is 47% of the patients that entered the GeneSight arm on a red medication, and physicians had reports that showed them they were on red medications, 47% of patients remained on red medications at week 8.
That was striking to payers and concerning to payers. And what was interesting they latched on to immediately is that the results that we presented were very positive, but you can only imagine what that would have looked like if those 43% of patients would have switched off those red medications because you can see from the red medication analysis that the impact was profound when patients switched. And so we have had payers immediately jump on the fact that, that alone would have made these results strikingly better and begin to immediately talk about what are some of the initiatives that they could launch as a payer to ensure that you would have much better compliance rates than 43% of patients staying on red medications. So I think that's an exciting opportunity for us to partner with payers. We're already in discussions with payers on exactly how to do that with them.
And I think that I think you will see that happen. Now just to expand on why you saw 43% of patients remain on red medications. Brian laid out three reasons. I think one of the most important is, remember, patients were blinded. They had no idea they were on red medications.
In the real world, when a doctor sits down and goes over a report with them and shows a patient they're on a red medication, I expect you're going to see compliance rates much higher. We'd be hard pressed to imagine patients Sounds good. Let's stay on a red med. I just think you're going to see patients much more actively engaged in switching conversations. But of course, it did provide us an opportunity to provide some very powerful data.
So I think you're spot on, Bill. I mean, it's exactly what payers have already started to latch on to, that they can get better results than this by ensuring that patients are switched off or read medications.
I'll just add one comment to March in that the Class A evidence everyone wants a double blind randomized controlled trial, but and that's what we have for the patients were blinded. So you couldn't tell a patient you're on a red medication. And if they're on 2 or 3 medications, that red one that they're on might be their favorite. And it's hard to keep them blinded by them saying, well, given a good reason for why they should switch off of it. However, in the previous studies that I highlighted in the dossier, those were open label studies where patients were actually able to have be in a dialogue with their doctors like the real world and we saw almost 95% to 100% switching off of red medication in those studies with very significant findings on symptom improvement response and remission in those previous open label studies, which is the value of open label designs as well.
Got it. Very helpful. Thanks to both of you. And then I'm just pivoting a little bit to the IMPACT study. Mark, you talked about asking Medicare to reconsider or to expand rather their LCD to expand GeneSight coverage to the primary care physicians as well.
Can you talk a little bit about some of the commercial implications here? I'm thinking specifically about potential sales adds and how should we think about that in terms of number of people, dollars, timelines and anything any details you could give us would be very helpful. Thank you.
Yes, thanks, Phil. You're right, we will be immediately submitting that request based on impact. And it's also important to note that we've actually reviewed, again, all of that data with Medicare. In fact, people in the room with me right now are ones that presented that data to Medicare. Again, they were very impressed with the guided data, the impact data.
The impact study was done specifically for the director medical director in the room. And so he as well was impressed with the results. And they also asked us to please submit the request when the manuscript was accepted and not wait for print publication. And so that's precisely what we will be doing. To your point, we're carefully planning a launch, a broader launch into the primary care setting, represents over half the market and probably the area where we can do even the most good for patients by getting them early on onto the right medications.
So I think as soon as we cross the threshold of reimbursement where financially that makes sense, we would be launching into that primary care market. The team has already drawn plans on what that sales team might look like. In addition, they've already drawn up plans on exactly what a direct to patient awareness campaign would look like. So we're going to have those plans ready to go. So there's no delay once we cross that threshold on a level of acceptable reimbursement.
Obviously, we'll give you some more details about that, Bill, as time draws near on that launch. But it is certainly an opportunity for a dramatic inflection and what we can see from a testing perspective.
Understood. Thanks guys and congratulations on the publication.
Our next question comes from the line of Tycho Peterson, JPMorgan. Your line is open.
Hey, guys. Congrats. This is Julia on for Tycho today. So just quickly, could you maybe give us a clear sense of how many payers have you presented these study days to at this point? And then do you guys have plans to proactively review the data with the FDA just given the recent FDA commentary around pharmacogenetics testing in general?
Thank you.
Yes. Thanks, Julia. We've reviewed the data with essentially all the payers in the country, certainly payers of any material size. And so it's been a pretty extensive effort by our payer markets team to get to each of those payers. The 60% number that I've referenced in these conversations is upon acceptance of the manuscript and not waiting for a upon acceptance of the manuscript and not waiting for a publication.
And so those are the ones that responded so positively that they asked us to send that information in. So that's where we are. We'll, of course, be sending it to that 60% into Medicare very quickly here in the coming days in responsiveness to their question. From an FDA perspective, I think our position has really remained the same, and this is one we've shared with the agency as well. First of all, we are very supportive of the legislation that is working its way through Congress that would increase FDA oversight of LVTs.
We have been very active architects in those conversations and we'll continue to do that, and we have expressed significant support for that effort and believe that's appropriate. The FDA, of course, has noted that from a policy perspective that they will continue to use enforcement discretion for LVTs until legislation has been passed. And both in public and private commentary, they've been very clear on that position. And so we're working to get that legislation passed, so that we can have a level playing field from a regulatory standpoint across this entire field. When that legislation is passed, we, of course, will comply with that.
And right now, as the legislation is written, it will grandfather all of the existing tests, which, in this case, would include GeneSight. That legislation could, of course, evolve over time and we'll see what happens. If once it's passed, it requires submission, we'll certainly be happy to do that and submit to the FDA. So that's our view where it stands. But like I say, they've been very clear that enforcement discretion for LDTs will continue until such time as legislation is passed.
Great. Thanks for the color and look forward to seeing you at our conference next week.
Yes. We're excited to be there, Julia. And as always, it's a lot of fun.
The next question comes from the line of Puneet Udda, Leerink Partners. Your line is open.
Yes. Hi, Mark. Thanks for all the details of the study. Appreciate all the slides. So maybe just the first one that on one question that we have received frequently around economic benefit and our conversation with the payers.
Economic benefit is central to the payers, but during your conversations, I was hoping to get a view from you in terms of how they're weighing the pharmacy benefit versus the inpatient Based on the data shown here in the slides, 13% is of that $5,500,000 $5,000 savings is coming from pharmacy benefits and you also said the CNS medications were also a smaller part of the $10.36 of annual savings per patient. So just wanted to get a view of how payers, you have had a number of conversations, how are they incorporating the inpatient and outpatient services in their cost savings models to make an economic decision here?
Yes, Puneet, thank you and happy New Year to you as well. You're right, a lot of the benefits for this obviously accrue in areas other than pharmacy. I think what's been excellent to see is that these payers are actually quite sophisticated in their understanding about the comprehensive impact of depression on their costs. Now I can't always say that that's true across other disease states, to be honest, but I think we've been pleasantly surprised at just how aware they are. And the statistics are this at the national level are compelling about just how much this cost.
That $20,000 a year cost figure that we mentioned has come from studies looking at what it costs to treat for a treatment resistant depressed patient per year, there was widespread agreement that that's a number that is in no way surprising and one that they understand that any way to reach remission will significantly reduce that. So they have been very sophisticated, and we're not looking necessarily to recover costs specifically in pharmacy. They have been looking at this on a very holistic level. I think the interesting component to this that has been different is that our payer markets team has done quite a bit of work on the employer side with self funded employers. Now remember, self funded employers represent about 50% of patients in the country.
And for them, there's an entirely additional component that actually in many ways for them is more important than all of this, and that's the lost productivity associated with patients that have inappropriately treated mental health issues. That has been very compelling to them. We've, of course, mentioned Kroger and fact that we have an initiative with Vectra and that we're in discussions about a GeneSight initiative as well. I think you'll see us announce other collaborations with self funded payers, and probably the most prominent in our portfolio to help them is what GeneSight can do for mental health just because this lost productivity number is just so compelling for them. So I think overall, we've been pleasantly surprised to have the receptivity that we've seen on the health economic analysis.
Last thing, of course, is that with an OPTIM study, highly credible study, large database, I think that carries a lot of credibility as we present that type of evidence to payers.
And the only thing I'll add is when we talk to the payers on the medical plan, non PBM plan, that's where the diagnostics get reimbursed. And so the nice thing about the Optum data is that that $6,000 in annual savings and 87% of it coming from inpatient and outpatient services. That's the medical plan and that's where the diagnostic gets reimbursed as well. So they get to realize the impact within that exact plan.
Got it. Thanks for that. And then just wanted to I'm not sure if this was covered already, but just wanted to understand. In the last quarter, you talked about claims that were getting submitted to Medicare that required additional documentation. Just wanted to make sure where that process stands and are you all caught up at this point regarding that documentation?
Yes. Thanks, Puneet. Obviously, we made commentary on the last call that reflected the fact that we're in the middle of training physicians to comply with some of the additional documentation. We'll, of course, give updates on that on the earnings call that's coming up here in a few weeks, and we haven't made any intra quarter commentary on that. It's probably best left for commentary after the quarter when we report out.
Okay. Sure. Thanks, guys.
Our next question comes from the line of Dan Leonard with Deutsche Bank. Your line is open.
Hello. Happy Friday.
Same to you, Dan. Happy New Year.
So this might be a bit of an apples and oranges question, but I actually thought that the fact that 80% of the patients in guided were congruent at baseline was surprising. It's higher than I would have thought it would have been. Can you compare how that ratio of folks on congruent versus non congruent, how does that compare to the assumptions you've been flowing through your various economic models?
Yes. And so it's it's probably important to break this out by red, yellow and green because to be honest, the congruent, I think, gets a tad confusing. And that data we've provided. I think by memory, there was about 30% that were on green, 40% So that's kind So that's kind of roughly the breakdown of how those patients entered the study. I think the difference probably the biggest difference we saw in this study is that 21% of patients that were on red medications was lower than what Brian had discussed in the other studies.
In those other studies, the average was somewhere around 25% to 27% of patients that were entering on red medications. So it was, in fact, lower in this study than we had seen. This is the largest study, so you'd have to probably take this as representative of probably what's out there in the general population. And I don't know that those are statistically different. But it was slightly lower than what we would have anticipated based on previous studies.
And do you think that impacts the math at all
around savings?
No, I don't.
Yes, sorry, that was your other question. Sorry, Dan. I don't think so because given the size of the health economics studies that we've done, both of them, and those were real world claims, right? So we got into the Optum database real world claims. So as a result of that, think those 2 are probably relatively aligned in that the size of each study was large, so they're probably respective of each other.
So I don't think we see any issues there just given the magnitude and a real world claims analysis.
Okay. Thank you.
The next question comes from the line of Doug Schenkel with Cowen. Your line is open.
Hey, good afternoon and happy New Year. What is your plan for communicating outcomes good or bad with commercial payers?
Yes. Thanks, Doug, and happy New Year to you as well. I think, Will, it's going to depend obviously on exactly how these tech assessments go. As we mentioned, this is going to cascade over the coming year and will depend on whether we're successful in getting the ones slated for later in the year, pulled earlier. I don't think we're going to be communicating blow by blow on this.
You shouldn't necessarily expect us to do that for significant payers that issue coverage decisions, I think that's significant payers that issue coverage decisions, I think that's what you should expect, and that's what you'll see here over the coming months is as coverage decisions are made. But that's, I think, our plans at this point.
Okay. And along those lines, there are examples where you entered into contracts pending positive tech assessment. I think that's the right way to put it. I'm just curious based on the fact that some of those or at least one of those is in place, how quickly do you think that a decision could come here? Is it a matter of a couple of months or should most folks really be thinking of this as likely a multi quarter process?
Well, I think as you well know, you're incredibly experienced in this space. Nothing tends to happen quickly. We're obviously, I think, have done everything humanly speculate on just how quickly this might translate into coverage decisions. I think you rightfully point out that 25% of covered lives, we actually already have contracts in place. So when those 25% issue reimbursement will be immediate.
And so those are included in the 60%, and they'll be getting the complete dossier here in the coming days. I don't want to speculate how long this will take. It will certainly take longer than I would like. I can guarantee you that, but I'm a rather impatient person. So I think we'll move as aggressively as we can here to get these decisions made.
But I do think the team has done a remarkable job and far more than we have ever done prior to a dossier submission to get medical directors, behavioral health experts and everybody in front of this data before the dossier is sent in. So we'll have to see how successful we are in translating that quickly to decision.
Okay. Thank you for that. And if I could just ask one more, I just want to go back to the question about the FDA safety communication issued back in November on the use of genetic tests to predict the patient's response to specific medications. I appreciate your reiteration of your stance on LDT reform, your position on LDT reform and the outlook at least in the near term for continued FDA enforcement discretion. That said, just to be more specific about it, I'm curious if there's been any clarity provided by the agency to Myriad that GeneSight was not really a targeted or focused on product and that indeed was more focused on some of the DTC companies.
I go back to this because it's clearly a focus area for some investors and I just wanted to give you an opportunity to maybe address that question more specifically.
Yes. Thanks, Doug. We certainly had obviously, there's public commentary that's been made, and we've had private discussions as well. I think I mentioned before, we happen to be at Bio Utah together with Doctor. Jeff Sheeran on the day that, that actually came out.
So I was there with him. Doctor. Sheeran was the keynote speaker there, and so we were there and got a chance to catch up on a number of topics that we've discussed over the years. What I can say is they have always publicly differentiated between consumer testing and hand testing and LDTs. As you well know, there were efforts made a few years ago specifically to crack down on consumer testing.
That's testing done on a more recreational basis without having health care professionals involved. That has always been a significant concern for the agency, and I think that remains a concern for the agency that, that is an area that they're concerned about how what the impact to patients could be for direct to consumer types of testing. Obviously, we're in a very different space. We're in the LVT space, and they've been very clear that enforcement discretion remains in the LDT space. So I know there is a very clear distinction in the line, and I think that distinction remains.
Next question comes from the line of Jack Meehan with Barclays. Your line is open.
Thank you for taking my question. Mark, you referenced the APA guidelines. They do have a statement from July. And this afternoon on a public call, the head of the task force of novel biomarkers and treatments said the study failed and that their negative guideline statement stands. So without guideline support, what makes you think you're going to get broader reimbursement coverage from payers?
So this is Brian, I'll start. Just to clarify, there was a publication from a group headed up by Doctor. Nemerov and team that was asked for by a subcommittee of the APA to review pharmacogenomics, which resulted in a publication of a review of pharmacogenomics before the guidance study had actually been published since it was published today and was not included in that review. That is different from guidelines and the last guidelines that have actually been issued by the APA for the treatment of depression came out in 2010 and have not been updated since. And so there are no current guidelines for pharmacogenomics and for the treatment of depression by the APA at this time.
As my follow-up question, he said that, that guideline statement was endorsed by the APA Board of Directors. Is that not true?
I don't know what has happened within the APA, closed door, non open minutes to what the APA has discussed. We're not privy to that. So I cannot say that, but public statements or public written statements around guidelines have not been updated since 2010 for the treatment of depression. Thank you.
And Mr. Gleeson, there are no further questions. Please continue with your presentation or closing remarks.
All right. Thank you, David. This concludes our call. A replay will be available on webcast on our website for 1 week. Thanks again for joining us this afternoon.
Ladies and gentlemen, that does conclude the conference call for today. We thank you for your participation and ask that you please disconnect your line.