About This Episode
Expanding our scientific understanding of the effectiveness and safety of interventions for individuals with End Stage Kidney Disease is an important goal of researchers. In this episode of Dialogues, we’ll talk with Dr. Linda Ficociello and Dr. Anke Winter, two Fresenius Medical Care experts in epidemiology and research. They discuss ways Real World Evidence can complement existing research in gaining new and valuable insights that improve kidney disease care.
Featured Guest: Dr. Linda Ficociello
As part of the Global Applied Data Science, Biostatics, and Epidemiology organization, Linda leads a Real-World Evidence generation team for FMC North America. Her team analyzes a multitude of clinical and economic data through utilization of advanced analytics such as biostatistics and epidemiology to demonstrate the clinical and cost effectiveness of FME products and services with primary focus on FMCNA activities. This information is conveyed to the medical, clinical, and scientific community through differing means such as peer-reviewed publications and presentations.
Featured Guest: Dr. Anke Winter
Within the Global Applied Data Science, Biostatistics, and Epidemiology organization, Anke oversees Epidemiology & Real-World Evidence (RWE) activities in the EMEA region. Her team provides support in assessing the value of FME products, therapies, and clinical strategies in real-world settings. Anke has over a decade of research experience in academic and industry settings with 32 scientific publications. Prior to joining Fresenius, Anke held faculty appointments at the Washington University School of Medicine in St. Louis.
Listen to This Episode
Maddux: Expanding our scientific understanding of the effectiveness and safety of interventions for individuals with end-stage kidney disease is an important goal of researchers. In this episode of dialogues, we’ll talk with Dr. Linda Ficociello and Dr. Anke Winter, two Fresenius Medical Care experts in epidemiology and research. Both Dr. Ficociello and Dr. Winter discuss the ways real-world evidence can complement existing research in gaining new and valuable insights that improve kidney disease care. Welcome, and thank you both for joining me today.
Maddux: Anke, let’s start with you. Tell me a little bit about just the description, your sense of how real-world evidence fits into the world of clinical research and what you see there.
Winter: Thank you so much, Frank. I think real-world evidence is really an opportunity for us to gain insight into real-world utilizations and real-world use of our products, therapies and also our clinical strategies. So a lot of times we gain insights through well-controlled clinical trials, but then again, this may not reflect the patient populations or the settings we really provide care in. So real-world evidence is an opportunity to fill that gap and to particularly focus on gaining insights into real-world utilizations within the settings we typically provide the care for our patients in.
Maddux: So you both deal with supporting the clinical research, predominately with our products that we develop, and we have products that go through various regulatory pathways. Linda, give me a sense of, how does real-world evidence fit within the regulatory framework, and does, in your case, the FDA and in Anke’s case the E.U. regulators and the MDR-- does it accept real-world evidence as part of the package?
Ficociello: So for what we’ve done outside of clinical research, for instance, has been all in the post-approval. So we might have publications on Velphoro, which has gone through a clinical-trial process, but then afterwards there might be some data gaps and some things that we want to fill in. So we’ve really focused on seeing how these products are used in the real world, like Anke just said, and also I feel like a lot of that data exists, and to not look at it and not to explore that is really a waste, right, and so we often talk about populations within these groups. For instance, we might have populations in our clinics that would never be in a clinical trial, and this is really the way to gain some insights into those patient populations. Also the sub-analyses that we can do might not’ve been done in a clinical trial. So I think that mostly what we’ve done is kind of expanded on the work that’s been done within the clinical trials in these real-world settings.
Maddux: So how much of your all’s work is preapproval versus post-approval? Are you more concentrated on sort of those preapproval-related studies or on filling in these gaps that you described?
Ficociello: mostly all post-approval.
Ficociello: Yes. So some of the work that we might do in more of the cost-effectiveness can also be done preapproval, just to give some insights into something that might be developed within the products or pharmaceutical side. But as far as the data analysis, we mostly work on post-approval.
Maddux: How about you, Anke?
Winter: Yes. Similar to what Linda described, we are also working on questions and gaining insights, really, once a product or therapy is approved and on the market and then trying really to work out how it performs in these real-world settings.
Maddux: As a clinician, a new product comes on the market, and if it’s highly innovative, sometimes I’m a little anxious about being the first to use it. So I’d imagine a lot of the work that you all are doing is trying to help socialize and make clinicians like myself comfortable with trying something different from what we might’ve been trained on before. How unique is the Fresenius set of data that we have from all the clinics that we operate in trying to create this data as opposed to it always being a post-marketing study? You have the opportunity to look at a lot of internal data on practice patterns and subpopulations and other things. Tell me a little bit about the uniqueness of your data set.
Winter: I think having this real-world data set that really reflects the patient care stems from our dialysis centers. It’s really a unique asset for Fresenius Medical Care, and this certainly allows us, as Linda earlier mentioned, also to look into practice pattern, heterogeneity of treatment, the facts where we try to understand really at the population at hand, how-- which treatment or which therapeutic option may work best for the individual patient, and I think this is-- where we don’t have a selected population, this is really where we have the patients that receive treatment routinely. So this is, I personally think, a really great asset, where we as a company can support various activities through real-world evidence-generation. We can gain more insights into our quality-improvement initiatives, supporting through analysis our clinical services. We may have some opportunities to add to some of our regulatory requirements in the post-market surveillance process, and certainly this is also an asset which we can utilize to advance our understanding of kidney disease and contribute to the scientific community through publications and contributions at conferences.
Ficociello: I think, in addition to what you just mentioned about the frequency in which we see our patients-- in addition, I think Fresenius also has all these other ways that data’s brought in, right, whether it’s through the machine and the information that’s brought over to the data warehouse through the dialysis machine or what the patient might be entering at home or coming from their machines at home. I think this is a wonderful opportunity to bring in all of those sources of data, and I think that’s a little bit unique to the vertically integrated company.
Maddux: Linda, so we have data sources that are different around the world. Can you describe what the date warehouse is in North America?
Linda Ficociello: So the data warehouse is kind of the place where all the data from the different sources end up. So, for instance, we have things from the labs, we have things from within the clinic, some of the things that are captured from home, and they’re all kind of put into this one space.
Maddux: And that data warehouse becomes your sort of engine for deciding what you have access to for your epidemiologic research, right?
Linda Ficociello: Definitely. So we can ask the question, but we need to also have that data, right? And so if we’re asking questions, we might have something that exactly matches that question or something that we can say can stand in for something we’re looking for.
Maddux: And how often do you have to go outside for an outside data source? Like I know we’ve done studies where we looked at weather-related items. Is that frequent or just rare?
Linda Ficociello: Yeah, for the things that I do, it’s pretty rare. I think that the only times that we really go outside is when we want a different perspective from a different provider or if we have a situation that it’s not within our patient population. For instance, some of our products might be for acute care that we don’t have that information in the data warehouse, so we might have to go somewhere else to get that.
Maddux: So I’m interested in not just the amount of data that we’re creating from our dialysis treatments today, but also, what are the other data sources that you all see that are likely to become part of our mix for real-world evidence, whether that’s data that comes from sensing environments, whether it’s other sources of data. Anke, what do you see as the opportunity there?
Anke Winter: I think currently we have really huge and broad data available coming really from our dialysis centers, and I think I could see two future applications or opportunities. I think we might see in the future more data coming from the patient or coming from the experience the patients are having while performing their therapies at home themselves, and I also think that in the future, we may want to expand our data portfolio to having more data available from critical care setting.
Maddux: Linda, what sort of outside sources of data could you imagine we might be utilizing in the future?
Linda Ficociello: I think that there’s a lot of opportunity for patients at home. I think that with different monitoring devices that could be had in the future, that would give the physician more opportunity to engage with the patients. I think that one of the things that I find really interesting is some of the big data that’s in the cloud. So the information that’s coming from the machine, as you know, kind of spits out information every second or every so many seconds, and that kind of information like with the Crit-Line, for instance, that can be stored in a cloud environment, that can be merged with that machine data, and that you would be able to have instances where you could know exactly what’s happening at that moment, what’s happening with the machine, what’s happening to the blood volume of the patient. You have blood pressure information. You really have quite a robust bit of information, and right now, all of that kind of information is available in the machine and can be cloud based.
Maddux: Is there any opportunity, you think, in the future to incorporate genetic information or genomics into the mix?
Linda Ficociello: Yes, I think that’s a big question. So I think that there’s-- as information becomes more and more specific to the patient, it increases the ability to specialize and to have precision medicine, right? So I think that’s important in our patient population and also before they get to be in our population, if that makes sense, so that for patients with kidney disease and with CKD, if we have markers that we’d know can improve that person’s renal function and preserve it, that’s going to be very important in the future.
Maddux: Clearly, one area that I think for us is potentially an opportunity to expand the kind of way we look at information and we look at the environment somebody lives in because I think that has substantial impact on their outcomes ultimately.
Linda Ficociello: Yeah, and I think that’s-- the social determinants of health, I think, is such an important aspect of it because if you think about it, we’re looking at lab values and other things about these patients, but you can’t really see what that environment is, and if someone’s struggling for their living situation, it’s going to be really hard for them to stay at home for hemodialysis, for instance. I hope on the clinic level that they’re really seeing the full patient, but when we do our research, we’re seeing just like little bits and pieces sometimes.
Maddux: I think as we bring more of the social determinants into the mix of what our care model looks like, we’re going to have to look at those ways that we are either passively or actively capturing information and figuring out how we incorporate that into the way we look at the real-world research and evidence that we’re trying to create because at the end of the day, that probably has more impact than we’re acknowledging today. So I’ve recently heard from Anjana Harve, global chief information officer for Fresenius Medical Care that we aggregate over a terabyte of data on a regular basis from our clinics, say, massive amount of data growth and opportunity to have substrate for real-world evidence investigations. How has the information-technology infrastructure changed over the course of your all’s career? I mean, what were you doing in the early part of your career that’s fundamentally different today the way you actually do this, and has COVID-19 shown you that you can actually do some of this work in a different way, because you’ve had to be remote in doing some of it?
Ficociello: Yeah, there’s a lot in that. So just on the technology alone side, when I first started, we were on flowsheets. So that move from paper records to everything being accessible through the data warehouse has been amazing. I mean, as far as a project that we can only do maybe in one dialysis unit can now be looked at overall. So I think that piece of it has been amazing, just the integration of all the information, the fact that you could see directly from machine, and it doesn’t add a lot to the person who’s in the-- caring for the patient, and I think that’s important, too, right? We don’t want to be invasive to caring for actual patients. So I think that’s been really amazing. As far as the pieces about COVID, I think we’ve definitely seen that we can do a lot, and we can do a lot remotely. I think before, it might’ve seemed like we were quite a distance away, but now she could be in Massachusetts right now, right, or she could be in Germany. So I think that we’ve been able to reach out and work together quite a bit.
Maddux: Last year I pretty much upended the way we were organized as a medical office and combined a lot of folks, and one of the things that got combined was the kind of work that you all do and the access that people would have to other individuals with like skills and same interests, and I’m just curious. How is that going? Has there been any opportunity to interact sort of cross-regionally or with other folks in other parts of the world with expertise? I’m just curious whether any of that has evolved to get to the point where we’re actually seeing some benefit from bringing all of you together.
Ficociello: I was really integrated with RTG Medical before, and so kind of coming over to the more Global Medical Office, it’s allowed me to do other things. I think, too, I’ve kept a lot of the responsibilities on RTG Medical, but I’ve also taken on some FKC projects, too, and in the process of doing that, I’ve had to also work with different people within Len’s team, and so that’s been amazing, and I haven’t had the opportunity to do that before, and one of the projects that we’ve been working on recently was on the antibody response in COVID vaccines, and I had to work very closely with Joanna, and she has been wonderful, and she has direct access to the data, which we’ve never had before, and so with a project like that, you had to, because everything was so fast, right? They were working with Spectra. We were working with the clinics. We were working with the data warehouse, so there was so many pieces there. Having someone who had direct patient access and also who was willing to be working crazy hours with me to do it was awesome.
Maddux: You all did a very rapid analysis of that Massachusetts study and so forth, yeah.
Ficociello: Yeah, so it definitely needed that level of speed and also cooperation, and that’s the other piece that I feel like has really been great, the cooperation amongst all the people.
Maddux: Anke, you’ve got connections throughout not just Europe but other continents as well. Has the change made much difference for you? How’s it going?
Winter: Yes, I mean, I personally think it’s such a pleasure to work in a team of experts globally together. That’s just my personal opinion, but we also had opportunities where we could really bring different expertises together. So we recently worked closely with our colleagues in the Asia-Pacific region together, where we had an opportunity to provide epidemiological expertise to a project, where there was an interest in understanding better the quality of care provided. So for us it was a fantastic opportunity to really learn more about health care settings, practice patterns in the Asia-Pacific region, which, prior to coming together as a Global Medical Office and as our global team, was something that I had rarely opportunities to. So this is one example where we could really leverage on expertise existing in different regions and come together and collaborate in an efficient way on a project together.
Maddux: The databases primarily in North America and in the rest of the world are slightly different. I’m just curious whether there are any other distinct differences between the kind of work that you’re working on when you’ve got a project like Velphoro in North America versus the kind of projects, Anke, that you’re working on with regard to supporting the real-world analyses in an MDR world as opposed to an FDA world. Are there fundamental differences or just-- it’s a different database, but it’s the same kind of activity?
Ficociello: I don’t work in the same database that she does, but from my understanding of it, we do have similar databases. I think within our team we now have direct access to the database, which I think is different than your access level. So any project that is involved with RTG Medical, for instance, we have a data request through Frenova. It’s a data-licensing agreement. We have de-identified data and so forth, and from what I understand, your model is more like that versus kind of the FKC-related projects that we do, where we have direct patient access, and I think-- and you might be able to speak to this more, but you’d also do more data analytics on the regulatory side, right?
Winter: We are at the moment exploring really opportunities, how we can leverage our existing data or existing real-world data to support post-market surveillance activities of our quite-broad product portfolio, and as we have a new device regulation, it’s something that is really of importance that we constantly add to our understanding of how our products perform and how safe they are when utilized after their approval. So this is really adding a piece, I would say an evidence piece, to already existing important activities that the clinical research department is certainly performing on a regular basis when it comes to post-market clinical follow-up of our devices.
Maddux: One of the things that I know that the larger team is working on is creating a universal de-identified database of all of our clinical data, wherever the clinics sit, and that process has matured some and is getting closer to fruition. But how do you see working with some of the other potential customers that you might have? So who do you consider your customers, and what do you think the future may look like when we have, for example, a truly fully anonymized database that becomes available to have various questions posed to it?
Ficociello: As far as our customers, I think that we have different customers around the organization. I think that, like I said, we’ve really been focused on RTG data earlier, but I think that that’s kind of changing, and I think that from RTG’s perspective, they’ve really seen that this has been a successful thing to do, and so we’re working more, like I say, with FKC, also a little bit with FHP, and so I feel like as we move more global, there’ll also be an opportunity for some of the products that’re going to be global that you might have data on now in Europe that we don’t have yet, right, and so I think getting some of that early data for products that’re going to be coming over to the U.S. will be very different when there is that kind of global database.
Maddux: Anke, what do you think about-- what’re some of the key questions that you believe you may have to address related to the coral dialyzer, as an example, which is one of these novel products that is hitting the market now but clearly is one that’s got some new features to it? Do you see any opportunities there?
Winter: Yes. We actually already are, as part of our clinical evidence-generation initiative, actively looking into experience and real-world evidence-generation within the EMEA region. But this is certainly a product that subsequently may be launched in different regions and countries globally. So we’ve already been in contact with our colleagues, for example, in Latin America to share our experience and also to see what opportunities there may be to certainly generate more evidence and also have experiences that are really fitting the local context of the health care provided. So I think there will be opportunities with our product family as we branch out to different regions, certainly also see how we can reflect this in some of our data-analysis activities and evidence-generation initiatives.
Maddux: Before we wrap up, I want to ask each of you, do you have a favorite project that you have done in the past that you’d love to do something similar in the future?
Ficociello: I think I would probably talk about a project that we’re in the midst of right now, because I think it’s so important. So we’ve been looking at factors that are modifiable -- that are increasing the risk of people dropping PD, so patients who are dialyzing at home with peritoneal dialysis, and what are the risk factors for them switching to in-center, and with such a push on home dialysis and having people go home, I think maintaining the patients that are home is really important, and so for this-- and this kind of brings out a project where we had to bring in a lot of different data sources, and so we’re looking at things from the machine, prescriptions. We’re also looking at things that’re coming from social workers, from the home nurse, from the patients themselves, patient-reported outcomes, and we’re able to kind of put together all of that information to support all of these initiatives for people staying at home for peritoneal dialysis, and I think that’s been really interesting for me.
Maddux: I recently was interviewed at an investor conference and was asked the question what I would imagine things to be like five years from now if I had my way in the field, and it was this ability to look at these modalities quite seamlessly so that people who are at home can stay at home. They have greater opportunities to choose, and the infrastructure is there to support their activity, and when they have to transition to another modality, it’s not quite the upheaval that it is today, I think. So it’s very similar to the transition project of trying to keep people at home that you’re describing. Anke, what about you? Any favorite projects over the years?
Winter: I would say I love projects that really have some immediate implications, and we can answer some questions, for example, that our clinical colleagues are wondering about. I think one example of a project we recently published was about understanding as to whether the time of day when patients received dialysis care may potentially impact their nutritional status, because there’s been some concern in the scientific and clinical community that the time during dialysis may impact meal intake and potentially then also have some impact on the nutrition status, and we know that poor nutritional status is associated with unfavorable outcomes, and we could leverage really our real-world data and to explore this question in data stemming from our clinics, and the good news was really-- we typically don’t enjoy null results, but this was a very good null result that we didn’t see any differences in nutritional markers over two-year period comparing patients who received dialysis in the morning versus the afternoon shift. So I think that was a project I enjoyed very much, because it had a clinical question and would have had an immediate clinical impact. So these are the projects I also enjoy doing. I mean, we’re involved in so many different projects, and I think this is also what makes the work exciting at Fresenius, I have to say, because I would say it never gets boring.
Maddux: I would like to thank Dr. Linda Ficociello, Dr. Anke Winter, for joining me today on our dialogue segment talking a little bit about insights from epidemiology and the work that they do with real-world evidence. Thank you both.
Ficociello: Thank you.