at this topic for 10 minutes, you know? So first, I wanted to say I have really no, I have tons of disclosures, none of which are pertinent to this. So it's interesting to me to hear Jim talk because it was, basically will reiterate some of the things I have to say here and hopefully say it in a little different way that might resonate in a little different part of your mind. But I would maybe consider myself somewhat of a groupie because I, or a stalker. And you'll see, I'm going to be citing Dr. Wright's work throughout this. We've heard a lot about the levels of evidence and the grading of the quality of the evidence that we have. And I think it is important to recognize the unbelievable contribution that Dr. Wright made to our literature with his efforts. He had little different numbers than I have. Maybe they're a little more up to date, I'm not sure. But I'm going to talk about level one evidence, a randomized clinical trial, the things that we all would hope to aspire to get to. And really, it's really quite rare. And I'll perhaps talk a little bit about why that might be. And foot and ankle, surprisingly, probably because the denominator is so small and there was like one randomized trial that made it a higher percentage. So it's interesting. I also was interested to hear about the AOA opportunity to look at those modules. But I might be able to save you a few bucks because I'm thinking that the three-part series that Dr. Wright was part of with other authors probably reviews a lot of that AOA module. So maybe Jim can tell us about that too. But he has articles on clinical trials and orthopedic research that talks about barriers. He talks about prioritization for randomized trials in his part two and then subsequently challenges and designs and conducting clinical trials. And I would tell you that these articles are outstanding. And then there's a recent sort of one that takes it all together that was a review article. And I would completely suggest that if you're really interested in this topic, you might want to just PubMed him and pull up those articles. So if I were to talk about the different issues in regards to the clinical trials and orthopedic research and sort of take the big picture item, which is all I can in this time limitation here, we really want to talk about a number of different factors. And again, Dr. Wright sort of highlighted some of these. But this is a little bit more comprehensive list but not completely comprehensive. So first of all, we've heard a lot of talks today, presentations that have been at the podium and they've been excellent. We've had a bunch of level four studies. We had some level threes and some level twos and even some level one studies. You want to really look at what sample size you're looking at. So for some of these studies where they're not going to be powered enough to even look at some of the subset of information that they're providing to you, you have to be sort of critical. And I think a lot of us know that. But when we're setting up a trial, we have the opportunity to plan for our sample size and then give ourselves a little bit of slush. Usually it's around 20%, 15 to 20% slush for people that are going to, patients that are going to drop out potentially. Yeah, we just heard Ellie just gave us a great talk on outcomes instruments. And clearly you want to pick the right outcomes instrument because the key item is to pick the right question. And what that outcome instrument is going to enable you to do. I should also mention about the sample size. You have to make sure that you use the literature to define what the difference is that you're interested in defining to get a good sample size. Enrollment's really important. And unfortunately, even though it sounds like a simple topic, it's really hard to get patients to enroll for a multitude of reasons. It might be that the patient doesn't want to enroll in a clinical trial or that there's no equipoise by the surgeon. The surgeon doesn't feel as though they feel that patient is a particularly good choice to enroll. So our biases really influence enrollment. Randomization, there's different ways to randomize for clinical trials. And you have to make sure that you pick an appropriate randomization protocol so that you're actually doing it in a good statistical fashion. Blinding can also be really quite challenging. And I thought I'd give the example of the STAR trial. So the STAR was a non-inferiority trial between a fusion and a total ankle replacement, right? They couldn't blind for that, of course. So blinding can be to the patient, it can be to the surgeon. But there's times when blinding isn't appropriate. We also have unplanned crossover. And I'll use an example from our CARTIVA trial that we had. We randomized our patients and as soon as they randomized to a fusion, they refused to continue on in the trial because they wanted the implant. So we had some loss in that capacity and we also had some failures with the implant that went on to have a fusion. So we had some crossover. You have to make sure that you are analyzing and reporting your data appropriately and getting some statistical help is important. You have to have, as Jim had mentioned, you have to have some education about doing some of these things. And I went on to get my master's in public health because I thought it was really important and I understood a little bit more about clinical trials. And it was really, really helpful to me and very interesting. But there's a lot of ways that you can learn how to do some of these things or you can just consult your colleagues that are really experts in helping you analyze and report your data. Some of these subgroup analyses that we see are not, the primary outcome measure is powered but yet the subgroup analyses are not. So if you're planning on doing an important subgroup analysis as well, you need to consider that in your power. The data needs to be generalizable. And when you have one group that presents the data, or you have one person, like for instance, I always use the example of Roger Mann. So Roger Mann does a bunion operation. It turns out fantastic for Roger Mann but maybe it's not generalizable to Judy Baumhauer. So you need to make sure that you have a number of individuals and those individuals can contribute to the data so that you have an understanding that it's generalizable. And lastly, whatever your study is looking at is gonna have an economic impact on the findings. So you might want to make sure you understand what that economic impact's going to be as well. So the challenges in clinical trials, I think really funding is a major barrier to a lot of us doing anything that's a level one trial. You know, the CARTIVA trial I think was $29 million. It's very difficult to get funding from sources that are outside of industry for us at these times. There are funding sources but it's very challenging. It takes a lot of time. That particular trial took me 10 years and a lot of other people in this room were participants in that. It takes a lot of time to run something like that from soup to nuts. You have to have some experience, as I mentioned before. You have to have infrastructure with clinical coordinators. So these are the challenges that we meet in order to, we try and meet in order to get a good clinical, randomized controlled trial to go. And as I mentioned before, the lack of equipoise, the selection of your patient criteria, they should be every patient that comes into your office should be enrolled into a clinical trial. That's what they do in oncology. That's what we should do. So what opportunities we have, it sounds like, that sounds like a bunch of challenges and we'll never get past that. No, we have great opportunities. And one of them was mentioned before, clinical trial networks. So we can all network together towards answering a clinical question. And what you need to do is you need to find out and unify to figure out that you feel a clinical relevant question needs to be answered and then get the individuals to participate. You do need some standardizations for education and training when you start to enroll patients and make it be this multi-centered clinical trial. And then you need to disseminate and adopt the clinical trial results. You have to have those points all in mind as you move forward. And this article that I cited here is a great informative article to allow you to guide people into clinical trial networks. Well, what do we have? We have OFAR. We had OFAR that started out to be a network for us to be able to provide information into a centralized hub and then draw from that centralized hub. That may be changing to some extent, but we'll still have opportunities to work together. And then Jim also mentioned the small, simple trials. So these randomized trials can be quite challenging from a standpoint of a level one clinical trial with cost and all those aspects. But a few patients, and this paper that he wrote was really around sort of orphaned conditions that you might not have that many patients that would represent a large sample site. But we can take just a few samples from a lot of different people in this room and be able to answer a good clinical question. So where do you find clinical trials and where are they listed? And so anyone who has not looked at clinicaltrials.gov, you really should. There's a lot of foot and ankle trials that might be available to your patients that you could turn them on to. And again, it would help us with the science. Thank you very much. Thank you.

Dr. Wright

level one evidence

clinical trials

funding

clinicaltrials.gov