BETA - What are challenges associated with using real world data?

What challenges are associated with using real-world data? That particular bucket of investigational trials, new trials, that is an important part of research and most work happening at cancer centers does focus on that kind of research. What we call phase one trials, phase two trials, phase three trials, those are all prospectives, meaning that we follow patients, we enroll them in a trial and follow them prospectively. Not all prospective trials are interventional or pharmacologic. For example, when I was a fellow, when I was a trainee, the big project that I'm interested in myeloma to begin with was digital life coaching during transplant for myeloma. That's a good example of research where we actually randomly assign patients receiving transplant to either get usual care with some handouts about how to stay well and how to feel well and rebuild their lives with a transplant, or we did that, plus we gave them access to a life coach by phone or text who could help them with sleeping, with moving, with feeling just less stressed about returning to work after transplant. That's research too. Even though there's no drugs involved, nothing is changing about the transplant itself or the myeloma itself. That absolutely is prospective research. I have colleagues, for example, Dr. Urvi Shah at Memorial Sloan Kettering in New York who's doing prospective research around gut microbiome, seeing how people's gut bacteria changes over time and what that means for them and for the myeloma precursor conditions. Not all research needs to involve new drugs. Also, there can be trials, prospective trials of drugs that are already approved using them in different ways. A good example of that would be this CAR T therapy. CAR T therapy is approved in the US. As of the day that I'm filming this, April 5th, the FDA has just approved one kind of CAR T for two prior lines and not four prior lines of therapy. So patients earlier in their myeloma journey, that trial that led to that approval was an example of research. Even though the drug is already approved, it's not approved in that line of therapy. That's also prospective research. Then, if you go this big picture separately from prospective research, there are other kinds of research as well. So there's retrospective research. So for example, what I alluded to earlier, if you go back and look at people's medical records and say, look, for everyone diagnosed with myeloma in the year 2021, how would they do? Or if we look at their dexamethasone dosing or look at their acyclovir dosing, what changed about it? And that's retrospective research, meaning that we already have our question in mind. We're not going to enroll patients in a trial. We're going to look back and what happened to these patients over the last two years, three years, et cetera, and make conclusions based on that. Retrospective research is not as strong as prospective research. Obviously, ideally, we should run trials for the big questions in myeloma. But as we'll talk about, there are some cases about real-world data, which often is retrospective by definition, is very useful in that regard. And I would say there's a third bucket of research, which is health services research or cross-sectional research. So I have also done work with Health Tree and with other organizations for survey-based research. Survey research is kind of in the middle somewhere, where it's not really retrospective, because you are asking a patient to donate their time and physically answer these survey questions in front of you. It's not always prospective. We're not always following them over time. Right now, for example, with Health Tree, we have a survey ongoing of eye health with myeloma, alluding to my earlier retrospective question with dexamethasone and eye complications in myeloma. This is a one-time survey. Could I serve you?