Dr. Barkoudah JCOM’s audience are the QI implementers and hospital leadership. And what caught my eye in your article is your perspective on the pharmacoeconomics of treating COVID-19, and I really appreciate your looking at the cost aspect. Would you talk about the economics of inpatient care, the total care that we provide now that we’re in the age of tocilizumab, and the current state of multiple layers of therapy?
Dr. Sakoulas The reason to look at the economics of it is because IVIG—which is actually not a drug, it’s a blood product—is very expensive. So, we received a considerable amount of administrative pushback implementing this treatment at the beginning outside of the clinical trial setting because it hadn’t been studied on a large scale and because the cost was so high, even though, as a clinician at the bedside, I was seeing a benefit in patients. This study came out of my trying to demonstrate to the folks that are keeping the economics of medicine in mind that, in fact, investing several thousand dollars of treatment in IVIG will save you cost of care, the cost of an ICU bed, the cost of a ventilator, and the cost even of ECMO, which is hugely expensive.
If you look at the numbers in the study, for two-thirds or three-quarters of the patients, your cost of care is actually greater than the controls because you’re giving them IVIG, and it’s increasing the cost of their care, even though three-quarters of the patients are going to do just as well without it. It’s that 20% to 25% of patients that really are going to benefit from it, where you’re reducing your cost of care so much, and you’re getting rid of that very, very expensive 20%, that there’s a cost savings across the board per patient. So, it’s hard to understand when you say you’re losing money on three-quarters of the patients, you’re only saving money on a quarter of the patients, but that cost of saving on that small subset is so substantial it’s really impacting all numbers.
Also, abandoning the outlier principle is sort of an underlying theme in how we think of things. We tend to ignore outliers, not consider them, but I think we really have to pay attention to the more extreme cases because those patients are the ones that drive not just the financial cost of care. Remember, if you’re down to 1 ventilator and you can cut down the use of scarce ICU resources, the cost is sort of even beyond the cost of money. It’s the cost of resources that may become scarce in some settings. So, I think it speaks to that as well.
A lot of the drugs that we use, for example, tocilizumab, were able to be studied in thousands of patients. If you look at the absolute numbers, the benefit of tocilizumab from a magnitude standpoint—low to mid twenties to high twenties—you know, reducing mortality from 29% to 24%. I mean, just take a step back and think about that. Even though it’s statistically significant, try telling a patient, “Well, I’m going to give you this treatment that’s going to reduce mortality from 29% to 24%.” You know, that doesn’t really change anything from a clinical significance standpoint. But they have a P value less than .05, which is our standard, and they were able to do a study with thousands of patients. We didn’t have that luxury with IVIG. No one studied thousands of patients, only retrospectively, and those retrospective studies don’t get the attention because they’re considered biased with all their limitations. But I think one of the difficulties we have here is the balance between statistical and clinical significance. For example, in our pilot study, our ventilation rate was 58% with the non-IVIG patients versus 14% for IVIG patients. So you might say, magnitude-wise, that’s a big number, but the statistical significance of it is borderline because of small numbers.
Anyway, that’s a challenge that we have as clinicians trying to incorporate what’s published—the balancing of statistics, absolute numbers, and practicalities of delivering care. And I think this study highlights some of the nuances that go into that incorporation and those clinical decisions.
Dr. Barkoudah Would you mind sharing with our audience how we can make the connection between the medical outcomes and pharmacoeconomics findings from your article and link it to the bedside and treatment of our patients?
Dr. Sakoulas One of the points this article brings out is the importance of bringing together not just level 1A data, but also small studies with data such as this, where the magnitude of the effect is pretty big but you lose the statistics because of the small numbers. And then also the patients’ aspects of things. I think, as a bedside clinician, you appreciate things, the nuances, much sooner than what percolates out from a level 1A study. Case in point, in the sponsored phase 3 study that we did, and in some other studies that were prospectively done as well, these studies of IVIG simply had an enrollment of patients that was very broad, and not every patient benefits from the same therapy. A great example of this is the sepsis trials with Xigris and those types of agents that failed. You know, there are clinicians to this day who believe that there is a subset of patients that benefit from agents like this. The IVIG story falls a little bit into that category. It comes down to trying to identify the subset of patients that might benefit. And I think we’ve outlined this subset pretty well in our study: the younger, obese diabetic or hypertensive patient who’s rapidly declining.
It really brings together the need to not necessarily toss out these smaller studies, but kind of summarize everything together, and clinicians who are bedside, who are more in tune with the nuances of individual decisions at the individual patient level, might better appreciate these kinds of data. But I think we all have to put it together. IVIG does not make treatment guidelines at national levels and so forth. It’s not even listed in many of them. But there are patients out there who, if you ask them specifically how they felt, including a friend of mine who received the medication, there’s no question from their end, how they felt about this treatment option. Now, some people will get it and will not benefit. We just have to be really tuned into the fact that the same drug does not have the same result for every patient. And just to consider this in the high-risk patients that we talked about in our study.
Dr. Barkoudah While we were prepping for this interview, you made an analogy regarding clinical evidence along the lines of, “Do we need randomized clinical trials to do a parachute-type of experiment,” and we chatted about clinical wisdom. Would you mind sharing with our readers your thoughts on that?
Dr. Sakoulas Sometimes, we try a treatment and it’s very obvious for that particular patient that it helped them. Then you study the treatment in a large trial setting and it doesn’t work. For us bedside clinicians, there are some interventions sometimes that do appear as beneficial as a parachute would be, but yet, there has never been a randomized clinical trial proving that parachutes work. Again, a part of the challenge we have is patients are so different, their immunology is different, the pathogen infecting them is different, the time they present is different. Some present early, some present late. There are just so many moving parts to treating an infection that only a subset of people are going to benefit. And sometimes as clinicians, we’re so nuanced, that we identify a specific subset of patients where we know we can help them. And it’s so obvious for us, like a parachute would be, but to people who are looking at the world from 30,000 feet, they don’t necessarily grasp that because, when you look at all comers, it doesn’t show a benefit.
So the problem is that now those treatments that might help a subset of patients are being denied, and the subset of patients that are going to benefit never get the treatment. Now we have to balance that with a lot of stuff that went on during the pandemic with, you know, ivermectin, hydroxychloroquine, and people pushing those things. Someone asked me once what I thought about hydroxychloroquine, and I said, “Well, somebody in the lab probably showed that it was beneficial, analogous to lighting tissue paper on fire on a plate and taking a cup of water and putting the fire out. Well, now, if you take that cup of water to the Caldor fire that’s burning in California on thousands of acres, you’re not going to be able to put the fire out with that cup of water.” So while it might work in the lab, it’s truly not going to work in a clinical setting. We have to balance individualizing care for patients with some information people are pushing out there that may not be necessarily translatable to the clinical setting.
I think there’s nothing better than being at the bedside, though, and being able to implement something and seeing what works. And really, experience goes a long way in being able to individually treat a patient optimally.
Dr. Barkoudah Thank you for everything you do at the bedside and your work on improving the treatment we have and how we can leverage knowledge to treat our patients. Thank you very much for your time and your scholarly contribution. We appreciate it and I hope the work will continue. We will keep working on treating COVID-19 patients with the best knowledge we have.
Q&A participants: George Sakoulas, MD, Sharp Rees-Stealy Medical Group, La Jolla, CA, and University of California San Diego School of Medicine, San Diego, CA; and Ebrahim Barkoudah, MD, MPH, Department of Medicine, Brigham and Women’s Hospital, Boston, MA.
Disclosures: None reported.