How to Outsmart Big Pharma - Part I

How to Outsmart Big Pharma - Part I

As a health care professional, one of your duties is to evaluate literature and make clinical decisions for your patients. What? I didn't say it was an easy part of your job. Maybe not even a fun part. You've got to be able to separate the wheat from the chaff. To read between the lines and see through the BS. To arrive at that happy place where sound evidence-based decisions come from. 

This special tl;dr two-part post will help you see some of Big Pharma's tricks--so you'll be better prepared when you read up on that new drug approved by the FDA.

Part I is like a mini journal club. We'll focus on a recent secondary analysis of the ARISTOTLE trial.

Part II will take a broader look at the other marketing practices of Big Pharma.

We should quickly emphasize, these posts are (somewhat) tongue in cheek. Despite what you read online, Big Pharma is not inherently evil. Oh sure, there are many examples of drug companies doing some shady shit. 

But on the whole, they're just trying to put their products in the best possible light. Yes, they're trying to make money. But labeling things as "good" or "evil" is painting a very complex situation too black and white.

All of that said--It is really fun to call shenanigans on some of the tactics of Big Pharma. So let's get started. 

Part I

I came across an interesting study late last year. Go ahead and read the link. We're going to do a quick journal club. 

What you just read (you DID read the study, right?) is a secondary analysis of the ARISTOTLE trial....which is the landmark trial that led to the approval of apixaban [Eliquis].

Of the 18,201 patients that went through the ARISTOTLE trial, the authors here filtered out 4,808 of them. These 4,808 patients had valvular heart disease. The authors wanted to specifically test apixaban vs. warfarin in a sudden-death cage match in this population. What did they find? That apixaban was no different than warfarin at preventing stroke in patients with or without valvular heart disease.

So, apixaban = warfarin for stroke prevention. Minus all of the monitoring and food/drug interactions of warfarin. #Winning

Alrighty then. Let's get started with the fastest journal club ever.

What do you think of when you see "valvular heart disease?" Quickly now. 

You're thinking mechanical heart valve, aren't you? Your brain is jumping to the warfarin patients with a goal INR of 2.5 - 2.5. That's definitely what I thought. I'm not a cardio specialist, but I'd bet that a good number of us hear "valve" and our brain immediately associates to "mechanical." 

Now admit something else. You didn't read the entire study above, did you? You just read the abstract. Who has time to click the "full text" button in the upper right-hand corner, and then read an entire study?

What point am I getting at here? 

The title and abstract of this study are a fantastic piece of marketing. 

Before I go further, I am not attacking apixaban, this study, or the authors. The ARISTOTLE trial (and this sub-analysis) are very well-designed. And in fact, of the new oral anticoagulants (NOACs), apixaban is probably my favorite. But BMS and Pfizer know what they're doing. "Valvular heart disease" does not mean "mechanical valve."

When you actually read through the study, you'll see that the comparison warfarin arm was titrated to an INR of 2.0 - 3.0. That makes sense, because that's the goal in 'valvular heart disease' (although you probably need to shoot for the higher end of that range). It's worth noting, because seeing the reference INR range is a enough of a clue to look more closely at what they're studying. The abstract makes no mention of the reference INR range. I'm sure it's elementary and obvious to a cardiologist. But a lot of non-cardiologists also prescribe apixaban. 

Here's what's going to happen with this study. A patient with a mechanical valve will see the direct to consumer commercials while watching TV one night. They're tired of the constant INR checks, so they'll do like the ad says and "talk to their doctor about Eliquis." 

Their (extremely busy, and hurried) doctor will peruse literature on the NOACs, and find the abstract above. All of the trigger words are there. "Apixaban," "Valve," "Non-inferior to warfarin." It's a perfect match! Eliquis it is for the patient. The problem here is that the drug has not been studied in MECHANICAL valve patients.  

This isn't the first time I've come across apixaban being used creatively. I've also seen apixaban prescribed in dialysis patients. Now this one is particularly tricky. If you read the package insert, or the healthcare professionals website, you'll see that there is no dose adjustment for renal failure, including hemodialysis patients.

But there's also an asterisk by the HD recommendation. When you read the fine print, you'll read that HD patients were not included in safety or efficacy trials. How'd they get away with that? The "no dose adjustment" recommendation is based on a single dose kinetic study in eight patients. This is a far cry from a 10mg BID starting dose for DVT/PE, wouldn't you say? So apixaban has never actually been studied in dialysis patients. But it IS marketed for dialysis patients. 



Anyway, maybe I'm over-reacting. Maybe it's my own mistake for incorrectly associating "valvular disease" with "mechanical valve." And maybe apixaban is great for both mechanical valves and dialysis. But show me the data, that's all. 

And again, I like apixaban. I'm not rallying against it. I'm just pointing how some seemingly innocuous recommendations come from questionable (if not outright sneaky) data. Your future job as a pharmacist will be to notice things like this. You have to know the limitations of the data you're using to treat your patients. 

But again, it IS fun to call BS, wouldn't you say?

In Part II of this series, we'll leave the journal club behind, and take a broader look at Big Pharma's advertising practices as a whole.

What do you think about the ARISTOTLE trial? Do you have any other studies you've come across using iffy data? Let us know in the comments!

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