The FDA Azithromycin Softshoe and Why It Matters

This week, a Danish study by Svanstrom and colleagues appeared in the New England Journal of Medicine that failed to show significant cardiovascular risk to azithromycin compared to other antibiotics in the Danish national health care system.  This report was in direct contradiction to an earlier report from Ray, et al. published in the New England Journal of Medicine (and widely hailed in press) that suggested a significant risk of cardiovascular death attributed to azithromycin compared to other antibiotics in a Tennesse Medicaid population - and a report that the FDA used to justify the wide dissemination of a Drug Safety Communication for azithromycin.

While I have been quite critical of the conclusions drawn by Ray, et al. before, I was even more surprised by the Drug Safety Communication for azithromycin issued by the FDA that basically said: "any time a patient has a bunch of conditions that are known to cause prolonged QT interval, be careful prescribing azithromycin."  Such warnings, of course, should apply to any drug that could cause prolongation of QT interval, but for some unclear reason, the FDA felt they had to act in the case of azithromycin.

Now it seems the FDA doing a softshoe on their earlier warning regarding azithromycin, trying to justify their warning that was based on retrospective data-mining techniques drawn from diagnosis and treatment codes, not randomized trials. 

In a perspective piece from Andrew D. Mosholder et al, from the FDA that accompanied the report from Svanstrom et al, the authors acknowedge the many limitations of the original study by Ray et al.:

"The study by Ray et al. has limitations that are intrinsic to obervational, nonrandomized clinical studies.  In particular, nonrandomized studies cannot exclude the possibility that patients receiving a drug under evaluation differ from the control patients in some important but undetected way, causing bias in the results. Such confounding may bias comparisons not only between patients receiving antibacterial drugs and those receiving no antibacterials but also between patients receiving different antibacterials."

Yet in the very next paragraph of the FDA member's perspective piece, they persist in their indifference to their prior statement regarding the bias inherent to Ray et al.'s report and decide to focus on timing:

"Despite these caveats, the results presented by Ray et al. warrant serious attention.  A chief strength of the study is the time-limited pattern of the risk: the azithromycin-associated increase in rates of death from any cause and from cardiovascular causes spanned days 1 through 5, reflecting the typical 5-day duration of azithromycin administration (e.g., Zithromax Z-pak)."

The FDA authors refuse to believe that there could be any other confounding variables that might have occurred in the first five days of hospitalization that lead to the increased cardiovascular risk seen in their azithromycin-treated group.  It is more important, I guess, to support retrospective data-mining and statistical data manipulation of diagnosis and procedure codes.  This, you see, they must support.  Big Data in our new era of expanded codes and computers is to be our new saving grace, you see.

Fortunately, I think the FDA folks mean well: they give us salient advice in their final paragraphs of their perspective piece explaining their mistake.  Things like "Clinicians must consider the arrhythmogenic potential not only of azithromycin but also of potential alternative antibacterial drugs." and "The risks and benefits of antibacterial therapy should be considered in prescribing decisions." 

No kidding.

But we will not see a black box warning retracted - that would be too obvious.  Nor will we see extensive news coverage about these new findings regarding this antibiotic's cardiovascular safety - that doesn't grab the main stream media's attention. 

What we have, instead, is something much more concerning to me when the members of our own FDA make claims based on poor data: irrelevance. 

Publishing warnings on QT prolongation that should apply to any drug administered to the patient that is older, bradycardic, with low potassium or magnesium levels, or already on known drugs that can cause prolonged QT - generates irrelevant noise for doctors.  Like the Boy Who Cried Wolf, we risk compromising the FDA's relevance to patient safety.   When they spend time on retrospective data-mining exercises that find risks in the neighborhood of 1 in 100,000, they risk failing to report important deaths related to new technologies with an incidence of at least 3 in 16,000 that reside in their own MAUDE database.

In today's internet age, doctors don't need any more Big Data-driven safety noise, we need razor-sharp analytic safety focus.

-Wes