Utilizing a new "data-mining" research technique, the Food and
Drug Administration (FDA) has identified a potential increased incidence of
pituitary tumors associated with the second-generation antipsychotic
risperidone (Risperdal).
While the finding is preliminary, the study illustrates the successful use
of a relatively new technique to comb through millions of individual records
in the FDA's Adverse Event Reporting System (AERS) database.
"This report was primarily a methods paper," said Paul
Seligman, M.D., director of the FDA's Office of Pharmacoepidemiology and
Statistical Sciences. The report "looks at the application of a
particular datamining technique" to the AERS database.
"We do a lot of these data-mining runs," he added, "and
what we are really talking about here is an increased frequency of reporting
of a particular adverse event [associated with a certain drug], compared with
other products."
There are "lots of reasons," Seligman continued, "why one
could observe an increased frequency of a reported adverse-event/drug
combination in our dataset." The more difficult, but essential, task, he
told Psychiatric News, is to "go back and carefully look at
each of the cases and consider whether they might indeed represent a true
association between the drug's use and the particular adverse
event."
The research was led by Ana Szarfman, M.D., Ph.D., an FDA staff researcher
in the Office of Pharmacoepidemiology, and other members of Seligman's team.
(Szarfman was unavailable to comment for this article.)
The unpublished report was presented in June at the International
Conference on Bipolar Disorder in Pittsburgh by P. Murali Doraiswamy, M.D., an
associate professor and head of the Division of Biological Psychiatry at Duke
University. Doraiswamy, who has become well known for his analyses of FDA
adverse-event data regarding psychiatric medications, collaborated with the
FDA team on the current project.
Specifically, the team looked for any adverse-event report of a pituitary
tumor involving any of the six second-generation antipsychotics and the
first-generation drug haloperidol (Haldol). They found 307 reports of
pituitary tumors in the AERS database; 64 of those were associated with an
antipsychotic medication. One report involved haloperidol, leaving 63 reports
associated with a second-generation antipsychotic. Risperidone was linked to
75 percent of those 63 reports.
To find the reports, the team used a technique dubbed the Multi-Item Gamma
Poisson Shrinker (MGPS). The technique was developed through a cooperative
research development program of the FDA and outside statisticians and
information-systems experts.
"We are just finishing that agreement and now moving this tool into
the hands of our safety evaluators to use on a more routine and regular
basis," Seligman explained.
The FDA's AERS database receives an estimated 420,000 reports a year,
Seligman continued. Since its inception in 1968, the database has compiled
more than 2.5 million reports for more than 8,000 drugs and biological
products.
"We only have a staff of 24 safety evaluators who are monitoring
these reports," he added, "and so part of the motivation for
developing this tool was to help us have another way—other than the
human mind—to sift through all of these data and look for potential
statistical associations that need subsequent careful review and
follow-up."
The MGPS is a complex Bayesian computer-based algorithm that calculates
relationships between a drug and a particular adverse event to determine if
the event occurs on a higher-than-expected basis. The resulting calculation (a"
reporting rate") can be adjusted for estimated patient-exposure
rates (how many patients have taken the specific medication for how long a
period) and for background rates of a given event in a specific population.
The result is also adjusted for common demographic variables that could
confound the reporting rate. The reporting rate for the adverse event in
people taking the drug in question is then compared with reporting of the same
adverse event over the entire 35 years of data for all medications in the
database.
A reporting rate that is statistically significantly higher than the rate
for the whole database is referred to as a "signal."
Researchers both inside and outside the FDA believe the method is reliable
enough to provide safety evaluators with consistent signals that deserve
further scrutiny.
Using MGPS to mine AERS has its limitations. Adverse events reported to
AERS are widely accepted as representing only a fraction of the true number of
such events. This underreporting, along with incomplete reports, makes it
difficult to determine causality in a drug/adverse-event combination.
In addition, numerous factors may bias reporting of particular
drug/adverse-event combinations. For example, the recent FDA warnings
regarding adverse events associated with antipsychotics and antidepressants
likely increased awareness of those events among both prescribers and
patients, possibly leading to an increase in reporting.
Nevertheless, "validated data-mining techniques offer great promise
to enhance pharmacovigilance practices," Doraiswamy and Szarfman wrote
in an article in the September 2004 Pharmacotherapy.
The FDA's Seligman agreed, noting, "Safety evaluators need tools that
will allow them to compare drugs within classes, drugs across classes, and
multiple drugs in combination that may be associated with a particular adverse
event. They need tools that will also allow them to combine different sets of
adverse-event terms that might all be associated with a particular outcome. In
the case of risperidone, for example, we looked at various terms, such as
`elevated prolactin,' `hyperprolactinemia,' and `galactorrhea,' as well as
`benign pituitary tumor' or `pituitary adenoma.'"
In the end, the finding of a risperidone/pituitary tumor signal is not all
that surprising, Seligman told Psychiatric News.
"Given that you have here a drug that is well known to cause elevated
prolactin levels, and there is pretty solid evidence of induction of pituitary
adenomas in rodent models," the finding appears to confirm the validity
of the new data-mining technique. In this case, the method successfully
identified an increased frequency of reporting of an adverse event that would,
in theory, not only be plausible, but also predictable.
However, Seligman cautioned, the technique cannot confirm or rule out a
causal association between a specific drug—or group of drugs—and
an adverse event. Finding a signal simply suggests the need for follow-up.
The FDA-approved labeling of risperidone does include a precaution
regarding the drug's documented tendency to induce hyperprolactinemia. The
label notes that increased prolactin levels can increase rate of growth in
about one-third of human breast cancers. In addition, the label acknowledges
that "an increase in pituitary gland, mammary gland, and pancreatic
islet cell hyperplasia and/or neoplasia was observed in the risperidone
carcinogenicity studies conducted in mice and rats."
Doug Arbesfeld, a spokesperson for Johnson and Johnson Pharmaceutical
Services, whose Janssen unit markets Risperdal, told Psychiatric
News, "We take seriously all reports concerning patient safety, and
we agree with the study's authors that their findings are preliminary."
He added, "It is something that we are aware of and that we are looking
into." ▪