PVmap^® of Interest

ProSanos has initiated a program to publicly provide a limited set of data mining results generated from the FDA's Adverse Event database. On a periodic basis, we will post results focusing on a drug and adverse event combination that is a current topic of discussion within the industry or in the published literature. For more information about CLÆRITY^®, PVmaps or the PVmap of Interest program, .

Anosmia and Zicam Cold Remedies: The Effects of Stimulated Reporting in AERS (1/15/2010)
On June 16, 2009 the FDA posted a notice to patients and providers regarding post marketing drug safety information regarding Zicam nasal products and the potential adverse event, Anosmia (the inability to perceive odors) - FDA Advises Consumers Not To Use Certain Zicam Cold Remedies Intranasal Zinc Product Linked to Loss of Sense of Smell. At that time, it was very clear in the FDA AERS database that there was a statistical association between these Zicam products and anosmia.

What was the FDA seeing in the FDA AERS data and what effect has this publicity had on the reporting characteristics for Zicam subsequent to the public notice? In the discussion below, we first present the information leading up to the FDA's notice and then conclude with a review of the data following it, using CLÆRITY^® software to visualize the relationship, and put it into context.

First we begin our investigation by producing a "Drug-focused PVmap" for Zicam, showing the adverse events that are reported more disproportionately for Zicam than all other drugs combined. Our initial review here utilizes the FDA's Adverse Event Reporting System database from the fourth quarter of 1997 through the fourth quarter of 2008, available at the time of the FDA's notice.

As we can see in the above chart (anosmia is the yellow highlighted point), at the time of the FDA's notice, the statistical relationship between Zicam and anosmia is very strong (Reporting Ratio approaching 1,000 and a Statistical Unexpectedness Value equal 308, the maximum value we calculate). This made anosmia the #1 ranked statistical signal at that time. Several of the other events shown to be reported disproportionately more for Zicam include ageusia (closely related to anosmia) and nasal discomfort (likely to be reported when using a nasal-type product).

Let's now look at the evolution of this statistical signal over time by producing a "Trajectory" PVMap. The Trajectory PVmap below shows the Statistical Unexpectedness and Reporting Ratio by quarter for Zicam and anosmia.

We see the disproportionate association has been in existence for quite some time (Reporting Ratio remaining near 1,000 throughout) with the Statistical Unexpectedness growing steadily between 1999 and 2005 when it achieved the maximum value of the Statistical Unexpectedness scale equal 308. It has remained there ever since.

What have we seen since the FDA's public notice? We first look at the "Drug-focused PVmap" using the FDA AERS database through 2009 Q2 which contains six months of additional reports.

From a statistical perspective, little has changed with anosmia, but we now see a few closely associated events with higher degrees of disproportionality for Zicam (nasal discomfort, ageusia, hyposmia, hypogusia). Let's consider data table for the "Trajectory PVmap" using the same updated data.

In the year leading up to the public notice there were 61 total reports for Zicam, 38 noting anosmia. In the AERS 2009 Q2 data release there were 563 total reports for Zicam, 425 of them noting anosmia. This is nearly a 10-fold increase in reports for just one quarter versus the entire previous year! All but seven of these reports were received at the FDA after June 16, 2009, representing just two weeks of the entire quarter.

Here we have shown the use of CLÆRITY to produce a number of different PVmap investigations - Drug-Focused and Trajectory - that provide insight into what led up to the FDA public notice as well as the effects of this publicity on these databases. In this particular case, we also demonstrated the emergence of this statistical signal, at a very early stage. But perhaps of greater interest in this situation is the evidence of the power of publicity on the FDA AERS database. Certainly this is a clear example for a product that has been on the market for many years, but the observer should note the impact that publicity may influence on these spontaneous databases when performing automated signal detection on them. Consideration must be given to the temporal relationship between product-related publicity and the reporting of adverse events. Note that we have done a rapid analysis of these data considering all Zicam reports for illustrative purposes. The FDA also considered the route of administration of Zicam for their analyses.

About Drug-focused PVmaps
A Drug-focused PVmap allows you to visualize which adverse events are most highly associated with a particular drug of interest. In this case, the drug is Zicam and the red dots represent Adverse Events reported in the AERS database to be associated with Zicam. On the horizontal axis of this graph is the reporting ratio, which compares the number of cases of a particular adverse event with the number expected due to chance alone. The vertical axis expresses the statistical significance of the finding. Dots above the horizontal blue line and to the right of the vertical blue line represent "significant signals". The adverse events with the strongest association to Zicam appear at the top and to the right on the PVmap.

About Trajectory PVmaps

A Trajectory PVmap traces the evolution of a potential drug safety signal over time. The horizontal axis represents the reporting ratio, which compares the number of cases of a particular adverse event with the number expected due to chance alone. The vertical axis expresses the statistical significance of the finding. Thus significant drug safety signals show an upward trajectory over time, sometimes with some small statistical fluctuation. Generally, it is important to investigate signals when they reach a Statistical Unexpectedness level of 5 or more (corresponding to a p-value of 10-5).

Sponsor companies have used CLÆRITY Software for multiple therapeutic areas. To learn more about CLÆRITY projects in your therapeutic area or indication, please .

Disclaimers

1. Potential risks highlighted by drug safety analysis must be balanced against the clinical benefit attained by the use of a pharmaceutical product in a given clinical situation. Nothing in these analyses is intended to influence the practice of medicine, nor to weigh the benefits of one product over another.
2. Whether the reporting ratio of an adverse event is high enough to influence the decision to use a given product or products can only be determined by a complete analysis of the benefits, risks, and therapeutic alternatives.
3. Use of the publicly available FDA AERS data does not imply endorsement or agreement of the findings by the FDA Center for Drug Evaluation and Research.
4. There are many factors that can influence how the adverse events are reported in the AERS database and may impact the resulting safety signal. These include but are not limited to: publicity and media attention, litigation, length of time drug is on the market, whether the event in question has been previously attributed to the drug, the source of the report, etc.
5. AERS data must often be "cleaned" prior to analysis. This process may include de-duplication, reconciliation of misspelled product names, mapping of adverse events terms, and other manipulations which could introduce bias into the analysis.
6. PVmaps has been evaluated as a safety signal investigation tool for over two years.