PVmap™ of the Week

ProSanos has initiated a program to publicly provide a limited set of PVmaps™ generated from the FDA's Adverse Event database. A different map will be posted each week 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 PVmaps or the PVmap of the Week program, .

Abnormal Sleep-Related Events and Sedative-Hypnotic Products (3/25/2007)
The FDA recently requested a label change for all sedative-hypnotic products, which includes a warning regarding "complex sleep-related behaviors, which may include sleep driving. Sleep driving is defined as driving while not fully awake after ingestion of a sedative-hypnotic product, with no memory of the event." Other behaviors include making phone calls, and preparing and eating food while asleep.²⁸

Investigating an adverse event constellation such as this raises issues of adverse event coding and case definition. In the Medical Dictionary for Regulatory Activities (MedDRA) used for coding adverse events in the FDA AERS database, there is currently no precise code for sleep driving or sleep eating. Sleep talking is a coded event, but does not involve a telephone. The closest terms appear to be abnormal sleep-related event, and abnormal sleep-related event nos. To investigate this event further, we created an Event-focused PVmap for the former, using publicly-available data from the FDA via its Adverse Event Reporting System (AERS) covering the period from 2001 through the first quarter of 2006.

The Event-focused map above quickly identifies the drugs most highly associated with the MedDRA term abnormal sleep-related event. The drug "Ambien" shows the strongest statistical relationship to the event in question, well above the threshold of statistical significance (horizontal blue line), while other popular sedative-hypnotic products aren't significantly associated. In view of this striking map, a follow-on question might be to consider whether these abnormal sleep-related events are related specifically to "ambien" (zolpidem, marketed as AMBIEN^®) or apply to all sedative hypnotic products. Generally, all of the products covered by the FDA labeling request are used in the same patient population, for the same indication, and with the same concomitant medications. The drugs have mostly been on the market for a long time, so the "Weber Effect" (the tendency for newer drugs to have a higher rate of adverse event reports generally)²⁹ does not apply. However, one important question to ask in this case concerns the possibility of publicity causing stimulated reporting into the AERS database. A Trajectory PVmap can be used to help answer this question.

The Trajectory PVmap for zolpidem and abnormal sleep related event is shown above illustrates a curious phenomenon. While zolpidem has been on the market since 1999, all of the reports to the FDA of abnormal sleep-related event came in the first quarter of 2006. Why is this so? In early 2006, there was publicity regarding zolpidem and "sleep-eating". Because of the unusual nature of this adverse event, this drug-event relationship was widely covered in the popular press. A Google search for "ambien" and "sleep eating" finds 27,400 hits.

This is not to say that the safety signal is not "real". But it casts doubt on whether data mining of spontaneous reports, which are subject to stimulation by publicity, could be reliably used to determine whether the adverse events in question here are real and are related to zolpidem specifically or to all members of the class. At this point, appropriate methodology for gaining further information about these events may be a carefully-designed study, including patients using a number of sleep medications, to measure the incidence of abnormal sleep-related events using a methodology that is unaffected by publicity.

Event-focused PVmap
The PVmap shown in the case study above is an Event-focused PVmap, allowing you to visualize which drugs are most highly associated with a particular adverse event (rather than the other way around). In this case, the adverse event is the MedDRA term abnormal sleep-related event and the red dots represent drugs reported in the AERS database to be associated with this condition. On the horizontal axis of this graph is the reporting ratio, which compares the number of times that a drug is reported with the specified adverse event to 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 drugs with the strongest association to abnormal sleep-related events appear at the top and to the right on the PVmap.

Trajectory PVmap
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 ProSanos PVMaps for multiple therapeutic areas. To learn more about PVMaps projects in your therapeutic area or indication, please .

Disclaimers

1. ProSanos is not affiliated with the authors of cited references, and this article does not imply endorsement of their findings, content, or offerings.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. PVmaps has been evaluated as a safety signal investigation tool for over two years.

References

28. FDA Requests Label Change for All Sleep Disorder Drug Products. Accessed on the Internet at http://www.fda.gov/bbs/topics/NEWS/2007/NEW01587.html, 21 March 2007.
29. Hartnell NR, Wilson JP. Replication of the Weber effect using postmarketing adverse event reports voluntarily submitted to the United States Food and Drug Administration. Pharmacotherapy. 2004 Jun;24(6):743-9.