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. On a regular basis, we will post a map 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, .

Diabetic Ketoacidosis and Atypical Antipsychotics (2/2/2009)
A recent article in Annals if Clinical Psychiatry provides an excellent review and thorough analysis of the evidence in AERS for an association between diabetes-related symptoms and atypical antipsychotic agents. ⁶⁴ This association has been under study for some time. It is complicated by the fact that diabetes appears to occur more frequently in patients with schizophrenia. This complication to statistical analysis is known as "confounding by indication" or "confounding due to underlying disease". A further complication is that the incidence of diabetic symptoms seems to differ dramatically from drug to drug within the atypical-antipsychotic class, even though the FDA new requires all drugs of the class to bear a warning about the possibility of diabetes and ketoacidosis.

We used PVmaps to visualize the relationship between diabetic ketoacidosis and these drugs. In order to illustrate this relationship in a way that was not redundant with the comprehensive work of DuMouchel and colleagues, we chose an "Event-Focused" analysis, which describes the relationship between an adverse event, in this case, diabetic ketoacidosis, and all drugs. We utilized a different time window than the DuMouchel paper, and included data from the FDA Adverse Event Reporting System from the fourth quarter of 1997 through the third quarter of 2007:

We see here that, out of all of the thousands of drugs in the AERS database, the two drugs with the strongest statistical association to diabetic ketoacidosis are two atypical antipsychotic agents, olanzepine and quetiapine. In fact, these two drugs have "maxed out" the log Statistical Unexpectedness scale at 308, corresponding to a P-value for the test of association of 10^-308, the smallest number different from zero that can be represented on the typical computer. Further down the list we see various insulin formulations, which are there simply due to confounding by indication. Mixed in is risperidone, another atypical antipsychotic agent.

We see far weaker associations with phenothiazines, which are also anti-psychotic drugs but are not atypical antipsychotic agents. We can easily investigate this further by creating a Potential Interactions PVmap for chlorpromazine (a phenothiazine) and diabetic ketoacidosis. The Potential Interactions map shows that, in the majority of cases, patients who reported chlorpromazine and Diabetic ketoacidosis also reported the concomitant use of an atypical antipsychotic agent. Below we show that 32 of the 47 chlorpromazine cases had concomitant quetiapine. We obtained this information by simply clicking on the dot for quetiapine. Similar actions for olanzepine and risperidone account for the rest of the cases:

Much of this statistical information is previously known from the thorough investigation of this drug safety information. Still, we think that the Event Focused PVMap makes a strong visual statement about the widely-varying strength of association between diabetic ketoacidosis and various atypical antipsychotic drugs. We also think it clearly illustrates the specificity of the drug-induced ketoacidosis issue, in that nearly all of the non-insulin drugs are antipsychotic agents. For other adverse events (such as thrombocytopenia) a much wider variety of pharmaceutical classes and indications would be seen.

About Event-focused PVmaps
The PVmap shown in this case study is an Event-focused PVmap that allows 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 diabetic ketoacidosis 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 a drug is reported with the specified adverse event to the number expected due to chance a lone. 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 ketoacidosis appear at the top and to the right on the PVmap.

About Potential Interactions PVmaps

Above is a Potential Interactions PVmap that allows you to visualize what concomitant drugs are significantly associated with a specified drug/adverse event combination. In this case, the drug/adverse event combination is the drug chlorpromzine reported with the MedDRA term diabetic ketoacidosis. The red dots on the map represent concomitant drugs in use when the drug / adverse event combination chlorpromazine / diabetic ketoacidosis occurred. On the horizontal axis of this graph is the reporting ratio, which compares the use of the concomitant drug during chlorpromazine / diabetic ketoacidosis with the use of the concomitant drug 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 concomitant drugs that are most highly associated with the drug/event combination of interest appear at the top and to the right of the PVmap.

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. 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.

References

64. DuMouchel W, Fram D, Yang X, et al. Antipsychotics, Glycemic Disorders, and Life-Threatening Diabetic Events : A Bayesian Data-Mining Analysis of the FDA Adverse Event Reporting System (1968-2004). Ann Clin Psychiatry 2008; 20(1):21-31.