# Presentation: 195612

## Epidemiologic Analysis of Spontaneous Adverse Reports

- Mary Willy, Ph.D.
- Division of Drug Risk Evaluation
- Office of Drug Safety
- Center for Drug Evaluation and Research
- Food and Drug Administration

## Objectives

**To describe the limitations in using passive surveillance data for an epidemiological analysis**
**To describe the methods used to identify and analyze rare adverse drug events**

## Limitations of Passive Surveillance Data 

**Underreporting; **
**Rarely more than 10% of serious events and 2-4% of non-serious events reporting**
**Reporting rate varies over life of marketed drug (“Weber” effect)**
**Secular trends in reporting**
**Systematic definitions not used by reporters **
**Cannot yield an incidence rate**** **

## Underreporting (1)

**Canadian study of toxic epidermal necrolysis (TEN) reporting to Canadian regulatory agency**
**TEN is almost always drug-related**
**Of 250 cases of TEN admitted to burn centers, only 25 were reported to Health Canada’s surveillance program**
**Mittman et al., Drug Safety 2004; 27 (7): 477-487**

## Underreporting (2)

**In 1985 the Rhode Island Department of Health started a pilot program designed to encourage physicians to report ADRs**
**After 2 years, there was a 17-fold increase in reporting from Rhode Island**
**Scott et al., JAMA 1990:263:1785-88**

## Factors Affecting Reporting to FDA

**Nature of the adverse event**
**Type of drug product and indication**
**Length of time on market**
**Extent and quality of manufacturer’s surveillance system**
**Rx or OTC drug status**
**Perception of liability**

## Weber Effect

**Peak of adverse event reporting is often at the end of second year**
**Despite lack of decline in usage **
**When comparing reporting rates of several drugs must consider length of time on market**

## Secular Trends

**Reporting has increased over time**
**More emphasis on training healthcare professionals to report to FDA**
**Comparing newer drugs to older drugs difficult because of differences in reporting to FDA**

## AERS Report Counts by Type: 1990 through 2004

## Media Attention

**Analysis of potential signals difficult when see increase in reporting**
**News about a signal with one drug in a class may impact on others**
**Reports from lawyers and patients increase**
**High profile news report about one unusual case may stimulate others to report**

## Definitions Used for Reporting

**Definitions used for analysis can be difficult**
**Reporters use different terms for reporting same syndrome**
**When missing information, not clear how to identify cases**

## Methods

## Methods of Safety Signal Evaluation with Passive Surveillance

**Case series**
**Descriptive analysis of cases**
**“****Reporting rate” calculations**** **
**Numerator = number of case reports received**
**Denominator = some measure of drug exposure in population**

## Reporting Rate Difficulties

**Numerator **
**Can be difficult developing definition of case**
**Search terms used to find cases may miss cases**
**Denominator **
**National data on patient exposure not always available**
**“****Exposure” can be continuous, short-term, or intermittent; all difficult to measure and project nationally**
**Traditionally use prescription or sales data as proxies for exposure**

## How to Use Reporting Rates?

**Compare to background rates**
**Compare to drugs within the same class**
**Compare to drugs for similar indication**

## Factors Considered When Interpreting Reporting Rates

**Magnitude: Comparisons to background and other drugs show difference**
**Consistency: See increase in AERS reports for less severe form of event**
**Clinical trial support: Pre-marketing clinical trial data suggest possible risk**
**Literature reports provide support**

## Reporting Rates (RR) Comparison*

**Glitazones and acute liver failure**
**Troglitazone RR = 107 per million pyrs**
**Rosiglitazone RR = 11 per million pyrs**
**Pioglitazone RR = 13 per million pyrs**
***Rates per 2001 publication - source: Rodriguez EM et al Pharmacoepidemiology and Drug Safety 2001; 10: 407-410**

## Reported Cases of Fatal Rhabdomyolysis (as of May 2001) and Numbers of Prescriptions (in thousands) for All Statins Dispensed in the U.S. Since Launch

|  | Lovastatin | Pravastatin | Simvastatin | Fluvastatin | Atorvastatin | Cerivastatin |
| --- | --- | --- | --- | --- | --- | --- |
| Fatal Cases | 19 | 3 | 14 | 0 | 6 | 31 |
| No. of RX‡ | 99,197 | 81,364 | 116,145 | 37,392
 | 140,360
 | 9,815
 |
| RR*/
million RX | 0.19 | 0.04 | 0.12 | 0 | 0.04 | 3.16 |

**Source: Staffa et al. NEJM 2002: 346 (7): 539.**

- ‡Data are through May 2001 and are from National Prescription Audit Plus, excluding the Long Term Care Channel; * RR=Reporting Rate

## Background Rates

**Background rate data sources**
**Literature**
**NCHS data (hospital discharge, mortality)**
**Not available for all diseases / outcomes or patient subgroups (e.g. childhood syndromes)**
**Provides context**
**If reporting rates are similar to or greater than background rates, suggests there is a safety signal of concern**

## Background Rate (RR) Comparison*

**Glitazones and acute liver failure**
**Troglitazone RR = 107 per million pyrs**
**Background rate ****~ 1 per million pyrs**
***Rates per 2001 publication - source: Rodriguez EM et al Pharmacoepidemiology and Drug Safety 2001; 10: 407-410**

## Reporting Rates ≠ Incidence Rates

**Incomplete numerator**
**Crude estimate of denominator**
**Utility**
**Provide crude context for reported cases**
**Comparisons between drugs which account for difference in use**
**Comparisons with background rates of disease**

## Conclusions

**The analyses of passive surveillance data can identify potential signals**
**Epidemiology tools are helpful to further quantitate the safety signal**
**Limitations in the system can make final conclusions difficult**
**No standard metric for “calling” a finding “real”**

## DDRE Epidemiologists

**Syed Ahmad**
**Allen Brinker**
**Cathy Dormitzer**
**Kate Gelperin**
**Cynthia Kornegay**
**Lois La Grenade**
**Carolyn McCloskey**

**Andrew Mosholder**
**Parivash Nourjah**
**Rita Ouellet-Hellstrom**
**Mary Willy**
**Diane Wysowski**