A Quantitative Analysis of Adverse Events and “Overwarning” in Drug Labeling FREE

Product labeling is a primary source of drug safety information for physicians. However, the effectiveness of labeling in communicating adverse drug events (ADEs) may be diminished by the problem of “overwarning,” in which excessively long and complex lists of potential reactions can result in information overload.^1- 2 The Food and Drug Administration (FDA) highlighted this issue in 2006 as they unveiled new labeling guidelines, specifically discouraging the inclusion of “exhaustive lists of every reported adverse event, no matter how infrequent or minor.”^3- 4(p2) Yet, at present, there are no baseline data on overwarning, nor are there benchmarks against which the success of the FDA's interventions can be measured. The goal of our study was to address this gap by producing comprehensive quantitative data on ADE labeling patterns. We further sought to measure whether the 2006 guidelines were successful in reducing the burden of overwarning.

We retrieved all drug labels available as of December 17, 2009, on the federal Web site DailyMed.⁵ DailyMed provides drug data in Structured Product Label (SPL) format, an electronic labeling standard mandated by the FDA and available for more than 85% of prescription drugs.⁶ We developed a software tool, known as the Structured Product Label Information Coder and Extractor (SPLICER), that uses natural language processing to extract ADE data from SPLs. A previous study of its performance on 100 labels showed a recall of 92.8% and a precision of 95.1%.⁷

We processed 5602 SPLs using SPLICER and performed descriptive statistics on the extracted ADE counts. We then used Wilcoxon rank-sum testing to perform subset analyses along 4 parameters: prescribing frequency, therapeutic category, approval date, and labeling format. Prescribing frequency was determined based on 2008 national dispensing data, and SPLs were divided into the 200 most commonly dispensed medications and all other drugs. Therapeutic category was determined using the National Drug File Reference Terminology “mechanism of action” classifications⁸ (eg, angiotension-converting enzyme inhibitors), and SPLs were broadly grouped by clinical specialty (eg, cardiovascular). Approval date was based on the original FDA acceptance of the drug as a new molecular entity,⁹ and SPLs were grouped by decade of approval. Finally, to determine the impact of the new FDA regulations, SPLs were separated into those compliant with the 2006 formatting guidelines and those in any other format.

We extracted 534 125 ADEs from 5602 SPLs. As given in the Table, the number of unique ADEs per label ranged from 0 to 525, with a median of 49 and a mean of 69.8. At the upper extreme, we identified 588 labels having more than 150 ADEs and 84 labels with more than 300 ADEs. In terms of prescribing frequency, labels for the 200 most commonly dispensed medications contained significantly more ADEs than other labels (median, 79 vs 47; P < .001). Aggregating drugs by medical specialty, we found ADEs to be highest in medications associated with neurology (n = 168), psychiatry (n = 116), and rheumatology (n = 111). Looking at date of approval, we found that newer medications had significantly more labeled ADEs than older medications, with drugs approved during the 1980s and 1990s having the highest overall number of ADEs.

Structured Product Labels formatted in accordance with the 2006 labeling guidelines contained a greater number of ADEs than other SPLs (72 vs 47; P < .001). To control for the possibility that this differential was due simply to new format labels being associated with newer drugs, we repeated the comparison looking only at medications approved since 1980. Again, we found a significantly higher number of ADEs in new-format SPLs than in older label formats (113 vs 72; P < .001).

The goal of our research was to survey the current landscape of ADE labeling. We found the volume of ADEs to be remarkably high, particularly in newer and more commonly prescribed medications as well as in psychiatric and neurologic drugs. These patterns are not entirely unexpected. Newer drugs may face more rigorous clinical trials and postmarketing surveillance compared with older medications. Similarly, commonly prescribed drugs, by sheer volume of patient exposures, are likely to generate more ADE reports than less common drugs. The high volume of ADEs found in neuropsychiatric medications may relate as much to patient population as to the effects of the drugs themselves. Yet while a high number of labeled ADEs is not necessarily indicative of drug's true toxicity, the presence of such excess data still may induce information overload and reduce physician comprehension of important safety warnings.

Recent FDA guidelines do not appear to have reduced overwarning. Structured Product Labels formatted in compliance with the 2006 regulations actually contained more ADEs than other labels. This finding underscores the tremendous challenge faced by the FDA in reversing the long-standing trend toward overwarning. It is our hope that the baseline data provided by this study will inform the design and evaluation of future efforts to decrease the complexity of adverse event labeling.

Correspondence: Dr Duke, Regenstrief Institute, 410 W 10th St, Ste 2000, Indianapolis, IN 46202 (jduke@regenstrief.org).

Author Contributions:Study concept and design: Duke, Friedlin, and Ryan. Acquisition of data: Duke and Friedlin. Analysis and interpretation of data: Duke, Friedlin, and Ryan. Drafting of the manuscript: Duke, Friedlin, and Ryan. Critical revision of the manuscript for important intellectual content: Duke, Friedlin, and Ryan. Statistical analysis: Duke and Ryan. Administrative, technical, and material support: Duke, Friedlin, and Ryan.

Financial Disclosure: None reported.