Sensitivity and specificity in signal detection with the reporting odds ratio and the information component.

Abstract

As measures of association between an adverse drug reaction (ADR) and exposure to a drug the reporting odds ratio (ROR) and the information component (IC) can be used. We sought to test the reliability of signal detection with these. We simulated ADR counts as binomially distributed random numbers for different expected ADR frequencies and theoretical reporting odds ratios (RORs). We then calculated the empirical IC and the empirical ROR and their confidence intervals. The rate of signals that was detected despite a theoretical ROR of 1 represented the false positive rate, and represented the sensitivity if the ROR was >1. For expected case counts below 1 the false positive rate oscillates from 0.01 to 0.1 even though 0.025 were intended. Even beyond expected case counts of 5 oscillations can cover a range of 0.018 to 0.035. The first n oscillations with the largest amplitude are eliminated if a minimum case count of n is required. To detect an ROR of 2 with a sensitivity of 0.8, a minimum of 12 expected ADRs are required. In contrast, 2 expected ADRs suffice to detect an ROR of 4. Summaries of measures for disproportionality should include the expected number of cases in the group of interest if a signal was detected. If no signal was detected the sensitivity for the detection of a representative ROR or the minimum ROR that could be detected with probability 0.8 should be reported.