Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports

TLDR

Signal generation from spontaneous adverse drug reaction reports is likened to finding a needle in a haystack, yet statistical approaches have been under‑utilised. The authors developed and evaluated a Proportional Reporting Ratio (PRR) as a statistical aid for signal generation. PRR compares the proportion of a specific reaction for a drug to that proportion across all drugs using a 2×2 table, and was applied to 15 newly‑marketed UK drugs with thresholds of ≥3 cases, PRR ≥ 2, and chi‑square ≥ 4. The PRR identified 481 signals, of which 70 % were known adverse reactions, 13 % were likely disease‑related, and 17 % required further investigation, demonstrating its usefulness.

Abstract

The process of generating 'signals' of possible unrecognized hazards from spontaneous adverse drug reaction reporting data has been likened to looking for a needle in a haystack. However, statistical approaches to the data have been under-utilised.Using the UK Yellow Card database, we have developed and evaluated a statistical aid to signal generation called a Proportional Reporting Ratio (PRR). The proportion of all reactions to a drug which are for a particular medical condition of interest is compared to the same proportion for all drugs in the database, in a 2 x 2 table. We investigated a group of newly-marketed drugs using as minimum criteria for a signal, 3 or more cases, PRR at least 2, chi-squared of at least 4.The database was used to examine retrospectively 15 drugs newly-marketed in the UK, with the highest levels of ADR reporting. The method identified 481 signals meeting the minimum criteria during the period 1996-8. Further evaluation of these showed that 70% were known adverse reactions, 13% were events which were likely to be related to the underlying disease and 17% were signals requiring further evaluation.Proportional reporting ratios are a valuable aid to signal generation from spontaneous reporting data which are easy to calculate and interpret, and various refinements are possible.