Prescription sequence symmetry analysis: assessing risk, temporality, and consistency for adverse drug reactions across datasets in five countries

Background Prescription sequence symmetry analysis (PSSA) is a signal detection method for adverse drug events. Its capacity to consistently detect adverse drug events across different settings has not been tested. We aimed to determine the consistency of PSSA results for detecting positive and negative control adverse drug events across different settings. Methods Using a distributed network model, we analyzed prescription dispensing data using PSSA in Australia, Hong Kong, Japan, Korea, and Taiwan. Positive control was amiodarone and thyroxine, as a marker of amiodarone-induced hypothyroidism, a known adverse event with a clear temporal relationship to amiodarone initiation. Negative controls were amiodarone and allopurinol, as a marker of amiodarone-induced gout and thyroxine and allopurinol, as a marker of thyroxine-induced gout. Gout is not recorded as an adverse event in product information for either medicine. Adjusted sequence ratios (ASR) were calculated for each country. Pooled estimates were obtained by using the generic inverse variance method. Results A positive association was identified between amiodarone and thyroxine in all settings with a pooled ASR 2.63 (95% confidence interval (CI) 1.47–4.72). Temporal analysis showed the effect occurred within the first few weeks of treatment. No significant associations were found for the negative controls in any setting; pooled ASR were 0.76 (95%CI 0.62–0.93) and 0.98 (95%CI 0.85–1.12) for amiodaroneallopurinol and thyroxine-allopurinol, respectively. Conclusion Despite different health settings, different populations, and different patterns of medicine utilization, PSSA gave consistent estimates across countries for a well-known positive association and two negative control adverse events. © 2015 The Authors Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd. key words—prescription symmetry analysis; pharmacovigilance; amiodarone; hyperthyroidism; pharmacoepidemiology