Skip to main content

Advertisement

Log in

Sequence symmetry analysis in pharmacovigilance and pharmacoepidemiologic studies

  • PHARMACO-EPIDEMIOLOGY
  • Published:
European Journal of Epidemiology Aims and scope Submit manuscript

Abstract

Sequence symmetry analysis (SSA) is a method for detecting adverse drug events by utilizing computerized claims data. The method has been increasingly used to investigate safety concerns of medications and as a pharmacovigilance tool to identify unsuspected side effects. Validation studies have indicated that SSA has moderate sensitivity and high specificity and has robust performance. In this review we present the conceptual framework of SSA and discuss advantages and potential pitfalls of the method in practice. SSA is based on analyzing the sequences of medications; if one medication (drug B) is more often initiated after another medication (drug A) than before, it may be an indication of an adverse effect of drug A. The main advantage of the method is that it requires a minimal dataset and is computationally efficient. By design, SSA controls time-constant confounders. However, the validity of SSA may be affected by time-varying confounders, as well as by time trends in the occurrence of exposure or outcome events. Trend effects may be adjusted by modeling the expected sequence ratio in the absence of a true association. There is a potential for false positive or negative results and careful consideration should be given to potential sources of bias when interpreting the results of SSA studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Hall GC, Sauer B, Bourke A, Brown JS, Reynolds MW, LoCasale R. Guidelines for good database selection and use in pharmacoepidemiology research. Pharmacoepidemiol Drug Saf. 2012;21(1):1–10.

    Article  PubMed  Google Scholar 

  2. Strom B, Kimmel S, Hennessy S. Pharmacoepidemiology. 5th ed. Wiley; 2012. p. 71–117.

  3. Petri H, de Vet HC, Naus J, Urquhart J. Prescription sequence analysis: a new and fast method for assessing certain adverse reactions of prescription drugs in large populations. Stat Med. 1988;7(11):1171–5.

    Article  CAS  PubMed  Google Scholar 

  4. Hallas J. Evidence of depression provoked by cardiovascular medication: a prescription sequence symmetry analysis. Epidemiology. 1996;7(5):478–84.

    Article  CAS  PubMed  Google Scholar 

  5. Wahab IA, Pratt NL, Ellett LK, Roughead EE. Sequence symmetry analysis as a signal detection tool for potential heart failure adverse events in an administrative claims database. Drug Saf. 2016;39:347.

    Article  CAS  PubMed  Google Scholar 

  6. Lai EC, Hsieh CY, Kao Yang YH, Lin SJ. Detecting potential adverse reactions of sulpiride in schizophrenic patients by prescription sequence symmetry analysis. PLoS ONE. 2014;9(2):e89795.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Tsiropoulos I, Andersen M, Hallas J. Adverse events with use of antiepileptic drugs: a prescription and event symmetry analysis. Pharmacoepidemiol Drug Saf. 2009;18(6):483–91.

    Article  CAS  PubMed  Google Scholar 

  8. Wahab IA, Pratt NL, Wiese MD, Kalisch LM, Roughead EE. The validity of sequence symmetry analysis (SSA) for adverse drug reaction signal detection. Pharmacoepidemiol Drug Saf. 2013;22(5):496–502.

    Article  PubMed  Google Scholar 

  9. Pratt N, Chan EW, Choi NK, Kimura M, Kimura T, Kubota K, et al. Prescription sequence symmetry analysis: assessing risk, temporality, and consistency for adverse drug reactions across datasets in five countries. Pharmacoepidemiol Drug Saf. 2015;24(8):858–64.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Pratt N, Andersen M, Bergman U, Choi NK, Gerhard T, Huang C, et al. Multi-country rapid adverse drug event assessment: the Asian Pharmacoepidemiology Network (AsPEN) antipsychotic and acute hyperglycaemia study. Pharmacoepidemiol Drug Saf. 2013;22(9):915–24.

    CAS  PubMed  Google Scholar 

  11. Hallas J, Bytzer P. Screening for drug related dyspepsia: an analysis of prescription symmetry. Eur J Gastroenterol Hepatol. 1998;10(1):27–32.

    Article  CAS  PubMed  Google Scholar 

  12. Maclure M, Fireman B, Nelson JC, Hua W, Shoaibi A, Paredes A, et al. When should case-only designs be used for safety monitoring of medical products? Pharmacoepidemiol Drug Saf. 2012;21(Suppl 1):50–61.

    Article  PubMed  Google Scholar 

  13. Pratt N, Chan EW, Choi NK, Kimura M, Kimura T, Kubota K, et al. Prescription sequence symmetry analysis: assessing risk, temporality, and consistency for adverse drug reactions across datasets in five countries. Pharmacoepidemiol Drug Saf. 2015;24:858–64.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Lai EC, Yang YH, Lin SJ, Hsieh CY. Use of antiepileptic drugs and risk of hypothyroidism. Pharmacoepidemiol Drug Saf. 2013;22(10):1071–9.

    CAS  PubMed  Google Scholar 

  15. Hallas J, Gaist D, Bjerrum L. The waiting time distribution as a graphical approach to epidemiologic measures of drug utilization. Epidemiology. 1997;8(6):666–70.

    Article  CAS  PubMed  Google Scholar 

  16. Caughey GE, Roughead EE, Pratt N, Shakib S, Vitry AI, Gilbert AL. Increased risk of hip fracture in the elderly associated with prochlorperazine: is a prescribing cascade contributing? Pharmacoepidemiol Drug Saf. 2010;19(9):977–82.

    Article  PubMed  Google Scholar 

  17. Cole JA, Farraye FA, Cabral HJ, Zhang Y, Rothman KJ. Irritable bowel syndrome and hysterectomy: a sequence symmetry analysis. Epidemiology. 2007;18(6):837–8.

    Article  PubMed  Google Scholar 

  18. Hallas J, Pottegard A. Use of self-controlled designs in pharmacoepidemiology. J Intern Med. 2014;275(6):581–9.

    Article  CAS  PubMed  Google Scholar 

  19. Wahab IA, Pratt NL, Kalisch LM, Roughead EE. Comparing time to adverse drug reaction signals in a spontaneous reporting database and a claims database: a case study of rofecoxib-induced myocardial infarction and rosiglitazone-induced heart failure signals in Australia. Drug Saf. 2014;37(1):53–64.

    Article  Google Scholar 

  20. Wahab IA, Pratt NL, Kalisch LM, Roughead EE. Sequence symmetry analysis and disproportionality analyses: what percentage of adverse drug reaction do they signal? Adv Pharmacoepidemiol Drug Saf. 2013;2:140.

    Google Scholar 

  21. As PENc, Andersen M, Bergman U, Choi NK, Gerhard T, Huang C, et al. The Asian Pharmacoepidemiology Network (AsPEN): promoting multi-national collaboration for pharmacoepidemiologic research in Asia. Pharmacoepidemiol Drug Saf. 2013;22(7):700–4.

    Article  Google Scholar 

  22. Roughead EE, Chan EW, Choi NK, Kimura M, Kimura T, Kubota K, et al. Variation in association between thiazolidinediones and heart failure across ethnic groups: retrospective analysis of large healthcare claims databases in six countries. Drug Saf. 2015;38(9):823–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Asian Pharmacoepidemiology Network. http://aspennet.asia/. 4 Apr 2015.

  24. Garrison SR, Dormuth CR, Morrow RL, Carney GA, Khan KM. Nocturnal leg cramps and prescription use that precedes them: a sequence symmetry analysis. Arch Intern Med. 2012;172(2):120–6.

    Article  PubMed  Google Scholar 

  25. Pratt NL, Ilomaki J, Raymond C, Roughead EE. The performance of sequence symmetry analysis as a tool for post-market surveillance of newly marketed medicines: a simulation study. BMC Med Res Methodol. 2014;14:66.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Leucht S, Corves C, Arbter D, Engel RR, Li C, Davis JM. Second-generation versus first-generation antipsychotic drugs for schizophrenia: a meta-analysis. Lancet. 2009;373(9657):31–41.

    Article  CAS  PubMed  Google Scholar 

  27. Maclure M. ‘Why me?’ versus ‘why now? Differences between operational hypotheses in case-control versus case-crossover studies. Pharmacoepidemiol Drug Saf. 2007;16(8):850–3.

    Article  PubMed  Google Scholar 

  28. Pottegard A, Hallas J. New use of prescription drugs prior to a cancer diagnosis. Pharmacoepidemiol Drug Saf. 2016;26:223–7.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Roughead EE, Kalisch LM, Pratt NL, Killer G, Barnard A, Gilbert AL. Managing glaucoma in those with co-morbidity: not as easy as it seems. Ophthalmic Epidemiol. 2012;19(2):74–82.

    Article  PubMed  Google Scholar 

  30. Rothman KJ. Six persistent research misconceptions. J Gen Intern Med. 2014;29(7):1060–4.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Lindberg G, Hallas J. Cholesterol-lowering drugs and antidepressants—a study of prescription symmetry. Pharmacoepidemiol Drug Saf. 1998;7(6):399–402.

    Article  CAS  PubMed  Google Scholar 

  32. Cher DJ. Myocardial infarction and acute cholecystitis: an application of sequence symmetry analysis. Epidemiology. 2000;11(4):446–9.

    Article  CAS  PubMed  Google Scholar 

  33. Bytzer P, Hallas J. Drug-induced symptoms of functional dyspepsia and nausea. A symmetry analysis of one million prescriptions. Aliment Pharmacol Ther. 2000;14(11):1479–84.

    Article  CAS  PubMed  Google Scholar 

  34. Corrao G, Botteri E, Bagnardi V, Zambon A, Carobbio A, Falcone C, et al. Generating signals of drug-adverse effects from prescription databases and application to the risk of arrhythmia associated with antibacterials. Pharmacoepidemiol Drug Saf. 2005;14(1):31–40.

    Article  PubMed  Google Scholar 

  35. Thacker EL, Schneeweiss S. Initiation of acetylcholinesterase inhibitors and complications of chronic airways disorders in elderly patients. Drug Saf. 2006;29(11):1077–85.

    Article  CAS  PubMed  Google Scholar 

  36. Silwer L, Petzold M, Hallas J, Lundborg CS. Statins and nonsteroidal anti-inflammatory drugs—an analysis of prescription symmetry. Pharmacoepidemiol Drug Saf. 2006;15(7):510–1.

    Article  PubMed  Google Scholar 

  37. Vegter S, Jong-van den Berg D, Lolkje TW. Misdiagnosis and mistreatment of a common side-effect–angiotensin-converting enzyme inhibitor-induced cough. Br J Clin Pharmacol. 2010;69(2):200–3.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Caughey GE, Roughead EE, Pratt N, Killer G, Gilbert AL. Stroke risk and NSAIDs: an Australian population-based study. Med J Aust. 2011;195(9):525–9.

    Article  PubMed  Google Scholar 

  39. Vegter S, de Boer P, van Dijk KW, Visser S, Jong-van den Berg D, Lolkje TW. The effects of antitussive treatment of ACE inhibitor-induced cough on therapy compliance: a prescription sequence symmetry analysis. Drug Saf. 2013;36(6):435–9.

    Article  CAS  PubMed  Google Scholar 

  40. Pouwels KB, Visser ST, Bos HJ, Hak E. Angiotensin-converting enzyme inhibitor treatment and the development of urinary tract infections: a prescription sequence symmetry analysis. Drug Saf. 2013;36(11):1079–86.

    Article  CAS  PubMed  Google Scholar 

  41. van Boven JF, Jong-van den Berg D, Lolkje TW, Vegter S. Inhaled corticosteroids and the occurrence of oral candidiasis: a prescription sequence symmetry analysis. Drug Saf. 2013;36(4):231–6.

    Article  CAS  PubMed  Google Scholar 

  42. Fujimoto M, Higuchi T, Hosomi K, Takada M. Association of statin use with storage lower urinary tract symptoms (LUTS): data mining of prescription database. Int J Clin Pharmacol Ther. 2014;52(9):762–9.

    Article  CAS  PubMed  Google Scholar 

  43. Kalisch Ellett LM, Pratt NL, Barratt JD, Rowett D, Roughead EE. Risk of medication-associated initiation of oxybutynin in elderly men and women. J Am Geriatr Soc. 2014;62(4):690–5.

    Article  PubMed  Google Scholar 

  44. Takada M, Fujimoto M, Hosomi K. Difference in risk of gastrointestinal complications between users of enteric-coated and buffered low-dose aspirin. Int J Clin Pharmacol Ther. 2014;52(3):181–91.

    Article  CAS  PubMed  Google Scholar 

  45. Takada M, Fujimoto M, Yamazaki K, Takamoto M, Hosomi K. Association of statin use with sleep disturbances: data mining of a spontaneous reporting database and a prescription database. Drug Saf. 2014;37(6):421–31.

    Article  CAS  PubMed  Google Scholar 

  46. Fujimoto M, Higuchi T, Hosomi K, Takada M. Association between statin use and cancer: data mining of a spontaneous reporting database and a claims database. Int J Med Sci. 2015;12(3):223–33.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Rasmussen L, Hallas J, Madsen KG, Pottegard A. Cardiovascular drugs and erectile dysfunction—a symmetry analysis. Br J Clin Pharmacol. 2015;80(5):1219–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Takeuchi Y, Kajiyama K, Ishiguro C, Uyama Y. Atypical antipsychotics and the risk of hyperlipidemia: a sequence symmetry analysis. Drug Saf. 2015;38(7):641–50.

    Article  CAS  PubMed  Google Scholar 

  49. Pouwels KB, Widyakusuma NN, Bos JH, Hak E. Association between statins and infections among patients with diabetes: a cohort and prescription sequence symmetry analysis. Pharmacoepidemiol Drug Saf. 2016;25:1124–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Takada M, Fujimoto M, Motomura H, Hosomi K. Inverse association between sodium channel-blocking antiepileptic drug use and cancer: data mining of spontaneous reporting and claims databases. Int J Med Sci. 2016;13(1):48–59.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Hashimoto M, Hashimoto K, Ando F, Kimura Y, Nagase K, Arai K. Prescription rate of medications potentially contributing to lower urinary tract symptoms and detection of adverse reactions by prescription sequence symmetry analysis. J Pharm Health Care Sci. 2015;1:7.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Kalisch Ellett LM, Pratt NL, Le Blanc VT, Westaway K, Roughead EE. Increased risk of hospital admission for dehydration or heat-related illness after initiation of medicines: a sequence symmetry analysis. J Clin Pharm Ther. 2016;41:503–7.

    Article  CAS  PubMed  Google Scholar 

  53. Wahab IA, Pratt NL, Ellett LK, Roughead EE. Sequence symmetry analysis as a signal detection tool for potential heart failure adverse events in an administrative claims database. Drug Saf. 2016;39(4):347–54.

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

This study was supported by a grant from the Ministry of Science and Technology of Taiwan (ID: NSC 102-2628-B-006-003-MY).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Elizabeth E. Roughead, Yea-Huei Kao Yang or Jesper Hallas.

Ethics declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lai, E.CC., Pratt, N., Hsieh, CY. et al. Sequence symmetry analysis in pharmacovigilance and pharmacoepidemiologic studies. Eur J Epidemiol 32, 567–582 (2017). https://doi.org/10.1007/s10654-017-0281-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10654-017-0281-8

Keywords

Navigation