Skip to main content
SpringerLink
Log in

Identification of Suicide-Related Events Through Network Analysis of Adverse Event Reports

  • Original Research Article
  • Published:
Drug Safety Aims and scope Submit manuscript

Abstract

Background

In the treatment of depression, it is essential to monitor for early warnings of suicide.

Objective

The aim of this study was to identify the symptoms that would suggest a high suicide risk by analyzing data obtained from the US Food and Drug Administration Adverse Event Reporting System (FAERS) of selective serotonin reuptake inhibitors.

Methods

Using FAERS reports from 1997 to the second quarter of 2012, we constructed the co-occurrence network of adverse events. From this network, we extracted the events that were strongly connected to suicidal events (suicidal attempts, suicidal ideation, suicidal behavior, and complete suicide) by means of the community detection method.

Results

We succeeded in obtaining a list of suicide-related adverse events. Owing to the randomness inherent in the algorithms of community detection, we found that the obtained list differed according to each trial of analysis. However, the lists we derived show considerable efficiency in identifying suicidal events.

Conclusion

The network analysis appears to be a promising method for identifying signals of suicide.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Notes

  1. MedDRA®, the Medical Dictionary for Regulatory Activities terminology, is the international medical terminology developed under the auspices of the International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH). The MedDRA® trademark is owned by the International Federation of Pharmaceutical Manufacturers and Associations (IFPMA) on behalf of ICH.

References

  1. Harris EC, Barraclough B. Suicide as an outcome for mental disorders. A meta-analysis. Br J Psychiatry. 1997;170:205–28.

    Article  CAS  PubMed  Google Scholar 

  2. Mann JJ, Waternaux C, Haas GL, Malone KM. Toward a clinical model of suicidal behavior in psychiatric patients. Am J Psychiatry. 1999;156:181–9.

    CAS  PubMed  Google Scholar 

  3. Reihmer Z. Suicide and bipolar disorder. In: Zarate CA, Manji HK, editors. Bipolar depression: molecular neurobiology, clinical diagnosis and pharmacotherapy. Basel: Birkhäuser; 2009. p. 47–56.

    Google Scholar 

  4. Vaswani MK, Linda FK, Ramesh S. Role of selective serotonin reuptake inhibitors in psychiatric disorders: a comprehensive review. Prog Neuropsychopharmacol Biol Psychiatry. 2003;27:85–102.

    Article  CAS  PubMed  Google Scholar 

  5. Szarfman A, Machado SG, O’Neill RT. Use of screening algorithms and computer systems to efficiently signal higher-than-expected combinations of drugs and events in the US FDA’s spontaneous reports database. Drug Saf. 2002;25:381–92.

    Article  CAS  PubMed  Google Scholar 

  6. Hauben M, Madigan D, Gerrits CM, Walsh L, Van Puijenbroek EP. The role of data mining in pharmacovigilance. Expert Opin Drug Saf. 2005;4:929–48.

    Article  CAS  PubMed  Google Scholar 

  7. Piccinni C, Motola D, Marchesini G, Poluzzi E. Assessing the association of pioglitazone use and bladder cancer through drug adverse event reporting. Diabetes Care. 2011;34:1369–71.

    Article  PubMed Central  PubMed  Google Scholar 

  8. Gunguly N, Deutsh A, Mukherjee A, editors. Dynamics on and of complex networks: application to biology, computer science, and the social sciences. Basel: Birkhäuser; 2009.

    Google Scholar 

  9. Liljeros F, Edling CR, Amaral LAN, Stanley HE, Aberg Y. The web of human sexual contacts. Nature. 2001;411:907–8.

    Article  CAS  PubMed  Google Scholar 

  10. Pastor-Satorras R, Vespignani A. Immunization of complex networks. Phys Rev E. 2002;65:036104.

    Article  Google Scholar 

  11. Alon U. An introduction to systems biology: design principles of biological circuits. London: Chapman and Hall; 2006.

    Google Scholar 

  12. Barabási AL. Network medicine: from obesity to the “diseasome”. N Engl J Med. 2007;357:404–7.

    Article  PubMed  Google Scholar 

  13. DuMouchel W. Bayesian data mining in large frequency tables, with an application to the FDA spontaneous reporting systems. Am Stat. 1999;53:177–90.

    Google Scholar 

  14. Harpaz R, Chase HS, Friedman C. Mining multi-item drug adverse effect associations in spontaneous reporting systems. BMC Bioinform. 2010;11(Suppl. 9):S7.

    Article  Google Scholar 

  15. Newman MEJ. Modularity and community structure in networks. Proc Natl Acad Sci USA 2006;103:8577–8582.

  16. American Society of Health-System Pharmacists. AHFS drug information 2010. Maryland: American Society of Health-System Pharmacists; 2010.

    Google Scholar 

  17. Wishart DS, Knox C, Guo AC, et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res. 2008;36:D901–6.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  18. Newman MEJ. Finding and evaluating community structure in networks. Phys Rev E. 2004;69:026113.

    Article  CAS  Google Scholar 

  19. Guimerà R, Sales-Pardo M, Amaral LAN. Modularity from fluctuations in random graphs and complex networks. Phys Rev E. 2004;70:R025101.

    Article  Google Scholar 

  20. Rosvall M, Bergstrom CT. An information-theoretic framework for resolving community structure in complex network. Proc Natl Acad Sci USA. 2007;104:7327–31.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  21. Blondel VD, Guillaume JL, Lambiotte R, Lefebvre E. Fast unfolding of communities in large networks. J Stat Mech. 2008;2008:P10008.

  22. Fortunato S, Barthélemy M. Resolution limit in community detection. Proc Natl Acad Sci USA. 2007;104:36–41.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  23. Lambiotte R, Delvenne J -C, Barahona M. Laplacian dynamics and multiscale modular structure in networks [internet]. 2008. arXiv:0812.1770.

  24. Bastian M, Heymann S, Jacomy M. Gephi: an open source software for exploring and manipulating networks. In: International AAAI conference on weblogs and social media; 17–20 May 2009, San Jose, USA. http://www.aaai.org/ocs/index.php/ICWSM/09/paper/view/154. Accessed 23 Mar 2014.

  25. Huang L, Zalkikar J, Tiwari RC. A likelihood ratio test based method for signal detection with application to FDA’s drug safety data. J Am Stat Assoc. 2011;106:1230–41.

    Article  CAS  Google Scholar 

  26. Huang L, Guo T, Zalkikar JN, Tiwari RC. A review of statistical methods for safety surveillance. Ther Innov Regul Sci. 2014;48:98–108.

    Google Scholar 

Download references

Conflict of interest statement

No external sources of funding were used in the preparation of this study. Alwis Nazir, Takashi Ichinomiya, Nobuteru Miyamura, Yasuaki Sekiya and Yasutomi Kinosada have no conflicts of interest that are directly relevant to the contents of this study.

Author information

Authors and Affiliations

  1. The United Graduate School of Drug Discovery and Medical Information Sciences of Gifu University, Yanagido 1-1, Gifu, 501-1194, Japan

    Alwis Nazir, Takashi Ichinomiya, Nobuteru Miyamura, Yasuaki Sekiya & Yasutomi Kinosada

  2. State Islamic University of Sultan Syarif Kasim Riau, Jl. H.R.Soebrantas No.155 KM 18, Simpang Baru Panam, Pekanbaru, 28293, Indonesia

    Alwis Nazir

  3. Department of Biomedical Informatics, Gifu University School of Medicine, Yanagido 1-1, Gifu, 501-1194, Japan

    Takashi Ichinomiya & Yasutomi Kinosada

Authors
  1. Alwis Nazir
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Takashi Ichinomiya
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nobuteru Miyamura
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yasuaki Sekiya
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yasutomi Kinosada
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alwis Nazir.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nazir, A., Ichinomiya, T., Miyamura, N. et al. Identification of Suicide-Related Events Through Network Analysis of Adverse Event Reports. Drug Saf 37, 609–616 (2014). https://doi.org/10.1007/s40264-014-0195-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40264-014-0195-2

Keywords

Search

Navigation