Advertisement

Paradigm Shift in Study of Treatment-Resistant Psychiatric Disorder

  • Sang Won Jeon
  • Meysam Amidfar
  • Yong-Ku KimEmail author
Chapter

Abstract

Psychiatric patients with many episodes that do not respond satisfactorily to numerous sequential treatment regimens were included in the treatment resistance studies. Most studies have, however, used a post hoc experimental design that failed to determine the association between biomarkers and the initial risk of treatment-resistant psychiatric disorder (TRP). Such post hoc experimental design can be regarded only as a consequence of having treatment resistance, rather than being a causal risk factor for it. Although informative, data derived from such studies often do not allow for a distinction to be made between cause and effect. To deal with this problem, it is most ideal to enroll untreated patients (those who were diagnosed but have not yet undergone treatment) as study subjects. In this chapter, the authors will review methodological considerations to uncover initial biological risk factors for TRP and propose a better study design for future research by discussing the shortcomings of the traditional study design.

Keywords

Treatment resistance Psychiatric disorders Biomarkers Risk factors Experimental study design Nested case-control study design 

References

  1. 1.
    Berlim MT, Turecki G. Definition, assessment, and staging of treatment-resistant refractory major depression: a review of current concepts and methods. Can J Psychiatr. 2007;52(1):46–54.CrossRefGoogle Scholar
  2. 2.
    Cepeda MS, Reps J, Fife D, Blacketer C, Stang P, Ryan P. Finding treatment-resistant depression in real-world data: how a data-driven approach compares with expert-based heuristics. Depress Anxiety. 2017;35:220–8.CrossRefGoogle Scholar
  3. 3.
    Conley RR, Kelly DL. Management of treatment resistance in schizophrenia. Biol Psychiatry. 2001;50(11):898–911.CrossRefGoogle Scholar
  4. 4.
    Conway CR, George MS, Sackeim HA. Toward an evidence-based, operational definition of treatment-resistant depression: when enough is enough. JAMA Psychiat. 2017;74(1):9–10.CrossRefGoogle Scholar
  5. 5.
    Holtzmann J, Richieri R, Saba G, Allaili N, Bation R, Moliere F, et al. How to define treatment-resistant depression? Presse Med. 2016;45(3):323–8.CrossRefGoogle Scholar
  6. 6.
    Kalia M, Costa E Silva J. Biomarkers of psychiatric diseases: current status and future prospects. Metabolism. 2015;64(3 Suppl 1):S11–5.CrossRefGoogle Scholar
  7. 7.
    Liu C, Cripe TP, Kim MO. Statistical issues in longitudinal data analysis for treatment efficacy studies in the biomedical sciences. Mol Ther. 2010;18(9):1724–30.CrossRefGoogle Scholar
  8. 8.
    Liu Y, Zhou X, Qin B, Del Giovane C, Zhang Y, Xie P. Efficacy, quality of life, and acceptability outcomes of atypical antipsychotic augmentation treatment for treatment-resistant depression: protocol for a systematic review and network meta-analysis. Syst Rev. 2014;3:133.CrossRefGoogle Scholar
  9. 9.
    Lucas N, Hubain P, Loas G, Jurysta F. Treatment resistant depression: actuality and perspectives in 2017. Rev Med Brux. 2017;38(1):16–25.PubMedGoogle Scholar
  10. 10.
    Malhi GS, Byrow Y. Is treatment-resistant depression a useful concept? Evid Based Ment Health. 2016;19(1):1–3.CrossRefGoogle Scholar
  11. 11.
    McIntyre RS, Filteau MJ, Martin L, Patry S, Carvalho A, Cha DS, et al. Treatment-resistant depression: definitions, review of the evidence, and algorithmic approach. J Affect Disord. 2014;156:1–7.CrossRefGoogle Scholar
  12. 12.
    Miyamoto S, Jarskog LF, Fleischhacker WW. New therapeutic approaches for treatment-resistant schizophrenia: a look to the future. J Psychiatr Res. 2014;58:1–6.CrossRefGoogle Scholar
  13. 13.
    Mrazek DA, Hornberger JC, Altar CA, Degtiar I. A review of the clinical, economic, and societal burden of treatment-resistant depression: 1996–2013. Psychiatr Serv. 2014;65(8):977–87.CrossRefGoogle Scholar
  14. 14.
    Murphy JA, Sarris J, Byrne GJ. A review of the conceptualisation and risk factors associated with treatment-resistant depression. Depress Res Treat. 2017;2017:4176825.PubMedPubMedCentralGoogle Scholar
  15. 15.
    Perlis RH. A clinical risk stratification tool for predicting treatment resistance in major depressive disorder. Biol Psychiatry. 2013;74(1):7–14.CrossRefGoogle Scholar
  16. 16.
    Samara MT, Dold M, Gianatsi M, Nikolakopoulou A, Helfer B, Salanti G, et al. Efficacy, acceptability, and tolerability of antipsychotics in treatment-resistant schizophrenia: a network meta-analysis. JAMA Psychiat. 2016;73(3):199–210.CrossRefGoogle Scholar
  17. 17.
    Smith DF. Quest for biomarkers of treatment-resistant depression: shifting the paradigm toward risk. Front Psych. 2013;4:57.Google Scholar
  18. 18.
    Souery D, Amsterdam J, de Montigny C, Lecrubier Y, Montgomery S, Lipp O, et al. Treatment resistant depression: methodological overview and operational criteria. Eur Neuropsychopharmacol. 1999;9(1–2):83–91.CrossRefGoogle Scholar
  19. 19.
    Trevino K, McClintock SM, McDonald Fischer N, Vora A, Husain MM. Defining treatment-resistant depression: a comprehensive review of the literature. Ann Clin Psychiatry. 2014;26(3):222–32.PubMedGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of PsychiatryKangbuk Samsung Hospital, Sungkyunkwan University School of MedicineSeoulRepublic of Korea
  2. 2.Fasa University of Medical SciencesFasaIran
  3. 3.Department of Psychiatry, College of MedicineKorea University Ansan HospitalAnsan-siRepublic of Korea

Personalised recommendations