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Galkin S.A.

Mental Health Research Institute of the Tomsk National Research Medical Center of the Russian Academy of Science

Ivanova S.A.

Tomsk National Research Medical Center of the Russian Academy of Sciences

Bokhan N.A.

Mental Health Research Institute of the Tomsk National Research Medical Center of the Russian Academy of Science

Current methods for predicting therapeutic response in patients with depressive disorders

Authors:

Galkin S.A., Ivanova S.A., Bokhan N.A.

More about the authors

Journal: S.S. Korsakov Journal of Neurology and Psychiatry. 2022;122(2): 15‑21

DOI: 10.17116/jnevro202212202115

Read: 1566 times

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Table of contents

CURRENT METHODS FOR PREDICTING THERAPEUTIC RESPONSE IN PATIENTS WITH DEPRESSIVE DISORDERS
CURRENT METHODS FOR PREDICTING THERAPEUTIC RESPONSE IN PATIENTS WITH DEPRESSIVE DISORDERS

To cite this article:

Galkin SA, Ivanova SA, Bokhan NA. Current methods for predicting therapeutic response in patients with depressive disorders. S.S. Korsakov Journal of Neurology and Psychiatry. 2022;122(2):15‑21. (In Russ.)
https://doi.org/10.17116/jnevro202212202115

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Depressive disorder is the most common mental illness, which is also one of the leading causes of disability worldwide. In addition, most suicides are associated with depression. Despite all modern achievements in the treatment of depressive disorders, up to 60% of patients did not adequately respond to psychopharmacotherapy (non—responders). Current guidelines and studies characterize non—responders as patients who have an inadequate response to taking two or more antidepressants from different classes within 4 weeks. However, in some cases, such a long wait for a therapeutic response can lead to adverse consequences. Thus, there is a need to develop prognostic methods of therapeutic resistance in patients with depressive disorders. The purpose of this review is to summarize current methods used to predict therapeutic response in patients with depressive disorders. A literature search was conducted using the search terms «depression», «antidepressant», «outcome», «predictor», «(bio) marker», «treatment—resistant depression» and «chronic depression». The search was conducted in the PubMed, Scopus, and Google Scholar databases for the time period from 2005 to 2020.

Keywords:

diagnostics
therapeutic resistance
antidepressants
depression
therapy prognosis

Authors:

Galkin S.A.

Mental Health Research Institute of the Tomsk National Research Medical Center of the Russian Academy of Science

Ivanova S.A.

Tomsk National Research Medical Center of the Russian Academy of Sciences

Bokhan N.A.

Mental Health Research Institute of the Tomsk National Research Medical Center of the Russian Academy of Science

Received:

16.09.2020

Accepted:

24.12.2020

List of references:

  1. Charlson F, Ommeren M, Flaxman A, Cornett J, Whiteford B, Saxena S. New WHO prevalence estimates of mental disorders in conflict settings: a systematic review and metaanalysis. The Lancet. 2019;394:240-248.  https://doi.org/10.1016/S0140-6736(19)30934-1
  2. Krasnov VN. Depression as a social and clinical problem of modern medicine. Rossijskij Psihiatricheskij Zhurnal. 2011;6: 8—10. (In Russ.).
  3. Lim GY, Tam WW, Lu Y, Ho CS, Zhang MW, Ho RC. Prevalence of Depression in the Community from 30 Countries between 1994 and 2014. Sci Rep. 2018;8(1):2861. https://doi.org/10.1038/s41598-018-21243-x
  4. Laird KT, Krause B, Funes C. Psychobiological factors of resilience and depression in late life. Transl. Psychiatry. 2019;88.  https://doi.org/10.1038/s41398-019-0424-7
  5. National Institute of Mental Health. Depression. www.nimh.nih.gov/health/topics/depression/index.shtml.
  6. Priyam K, Davis DM. Managing Treatment-Resistant Depression. US Pharm. 2020;45(5):15-19. 
  7. Ionescu D, Papakostas G. Experimental medication treatment approaches for depression. Transl Psychiatry. 2017. https://doi.org/10.1038/tp.2017.33
  8. Jakobsen JC, Gluud C, Kirsch I. Should antidepressants be used for major depressive disorder? BMJ Evidence — Based Medicine. 2020;25:130. 
  9. Katon W. Epidemiology and treatment of depression in patients with chronic medical illness. Dialogues Clin Neurosci. 2011;13(1):7-23. 
  10. Starostina EG, Volodina MN, Starostin IV, Bobrov AE. Depression and diabetes as comorbid diseases. RMZh. 2017;25(22):1613-1620. (In Russ.).
  11. Ghio L, Gotelli S, Marcenaro M, Amore M, Natta W. Duration of untreated illness and outcomes in unipolar depression: a systematic review and metaanalysis. J Affect Disord. 2014;152-154:45-51.  https://doi.org/10.1016/j.jad.2013.10.002
  12. Hung CI, Liu CY, Yang CH. Untreated duration predicted the severity of depression at the two-year follow-up point. PLoS ONE. 2017;12:e0185119.
  13. Bukh JD, Bock C, Vinberg M, Kessing LV. The effect of prolonged duration of untreated depression on antidepressant treatment outcome. J Affect Disord. 2013;145:42-48. 
  14. Kautzky A, Dold M, Bartova L, Spies M, Kranz GS, Souery D, Montgomery S, Mendlewicz J, Zohar J, Fabbri C, Serretti A, Lanzenberger R, Dikeos D. Clinical factors predicting treatment resistant depression: affirmative results from the European multicenter study. Acta Psychiatr Scand. 2019;139(1):78-88.  https://doi.org/10.1111/acps.12959
  15. Furukawa TA, Kitamura T, Takahashi K. Time to recovery of an inception cohort with hitherto untreated unipolar major depressive episodes. Br J Psychiatry J Ment Sci. 2010;177:331-335. 
  16. Habert J, Katzman MA, Oluboka OJ, McIntosh D, MacQueen GM, Milev RV, McIntyre RS, Blier P. Functional Recovery in Major Depressive Disorder: Focus on Early Optimized Treatment. Prim Care Companion CNS Disord. 2016;18(5):10.4088/PCC.15r01926. https://doi.org/10.4088/PCC.15r01926
  17. Jha MK, Minhajuddin A, Greer TL, Carmody T, Rush AJ, Trivedi MH. Early Improvement in Work Productivity Predicts Future Clinical Course in Depressed Outpatients: Findings From the CO-MED Trial. Am J Psychiatry. 2016;173(12):1196-1204. https://doi.org/10.1176/appi.ajp.2016.16020176
  18. Riedel M, Möller H, Obermeier M, Adli M, Bauer M, Kronmüller K, Brieger P, Laux G, Bender W, Heuser I, Zeiler J, Gaebel W, Schennach-Wolff R, Henkel V, Seemüller F. Clinical predictors of response and remission in inpatients with depressive syndromes. J Affect Disord. 2011;133(1-2):137-149.  https://doi.org/10.1016/j.jad.2011.04.007
  19. Balestri M, Calati R, Souery D, Kautzky A, Kasper S, Montgomery S, Zohar J, Mendlewicz J, Serretti A. Socio-demographic and clinical predictors of treatment resistant depression: A prospective European multicenter study. J Affect Disord. 2016;189:224-232.  https://doi.org/10.1016/j.jad.2015.09.033
  20. Trivedi M, Rush A, Wisniewski S, Nierenberg A, Warden D, Ritz L, Norquist G, Howland R, Lebowitz B, McGrath P, Shores-Wilson K, Biggs M, Balasubramani G, Fava M.. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006;163(1):28-40.  https://doi.org/10.1176/appi.ajp.163.1.28
  21. Mandelli L, Serretti A, Porcelli S, Souery D, Mendlewicz J, Kasper S, Montgomery S, Zohar J. Opinion paper: poor response to treatment of depression in people in high occupational levels. Psychol Med. 2019;49(1):49-54.  https://doi.org/10.1017/S003329171800288X
  22. Vinkers CH, Joëls M, Milaneschi Y, Kahn RS, Penninx BW, Boks MP. Stress exposure across the life span cumulatively increases depression risk and is moderated by neuroticism. Depress Anxiety. 2014;31(9):737-745.  https://doi.org/10.1002/da.22262
  23. Nanni V, Uher R, Danese A. Childhood maltreatment predicts unfavorable course of illness and treatment outcome in depression: a metaanalysis. Am J Psychiatry. 2012;169(2):141-151.  https://doi.org/10.1176/appi.ajp.2011.11020335
  24. Nelson J, Klumparendt A, Doebler P, Ehring T. Childhood maltreatment and characteristics of adult depression: metaanalysis. Br J Psychiatry. 2017;210(2):96-104.  https://doi.org/10.1192/bjp.bp.115.180752
  25. Kautzky A, Baldinger-Melich P, Kranz GS. A New Prediction Model for Evaluating Treatment-Resistant Depression. J Clin Psychiatry. 2017;78(2):215-222.  https://doi.org/10.4088/JCP.15m10381
  26. Galkin SA, Peshkovskaya AG, Simutkin GG, Vasilieva SN, Roshchina OV, Ivanova SA, Bohan NA. Violations of the function of spatial working memory in mild depression and their neurophysiological correlates. Zhurnal Nevrologii i Psihiatrii im. S.S. Korsakova. 2019;10:56-61. (In Russ.). https://doi.org/10.17116/jnevro201911910156
  27. Galkin SA, Vasilyeva SN, Ivanova SA, Bohan NA. Inhibitory control and its effect on the treatment of patients with affective disorders. Rossijskij Psihiatricheskij Zhurnal. 2020;4:71-76. (In Russ.).
  28. Henriksen C. Identifying factors that predict longitudinal outcomes of untreated common mental disorders. Psychiatr Serv. 2015;66:163-170. 
  29. Dennehy EB, Marangell LB, Martinez J, Balasubramani GK, Wisniewski SR. Clinical and functional outcomes of patients who experience partial response to citalopram: secondary analysis of STAR*D. J Psychiatr Pract. 2014;20:178-187. 
  30. Dold M, Bartova L, Souery D, Mendlewicz J, Serretti A, Porcelli S, Zohar J, Montgomery S, Kasper S. Clinical characteristics and treatment outcomes of patients with major depressive disorder and comorbid anxiety disorders — results from a European multicenter study. J Psychiatr Res. 2017;91:1-13.  https://doi.org/10.1016/j.jpsychires.2017.02.020
  31. Friedman ES, Davis LL, Zisook S, Wisniewski SR, Trivedi MH, Fava M, Rush AJ. Baseline depression severity as a predictor of single and combination antidepressant treatment outcome: results from the CO-MED trial. Eur Neuropsychopharmacol. 2012;22(3):183-199.  https://doi.org/10.1016/j.euroneuro.2011.07.010
  32. Angstman KB, Seshadri A, Marcelin A, Gonzalez CA, Garrison GM, Allen JS. Personality Disorders in Primary Care: Impact on Depression Outcomes Within Collaborative Care. J Prim Care Community Health. 2017;8(4):233-238.  https://doi.org/10.1177/2150131917714929
  33. Zeeck A, von Wietersheim J, Weiss H, Scheidt C, Völker A, Helesic A, Eckhardt-Henn A, Beutel M, Endorf K, Treiber F, Rochlitz P, Hartmann A. Prognostic and prescriptive predictors of improvement in a naturalistic study on inpatient and day hospital treatment of depression. J Affect Disord. 2016;197:205-214.  https://doi.org/10.1016/j.jad.2016.03.039
  34. Newton-Howes G, Tyrer P, Johnson T. Personality disorder and the outcome of depression: meta-analysis of published studies. Br J Psychiatry: J Ment Sci. 2006;188:13-20. 
  35. Ducat L, Philipson LH, Anderson BJ. The mental health comorbidities of diabetes. JAMA. 2014;312:691-692. 
  36. Iosifescu DV, Nierenberg AA, Alpert JE, Smith M, Bitran S, Dording C, Fava M. The impact of medical comorbidity on acute treatment in major depressive disorder. Am J Psychiatry. 2003;160(12):2122-2127. https://doi.org/10.1176/appi.ajp.160.12.2122
  37. Karp JF, Scott J, Houck P, Reynolds CF, Kupfer DJ, Frank E. Pain predicts longer time to remission during treatment of recurrent depression. J Clin Psychiatry. 2005;66(5):591-597.  https://doi.org/10.4088/jcp.v66n0508
  38. Racine M. Chronic pain and suicide risk: A comprehensive review. Prog Neuropsychopharmacol Biol Psychiatry. 2018;87:269-280. 
  39. Petrunko OV, Mikhalevich IM. Predicting the response to modern antidepressant therapy for depressive disorder. Zabajkal’skij Medicinskij Vestnik. 2017;3:22-28. (In Russ.).
  40. Uher R, Huezo-Diaz P, Perroud N, Smith S, Rietschel M, Mors O, Hauser J, Maier W, Kozel D, Henigsberg N, Barreto M, Placentino A, Zvezdana M, Schulze T, Kalember P, Zobel A, Czerski P, Larsen E, Souery D, Giovannini C, Gray J, Lewis C, Farmer A, Aitchison K, McGuffin P, Craig I. Genetic predictors of response to antidepressants in the GENDEP project. Pharmacogenomics J. 2009;9(4):225-233.  https://doi.org/10.1038/tpj.2009.12
  41. Biernacka JM, Sangkuhl K, Jenkins G, Whaley RM, Barman P, Batzler A, Altman RB, Arolt V, Brockmöller J, Chen CH, Domschke K, Hall-Flavin DK, Hong CJ, Illi A, Ji Y, Kampman O, Kinoshita T, Leinonen E, Liou YJ, Mushiroda T, Nonen S, Skime MK, Wang L, Baune BT, Kato M, Liu YL, Praphanphoj V, Stingl JC, Tsai SJ, Kubo M, Klein TE, Weinshilboum R. The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response. Transl Psychiatry. 2015;5(4):e553. https://doi.org/10.1038/tp.2015.47
  42. Iniesta R, Hodgson K, Stahl D, Malki K, Maier W, Rietschel M, Mors O, Hauser J, Henigsberg N, Dernovsek MZ, Souery D, Dobson R, Aitchison KJ, Farmer A, McGuffin P, Lewis CM, Uher R. Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables. Sci Rep. 2018;8(1):5530. https://doi.org/10.1038/s41598-018-23584-z
  43. Lin E, Kuo P, Liu Y, Yu Y, Yang AC, Tsai S. A Deep Learning Approach for Predicting Antidepressant Response in Major Depression Using Clinical and Genetic Biomarkers. Front Psychiatry. 2018. https://doi.org/10.3389/fpsyt.2018.00290
  44. Zhang H, Li X, Pang J, Zhao X, Cao S, Wang X, Wang X, Li H. Predicting SSRI-Resistance: Clinical Features and tagSNPs Prediction Models Based on Support Vector Machine. Front Psychiatry. 2020. https://doi.org/10.3389/fpsyt.2020.00493
  45. Kautzky A, Baldinger P, Souery D, Montgomery S, Mendlewicz J, Zohar J, Serretti A, Lanzenberger R, Kasper S. The combined effect of genetic polymorphisms and clinical parameters on treatment outcome in treatment-resistant depression. Eur Neuropsychopharmacol. 2015;25(4):441-453.  https://doi.org/10.1016/j.euroneuro.2015.01.001
  46. Stamm TJ, Rampp C, Wiethoff K, Stingl J, Mössner R, O’Malley G, Ricken R, Seemüller F, Keck ME, Fisher R, Gaebel W, Maier W, Möller H, Bauer M, Adli M. The FKBP5 polymorphism rs1360780 influences the effect of an algorithm-based antidepressant treatment and is associated with remission in patients with major depression. J Psychopharmacol. 2016;30(1):40-47.  https://doi.org/10.1177/0269881115620459
  47. Zeier Z, Carpenter LL, Kalin NH, Rodriguez CI, McDonald WM, Widge AS, Nemeroff CB. Clinical Implementation of Pharmacogenetic Decision Support Tools for Antidepressant Drug Prescribing. Am J Psychiatry. 2018;175(9):873-886.  https://doi.org/10.1176/appi.ajp.2018.17111282
  48. Serretti A, Kato M, De Ronchi D, Kinoshita T. Metaanalysis of serotonin transporter gene promoter polymorphism (5-HTTLPR) association with selective serotonin reuptake inhibitor efficacy in depressed patients. Mol Psychiatry. 2007;12(3):247-257.  https://doi.org/10.1038/sj.mp.4001926
  49. Serretti A, Zanardi R, Rossini D, Cusin C, Lilli R, Smeraldi E. Influence of tryptophan hydroxylase and serotonin transporter genes on fluvoxamine antidepressant activity. Mol Psychiatry. 2001;6(5):586-592.  https://doi.org/10.1038/sj.mp.4000876
  50. Iznak AF, Iznak EV, Abramova LI, Lozhnikov MA. models of quantitative prognosis of the therapeutic response of patients with depression according to the parameters of the initial EEG. Fiziologija Cheloveka. 2019;6:36-43. (In Russ.).
  51. Schiller MJ. Quantitative Electroencephalography in Guiding Treatment of Major Depression. Front Psychiatry. 2019;9:779.  https://doi.org/10.3389/fpsyt.2018.00779
  52. Bailey NW, Hoy KE, Rogasch NC, Thomson RH, McQueen S, Elliot D, et al. Differentiating responders and non-responders of rTMS treatment for depression one week using resting EEG connectivity measures. J Affect Disord. 2019;242:68-79.  https://doi.org/10.1016/j.jad.2018.08.058
  53. Mumtaz W, Xia L, Yasin M, Ali S, Malik A. A wavelet-based technique to predict treatment outcome for major depressive disorder. PLoS ONE. 2017;12:2.  https://doi.org/10.1371/journal.pone.0171409
  54. Thase ME. Using biomarkers to predict treatment response in major depressive disorder: evidence from past and present studies. Dialogues Clin Neurosci. 2014;16(4):539-544. 
  55. Uher R, Tansey KE, Dew T, Maier W, Mors O, Hauser J, Zvezdana M, Henigsberg N, Souery D, Farmer A, McGuffin P. An inflammatory biomarker as a differential predictor of outcome of depression treatment with escitalopram and nortriptyline. Am J Psychiatry. 2014;171(12):1278-1286. https://doi.org/10.1176/appi.ajp.2014.14010094
  56. Nase S, Kohler S, Jennebach J, Eckert A, Schweinfurth N, Gallinat J, Lang U, Kühn S. Role of Serum Brain Derived Neurotrophic Factor and Central N-Acetylaspartate for Clinical Response under Antidepressive Pharmacotherapy. Neurosignals. 2016;24(1):1-14.  https://doi.org/10.1159/000442607
  57. Dreimuller N, Schlicht KF, Wagner S, Peetz D, Borysenko L, Hiemke C, Lieb K, Tadic A. Early reactions of brain-derived neurotrophic factor in plasma (pBDNF) and outcome to acute antidepressant treatment in patients with Major Depression. Neuropharmacology. 2012;62(1):264-269.  https://doi.org/10.1016/j.neuropharm.2011.07.017
  58. Pokrovsky DG. Method for predicting therapeutically resistant depressions in endogenous mental diseases. 2007. RU 2298190 C1. 
  59. Powell TR, Schalkwyk LC, Heffernan AL, Breen G, Lawrence T, Price T. Tumor necrosis factor and its targets in the inflammatory cytokine pathway are identified as putative transcriptomic biomarkers for escitalopram response. Eur Neuropsychopharmacol. 2013;23(9):1105-1114. https://doi.org/10.1016/j.euroneuro.2012.09.009
  60. Cattaneo A, Gennarelli M, Uher R, Breen G, Farmer A, Aitchison KJ, Craig IW, Anacker C, Zunsztain P, McGuffin P, Pariante C. Candidate genes expression profile associated with antidepressants response in the GENDEP study: differentiating between baseline ‘predictors’ and longitudinal ‘targets’. Neuropsychopharmacology. 2013;38(3):377-385.  https://doi.org/10.1038/npp.2012.191
  61. Guilloux JP, Bassi S, Ding Y, Walsh C, Turecki G, Tseng G, Cyranowski J, Sibille E. Testing the predictive value of peripheral gene expression for nonremission following citalopram treatment for major depression. Neuropsychopharmacology. 2015;40(3):701-710.  https://doi.org/10.1038/npp.2014.226
  62. Cattaneo A, Ferrari C, Uher R, Bocchio-Chiavetto L, Riva M., Pariante C. Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients. Int J Neuropsychopharmacol. 2016;19(10):pyw045. https://doi.org/10.1093/ijnp/pyw045

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