Clinical Psychopharmacology and Neuroscience

  • 제16권4호
  • /
  • Pages.469-480
  • /
  • 2018
  • /
  • 1738-1088(pISSN)
  • /
  • 2093-4327(eISSN)
대한정신약물학회 (Korean College of Neuropsychopharmacology)
권호 표지
DOI QR코드

DOI QR Code

A Pharmacogenomic-based Antidepressant Treatment for Patients with Major Depressive Disorder: Results from an 8-week, Randomized, Single-blinded Clinical Trial

  • Han, Changsu (Department of Psychiatry, Korea University College of Medicine) ;
  • Wang, Sheng-Min (Department of Psychiatry, College of Medicine, The Catholic University of Korea) ;
  • Bahk, Won-Myong (Department of Psychiatry, College of Medicine, The Catholic University of Korea) ;
  • Lee, Soo-Jung (Department of Psychiatry, College of Medicine, The Catholic University of Korea) ;
  • Patkar, Ashwin A. (Department of Psychiatry and Behavioral Sciences, Duke University Medical Center) ;
  • Masand, Prakash S. (Global Medical Education) ;
  • Mandelli, Laura (Department of Biomedical and Neuromotor Sciences, Psychiatric Section, University of Bologna) ;
  • Pae, Chi-Un (Department of Psychiatry, College of Medicine, The Catholic University of Korea) ;
  • Serretti, Alessandro (Department of Biomedical and Neuromotor Sciences, Psychiatric Section, University of Bologna)
  • 투고 : 2018.08.21
  • 심사 : 2018.08.27
  • 발행 : 2018.11.30
⟨ 이전 논문 다음 논문 ⟩

초록

Objective: Pharmacogenomic-based antidepressant treatment (PGATx) may result in more precise pharmacotherapy of major depressive disorder (MDD) with better drug therapy guidance. Methods: An 8-week, randomized, single-blind clinical trial was conducted to evaluate the effectiveness and tolerability of PGATx in 100 patients with MDD. All recruited patients were randomly allocated either to PGATx (n=52) or treatment as usual (TAU, n=48) groups. The primary endpoint was a change of total score of the Hamilton Depression Rating Scale-17 (HAMD-17) from baseline to end of treatment. Response rate (at least 50% reduction in HAMD-17 score from baseline), remission rate (HAMD-17 score ${\leq}7$ at the end of treatment) as well as the change of total score of Frequency, Intensity, and Burden of Side Effects Ratings (FIBSER) from baseline to end of treatment were also investigated. Results: The mean change of HAMD-17 score was significantly different between two groups favoring PGATx by -4.1 point of difference (p=0.010) at the end of treatment. The mean change in the FIBSER score from baseline was significantly different between two treatment groups favoring PGATx by -2.5 point of difference (p=0.028). The response rate (71.7 % vs. 43.6%, p=0.014) were also significantly higher in PGATx than in TAU at the end of treatment, while the remission rate was numerically higher in PGATx than in TAU groups without statistical difference (45.5% vs. 25.6%, p=0.071). The reason for early drop-out associated with adverse events was also numerically higher in TAU (n=9, 50.0%) than in PGATx (n=4, 30.8%). Conclusion: The present study clearly demonstrate that PGATx may be a better treatment option in the treatment of MDD in terms of effectiveness and tolerability; however, study shortcomings may limit a generalization. Adequately-powered, well-designed, subsequent studies should be mandatory to prove its practicability and clinical utility for routine practice.

키워드

과제정보

연구 과제 주관 기관 : Ministry of Health & Welfare

참고문헌

  1. Rakesh G, Pae CU, Masand PS. Beyond serotonin: newer antidepressants in the future. Expert Rev Neurother 2017;17:777-790. https://doi.org/10.1080/14737175.2017.1341310
  2. Wang SM, Han C, Pae CU. Criticisms of drugs in early development for the treatment of depression: what can be improved? Expert Opin Investig Drugs 2015;24:445-453. https://doi.org/10.1517/13543784.2014.985784
  3. Marks DM, Pae CU, Patkar AA. Triple reuptake inhibitors: a premise and promise. Psychiatry Investig 2008;5:142-147. https://doi.org/10.4306/pi.2008.5.3.142
  4. Wang HR, Bahk WM, Seo JS, Woo YS, Park YM, Jeong JH, et al. Korean Medication Algorithm for Depressive Disorder: comparisons with other treatment guidelines. Clin Psychopharmacol Neurosci 2017;15:199-209. https://doi.org/10.9758/cpn.2017.15.3.199
  5. Rush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Stewart JW, Warden D, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry 2006;163:1905-1917. https://doi.org/10.1176/ajp.2006.163.11.1905
  6. Rush AJ, Warden D, Wisniewski SR, Fava M, Trivedi MH, Gaynes BN, et al. STAR*D: revising conventional wisdom. CNS Drugs 2009;23:627-647.
  7. Gaynes BN, Warden D, Trivedi MH, Wisniewski SR, Fava M, Rush AJ. What did STAR*D teach us? Results from a large-scale, practical, clinical trial for patients with depression. Psychiatr Serv 2009;60:1439-1445. https://doi.org/10.1176/ps.2009.60.11.1439
  8. Pae CU, Wang SM, Han C, Lee SJ, Patkar AA, Masand PS, et al. Vortioxetine: a meta-analysis of 12 short-term, randomised, placebo-controlled clinical trials for the treatment of major depressive disorder. J Psychiatry Neurosci 2015;40:174-186. https://doi.org/10.1503/jpn.140120
  9. Cipriani A, Furukawa TA, Salanti G, Chaimani A, Atkinson LZ, Ogawa Y, et al. Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. Lancet 2018;391:1357-1366. https://doi.org/10.1016/S0140-6736(17)32802-7
  10. Hung CI. Factors predicting adherence to antidepressant treatment. Curr Opin Psychiatry 2014;27:344-349. https://doi.org/10.1097/YCO.0000000000000086
  11. Tansey KE, Guipponi M, Hu X, Domenici E, Lewis G, Malafosse A, et al. Contribution of common genetic variants to antidepressant response. Biol Psychiatry 2013;73:679-682. https://doi.org/10.1016/j.biopsych.2012.10.030
  12. Licinio J, Wong ML. Pharmacogenomics of antidepressant treatment effects. Dialogues Clin Neurosci 2011;13:63-71.
  13. Herbert D, Neves-Pereira M, Baidya R, Cheema S, Groleau S, Shahmirian A, et al. Genetic testing as a supporting tool in prescribing psychiatric medication: design and protocol of the IMPACT study. J Psychiatr Res 2018;96:265-272. https://doi.org/10.1016/j.jpsychires.2017.09.002
  14. Niitsu T, Fabbri C, Bentini F, Serretti A. Pharmacogenetics in major depression: a comprehensive meta-analysis. Prog Neuropsychopharmacol Biol Psychiatry 2013;45:183-194. https://doi.org/10.1016/j.pnpbp.2013.05.011
  15. Drozda K, Muller DJ, Bishop JR. Pharmacogenomic testing for neuropsychiatric drugs: current status of drug labeling, guidelines for using genetic information, and test options. Pharmacotherapy 2014;34:166-184. https://doi.org/10.1002/phar.1398
  16. Schuck RN, Grillo JA. Pharmacogenomic biomarkers: an FDA perspective on utilization in biological product labeling. AAPS J 2016;18:573-577. https://doi.org/10.1208/s12248-016-9891-4
  17. Frueh FW, Amur S, Mummaneni P, Epstein RS, Aubert RE, DeLuca TM, et al. Pharmacogenomic biomarker information in drug labels approved by the United States food and drug administration: prevalence of related drug use. Pharmacotherapy 2008;28:992-998. https://doi.org/10.1592/phco.28.8.992
  18. Winner JG, Carhart JM, Altar CA, Goldfarb S, Allen JD, Lavezzari G, et al. Combinatorial pharmacogenomic guidance for psychiatric medications reduces overall pharmacy costs in a 1 year prospective evaluation. Curr Med Res Opin 2015;31:1633-1643. https://doi.org/10.1185/03007995.2015.1063483
  19. Nassan M, Nicholson WT, Elliott MA, Rohrer Vitek CR, Black JL, Frye MA. Pharmacokinetic pharmacogenetic prescribing guidelines for antidepressants: a template for psychiatric precision medicine. Mayo Clin Proc 2016;91:897-907. https://doi.org/10.1016/j.mayocp.2016.02.023
  20. de Leon J, Armstrong SC, Cozza KL. Clinical guidelines for psychiatrists for the use of pharmacogenetic testing for CYP450 2D6 and CYP450 2C19. Psychosomatics 2006;47:75-85. https://doi.org/10.1176/appi.psy.47.1.75
  21. Hall-Flavin DK, Winner JG, Allen JD, Jordan JJ, Nesheim RS, Snyder KA, et al. Using a pharmacogenomic algorithm to guide the treatment of depression. Transl Psychiatry 2012;2:e172. https://doi.org/10.1038/tp.2012.99
  22. Hafner S, Haubensak S, Paul T, Zolk O. [How to individualize drug therapy based on pharmacogenetic information? A systematic review of published guidelines]. Dtsch Med Wochenschr 2016;141:e183-e202. German. https://doi.org/10.1055/s-0042-100973
  23. Jurgens G, Jacobsen CB, Rasmussen HB, Werge T, Nordentoft M, Andersen SE. Utility and adoption of CYP2D6 and CYP2C19 genotyping and its translation into psychiatric clinical practice. Acta Psychiatr Scand 2012;125:228-237. https://doi.org/10.1111/j.1600-0447.2011.01802.x
  24. Benitez J, Jablonski MR, Allen JD, Winner JG. The clinical validity and utility of combinatorial pharmacogenomics: enhancing patient outcomes. Appl Transl Genom 2015;5:47-49. https://doi.org/10.1016/j.atg.2015.03.001
  25. Fabbri C, Serretti A. Clinical application of antidepressant pharmacogenetics: considerations for the design of future studies. Neurosci Lett 2018. doi: 10.1016/j.neulet.2018.06.020. [Epub ahead of print]
  26. Bousman CA, Dunlop BW. Genotype, phenotype, and medication recommendation agreement among commercial pharmacogenetic-based decision support tools. Pharmacogenomics J 2018;18:613-622. https://doi.org/10.1038/s41397-018-0027-3
  27. Bousman CA, Forbes M, Jayaram M, Eyre H, Reynolds CF, Berk M, et al. Antidepressant prescribing in the precision medicine era: a prescriber's primer on pharmacogenetic tools. BMC Psychiatry 2017;17:60. https://doi.org/10.1186/s12888-017-1230-5
  28. Bousman CA, Hopwood M. Commercial pharmacogenetic-based decision-support tools in psychiatry. Lancet Psychiatry 2016;3:585-590. https://doi.org/10.1016/S2215-0366(16)00017-1
  29. Zeier Z, Carpenter LL, Kalin NH, Rodriguez CI, McDonald WM, Widge AS, et al. Clinical implementation of pharmacogenetic decision support tools for antidepressant drug prescribing. Am J Psychiatry 2018;175:873-886. https://doi.org/10.1176/appi.ajp.2018.17111282
  30. Bousman CA, Muller DJ, Ng CH, Byron K, Berk M, Singh AB. Concordance between actual and pharmacogenetic predicted desvenlafaxine dose needed to achieve remission in major depressive disorder: a 10-week open-label study. Pharmacogenet Genomics 2017;27:1-6. https://doi.org/10.1097/FPC.0000000000000253
  31. Altar CA, Carhart JM, Allen JD, Hall-Flavin DK, Dechairo BM, Winner JG. Clinical validity: combinatorial pharmacogenomics predicts antidepressant responses and healthcare utilizations better than single gene phenotypes. Pharmacogenomics J 2015;15:443-451. https://doi.org/10.1038/tpj.2014.85
  32. Perez V, Salavert A, Espadaler J, Tuson M, Saiz-Ruiz J, Saez-Navarro C, et al. Efficacy of prospective pharmacogenetic testing in the treatment of major depressive disorder: results of a randomized, double-blind clinical trial. BMC Psychiatry 2017;17:250. https://doi.org/10.1186/s12888-017-1412-1
  33. Espadaler J, Tuson M, Lopez-Ibor JM, Lopez-Ibor F, Lopez-Ibor MI. Pharmacogenetic testing for the guidance of psychiatric treatment: a multicenter retrospective analysis. CNS Spectr 2017;22:315-324. https://doi.org/10.1017/S1092852915000711
  34. Bradley P, Shiekh M, Mehra V, Vrbicky K, Layle S, Olson MC, et al. Improved efficacy with targeted pharmacogenetic-guided treatment of patients with depression and anxiety: a randomized clinical trial demonstrating clinical utility. J Psychiatr Res 2018;96:100-107. https://doi.org/10.1016/j.jpsychires.2017.09.024
  35. Winner JG, Carhart JM, Altar CA, Allen JD, Dechairo BM. A prospective, randomized, double-blind study assessing the clinical impact of integrated pharmacogenomic testing for major depressive disorder. Discov Med 2013;16:219-227.
  36. Singh AB. Improved antidepressant remission in major depression via a pharmacokinetic pathway polygene pharmacogenetic report. Clin Psychopharmacol Neurosci 2015;13:150-156. https://doi.org/10.9758/cpn.2015.13.2.150
  37. Hall-Flavin DK, Winner JG, Allen JD, Carhart JM, Proctor B, Snyder KA, et al. Utility of integrated pharmacogenomic testing to support the treatment of major depressive disorder in a psychiatric outpatient setting. Pharmacogenet Genomics 2013;23:535-548. https://doi.org/10.1097/FPC.0b013e3283649b9a
  38. Brennan FX, Gardner KR, Lombard J, Perlis RH, Fava M, Harris HW, et al. A naturalistic study of the effectiveness of pharmacogenetic testing to guide treatment in psychiatric patients with mood and anxiety disorders. Prim Care Companion CNS Disord 2015;17. doi: 10.4088/PCC.14m01717.
  39. Kennedy SH, Lam RW, Cohen NL, Ravindran AV; Group CDW. Clinical guidelines for the treatment of depressive disorders. IV. Medications and other biological treatments. Can J Psychiatry 2001;46 Suppl 1:38S-58S.
  40. Anderson IM, Ferrier IN, Baldwin RC, Cowen PJ, Howard L, Lewis G, et al. Evidence-based guidelines for treating depressive disorders with antidepressants: a revision of the 2000 British association for psychopharmacology guidelines. J Psychopharmacol 2008;22:343-396. https://doi.org/10.1177/0269881107088441
  41. Bauer M, Pfennig A, Severus E, Whybrow PC, Angst J, Moller HJ. World Federation of Societies of Biological Psychiatry (WFSBP) guidelines for biological treatment of unipolar depressive disorders, part 1: update 2013 on the acute and continuation treatment of unipolar depressive disorders. World J Biol Psychiatry 2013;14:334-385. https://doi.org/10.3109/15622975.2013.804195
  42. Patkar AA, Pae CU. Atypical antipsychotic augmentation strategies in the context of guideline-based care for the treatment of major depressive disorder. CNS Drugs 2013;27 Suppl 1:S29-S37. https://doi.org/10.1007/s40263-012-0031-0
  43. Rush AJ, Trivedi MH, Stewart JW, Nierenberg AA, Fava M, Kurian BT, et al. Combining medications to enhance depression outcomes (CO-MED): acute and long-term outcomes of a single-blind randomized study. Am J Psychiatry 2011;168:689-701. https://doi.org/10.1176/appi.ajp.2011.10111645
  44. Pae CU, Patkar AA. Clinical issues in use of atypical antipsychotics for depressed patients. CNS Drugs 2013;27 Suppl 1:S39-S45. https://doi.org/10.1007/s40263-012-0032-z
  45. Han C, Yeh TL, Kato M, Sato S, Chang CM, Pae CU. Management of chronic depressive patients with residual symptoms. CNS Drugs 2013;27 Suppl 1:S53-S57. https://doi.org/10.1007/s40263-012-0034-x
  46. Han C, Wang SM, Kato M, Lee SJ, Patkar AA, Masand PS, et al. Second-generation antipsychotics in the treatment of major depressive disorder: current evidence. Expert Rev Neurother 2013;13:851-870. https://doi.org/10.1586/14737175.2013.811901
  47. Torrellas C, Carril JC, Cacabelos R. Optimization of antidepressant use with pharmacogenetic strategies. Curr Genomics 2017;18:442-449.
  48. Jeon SW, Han C, Ko YH, Yoon SY, Pae CU, Choi J, et al. Measurement-based treatment of residual symptoms using clinically useful depression outcome scale: Korean validation study. Clin Psychopharmacol Neurosci 2017;15:28-34. https://doi.org/10.9758/cpn.2017.15.1.28
  49. Serretti A, Kato M, De Ronchi D, Kinoshita T. Meta-analysis of serotonin transporter gene promoter polymorphism (5-HTTLPR) association with selective serotonin reuptake inhibitor efficacy in depressed patients. Mol Psychiatry 2007;12:247-257. https://doi.org/10.1038/sj.mp.4001926
  50. Reyes-Barron C, Tonarelli S, Delozier A, Briones DF, Su BB, Rubin LP, et al. Pharmacogenetics of antidepressants, a review of significant genetic variants in different populations. Clin Depress 2016;2:1-10.
  51. Hornberger J, Li Q, Quinn B. Cost-effectiveness of combinatorial pharmacogenomic testing for treatment-resistant major depressive disorder patients. Am J Manag Care 2015;21:e357-e365.
  52. Najafzadeh M, Garces JA, Maciel A. Economic evaluation of implementing a novel pharmacogenomic test $(IDgenetix^{(R)})$ to guide treatment of patients with depression and/or anxiety. Pharmacoeconomics 2017;35:1297-1310. https://doi.org/10.1007/s40273-017-0587-0
  53. Verbelen M, Weale ME, Lewis CM. Cost-effectiveness of pharmacogenetic-guided treatment: are we there yet? Pharmacogenomics J 2017;17:395-402. https://doi.org/10.1038/tpj.2017.21
  54. Stahl SM. Psychiatric pharmacogenomics: how to integrate into clinical practice. CNS Spectr 2017;22:1-4. https://doi.org/10.1017/S1092852917000864
  55. Perlis RH. Cytochrome P450 genotyping and antidepressants. BMJ 2007;334:759. https://doi.org/10.1136/bmj.39169.547512.80

피인용 문헌

  1. Optimizing drug selection in psychopharmacology based on 40 significant CYP2C19- and CYP2D6-biased adverse drug reactions of selective serotonin reuptake inhibitors vol.7, pp.None, 2018, https://doi.org/10.7717/peerj.7860
  2. Effectiveness of a Pharmacogenetic Tool at Improving Treatment Efficacy in Major Depressive Disorder: A Meta-Analysis of Three Clinical Studies vol.11, pp.9, 2018, https://doi.org/10.3390/pharmaceutics11090453
  3. The Potential Utility of Aripiprazole Augmentation for Major Depressive Disorder with Mixed Features Specifier: A Retrospective Study vol.17, pp.4, 2018, https://doi.org/10.9758/cpn.2019.17.4.495
  4. Consequences of Recurrence of Major Depressive Disorder: Is Stopping Effective Antidepressant Medications Ever Safe? vol.18, pp.2, 2018, https://doi.org/10.1176/appi.focus.20200008
  5. Effectiveness and Tolerability of Korean Red Ginseng Augmentation in Major Depressive Disorder Patients with Difficult-to-treat in Routine Practice vol.18, pp.4, 2020, https://doi.org/10.9758/cpn.2020.18.4.621
  6. Effect of Pharmacogenetic-Based Decision Support Tools in Improving Depression Outcomes: A Systematic Review vol.17, pp.None, 2021, https://doi.org/10.2147/ndt.s312966
  7. A Practical Utility and Benefit of Pharmacogenetic-based Antidepressant Treatment Strategy for Major Depressive Disorder Patients with Difficult-to-treat vol.19, pp.1, 2021, https://doi.org/10.9758/cpn.2021.19.1.160
  8. Acceptability of Pharmacogenetic Testing among French Psychiatrists, a National Survey vol.11, pp.6, 2018, https://doi.org/10.3390/jpm11060446
  9. Genetic Variations Associated with Long-Term Treatment Response in Bipolar Depression vol.12, pp.8, 2021, https://doi.org/10.3390/genes12081259
  10. Predictors of relapse following a stepwise psychopharmacotherapy regime in patients with depressive disorders vol.293, pp.None, 2021, https://doi.org/10.1016/j.jad.2021.06.015
  11. Pharmacist-guided pre-emptive pharmacogenetic testing in antidepressant therapy (PrePGx): study protocol for an open-label, randomized controlled trial vol.22, pp.1, 2018, https://doi.org/10.1186/s13063-021-05724-5