Cognitive-Behavioural Analysis System of Psychotherapy (CBASP), a drug, or their combination: Differential therapeutics for persistent depressive disorder: A study protocol of an individual participant data network meta-analysis

BMJ Open

Volumn 6, Issue 5, 2016, Pages

  Furukawa, Toshi A ^a   Schramm, Elisabeth ^b   Weitz, Erica S ^c   Salanti, Georgia ^d   Efthimiou, Orestis ^d   Michalak, Johannes ^e   Watanabe, Norio ^a   Cipriani, Andrea ^f   Keller, Martin B ^g   Kocsis, James H ^h   Klein, Daniel N ⁱ   Cuijpers, Pim ^c  

^a KYOTO UNIVERSITY GRADUATE SCHOOL OF MEDICINE   (Japan)

^b UNIVERSITY OF FREIBURG   (Germany)

^c UNIVERSITY OF AMSTERDAM   (Netherlands)

^d UNIVERSITY OF BERN   (Switzerland)

^e UNIVERSITY OF WITTEN HERDECKE   (Germany)

^f UNIVERSITY OF OXFORD   (United Kingdom)

^g BROWN UNIVERSITY   (United States)

^h WEILL CORNELL MEDICAL COLLEGE   (United States)

ⁱ STONY BROOK UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COGNITIVE BEHAVIORAL ANALYSIS SYSTEM OF PSYCHOTHERAPY; DEPRESSION; DSM-5; DSM-IV; DYSTHYMIA; HUMAN; MAJOR DEPRESSION; META ANALYSIS; PATIENT PREFERENCE; PSYCHOTHERAPY; RANDOMIZED CONTROLLED TRIAL (TOPIC); REMISSION; TREATMENT RESPONSE; COGNITIVE THERAPY; DRUG THERAPY; MULTIMODALITY CANCER THERAPY; NETWORK META-ANALYSIS; OUTCOME ASSESSMENT; PATHOPHYSIOLOGY; PSYCHOLOGY; SYSTEM ANALYSIS;

COGNITIVE THERAPY; COMBINED MODALITY THERAPY; DEPRESSIVE DISORDER; DRUG THERAPY; HUMANS; NETWORK META-ANALYSIS; OUTCOME ASSESSMENT (HEALTH CARE); PSYCHOTHERAPY; RANDOMIZED CONTROLLED TRIALS AS TOPIC; SYSTEMS ANALYSIS;

EID: 84971287215     PISSN: None     EISSN: 20446055     Source Type: Journal    
DOI: 10.1136/bmjopen-2016-011769     Document Type: Article

References (53)

1. Murphy JA, Byrne GJ. Prevalence and correlates of the proposed DSM-5 diagnosis of chronic depressive disorder. J Affect Disord 2012;139:172-80.
2. Kessler RC, Berglund P, Demler O, et al. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry 2005;62:593-602.
3. McCullough JP Jr, Klein DN, Keller MB, et al. Comparison of DSM-III-R chronic major depression and major depression superimposed on dysthymia (double depression): validity of the distinction. J Abnorm Psychol 2000;109:419-27.
4. McCullough JP Jr, Klein DN, Borian FE, et al. Group comparisons of DSM-IV subtypes of chronic depression: validity of the distinctions, part 2. J Abnorm Psychol 2003;112:614-22.
5. Angst J, Gamma A, Rössler W, et al. Long-term depression versus episodic major depression: results from the prospective Zurich study of a community sample. J Affect Disord 2009;115:112-21.
6. Kocsis JH, Gelenberg AJ, Rothbaum B, et al. Chronic forms of major depression are still undertreated in the 21st century: systematic assessment of 801 patients presenting for treatment. J Affect Disord 2008;110:55-61.
7. Klein DN, Shankman SA, Rose S. Ten-year prospective follow-up study of the naturalistic course of dysthymic disorder and double depression. Am J Psychiatry 2006;163:872-80.
8. Spijker J, van Straten A, Bockting CL, et al. Psychotherapy, antidepressants, and their combination for chronic major depressive disorder: a systematic review. Can J Psychiatry 2013;58:386-92.
9. Kriston L, von Wolff A, Westphal A, et al. Efficacy and acceptability of acute treatments for persistent depressive disorder: a network meta-analysis. Depress Anxiety 2014;31:621-30.
10. Cuijpers P, van Straten A, Schuurmans J, et al. Psychotherapy for chronic major depression and dysthymia: a meta-analysis. Clin Psychol Rev 2010;30:51-62.
11. von Wolff A, Hölzel LP, Westphal A, et al. Combination of pharmacotherapy and psychotherapy in the treatment of chronic depression: a systematic review and meta-analysis. BMC Psychiatry 2012;12:61.
12. McCullough JP Jr. Treatment for chronic depression: Cogntive Behavioral Analysis System of Psychotherapy (CBASP). New York: Guilford Press, 2000.
13. Hamburg MA, Collins FS. The path to personalized medicine. N Engl J Med 2010;363:301-4.
14. Jameson JL, Longo DL. Precision medicine - personalized, problematic, and promising. N Engl J Med 2015;372:2229-34.
15. Barber JP, Muenz LR. The role of avoidance and obsessiveness in matching patients to cognitive and interpersonal psychotherapy: empirical findings from the treatment for depression collaborative research program. J Consult Clin Psychol 1996;64:951-8.
16. DeRubeis RJ, Cohen ZD, Forand NR, et al. The personalized advantage index: translating research on prediction into individualized treatment recommendations. A demonstration. PLoS ONE 2014;9:e83875.
17. Willke RJ, Zheng Z, Subedi P, et al. From concepts, theory, and evidence of heterogeneity of treatment effects to methodological approaches: a primer. BMC Med Res Methodol 2012;12:185.
18. Kraemer HC. Discovering, comparing, and combining moderators of treatment on outcome after randomized clinical trials: a parametric approach. Stat Med 2013;32:1964-73.
19. Hayward RA, Kent DM, Vijan S, et al. Multivariable risk prediction can greatly enhance the statistical power of clinical trial subgroup analysis. BMC Med Res Methodol 2006;6:18.
20. Dorresteijn JA, Visseren FL, Ridker PM, et al. Estimating treatment effects for individual patients based on the results of randomised clinical trials. BMJ 2011;343:d5888.
21. Mavridis D, Giannatsi M, Cipriani A, et al. A primer on network meta-analysis with emphasis on mental health. Evid Based Ment Health 2015;18:40-6.
22. von Wolff A, Hölzel LP, Westphal A, et al. Selective serotonin reuptake inhibitors and tricyclic antidepressants in the acute treatment of chronic depression and dysthymia: a systematic review and meta-analysis. J Affect Disord 2013;144:7-15.
23. Carmody TJ, Rush AJ, Bernstein I, et al. The Montgomery Asberg and the Hamilton ratings of depression: a comparison of measures. Eur Neuropsychopharmacol 2006;16:601-11.
24. Furukawa TA, Akechi T, Azuma H, et al. Evidence-based guidelines for interpretation of the Hamilton Rating Scale for Depression. J Clin Psychopharmacol 2007;27:531-4.
25. Bandelow B, Baldwin DS, Dolberg OT, et al. What is the threshold for symptomatic response and remission for major depressive disorder, panic disorder, social anxiety disorder, and generalized anxiety disorder? J Clin Psychiatry 2006;67:1428-34.
26. Trivedi MH, Rush AJ, Ibrahim HM, et al. The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with mood disorders: a psychometric evaluation. Psychol Med 2004;34:73-82.
27. Endicott J, Spitzer RL, Fleiss JL, et al. The global assessment scale. A procedure for measuring overall severity of psychiatric disturbance. Arch Gen Psychiatry 1976;33:766-71.
28. Weissman MM, Bothwell S. Assessment of social adjustment by patient self-report. Arch Gen Psychiatry 1976;33:1111-15.
29. Kessler RC, Bossarte R, Brenner L, et al. Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder. Epidemiol Psychiatr Sci 2016;26:1-15.
30. Cuijpers P, Reynolds CF III, Donker T, et al. Personalized treatment of adult depression: medication, psychotherapy, or both? A systematic review. Depress Anxiety 2012;29:855-64.
31. Nemeroff CB, Heim CM, Thase ME, et al. Differential responses to psychotherapy versus pharmacotherapy in patients with chronic forms of major depression and childhood trauma. Proc Natl Acad Sci USA 2003;100:14293-6.
32. Perlis RH. A clinical risk stratification tool for predicting treatment resistance in major depressive disorder. Biol Psychiatry 2013;74:7-14.
33. Fournier JC, DeRubeis RJ, Shelton RC, et al. Prediction of response to medication and cognitive therapy in the treatment of moderate to severe depression. J Consult Clin Psychol 2009;77:775-87.
34. Frank E, Cassano GB, Rucci P, et al. Predictors and moderators of time to remission of major depression with interpersonal psychotherapy and SSRI pharmacotherapy. Psychol Med 2011;41:151-62.
35. Andreescu C, Mulsant BH, Houck PR, et al. Empirically derived decision trees for the treatment of late-life depression. Am J Psychiatry 2008;165:855-62.
36. Jarrett RB, Minhajuddin A, Kangas JL, et al. Acute phase cognitive therapy for recurrent major depressive disorder: who drops out and how much do patient skills influence response? Behav Res Ther 2013;51:221-30.
37. Fournier JC, DeRubeis RJ, Hollon SD, et al. Antidepressant drug effects and depression severity: a patient-level meta-analysis. JAMA 2010;303:47-53.
38. Driessen E, Cuijpers P, Hollon SD, et al. Does pretreatment severity moderate the efficacy of psychological treatment of adult outpatient depression? A meta-analysis. J Consult Clin Psychol 2010;78:668-80.
39. Weitz ES, Hollon SD, Twisk J, et al. Baseline depression severity as moderator of depression outcomes between cognitive behavioral therapy vs pharmacotherapy: an individual patient data meta-analysis. JAMA Psychiatry 2015;72:1102-9.
40. Rush AJ, Wisniewski SR, Warden D, et al. Selecting among second-step antidepressant medication monotherapies: predictive value of clinical, demographic, or first-step treatment features. Arch Gen Psychiatry 2008;65:870-80.
41. Ninan PT, Rush AJ, Crits-Christoph P, et al. Symptomatic and syndromal anxiety in chronic forms of major depression: effect of nefazodone, cognitive behavioral analysis system of psychotherapy, and their combination. J Clin Psychiatry 2002;63:434-41.
42. Steidtmann D, Manber R, Arnow BA, et al. Patient treatment preference as a predictor of response and attrition in treatment for chronic depression. Depress Anxiety 2012;29:896-905.
43. Kocsis JH, Leon AC, Markowitz JC, et al. Patient preference as a moderator of outcome for chronic forms of major depressive disorder treated with nefazodone, cognitive behavioral analysis system of psychotherapy, or their combination. J Clin Psychiatry 2009;70:354-61.
44. Arnow BA, Steidtmann D, Blasey C, et al. The relationship between the therapeutic alliance and treatment outcome in two distinct psychotherapies for chronic depression. J Consult Clin Psychol 2013;81:627-38.
45. Klein DN, Schwartz JE, Santiago NJ, et al. Therapeutic alliance in depression treatment: controlling for prior change and patient characteristics. J Consult Clin Psychol 2003;71:997-1006.
46. Steidtmann D, Manber R, Blasey C, et al. Detecting critical decision points in psychotherapy and psychotherapy + medication for chronic depression. J Consult Clin Psychol 2013;81:783-92.
47. Higgins JP, Green S, eds. Cochrane handbook for systematic reviews of interventions Version 5.1.0 (updated March 2011). 2011. http://www.cochrane-handbook.org.
48. Peters JL, Sutton AJ, Jones DR, et al. Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. J Clin Epidemiol 2008;61:991-6.
49. Chaimani A, Salanti G. Using network meta-analysis to evaluate the existence of small-study effects in a network of interventions. Res Synth Methods 2012;3:161-76.
50. Donegan S, Williamson P, D'Alessandro U, et al. Combining individual patient data and aggregate data in mixed treatment comparison meta-analysis: individual patient data may be beneficial if only for a subset of trials. Stat Med 2013;32:914-30.
51. Little RJ, Rubin DB. Statistical analysis with missing data. New York: John Wiley & Sons, 2002.
52. Turner RM, Davey J, Clarke MJ, et al. Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews. Int J Epidemiol 2012;41:818-27.
53. Rhodes KM, Turner RM, Higgins JP. Predictive distributions were developed for the extent of heterogeneity in meta-analyses of continuous outcome data. J Clin Epidemiol 2015;68:52-60.