Skip to main content

Advertisement

SpringerLink
Log in

Personalized Medicine and Cognitive Behavioral Therapies for Depression: Small Effects, Big Problems, and Bigger Data

  • Published:
International Journal of Cognitive Therapy Aims and scope Submit manuscript

Abstract

Cognitive-behavioral therapies (CBTs) are the most widely studied form of psychotherapy for disorders like depression and anxiety. Nonetheless, there is heterogeneity in response to CBTs vs. other treatments. Researchers have become increasingly interested in using pre-treatment individual differences (i.e., moderators) to match patients to the most effective treatments for them. Several methods to combine multiple variables to create precision treatment rules (PTRs) that identify subgroups have been proposed. We review the rationale behind multivariable PTRs as well as the findings of studies that have used different PTRs. We identify conceptual and methodological issues in the literature. Multivariable treatment assignment is a promising avenue of research. Nonetheless, effect sizes appear to be small and most of the samples that have been used to study these questions have been grossly underpowered to detect small effects. We recommend researchers explore multivariable treatment selection strategies, particularly those resembling risk stratification, in heterogeneous samples of patients undergoing low-intensity CBTs vs. realistic minimal controls.

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

Similar content being viewed by others

References

  • Aafjes-van Doorn, K., Kamsteeg, C., Bate, J., & Aafjes, M. (2020). A scoping review of machine learning in psychotherapy research. Psychother Res, 1–25. Advance online publication. https://doi.org/10.1080/10503307.2020.1808729.

  • American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders, 5th edn. American Psychiatric Association: Washington, DC.

  • Barber, J. P., & Muenz, L. R. (1996). 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, 64(5), 951–958. https://doi.org/10.1037/0022-006X.64.5.951.

    Article  PubMed  Google Scholar 

  • Barth, J., Munder, T., Gerger, H., Nüesch, E., Trelle, S., Znoj, H., Jüni, P., & Cuijpers, P. (2016). Comparative efficacy of seven psychotherapeutic interventions for patients with depression: a network meta-analysis. PLOS Medicine, 10, e1001454. https://doi.org/10.1371/journal.pmed.1001454.

    Article  Google Scholar 

  • Bathina, K. C., Thij, M. t., Lorenzo-Luaces, L., Rutter, L. A., & Bollen, J. (2020). Depressed individuals express more distorted thinking on social media. arXiv preprint arXiv:2002.02800.

  • Baumeister, H., & Parker, G. (2012). Meta-review of depressive subtyping models. J Affect Disord, 139(2), 126–140. https://doi.org/10.1016/j.jad.2011.07.015.

    Article  Google Scholar 

  • Beutler, L. E., Engle, D., Mohr, D., Daldrup, R. J., Bergan, J., Meredith, K., & Merry, W. (1991). Predictors of differential response to cognitive, experiential, and self-directed psychotherapeutic procedures. J Consult Clin Psychol, 59(2), 333–340. https://doi.org/10.1037/0022-006X.59.2.333.

    Article  PubMed  Google Scholar 

  • Bockting, C. L., Hollon, S. D., Jarrett, R. B., Kuyken, W., & Dobson, K. (2015). A lifetime approach to major depressive disorder: the contributions of psychological interventions in preventing relapse and recurrence. Clin Psychol Rev, 41, 16–26. https://doi.org/10.1016/j.cpr.2015.02.003.

    Article  PubMed  Google Scholar 

  • Boschloo, L., Bekhuis, E., Weitz, E. S., Reijnders, M., DeRubeis, R. J., Dimidjian, S., Dunner, D. L., Dunlop, B. W., Hegerl, U., Hollon, S. D., et al. (2019). The symptom-specific efficacy of antidepressant medication vs. cognitive behavioral therapy in the treatment of depression: results from an individual patient data meta-analysis. World Psychiatry, 18(2), 183–191. https://doi.org/10.1002/wps.20630.

    Article  PubMed  PubMed Central  Google Scholar 

  • Bower, P., Kontopantelis, E., Sutton, A., Kendrick, T., Richards, D. A., Gilbody, S., Knowles, S., Cuijpers, P., Andersson, G., Christensen, H., et al. (2013). Influence of initial severity of depression on effectiveness of low intensity interventions: meta-analysis of individual patient data. Br Med J, 346, f540. https://doi.org/10.1136/bmj.f540.

    Article  Google Scholar 

  • Bringmann, L. F., Elmer, T., Epskamp, S., Krause, R. W., Schoch, D., Wichers, M., Wigman, J. T., & Snippe, E. (2019). What do centrality measures measure in psychological networks? J Abnorm Psychol, 128(8), 892.

    Article  PubMed  Google Scholar 

  • Bruijniks, S. J., Lemmens, L. H., Hollon, S. D., Peeters, F. P., Cuijpers, P., Arntz, A., Dingemanse, P., Willems, L., Van Oppen, P., Twisk, J. W., et al. (2020). The effects of once-versus twice-weekly sessions on psychotherapy outcomes in depressed patients. Br J Psychiatry, 216(4), 222–230. https://doi.org/10.1192/bjp.2019.265.

    Article  PubMed  Google Scholar 

  • Bschor, T., Kern, H., Henssler, J., & Baethge, C. (2018). Switching the antidepressant after nonresponse in adults with major depression: a systematic literature search and meta-analysis., 79(1), 16r10749. https://doi.org/10.4088/JCP.16r10749.

  • Chambless, D. L. (2002). Beware the dodo bird: the dangers of overgeneralization. Clin Psychol Sci Pract, 9(1), 13–16. https://doi.org/10.1093/clipsy/9.1.13.

    Article  Google Scholar 

  • Cheavens, J. S., Strunk, D. R., Lazarus, S. A., & Goldstein, L. A. (2012). The compensation and capitalization models: a test of two approaches to individualizing the treatment of depression. Behav Res Ther, 50(11), 699–706. https://doi.org/10.1016/j.brat.2012.08.002.

    Article  PubMed  Google Scholar 

  • Cloitre, M., Petkova, E., Su, Z., & Weiss, B. J. (2016). Patient characteristics as a moderator of posttraumatic stress disorder treatment outcome: combining symptom burden and strengths. BJPsych Open, 2(2), 101–106. https://doi.org/10.1192/bjpo.bp.115.000745.

    Article  PubMed  PubMed Central  Google Scholar 

  • Cohen, Z. D., & DeRubeis, R. J. (2018). Treatment selection in depression. Annual Review of Clinical Psychology, 14(1), 209–236. https://doi.org/10.1146/annurev-clinpsy-050817-084746.

    Article  PubMed  Google Scholar 

  • Cohen, D., Deniau, E., Maturana, A., Tanguy, M.-L., Bodeau, N., Labelle, R., Breton, J.-J., & Guile, J.-M. (2008). Are child and adolescent responses to placebo higher in major depression than in anxiety disorders? A systematic review of placebo-controlled trials. PLoS One, 3(7), e2632. https://doi.org/10.1371/journal.pone.0002632.

    Article  PubMed  PubMed Central  Google Scholar 

  • Cohen, Z. D., Kim, T. T., Van, H. L., Dekker, J. J. M., & Driessen, E. (2020). A demonstration of a multi-method variable selection approach for treatment selection: recommending cognitive–behavioral versus psychodynamic therapy for mild to moderate adult depression. Psychother Res, 30(2), 137–150. https://doi.org/10.1080/10503307.2018.1563312.

    Article  PubMed  Google Scholar 

  • Cuijpers, P., van Straten, A., Schuurmans, J., van Oppen, P., Hollon, S. D., & Andersson, G. (2010). Psychotherapy for chronic major depression and dysthymia: a meta-analysis. Clin Psychol Rev, 30(1), 51–62. https://doi.org/10.1016/j.cpr.2009.09.003.

    Article  PubMed  Google Scholar 

  • Cuijpers, P., Driessen, E., Hollon, S. D., van Oppen, P., Barth, J., & Andersson, G. (2012). The efficacy of non-directive supportive therapy for adult depression: a meta-analysis. Clin Psychol Rev, 32(4), 280–291. https://doi.org/10.1016/j.cpr.2012.01.003.

    Article  PubMed  Google Scholar 

  • Cuijpers, P., Hollon, S. D., van Straten, A., Bockting, C., Berking, M., & Andersson, G. (2013). Does cognitive behaviour therapy have an enduring effect that is superior to keeping patients on continuation pharmacotherapy? A meta-analysis. BMJ Open, 3(4), e002542. https://doi.org/10.1136/bmjopen-2012-002542.

    Article  PubMed  PubMed Central  Google Scholar 

  • Cuijpers, P., Weitz, E., Twisk, J., Kuehner, C., Cristea, I., David, D., DeRubeis, R. J., Dimidjian, S., Dunlop, B. W., Faramarzi, M., et al. (2014). Gender as predictor and moderator of outcome in cognitive behavior therapy and pharmacotherapy for adult depression: an “individual patient data” meta-analysis. Depression and Anxiety, 31(11), 941–951. https://doi.org/10.1002/da.22328.

    Article  PubMed  Google Scholar 

  • Cuijpers, P., Weitz, E., Lamers, F., Penninx, B. W., Twisk, J., DeRubeis, R. J., Dimidjian, S., Dunlop, B. W., Jarrett, R. B., Segal, Z. V., et al. (2017). Melancholic and atypical depression as predictor and moderator of outcome in cognitive behavior therapy and pharmacotherapy for adult depression. Depression and Anxiety, 34(3), 246–256. https://doi.org/10.1002/da.22580.

    Article  PubMed  Google Scholar 

  • Cuijpers, P., Noma, H., Karyotaki, E., Cipriani, A., & Furukawa, T. A. (2019). Effectiveness and acceptability of cognitive behavior therapy delivery formats in adults with depression: a network meta-analysis. JAMA Psychiatry, 76(7), 700–707. https://doi.org/10.1001/jamapsychiatry.2019.0268.

    Article  PubMed  PubMed Central  Google Scholar 

  • Cuijpers, P., Karyotaki, E., Eckshtain, D., Ng, M. Y., Corteselli, K. A., Noma, H., Quero, S., & Weisz, J. R. (2020). Psychotherapy for depression across different age groups: a systematic review and meta-analysis. JAMA Psychiatry, 77(7), 694–702. https://doi.org/10.1001/jamapsychiatry.2020.0164.

    Article  PubMed  PubMed Central  Google Scholar 

  • Dablander, F., & Hinne, M. (2019). Node centrality measures are a poor substitute for causal inference. Sci Rep, 9(1), 1–13.

    Article  Google Scholar 

  • Delgadillo, J., & Gonzalez Salas Duhne, P. (2020). Targeted prescription of cognitive–behavioral therapy versus person-centered counseling for depression using a machine learning approach. Journal of Consulting and Clinical Psychology, 88(1), 14–24. https://doi.org/10.1037/ccp0000476.

    Article  PubMed  Google Scholar 

  • Delgadillo, J., Huey, D., Bennett, H., & McMillan, D. (2017). Case complexity as a guide for psychological treatment selection. J Consult Clin Psychol, 85(9), 835–853. https://doi.org/10.1037/ccp0000231.

    Article  PubMed  Google Scholar 

  • DeRubeis, R. J. (2019). The history, current status, and possible future of precision mental health. Behav Res Ther, 123, 103506. https://doi.org/10.1016/j.brat.2019.103506.

    Article  PubMed  Google Scholar 

  • DeRubeis, R. J., & Lorenzo-Luaces, L. (2017). Recognizing that truth is unattainable and attending to the most informative research evidence. Psychother Res, 27(1), 33–35. https://doi.org/10.1080/10503307.2016.1252072.

    Article  PubMed  Google Scholar 

  • DeRubeis, R. J., Hollon, S. D., Amsterdam, J. D., Shelton, R. C., Young, P. R., Salomon, R. M., O’Reardon, J. P., Lovett, M. L., Gladis, M. M., Brown, L. L., et al. (2005). Cognitive therapy vs medications in the treatment of moderate to severe depression. Arch Gen Psychiatry, 62(4), 409–416. https://doi.org/10.1001/archpsyc.62.4.409.

    Article  PubMed  Google Scholar 

  • DeRubeis, R. J., Cohen, Z. D., Forand, N. R., Fournier, J. C., Gelfand, L. A., & Lorenzo-Luaces, L. (2014a). The personalized advantage index: Translating research on prediction into individualized treatment recommendations. A demonstration. PLoS ONE, 9(1), e83875. https://doi.org/10.1371/journal.pone.0083875.

    Article  PubMed  PubMed Central  Google Scholar 

  • DeRubeis, R. J., Gelfand, L. A., German, R. E., Fournier, J. C., & Forand, N. R. (2014b). Understanding processes of change: how some patients reveal more than others—and some groups of therapists less—about what matters in psychotherapy. Psychother Res, 24(3), 419–428. https://doi.org/10.1080/10503307.2013.838654.

    Article  PubMed  Google Scholar 

  • Dinga, R., Schmaal, L., Penninx, B. W., van Tol, M. J., Veltman, D. J., van Velzen, L., Mennes, M., van der Wee, N. J., & Marquand, A. F. (2019). Evaluating the evidence for biotypes of depression: methodological replication and extension of Drysdale et al. (2017). NeuroImage: Clinical, 22, 101796. https://doi.org/10.1016/j.nicl.2019.101796.

    Article  Google Scholar 

  • Driessen, E., Cuijpers, P., Hollon, S. D., & Dekker, J. J. (2010). Does pretreatment severity moderate the efficacy of psychological treatment of adult outpatient depression? A meta-analysis. J Consult Clin Psychol, 78(5), 668–680. https://doi.org/10.1037/a0020570.

    Article  PubMed  Google Scholar 

  • Driessen, E., Van, H. L., Don, F. J., Peen, J., Kool, S., Westra, D., Hendriksen, M., Schoevers, R. A., Cuijpers, P., Twisk, J. W., et al. (2013). The efficacy of cognitive-behavioral therapy and psychodynamic therapy in the outpatient treatment of major depression: a randomized clinical trial. Am J Psychiatr, 170(9), 1041–1050. https://doi.org/10.1176/appi.ajp.2013.12070899.

    Article  PubMed  Google Scholar 

  • Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., Fetcho, R. N., Zebley, B., Oathes, D. J., Etkin, A., et al. (2017). Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med, 23(1), 28–38. https://doi.org/10.1038/nm.4246.

    Article  PubMed  Google Scholar 

  • Dunlop, B. W., LoParo, D., Kinkead, B., Mletzko-Crowe, T., Cole, S. P., Nemeroff, C. B., Mayberg, H. S., & Craighead, W. E. (2019). Benefits of sequentially adding cognitive-behavioral therapy or antidepressant medication for adults with nonremitting depression. Am J Psychiatr, 176(4), 275–286. https://doi.org/10.1176/appi.ajp.2018.18091075.

    Article  PubMed  Google Scholar 

  • Eskildsen, A., Reinholt, N., van Bronswijk, S. C., Brund, R. B., Christensen, A. B., Hvenegaard, M., Arendt, M., Alro, A., Poulsen, S., Rosenberg, N. K., et al. (2020). Personalized psychotherapy for outpatients with major depression and anxiety disorders: transdiagnostic versus diagnosis-specific group cognitive behavioural therapy. Cogn Ther Res, 44, 988–1001. https://doi.org/10.1007/s10608-020-10116-1.

    Article  Google Scholar 

  • Fatt, C. R. C., Cooper, C., Jha, M. K., Aslan, S., Grannemann, B., Kurian, B., Greer, T. L., Fava, M., Weissman, M., McGrath, P. J., et al. (2020). Dorsolateral prefrontal cortex and subcallosal cingulate connectivity show preferential antidepressant response in major depression. Biol Psychiatry. Advance online publication. https://doi.org/10.1016/j.bpsc.2020.06.019.

  • Fisher, A. J. (2015). Toward a dynamic model of psychological assessment: implications for personalized care. J Consult Clin Psychol, 83(4), 825–836. https://doi.org/10.1037/ccp0000026.

    Article  PubMed  Google Scholar 

  • Fisher, A. J., & Bosley, H. G. (2020). Identifying the presence and timing of discrete mood states prior to therapy. Behaviour Research and Therapy, 128, 103596. https://doi.org/10.1016/j.brat.2020.103596.

    Article  PubMed  Google Scholar 

  • Fisher, A. J., & Boswell, J. F. (2016). Enhancing the personalization of psychotherapy with dynamic assessment and modeling. Assessment, 23(4), 496–506. https://doi.org/10.1177/1073191116638735.

    Article  PubMed  Google Scholar 

  • Fisher, A. J., Bosley, H. G., Fernandez, K. C., Reeves, J. W., Soyster, P. D., Diamond, A. E., & Barkin, J. (2019). Open trial of a personalized modular treatment for mood and anxiety. Behav Res Ther, 116, 69–79. https://doi.org/10.1016/j.brat.2019.01.010.

    Article  PubMed  Google Scholar 

  • Flückiger, C., Forrer, L., Schnider, B., Bättig, I., Bodenmann, G., & Zinbarg, R. E. (2016). A single-blinded, randomized clinical trial of how to implement an evidence-based treatment for generalized anxiety disorder [IMPLEMENT]—effects of three different strategies of implementation. EBio Medicine, 3, 163–171. https://doi.org/10.1016/j.ebiom.2015.11.049.

    Article  Google Scholar 

  • Fournier, J. C., DeRubeis, R. J., Shelton, R. C., Gallop, R., Amsterdam, J. D., & Hollon, S. D. (2008). Antidepressant medications v. cognitive therapy in people with depression with or without personality disorder. Br J Psychiatry, 192(2), 124–129. https://doi.org/10.1192/bjp.bp.107.037234.

    Article  PubMed  PubMed Central  Google Scholar 

  • Fournier, J. C., DeRubeis, R. J., Shelton, R. C., Hollon, S. D., Amsterdam, J. D., & Gallop, R. (2009). Prediction of response to medication and cognitive therapy in the treatment of moderate to severe depression. J Consult Clin Psychol, 77(4), 775–787. https://doi.org/10.1037/a0015401.

    Article  PubMed  PubMed Central  Google Scholar 

  • Frank, E., Grochocinski, V. J., Spanier, C. A., Buysse, D. J., Cherry, C. R., Houck, P. R., Stapf, D. M., & Kupfer, D. J. (2000). Interpersonal psychotherapy and antidepressant medication: evaluation of a sequential treatment strategy in women with recurrent major depression. The Journal of clinical psychiatry, 1, 51–57.

    Article  Google Scholar 

  • Fried, E. I., & Nesse, R. M. (2015). Depression is not a consistent syndrome: an investigation of unique symptom patterns in the STAR* D study. J Affect Disord, 172, 96–102. https://doi.org/10.1016/j.jad.2014.10.010.

    Article  PubMed  Google Scholar 

  • Fried, E. I., Coomans, F., & Lorenzo-Luaces, L. (2020). The 341737 ways of qualifying for the melancholic specifier. The Lancet Psychiatry, 7(6), 479–480. https://doi.org/10.1016/S2215-0366(20)30169-3.

    Article  PubMed  Google Scholar 

  • Friedl, N., Berger, T., Krieger, T., Caspar, F., & Grosse Holtforth, M. (2020). Using the personalized advantage index for individual treatment allocation to cognitive behavioral therapy (CBT) or a cbt with integrated exposure and emotion-focused elements (CBT-EE). Psychotherapy Research, 30(6), 763–775. https://doi.org/10.1080/10503307.2019.1664782.

    Article  PubMed  Google Scholar 

  • Gaspersz, R., Lamers, F., Kent, J. M., Beekman, A. T., Smit, J. H., van Hemert, A. M., Schoevers, R. A., & Penninx, B. W. (2017). Anxious distress predicts subsequent treatment outcome and side effects in depressed patients starting antidepressant treatment. Journal of Psychiatric Research, 84, 41–48. https://doi.org/10.1016/j.jpsychires.2016.09.018.

    Article  PubMed  Google Scholar 

  • Germine, L., Nakayama, K., Duchaine, B. C., Chabris, C. F., Chatterjee, G., & Wilmer, J. B. (2012). Is the web as good as the lab? Comparable performance from web and lab in cognitive/perceptual experiments. Psychon Bull Rev, 19(5), 847–857. https://doi.org/10.3758/s13423-012-0296-9.

    Article  PubMed  Google Scholar 

  • Hartshorne, J. K., & Germine, L. T. (2015). When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the life span. Psychol Sci, 26(4), 433–443. https://doi.org/10.1177/0956797614567339.

    Article  PubMed  Google Scholar 

  • Hasin, D. S., Sarvet, A. L., Meyers, J. L., Saha, T. D., Ruan, W. J., Stohl, M., & Grant, B. F. (2018). Epidemiology of adult DSM-5 major depressive disorder and its specifiers in the United States. JAMA Psychiatry, 75(4), 336–346. https://doi.org/10.1001/jamapsychiatry.2017.4602.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hieronymus, F., Hieronymus, M., Nilsson, S., Eriksson, E., & Østergaard, S. D. (2020). Individual variability in treatment response to antidepressants in major depression: comparing trial-level and patient-level analyses. Acta Psychiatr Scand. Accepted Author Manuscript. https://doi.org/10.1111/acps.13205.

  • Hollon, S. D., DeRubeis, R. J., Fawcett, J., Amsterdam, J. D., Shelton, R. C., Zajecka, J., Young, P. R., & Gallop, R. (2014). Effect of cognitive therapy with antidepressant medications vs antidepressants alone on the rate of recovery in major depressive disorder: a randomized clinical trial. JAMA Psychiatry, 71(10), 1157–1164. https://doi.org/10.1001/jamapsychiatry.2014.1054.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hollon, S. D., Cohen, Z. D., Singla, D. R., & Andrews, P. W. (2019). Recent developments in the treatment of depression. Behav Ther, 50(2), 257–269. https://doi.org/10.1016/j.beth.2019.01.002.

    Article  PubMed  Google Scholar 

  • Huibers, M., Cohen, Z. D., Lemmens, L., HJM, L., Arntz, A., Peeters, F., Cuijpers, P., & DeRubeis, R. J. (2015). Predicting optimal outcomes in cognitive therapy or interpersonal psychotherapy for depressed individuals using the personalized advantage index approach. PLoS One, 10(11), e0140771. https://doi.org/10.1371/journal.pone.0140771.

  • Joyce, P. R., McKenzie, J. M., Carter, J. D., Rae, A. M., Luty, S. E., Frampton, C. M., & Mulder, R. T. (2007). Temperament, character and personality disorders as predictors of response to interpersonal psychotherapy and cognitive-behavioural therapy for depression. The British Journal of Psychiatry, 190(6), 503–508. https://doi.org/10.1192/bjp.bp.106.024737.

    Article  PubMed  Google Scholar 

  • Kappelmann, N., Rein, M., Fietz, J., Mayberg, H. S., Craighead, W. E., Dunlop, B. W., Nemeroff, C. B., Keller, M., Klein, D. N., Arnow, B. A., et al. (2020). Psychotherapy or medication for depression? Using individual symptom meta-analyses to derive a symptom-oriented therapy (SOrT) metric for a personalised psychiatry. BMC Med, 18, 170. https://doi.org/10.1186/s12916-020-01623-9.

    Article  PubMed  PubMed Central  Google Scholar 

  • Karyotaki, E., Ebert, D. D., Donkin, L., Riper, H., Twisk, J., Burger, S., Rozental, A., Lange, A., Williams, A. D., Zarski, A. C., et al. (2018). Do guided Internet-based interventions result in clinically relevant changes for patients with depression? An individual participant data meta-analysis. Clin Psychol Rev, 63, 80–92. https://doi.org/10.1016/j.cpr.2018.06.007.

    Article  PubMed  Google Scholar 

  • Kessler, R. C. (2018). The potential of predictive analytics to provide clinical decision support in depression treatment planning. Current Opinion in Psychiatry, 31(1), 32–39. https://doi.org/10.1097/YCO.0000000000000377.

    Article  PubMed  Google Scholar 

  • Kessler, R. C., Van Loo, H., Wardenaar, K., Bossarte, R., Brenner, L., Ebert, D., de Jonge, P., Nierenberg, A., Rosellini, A., Sampson, N., et al. (2017). Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder. Epidemiology and Psychiatric Sciences, 26(1), 22–36. https://doi.org/10.1017/S2045796016000020.

    Article  PubMed  Google Scholar 

  • Kessler, R. C., Bossarte, R. M., Luedtke, A., Zaslavsky, A. M., & Zubizarreta, J. R. (2019). Machine learning methods for developing precision treatment rules with observational data. Behav Res Ther, 120, 103412. https://doi.org/10.1016/j.brat.2019.103412.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kotov, R., Krueger, R. F., Watson, D., Achenbach, T. M., Althoff, R. R., Bagby, R. M., Brown, T. A., Carpenter, W. T., Caspi, A., Clark, L. A., et al. (2017). The hierarchical taxonomy of psychopathology (HiTOP): a dimensional alternative to traditional nosologies. J Abnorm Psychol, 126(4), 454. https://doi.org/10.1037/abn0000258.

    Article  PubMed  Google Scholar 

  • Kraemer, H. C. (2013). Discovering, comparing, and combining moderators of treatment on outcome after randomized clinical trials: a parametric approach. Stat Med, 32(11), 1964–1973. https://doi.org/10.1002/sim.5734.

    Article  PubMed  Google Scholar 

  • Kraemer, H. C., Wilson, G. T., Fairburn, C. G., & Agras, W. S. (2002). Mediators and moderators of treatment effects in randomized clinical trials. Arch Gen Psychiatry, 59(10), 877–883. https://doi.org/10.1001/archpsyc.59.10.877.

    Article  PubMed  Google Scholar 

  • Kriegeskorte, N., Simmons, W. K., Bellgowan, P. S., & Baker, C. I. (2009). Circular analysis in systems neuroscience: the dangers of double dipping. Nat Neurosci, 12(5), 535–540. https://doi.org/10.1038/nn.2303.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lee, Y., Ragguett, R.-M., Mansur, R. B., Boutilier, J. J., Rosenblat, J. D., Trevizol, A., Brietzke, E., Lin, K., Pan, Z., Subramaniapillai, M., et al. (2018). Applications of machine learning algorithms to predict therapeutic outcomes in depression: a meta-analysis and systematic review. J Affect Disord, 241, 519–532. https://doi.org/10.1016/j.jad.2018.08.073.

    Article  PubMed  Google Scholar 

  • Lemmens, L. H., van Bronswijk, S. C., Peeters, F., Arntz, A., Hollon, S. D., & Huibers, M. J. (2019). Long-term outcomes of acute treatment with cognitive therapy v. interpersonal psychotherapy for adult depression: Follow-up of a randomized controlled trial. Psychol Med, 49(3), 465–473. https://doi.org/10.1017/S0033291718001083.

    Article  PubMed  Google Scholar 

  • Leykin, Y., Amsterdam, J. D., DeRubeis, R. J., Gallop, R., Shelton, R. C., & Hollon, S. D. (2007). Progressive resistance to a selective serotonin reuptake inhibitor but not to cognitive therapy in the treatment of major depression. J Consult Clin Psychol, 75(2), 267–276. https://doi.org/10.1037/0022-006X.75.2.267.

    Article  PubMed  Google Scholar 

  • Locher, C., Koechlin, H., Zion, S. R., Werner, C., Pine, D. S., Kirsch, I., Kessler, R. C., & Kossowsky, J. (2017). Efficacy and safety of selective serotonin reuptake inhibitors, serotonin-norepinephrine reuptake inhibitors, and placebo for common psychiatric disorders among children and adolescents: a systematic review and meta-analysis. JAMA Psychiatry, 74(10), 1011–1020. https://doi.org/10.1001/jamapsychiatry.2017.2432.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lopez-Gomez, I., Lorenzo-Luaces, L., Chaves, C., Hervas, G., DeRubeis, R. J., & Vazquez, C. (2019). Predicting optimal interventions for clinical depression: moderators of outcomes in a positive psychological intervention vs. cognitive-behavioral therapy. Gen Hosp Psychiatry, 61, 104–110. https://doi.org/10.1016/j.genhosppsych.2019.07.004.

    Article  PubMed  Google Scholar 

  • Lorenzo-Luaces, L. (2015). Heterogeneity in the prognosis of major depression: from the common cold to a highly debilitating and recurrent illness. Epidemiology and Psychiatric Sciences, 24(6), 466–472. https://doi.org/10.1017/S2045796015000542.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lorenzo-Luaces, L., German, R. E., & DeRubeis, R. J. (2015). It’s complicated: the relation between cognitive change procedures, cognitive change, and symptom change in cognitive therapy for depression. Clin Psychol Rev, 41, 3–15. https://doi.org/10.1016/j.cpr.2014.12.003.

    Article  PubMed  Google Scholar 

  • Lorenzo-Luaces, L., Keefe, J. R., & DeRubeis, R. J. (2016). Cognitive-behavioral therapy: nature and relation to non-cognitive behavioral therapy. Behav Ther, 47(6), 785–803. https://doi.org/10.1016/j.beth.2016.02.012.

    Article  PubMed  Google Scholar 

  • Lorenzo-Luaces, L., DeRubeis, R. J., van Straten, A., & Tiemens, B. (2017). A prognostic index (PI) as a moderator of outcomes in the treatment of depression: a proof of concept combining multiple variables to inform risk-stratified stepped care models. J Affect Disord, 213, 78–85. https://doi.org/10.1016/j.jad.2017.02.010.

    Article  PubMed  Google Scholar 

  • Lorenzo-Luaces, L., Johns, E., & Keefe, J. R. (2018a). The generalizability of randomized controlled trials of self-guided Internet-based cognitive behavioral therapy for depressive symptoms: systematic review and meta-regression analysis. J Med Internet Res, 20(11), e10113. https://doi.org/10.2196/10113.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lorenzo-Luaces, L., Zimmerman, M., & Cuijpers, P. (2018b). Are studies of psychotherapies for depression more or less generalizable than studies of antidepressants? J Affect Disord, 234, 8–13. https://doi.org/10.1016/j.jad.2018.02.066.

    Article  PubMed  Google Scholar 

  • Lorenzo-Luaces, L., Buss, J., & Fried, E. I. (2020a). Do melancholic and atypical specifiers reduce heterogeneity in major depressive disorder?: A secondary analysis of the STAR*D trial. Manuscript submitted for publication. https://doi.org/10.31234/osf.io/ubndc.

  • Lorenzo-Luaces, L., Lemmens, L. H., Keefe, J. R., Cuijpers, P., & Bockting, C. L. (2020b). The efficacy of cognitive behavioral therapy for depression and anxiety: an updated review of meta-analyses (A. Wenzel, Ed.). In A. Wenzel (Ed.), Handbook of cognitive behavioral therapy. Oxford: Oxford University Press.

    Google Scholar 

  • Lorenzo-Luaces, L., Rodriguez-Quintana, N., & Bailey, A. J. (2020c). Double trouble: Do depression severity and duration interact to predicting treatment outcomes in adolescent depression? Behav Res Ther, 131, 103637. https://doi.org/10.1016/j.brat.2020.103637.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lorenzo-Luaces, L., Rodriguez-Quintana, N., Riley, T. N., & Weisz, J. R. (2020d). A placebo prognostic index (PI) as a moderator of outcomes in the treatment of adolescent depression: could it inform risk-stratification in treatment with cognitive-behavioral therapy, fluoxetine, or their combination? Psychotherapy Research. Advance online publication. https://doi.org/10.1080/10503307.2020.1747657.

  • Luedtke, A., Sadikova, E., & Kessler, R. C. (2019). Sample size requirements for multivariate models to predict between-patient differences in best treatments of major depressive disorder. Clinical Psychological Science, 7(3), 445–461. https://doi.org/10.1177/2167702618815466.

    Article  Google Scholar 

  • Lutz, W., Saunders, S. M., Leon, S. C., Martinovich, Z., Kosfelder, J., Schulte, D., Grawe, K., & Tholen, S. (2006). Empirically and clinically useful decision making in psychotherapy: differential predictions with treatment response models. Psychol Assess, 18(2), 133–141. https://doi.org/10.1037/1040-3590.18.2.133.

    Article  PubMed  Google Scholar 

  • Lutz, W., Leon, S. C., Martinovich, Z., Lyons, J. S., & Stiles, W. B. (2007). Therapist effects in outpatient psychotherapy: a three-level growth curve approach. J Couns Psychol, 54(1), 32. https://doi.org/10.1037/0022-0167.54.1.32.

    Article  Google Scholar 

  • McBride, C., Atkinson, L., Quilty, L. C., & Bagby, R. M. (2006). Attachment as moderator of treatment outcome in major depression: a randomized control trial of interpersonal psychotherapy versus cognitive behavior therapy. J Consult Clin Psychol, 74(6), 1041. https://doi.org/10.1037/0022-006X.74.6.1041.

    Article  PubMed  Google Scholar 

  • McGrath, C. L., Kelley, M. E., Holtzheimer, P. E., Dunlop, B. W., Craighead, W. E., Franco, A. R., Craddock, R. C., & Mayberg, H. S. (2013). Toward a neuroimaging treatment selection biomarker for major depressive disorder. JAMA Psychiatry, 70(8), 821–829. https://doi.org/10.1001/jamapsychiatry.2013.143.

    Article  PubMed  PubMed Central  Google Scholar 

  • Meyerson, P., & Tryon, W. W. (2003). Validating Internet research: a test of the psychometric equivalence of Internet and in-person samples. Behav Res Methods Instrum Comput, 35(4), 614–620. https://doi.org/10.3758/BF03195541.

    Article  PubMed  Google Scholar 

  • Monroe, S. M., & Harkness, K. L. (2005). Life stress, the “kindling” hypothesis, and the recurrence of depression: considerations from a life stress perspective. Psychol Rev, 112(2), 417–445. https://doi.org/10.1037/0033-295X.112.2.417.

    Article  PubMed  Google Scholar 

  • Monroe, S. M., & Harkness, K. L. (2011). Recurrence in major depression: a conceptual analysis. Psychol Rev, 118(4), 655–674. https://doi.org/10.1037/a0025190.

    Article  PubMed  Google Scholar 

  • Morin, C. M., et al. (2020). Effectiveness of sequential psychological and medication therapies for insomnia disorder: a randomized clinical trial. JAMA Psychiatry. 77(11), 1107–1115. https://doi.org/10.1001/jamapsychiatry.2020.1767.

  • Munkholm, K., Winkelbeiner, S., & Homan, P. (2020). Individual response to antidepressants for depression in adults-a meta-analysis and simulation study. PLoS One, 15(8), e0237950. https://doi.org/10.1371/journal.pone.0237950.

    Article  PubMed  PubMed Central  Google Scholar 

  • Niles, A. N., Loerinc, A. G., Krull, J. L., Roy-Byrne, P., Sullivan, G., Sherbourne, C. D., Bystritsky, A., & Craske, M. G. (2017a). Advancing personalized medicine: application of a novel statistical method to identify treatment moderators in the coordinated anxiety learning and management study. Behav Ther, 48(4), 490–500. https://doi.org/10.1016/j.beth.2017.02.001.

    Article  PubMed  PubMed Central  Google Scholar 

  • Niles, A. N., Wolitzky-Taylor, K. B., Arch, J. J., & Craske, M. G. (2017b). Applying a novel statistical method to advance the personalized treatment of anxiety disorders: a composite moderator of comparative drop-out from CBT and ACT. Behav Res Ther, 91, 13–23. https://doi.org/10.1016/j.brat.2017.01.001.

    Article  PubMed  Google Scholar 

  • Olbert, C. M., Gala, G. J., & Tupler, L. A. (2014). Quantifying heterogeneity attributable to polythetic diagnostic criteria: theoretical framework and empirical application. J Abnorm Psychol, 123(2), 452–462. https://doi.org/10.1037/a0036068.

    Article  PubMed  Google Scholar 

  • Otero, P., Smit, F., Cuijpers, P., DeRubeis, R. J., & Torres, A´., & Va’zquez, F. L. (2015). Differential response to depression prevention among a sample of informal caregivers: moderator analysis of longer-term follow-up trial data. Psychiatry Res, 230(2), 271–278. https://doi.org/10.1016/j.psychres.2015.09.005.

    Article  PubMed  Google Scholar 

  • Pae, C.-U., Vöhringer, P. A., Holtzman, N. S., Thommi, S. B., Patkar, A., Gilmer, W., & Ghaemi, S. N. (2012). Mixed depression: a study of its phenomenology and relation to treatment response. Journal of Affective Disorders, 136(3), 1059–1061. https://doi.org/10.1016/j.jad.2011.11.024.

    Article  PubMed  Google Scholar 

  • Patel, V., Chisholm, D., Parikh, R., Charlson, F. J., Degenhardt, L., Dua, T., Ferrari, A. J., Hyman, S., Laxminarayan, R., Levin, C., et al. (2016). Addressing the burden of mental, neurological, and substance use disorders: key messages from disease control priorities. The Lancet, 387(10028), 1672–1685. https://doi.org/10.1016/S0140-6736(15)00390-6.

    Article  Google Scholar 

  • Perez, J., Russo, D. A., Stochl, J., Clarke, J., Martin, Z., Jassi, C., French, P., Fowler, D., & Jones, P. B. (2018). Common mental disorder including psychotic experiences: trailblazing a new recovery pathway within the improving access to psychological therapies programme in England. Early Intervention in Psychiatry, 12(3), 497–504. https://doi.org/10.1111/eip.12434.

    Article  PubMed  Google Scholar 

  • Petkova, E., Park, H., Ciarleglio, A., Ogden, R. T., & Tarpey, T. (2020). Optimising treatment decision rules through generated effect modifiers: a precision medicine tutorial. BJPsych Open, 6(1), E2. https://doi.org/10.1192/bjo.2019.85.

    Article  Google Scholar 

  • Pew Research Center: Internet & Technology. (2019). Social media fact sheet. Retrieved September 8, 2020, from https://www.pewresearch.org/internet/fact-sheet/social-media/.

  • Plöderl, M., & Hengartner, M. P. (2019). What are the chances for personalised treatment with antidepressants? Detection of patient-by-treatment interaction with a variance ratio meta-analysis. BMJ open, 9, e034816. https://doi.org/10.1136/bmjopen-2019-034816.

  • Polo, A. J., Makol, B. A., Castro, A. S., Col’on-Quintana, N., Wagstaff, A. E., & Guo, S. (2019). Diversity in randomized clinical trials of depression: a 36-year review. Clin Psychol Rev, 67, 22–35. https://doi.org/10.1016/j.cpr.2018.09.004.

  • Project MATCH Research Group. (1998). Matching alcoholism treatments to client heterogeneity: project MATCH three-year drinking outcomes. Alcohol Clin Exp Res, 22(6), 1300–1311. https://doi.org/10.1111/j.1530-0277.1998.tb03912.x.

  • Rekkas, A., Paulus, J. K., Raman, G., Wong, J. B., Steyerberg, E. W., Rijnbeek, P. R., Kent, D. M., & van Klaveren, D. (2020). Predictive approaches to heterogeneous treatment effects: a scoping review. BMC Med Res Methodol 20, 264. https://doi.org/10.1186/s12874-020-01145-1.

  • Rubel, J. A., Fisher, A. J., Husen, K., & Lutz, W. (2018). Translating person-specific network models into personalized treatments: development and demonstration of the dynamic assessment treatment algorithm for individual networks (DATA-IN). Psychother Psychosom, 87(4), 249–251. https://doi.org/10.1159/000487769.

    Article  PubMed  Google Scholar 

  • Rush, A. J., Trivedi, M. H., Wisniewski, S. R., Nierenberg, A. A., Stewart, J. W., Warden, D., Niederehe, G., Thase, M. E., Lavori, P. W., Lebowitz, B. D., et al. (2006). Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: A STAR*D report. Am J Psychiatr, 163(11), 1905–1917.

    Article  PubMed  Google Scholar 

  • Sasso, K. E., Strunk, D. R., Braun, J. D., DeRubeis, R. J., & Brotman, M. A. (2015). Identifying moderators of the adherence-outcome relation in cognitive therapy for depression. J Consult Clin Psychol, 83(5), 976–984. https://doi.org/10.1037/ccp0000045.

    Article  PubMed  PubMed Central  Google Scholar 

  • Saxon, D., & Barkham, M. (2012). Patterns of therapist variability: therapist effects and the contribution of patient severity and risk. J Consult Clin Psychol, 80(4), 535–546. https://doi.org/10.1037/a0028898.

    Article  PubMed  Google Scholar 

  • Schwartz, B., Cohen, Z. D., Rubel, J. A., Zimmermann, D., Wittmann, W. W., & Lutz, W. (2020). Personalized treatment selection in routine care: integrating machine learning and statistical algorithms to recommend cognitive behavioral or psychodynamic therapy. Psychotherapy Research https://doi.org/10.1080/10503307.2020.1769219.

  • Serbanescu, I., Walter, H., Schnell, K., Kessler, H., Weber, B., Drost, S., Groß, M., Neudeck, P., Klein, J. P., Assmann, N., Zobel, I., Backenstrass, M., Hautzinger, M., Meister, R., & H¨arter, M., Schramm, E., & Schoepf, D. (2020). Combining baseline characteristics to disentangle response differences to disorder-specific versus supportive psychotherapy in patients with persistent depressive disorder. Behav Res Ther, 124, 103512. https://doi.org/10.1016/j.brat.2019.103512.

    Article  PubMed  Google Scholar 

  • ten Thij, M., van de Leemput, I., Bathina, K., Rutter, L., Lorenzo-Luaces, L., Scheffer, M., & Bollen, J. (2020). Depression alters circadian pattern of online activity. Sci Rep, 10, 17272. https://doi.org/10.1038/s41598-020-74314-3.

  • Thase, M. E. (2014). Using biomarkers to predict treatment response in major depressive disorder: evidence from past and present studies. Dialogues Clin Neurosci, 16(4), 539.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ungvari, G. S., Kau, L. S., Wai-Kw, T., & Shing, N. F. (2001). The pharmacological treatment of catatonia: an overview. Eur Arch Psychiatry Clin Neurosci, 251(1), I31–I34. https://doi.org/10.1007/PL00014198.

  • van Bronswijk, S. C., DeRubeis, R. J., Lemmens, L. H., Peeters, F. P., Keefe, J. R., Cohen, Z. D., & Huibers, M. J. (2019). Precision medicine for long-term depression outcomes using the personalized advantage index approach: cognitive therapy or interpersonal psychotherapy? Psychological medicine. https://doi.org/10.1017/S0033291719003192.

  • van Bronswijk, S. C., Sanne J E Bruijniks, Lorenzo-Luaces, L., DeRubeis, R. J., Lemmens, L. H. J. M., Peeters, F. P., & Huibers, M. J. (2020). Cross-trial prediction in psychotherapy: external validation of the Personalized Advantage Index using machine learning in two Dutch randomized trials comparing CBT versus IPT for depression. Manuscript submitted for publication.

    Google Scholar 

  • Van der Lem, R., De Wever, W. W., Van der Wee, N. J., Van Veen, T., Cuijpers, P., & Zitman, F. G. (2012). The generalizability of psychotherapy efficacy trials in major depressive disorder: an analysis of the influence of patient selection in efficacy trials on symptom outcome in daily practice. BMC Psychiatry, 12, 192. https://doi.org/10.1186/1471-244X-12-192.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wallace, M. L., Frank, E., & Kraemer, H. C. (2013). A novel approach for developing and interpreting treatment moderator profiles in randomized clinical trials. JAMA Psychiatry, 70(11), 1241–1247. https://doi.org/10.1001/jamapsychiatry.2013.1960.

    Article  PubMed  Google Scholar 

  • Webb, C. A., Cohen, Z. D., Beard, C., Forgeard, M., Peckham, A. D., & Björgvinsson, T. (2020). Personalized prognostic prediction of treatment outcome for depressed patients in a naturalistic psychiatric hospital setting: a comparison of machine learning approaches. Journal of Consulting and Clinical Psychology, 88(1), 25–38. https://doi.org/10.1037/ccp0000451.

    Article  PubMed  PubMed Central  Google Scholar 

  • Weitz, E. S., Hollon, S. D., Twisk, J., Van Straten, A., Huibers, M. J., David, D., DeRubeis, R. J., Dimidjian, S., Dunlop, B. W., Cristea, I. A., et al. (2015). Baseline depression severity as moderator of depression outcomes between cognitive behavioral therapy vs pharmacotherapy: an individual patient data meta-analysis. JAMA Psychiatry, 72(11), 1102–1109. https://doi.org/10.1001/jamapsychiatry.2015.1516.

    Article  PubMed  Google Scholar 

  • Westen, D., Novotny, C. M., & Thompson-Brenner, H. (2004). The empirical status of empirically supported psychotherapies: assumptions, findings, and reporting in controlled clinical trials. Psychol Bull, 130(4), 631. https://doi.org/10.1037/0033-2909.130.4.631.

    Article  PubMed  Google Scholar 

  • Whiteford, H. A., Degenhardt, L., Rehm, J., Baxter, A. J., Ferrari, A. J., Erskine, H. E., Charlson, F. J., Norman, R. E., Flaxman, A. D., Johns, N., et al. (2013). Global burden of disease attributable to mental and substance use disorders: findings from the global burden of disease study 2010. Lancet, 382(9904), 1575–1586. https://doi.org/10.1016/S0140-6736(13)61611-6.

    Article  PubMed  Google Scholar 

  • Windle, E., Tee, H., Sabitova, A., Jovanovic, N., Priebe, S., & Carr, C. (2020). Association of patient treatment preference with dropout and clinical outcomes in adult psychosocial mental health interventions: a systematic review and meta-analysis. JAMA Psychiatry, 77(3), 294–302. https://doi.org/10.1001/jamapsychiatry.2019.3750.

    Article  PubMed  Google Scholar 

  • Zimmerman, M., Ellison, W., Young, D., Chelminski, I., & Dalrymple, K. (2015). How many different ways do patients meet the diagnostic criteria for major depressive disorder? Compr Psychiatry, 56, 29–34. https://doi.org/10.1016/j.comppsych.2014.09.007.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA

    Lorenzo Lorenzo-Luaces, Allison Peipert, Robinson De Jesús Romero & Lauren A. Rutter

  2. Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA

    Natalie Rodriguez-Quintana

Authors
  1. Lorenzo Lorenzo-Luaces
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Allison Peipert
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Robinson De Jesús Romero
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lauren A. Rutter
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Natalie Rodriguez-Quintana
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lorenzo Lorenzo-Luaces.

Ethics declarations

Conflict of Interest

Prof. Lorenzo-Luaces has authored and co-authored articles that have attempted to develop precision treatment rules from depression studies (e.g., DeRubeis et al. 2014b; Lopez-Gomez et al. 2019; Lorenzo-Luaces et al. 2017, 2020d). He has also been a consultant for Happify, Inc., who had no role in the writing of the current manuscript. The other authors report no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lorenzo-Luaces, L., Peipert, A., De Jesús Romero, R. et al. Personalized Medicine and Cognitive Behavioral Therapies for Depression: Small Effects, Big Problems, and Bigger Data. J Cogn Ther 14, 59–85 (2021). https://doi.org/10.1007/s41811-020-00094-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41811-020-00094-3

Keywords

Search

Navigation