Skip to main content Accessibility help

Precision medicine for long-term depression outcomes using the Personalized Advantage Index approach: cognitive therapy or interpersonal psychotherapy?

Published online by Cambridge University Press:  22 November 2019

Suzanne C. van Bronswijk
Department of Clinical Psychological Science, Maastricht University, Maastricht, The Netherlands
Robert J. DeRubeis
Department of Psychology, University of Pennsylvania, Philadelphia, USA
Lotte H. J. M. Lemmens
Department of Clinical Psychological Science, Maastricht University, Maastricht, The Netherlands
Frenk P. M. L. Peeters
Department of Clinical Psychological Science, Maastricht University, Maastricht, The Netherlands
John R. Keefe
Department of Psychiatry, Weill Cornell Medical College, New York, USA
Zachary D. Cohen
Department of Psychiatry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
Marcus J. H. Huibers
Department of Psychology, University of Pennsylvania, Philadelphia, USA Department of Clinical Psychology, VU University Amsterdam, Amsterdam, The Netherlands



Psychotherapies for depression are equally effective on average, but individual responses vary widely. Outcomes can be improved by optimizing treatment selection using multivariate prediction models. A promising approach is the Personalized Advantage Index (PAI) that predicts the optimal treatment for a given individual and the magnitude of the advantage. The current study aimed to extend the PAI to long-term depression outcomes after acute-phase psychotherapy.


Data come from a randomized trial comparing cognitive therapy (CT, n = 76) and interpersonal psychotherapy (IPT, n = 75) for major depressive disorder (MDD). Primary outcome was depression severity, as assessed by the BDI-II, during 17-month follow-up. First, predictors and moderators were selected from 38 pre-treatment variables using a two-step machine learning approach. Second, predictors and moderators were combined into a final model, from which PAI predictions were computed with cross-validation. Long-term PAI predictions were then compared to actual follow-up outcomes and post-treatment PAI predictions.


One predictor (parental alcohol abuse) and two moderators (recent life events; childhood maltreatment) were identified. Individuals assigned to their PAI-indicated treatment had lower follow-up depression severity compared to those assigned to their PAI-non-indicated treatment. This difference was significant in two subsets of the overall sample: those whose PAI score was in the upper 60%, and those whose PAI indicated CT, irrespective of magnitude. Long-term predictions did not overlap substantially with predictions for acute benefit.


If replicated, long-term PAI predictions could enhance precision medicine by selecting the optimal treatment for a given depressed individual over the long term.

Original Articles
Copyright © Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below.


Anda, RF, Whitfield, CL, Felitti, VJ, Chapman, D, Edwards, VJ, Dube, SR and Williamson, DF (2002) Adverse childhood experiences, alcoholic parents, and later risk of alcoholism and depression. Psychiatric Services 53, 10011009.CrossRefGoogle ScholarPubMed
Asarnow, JR, Emslie, G, Clarke, G, Wagner, KD, Spirito, A, Vitiello, B, Iyengar, S, Shamseddeen, W, Ritz, L and Birmaher, B (2009) Treatment of selective serotonin reuptake inhibitor – resistant depression in adolescents: predictors and moderators of treatment response. Journal of the American Academy of Child & Adolescent Psychiatry 48, 330339.Google Scholar
Austin, PC and Tu, JV (2004) Bootstrap methods for developing predictive models. The American Statistician 58, 131137.CrossRefGoogle Scholar
Barbe, RP, Bridge, JA, Birmaher, B, Kolko, DJ and Brent, DA (2004) Lifetime history of sexual abuse, clinical presentation, and outcome in a clinical trial for adolescent depression. The Journal of Clinical Psychiatry 65, 7783.CrossRefGoogle Scholar
Barber, JP and Muenz, LR (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. Journal of Consulting and Clinical Psychology 64, 951958.CrossRefGoogle ScholarPubMed
Beck, AT and Steer, RA (1988) Manual for the Beck Hopelessness Scale. San Antonio: Psychological Corporation.Google Scholar
Beck, A, Rush, A, Shaw, B and Emery, G (1979) Cognitive Therapy of Depression. New York: Guilford Press Google Scholar.Google Scholar
Beck, AT, Steer, R and Brown, GK (1996) Beck Depression Inventory II: Manual. Boston: Harcourt Brace.Google Scholar
Bulmash, E, Harkness, KL, Stewart, JG and Bagby, RM (2009) Personality, stressful life events, and treatment response in major depression. Journal of Consulting and Clinical Psychology 77, 1067.CrossRefGoogle ScholarPubMed
Carter, JD, Luty, SE, McKenzie, JM, Mulder, RT, Frampton, CM and Joyce, PR (2011) Patient predictors of response to cognitive behaviour therapy and interpersonal psychotherapy in a randomised clinical trial for depression. Journal of Affective Disorders 128, 252261.CrossRefGoogle Scholar
Cohen, ZD and DeRubeis, RJ (2018) Treatment selection in depression. Annual Review of Clinical Psychology 14, 209236.CrossRefGoogle ScholarPubMed
Cohen, L, Van den Bout, J, Kramer, W and Van Vliet, T (1986) A Dutch attributional style questionnaire: psychometric properties and findings of some Dutch-American differences. Cognitive Therapy and Research 10, 665669.CrossRefGoogle Scholar
Cuijpers, P, Langendoen, Y and Bijl, RV (1999) Psychiatric disorders in adult children of problem drinkers: prevalence, first onset and comparison with other risk factors. Addiction 94, 14891498.CrossRefGoogle ScholarPubMed
Cuijpers, P, Andersson, G, Donker, T and van Straten, A (2011) Psychological treatment of depression: results of a series of meta-analyses. Nordic Journal of Psychiatry 65, 354364.CrossRefGoogle ScholarPubMed
de Graaf, LE, Roelofs, J and Huibers, MJ (2009) Measuring dysfunctional attitudes in the general population: the dysfunctional attitude scale (form A) revised. Cognitive Therapy and Research 33, 345355.CrossRefGoogle Scholar
Deisenhofer, AK, Delgadillo, J, Rubel, JA, Böhnke, JR, Zimmermann, D, Schwartz, B and Lutz, W (2018) Individual treatment selection for patients with posttraumatic stress disorder. Depression and Anxiety 35, 541550.CrossRefGoogle ScholarPubMed
Derogatis, LR and Melisaratos, N (1983) The brief symptom inventory: an introductory report. Psychological Medicine 13, 595605.CrossRefGoogle Scholar
DeRubeis, RJ, Cohen, ZD, Forand, NR, Fournier, JC, Gelfand, LA and Lorenzo-Luaces, L (2014) The Personalized Advantage Index: translating research on prediction into individualized treatment recommendations. A demonstration. PLoS ONE 9, e83875.CrossRefGoogle ScholarPubMed
Fiedler, K (2011) Voodoo correlations are everywhere – not only in neuroscience. Perspectives on Psychological Science 6, 163171.CrossRefGoogle Scholar
First, M, Spitzer, R, Gibbon, M and Williams, J (1995) Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I). New York: Biometrics Research Department, New York State Psychiatric Institute.Google Scholar
First, MB, Gibbon, M, Spitzer, RL, Williams, JBW and Benjamin, LS (1997) Structured Clinical Interview for DSM-IV Axis II Personality Disorders (SCID-II). Washington, DC: American Psychiatric Press.Google Scholar
Fournier, JC, DeRubeis, RJ, Shelton, RC, Hollon, SD, Amsterdam, JD and Gallop, R (2009) Prediction of response to medication and cognitive therapy in the treatment of moderate to severe depression. Journal of Consulting and Clinical Psychology 77, 775787.CrossRefGoogle ScholarPubMed
Garge, NR, Bobashev, G and Eggleston, B (2013) Random forest methodology for model-based recursive partitioning: the mobForest package for R. BMC bioinformatics 14, 125.CrossRefGoogle ScholarPubMed
Harkness, KL, Bagby, RM and Kennedy, SH (2012) Childhood maltreatment and differential treatment response and recurrence in adult major depressive disorder. Journal of Consulting and Clinical Psychology 80, 342.CrossRefGoogle ScholarPubMed
Hiroe, T, Kojima, M, Yamamoto, I, Nojima, S, Kinoshita, Y, Hashimoto, N, Watanabe, N, Maeda, T and Furukawa, TA (2005) Gradations of clinical severity and sensitivity to change assessed with the Beck Depression Inventory-II in Japanese patients with depression. Psychiatry Research 135, 229235.CrossRefGoogle ScholarPubMed
Horowitz, LM, Rosenberg, SE, Baer, BA, Ureno, G and Villasenor, VS (1988) Inventory of interpersonal problems: psychometric properties and clinical applications. Journal of Consulting and Clinical Psychology 56, 885892.CrossRefGoogle ScholarPubMed
Huibers, MJ, Cohen, ZD, Lemmens, LH, Arntz, A, Peeters, FP, Cuijpers, P and DeRubeis, RJ (2015) Predicting optimal outcomes in cognitive therapy or interpersonal psychotherapy for depressed individuals using the personalized advantage index approach. PLoS ONE 10, e0140771.CrossRefGoogle ScholarPubMed
Jakobsen, JC, Hansen, JL, Simonsen, S, Simonsen, E and Gluud, C (2012) Effects of cognitive therapy v. interpersonal psychotherapy in patients with major depressive disorder: a systematic review of randomized clinical trials with meta-analyses and trial sequential analyses. Psychological Medicine 42, 13431357.CrossRefGoogle Scholar
Johnson, PO and Neyman, J (1936) Tests of certain linear hypotheses and their application to some educational problems. Statistical Research Memoirs 1, 5793.Google Scholar
Joyce, PR, McKenzie, JM, Carter, JD, Rae, AM, Luty, SE, Frampton, CM and Mulder, RT (2007) Temperament, character and personality disorders as predictors of response to interpersonal psychotherapy and cognitive-behavioural therapy for depression. British Journal of Psychiatry 190, 503508.CrossRefGoogle Scholar
Katsnelson, A (2013) Momentum grows to make ‘personalized' medicine more ‘precise’. Nature Medicine 19, p. 249.Google Scholar
Keefe, JR, Wiltsey Stirman, S, Cohen, ZD, DeRubeis, RJ, Smith, BN and Resick, PA (2018). In rape trauma PTSD, patient characteristics indicate which trauma-focused treatment they are most likely to complete. Depression and Anxiety 35, 330338.CrossRefGoogle ScholarPubMed
Kelley, ML, Braitman, A, Henson, JM, Schroeder, V, Ladage, J and Gumienny, L (2010) Relationships among depressive mood symptoms and parent and peer relations in collegiate children of alcoholics. American Journal of Orthopsychiatry 80, 204212.CrossRefGoogle ScholarPubMed
Kessler, RC (2018) The potential of predictive analytics to provide clinical decision support in depression treatment planning. Current Opinion in Psychiatry 31, 3239.CrossRefGoogle ScholarPubMed
Kim, TT, Dufour, S, Xu, C, Cohen, ZD, Sylvia, L, Deckersbach, T, DeRubeis, RJ and Nierenberg, AA (2019) Predictive modeling for response to lithium and quetiapine in bipolar disorder. Bipolar Disorders 21, 428436.CrossRefGoogle ScholarPubMed
Klerman, GL, Weissman, MM, Rounsaville, BJ and Chevron, ES (1984) Interpersonal Psychotherapy for Depression. New York: Basis Books.Google Scholar
Klostermann, K, Chen, R, Kelley, ML, Schroeder, VM, Braitman, AL and Mignone, T (2011) Coping behavior and depressive symptoms in adult children of alcoholics. Substance Use & Misuse 46, 11621168.CrossRefGoogle ScholarPubMed
Kraemer, HC (2013) Discovering, comparing, and combining moderators of treatment on outcome after randomized clinical trials: a parametric approach. Statistics in Medicine 32, 19641973.CrossRefGoogle ScholarPubMed
Lemmens, L, Arntz, A, Peeters, F, Hollon, S, Roefs, A and Huibers, M (2015) Clinical effectiveness of cognitive therapy v. Interpersonal psychotherapy for depression: results of a randomized controlled trial. Psychological Medicine 45, 20952110.CrossRefGoogle ScholarPubMed
Lemmens, LH, van Bronswijk, SC, Peeters, F, Arntz, A, Hollon, SD and Huibers, MJ (2019) Long-term outcomes of acute treatment with cognitive therapy v. interpersonal psychotherapy for adult depression: follow-up of a randomized controlled trial. Psychological Medicine 49, 465473.CrossRefGoogle ScholarPubMed
Lewis, CC, Simons, AD, Nguyen, LJ, Murakami, JL, Reid, MW, Silva, SG and March, JS (2010) Impact of childhood trauma on treatment outcome in the Treatment for Adolescents with Depression Study (TADS). Journal of the American Academy of Child & Adolescent Psychiatry 49, 132140.Google Scholar
Lorenzo-Luaces, L, DeRubeis, RJ, van Straten, A and 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. Journal of Affective Disorders 213, 7885.CrossRefGoogle ScholarPubMed
Luedtke, A, Sadikova, E and Kessler, RC (2019) Sample size requirements for multivariate models to predict between-patient differences in best treatments of major depressive disorder. Clinical Psychological Science 7, 445461.CrossRefGoogle Scholar
Luty, SE, Carter, JD, McKenzie, JM, Rae, AM, Frampton, CM, Mulder, RT and Joyce, PR (2007) Randomised controlled trial of interpersonal psychotherapy and cognitive–behavioural therapy for depression. The British Journal of Psychiatry 190, 496502.CrossRefGoogle Scholar
Lutz, W, Saunders, SM, Leon, SC, Martinovich, Z, Kosfelder, J, Schulte, D, Grawe, K and Tholen, S (2006) Empirically and clinically useful decision making in psychotherapy: differential predictions with treatment response models. Psychological Assessment 18, 133.CrossRefGoogle ScholarPubMed
Lutz, W, Zimmermann, D, Müller, VN, Deisenhofer, A-K and Rubel, JA (2017) Randomized controlled trial to evaluate the effects of personalized prediction and adaptation tools on treatment outcome in outpatient psychotherapy: study protocol. BMC Psychiatry 17, 306.CrossRefGoogle ScholarPubMed
Mulder, R, Boden, J, Carter, J, Luty, S and Joyce, P (2017) Ten month outcome of cognitive behavioural therapy v. interpersonal psychotherapy in patients with major depression: a randomised trial of acute and maintenance psychotherapy. Psychological Medicine 47, 25402547.CrossRefGoogle ScholarPubMed
Mundt, JC, Marks, IM, Shear, MK and Greist, JH (2002) The work and social adjustment scale: a simple measure of impairment in functioning. British Journal of Psychiatry 180, 461464.CrossRefGoogle ScholarPubMed
Nemeroff, CB, Heim, CM, Thase, ME, Klein, DN, Rush, AJ, Schatzberg, AF, Ninan, PT, McCullough, JP, Weiss, PM and Dunner, DL (2003) Differential responses to psychotherapy v. pharmacotherapy in patients with chronic forms of major depression and childhood trauma. Proceedings of the National Academy of Sciences 100, 1429314296.CrossRefGoogle Scholar
Niles, AN, Loerinc, AG, Krull, JL, Roy-Byrne, P, Sullivan, G, Sherbourne, CD, Bystritsky, A and Craske, MG (2017 a) Advancing personalized medicine: application of a novel statistical method to identify treatment moderators in the coordinated anxiety learning and management study. Behavior Therapy 48, 490500.CrossRefGoogle ScholarPubMed
Niles, AN, Wolitzky-Taylor, KB, Arch, JJ and Craske, MG (2017 b) Applying a novel statistical method to advance the personalized treatment of anxiety disorders: a composite moderator of comparative drop-out from CBT and ACT. Behaviour Research and Therapy 91, 1323.CrossRefGoogle Scholar
Peterson, C, Semmel, A, Von Baeyer, C, Abramson, LY, Metalsky, GI and Seligman, ME (1982) The attributional style questionnaire. Cognitive Therapy and Research 6, 287299.CrossRefGoogle Scholar
Picard, RR and Cook, RD (1984) Cross-validation of regression models. Journal of the American Statistical Association 79, 575583.CrossRefGoogle Scholar
Raes, F, Hermans, D and Eelen, P (2003) Kort instrumenteel De Nederlandstalige versie van de Ruminative Response Scale (RRS-NL) en de Rumination on Sadness Scale (RSS-NL). Gedragstherapie. 36, 97104Google Scholar
Rizopoulos, D and Rizopoulos, MD (2009). Package ‘bootStepAIC’. [computer software].Google Scholar
Rush, AJ, Trivedi, MH, Wisniewski, SR, Nierenberg, AA, Stewart, JW, Warden, D, Niederehe, G, Thase, ME, Lavori, PW and Lebowitz, BD (2006) Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR* D report. American Journal of Psychiatry 163, 19051917.CrossRefGoogle ScholarPubMed
Ryder, AG, Quilty, LC, Vachon, DD and Bagby, RM (2010) Depressive personality and treatment outcome in major depressive disorder. Journal of Personality Disorders 24, 392404.CrossRefGoogle ScholarPubMed
Simon, GE and Perlis, RH (2010) Personalized medicine for depression: can we match patients with treatments? American Journal of Psychiatry 167, 14451455.CrossRefGoogle ScholarPubMed
Smagula, SF, Wallace, ML, Anderson, SJ, Karp, JF, Lenze, EJ, Mulsant, BH, Butters, MA, Blumberger, DM, Diniz, BS and Lotrich, FE (2016) Combining moderators to identify clinical profiles of patients who will, and will not, benefit from aripiprazole augmentation for treatment resistant late-life major depressive disorder. Journal of Psychiatric Research 81, 112118.CrossRefGoogle ScholarPubMed
Sotsky, SM, Glass, DR, Shea, MT, Pilkonis, PA, Collins, JF, Elkin, I, Watkins, JT, Imber, SD, Leber, WR, Moyer, J and Oliveri, ME (1991) Patients predictors of response to psychotherapy and pharmacotherapy: findings in the NIMH treatment of depression collaborative research program. American Journal of Psychiatry 148, 9971008.Google ScholarPubMed
Stekhoven, DJ and Bühlmann, P (2012) Missforest – non-parametric missing value imputation for mixed-type data. Bioinformatics (Oxford, England) 28, 112118.CrossRefGoogle ScholarPubMed
Strobl, C, Boulesteix, A-L, Kneib, T, Augustin, T and Zeileis, A (2008) Conditional variable importance for random forests. BMC Bioinformatics 9, 307.CrossRefGoogle ScholarPubMed
Tafarodi, RW and Swann, WB (2001) Two-dimensional self-esteem: theory and measurement. Personality and Individual Differences 31, 653673.CrossRefGoogle Scholar
Vandromme, H, Hermans, D, Spruyt, A and Eelen, P (2007) Dutch translation of the Self-Liking/Self-Competence Scale–Revised: a confirmatory factor analysis of the two-factor structure. Personality and Individual Differences 42, 157167.CrossRefGoogle Scholar
Vittengl, JR, Clark, LA, Thase, ME and Jarrett, RB (2017) Initial steps to inform selection of continuation cognitive therapy or fluoxetine for higher risk responders to cognitive therapy for recurrent major depressive disorder. Psychiatry Research 253, 174181.CrossRefGoogle ScholarPubMed
Vul, E, Harris, C, Winkielman, P and Pashler, H (2009) Puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition. Perspectives on Psychological Science 4, 274290.CrossRefGoogle ScholarPubMed
Waljee, AK, Mukherjee, A, Singal, AG, Zhang, Y, Warren, J, Balis, U, Marrero, J, Zhu, J and Higgins, PD (2013) Comparison of imputation methods for missing laboratory data in medicine. BMJ Open 3, e002847.CrossRefGoogle Scholar
Wallace, ML, Frank, E and Kraemer, HC (2013) A novel approach for developing and interpreting treatment moderator profiles in randomized clinical trials. JAMA Psychiatry 70, 12411247.CrossRefGoogle ScholarPubMed
Webb, CA, Trivedi, MH, Cohen, ZD, Dillon, DG, Fournier, JC, Goer, F, Fava, M, McGrath, PJ, Weissman, M and Parsey, R (2019) Personalized prediction of antidepressant v. placebo response: evidence from the EMBARC study. Psychological Medicine 49, 11181127.CrossRefGoogle ScholarPubMed
Weissman, AN and Beck, AT (1978) Development and validation of the Dysfunctional Attitude Scale: paper presented at the annual meeting of the Association for the Advancement of Behavior Therapy.Google Scholar
Zilcha-Mano, S, Keefe, JR, Chui, H, Rubin, A, Barrett, MS and Barber, JP (2016) Reducing dropout in treatment for depression: translating dropout predictors into individualized treatment recommendations. The Journal of Clinical Psychiatry 77, e1584e1590.CrossRefGoogle ScholarPubMed

van Bronswijk et al. supplementary material

van Bronswijk et al. supplementary material 1

File 21 KB

Altmetric attention score

Full text views

Full text views reflects PDF downloads, PDFs sent to Google Drive, Dropbox and Kindle and HTML full text views.

Total number of HTML views: 63
Total number of PDF views: 195 *
View data table for this chart

* Views captured on Cambridge Core between 22nd November 2019 - 26th January 2021. This data will be updated every 24 hours.

Hostname: page-component-898fc554b-t4g97 Total loading time: 0.514 Render date: 2021-01-26T06:44:50.339Z Query parameters: { "hasAccess": "0", "openAccess": "0", "isLogged": "0", "lang": "en" } Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": false, "newCiteModal": false }

Send article to Kindle

To send this article to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the or variations. ‘’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Precision medicine for long-term depression outcomes using the Personalized Advantage Index approach: cognitive therapy or interpersonal psychotherapy?
Available formats

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Precision medicine for long-term depression outcomes using the Personalized Advantage Index approach: cognitive therapy or interpersonal psychotherapy?
Available formats

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Precision medicine for long-term depression outcomes using the Personalized Advantage Index approach: cognitive therapy or interpersonal psychotherapy?
Available formats

Reply to: Submit a response

Your details

Conflicting interests

Do you have any conflicting interests? *