Subproject 1
Single-case prediction of treatment (non-) response to cognitive-behavioral therapy (CBT) in the outpatient sector: a prospective-longitudinal observational study
Although cognitive-behavioral therapy (CBT) is a first-line treatment for internalizing disorders, a substantial proportion of patients fails to benefit - with severe consequences for patients and increasing costs for societies. The paucity of standard clinical features that allow for single-case predictions, limited methodological approaches, and fragmented data levels serve as an impetus to implement state-of-the-art predictive analytics to search for the best predictors of (non-) response. The present project (SP1, TIKI study) aims to set up a prospective-longitudinal observational cohort of n = 500 patients with mental disorders from the internalizing spectrum (specific phobia, social anxiety disorder, panic disorder, agoraphobia, generalized anxiety disorder, obsessive-compulsive disorder, post-traumatic stress disorder, unipolar depressive disorders) who are treated with CBT. Embedded within the Research Unit, patients will be deeply phenotyped for several layers of bio-behavioral markers (SP3-SP6). It will be supported by our clinical (SP1), methods (SP2), and neuroimaging platform (SP3). As such, SP1 contains both a research and a service component. Research-wise, we will test the hypothesis if treatment (non-)response can be predicted with sufficient accuracy based on clinical routine data when state-of-the-art machine learning methods are applied. Service-wise, SP1 will coordinate the clinical trial by serving as a recruitment hub for the other Subprojects, implementing diagnostic assessments, documenting and quality-controlling treatment contents, and calculating primary and secondary outcomes. As an observational trial in the academic outpatient sector, the study design exerts a high degree of external validity as a prerequisite for translating predictive analytics into practice. No randomization applies - all patients receive active treatment. In line with the idea of precision medicine, our overall aim is to enable the prediction of treatment outcomes prior to therapy onset for the early identification and optimized treatment of patients at risk for non-response towards standard treatment.
People
Publications
Meinke, C., Lueken, U., Walter, H., & Hilbert, K. (2024). Predicting treatment outcome based on resting-state functional connectivity in internalizing mental disorders: A systematic review and meta-analysis. Neuroscience & Biobehavioral Reviews, 160, 105640. https://doi.org/10.1016/j.neubiorev.2024.105640
Langhammer, T., Unterfeld, C., Blankenburg, F., Erk, S., Fehm, L., Haynes, J.-D., Heinzel, S., Hilbert, K., Jacobi, F., Kathmann, N., Knaevelsrud, C., Renneberg, B., Ritter, K., Stenzel, N., Walter, H., & Lueken, U. (2024, June 26). Towards precision psychotherapy for non-respondent patients: Design and methods of a naturalistic observational CBT-trial for single-case prediction with machine learning [Poster presentation]. Annual SPR Meeting, Ottawa, Canada.
Langhammer, T., Blankenburg, F., Erk, S., Fehm, L., Haynes, J.-D., Heinzel, S., Hilbert, K., Jacobi, F., Kathmann, N., Knaevelsrud, C., Renneberg, B., Ritter, K., Stenzel, N., Walter, H., & Lueken, U. (2024, October 9). Towards Precision Psychotherapy for Non‐Respondent Patients: Recruitment Status and Descriptive Analysis of a Naturalistic Observational CBT Trial for Single‐Case Prediction with Machine Learning [Poster presentation]. 5187 PREACT Symposium: Precision Psychotherapy Signatures, Predictions, & Clinical Utility, Berlin, Germany.
Unterfeld, C., Langhammer, T., Blankenburg, F., Erk, S., Fehm, L., Haynes, J., Heinzel, S., Hilbert, K., Jacobi, F., Kathmann, N., Knaevelsrud, C., Renneberg, B., Ritter, K. Stenzel, N., Walter, H., Lueken, U. (2024, October 9). Towards Precision Psychotherapy for Non-Respondent Patients: Design and Methods of a Naturalistic Observational CBT Trial for Single-Case Prediction with Machine Learning [Poster presentation]. 5187 PREACT Symposium: Precision Psychotherapy Signatures, Predictions, & Clinical Utility, Berlin, Germany.
Langhammer, T., Hilbert, K., Adolph, D., Arolt, V., Bischoff, S., Böhnlein, J., Cwik, J. C., Dannlowski, U., Deckert, J., Domschke, K., Evens, R., Fydrich, T., Gathmann, B., Hamm, A. O., Heinig, I., Herrmann, M. J., Hollandt, M., Junghoefer, M., Kircher, T., … Lueken, U. (2024). Resting-state functional connectivity in anxiety disorders: A multicenter fMRI study. Molecular Psychiatry. https://doi.org/10.1038/s41380-024-02768-2
Torbecke, J., Langhammer, T., Mewes, L., Lueken, U., & Fendel, J. C. (2024). Augmentation of cognitive-behavioural therapy for obsessive-compulsive and anxiety disorders: A protocol for a systematic review and meta-analysis. BMJ Open, 14(10), e090431. https://doi.org/10.1136/bmjopen-2024-090431
Hilbert, K., Böhnlein, J., Meinke, C., Chavanne, A. V., Langhammer, T., Stumpe, L., Winter, N., Leenings, R., Adolph, D., Arolt, V., Bischoff, S., Cwik, J. C., Deckert, J., Domschke, K., Fydrich, T., Gathmann, B., Hamm, A. O., Heinig, I., Herrmann, M. J., … Lueken, U. (2024). Lack of evidence for predictive utility from resting state fMRI data for individual exposure-based cognitive behavioral therapy outcomes: A machine learning study in two large multi-site samples in anxiety disorders. NeuroImage, 295, 120639. https://doi.org/10.1016/j.neuroimage.2024.120639
Lueken, U. & FOR 5187 Konsortium (2023, May 9 -13). Personalisierte Psychotherapie für Patient:innen mit fehlendem Behandlungserfolg: Wie können wir unsere Prädiktionsmodelle verbessern? [Conference session]. 2. Deutscher Psychotherapie Kongress (DPK), Berlin, Germany.
Lueken, U., Hilbert, K., Kathmann, N., Hahn, T., Straube, B., Kircher, T., Wittchen, H.-U., Dannlowski, U. (2022, September 10-15). Precision Psychotherapy: From signatures to predictions to clinical utility [Conference session]. 52nd Congress of the German Society of Psychology (DGPs), Hildesheim, Germany.