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Theranostic markers for personalized therapy of spider phobia: Methods of a bicentric external cross‐validation machine learning approach

Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-213430
  • Objectives Embedded in the Collaborative Research Center “Fear, Anxiety, Anxiety Disorders” (CRC‐TRR58), this bicentric clinical study aims at identifying biobehavioral markers of treatment (non‐)response by applying machine learning methodology with an external cross‐validation protocol. We hypothesize that a priori prediction of treatment (non‐)response is possible in a second, independent sample based on multimodal markers. Methods One‐session virtual reality exposure treatment (VRET) with patients with spider phobia was conducted onObjectives Embedded in the Collaborative Research Center “Fear, Anxiety, Anxiety Disorders” (CRC‐TRR58), this bicentric clinical study aims at identifying biobehavioral markers of treatment (non‐)response by applying machine learning methodology with an external cross‐validation protocol. We hypothesize that a priori prediction of treatment (non‐)response is possible in a second, independent sample based on multimodal markers. Methods One‐session virtual reality exposure treatment (VRET) with patients with spider phobia was conducted on two sites. Clinical, neuroimaging, and genetic data were assessed at baseline, post‐treatment and after 6 months. The primary and secondary outcomes defining treatment response are as follows: 30% reduction regarding the individual score in the Spider Phobia Questionnaire and 50% reduction regarding the individual distance in the behavioral avoidance test. Results N = 204 patients have been included (n = 100 in Würzburg, n = 104 in Münster). Sample characteristics for both sites are comparable. Discussion This study will offer cross‐validated theranostic markers for predicting the individual success of exposure‐based therapy. Findings will support clinical decision‐making on personalized therapy, bridge the gap between basic and clinical research, and bring stratified therapy into reach. The study is registered at ClinicalTrials.gov (ID: NCT03208400).zeige mehrzeige weniger

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Autor(en): Hanna Schwarzmeier, Elisabeth Johanna Leehr, Joscha Böhnlein, Fabian Reinhard Seeger, Kati Roesmann, Bettina Gathmann, Martin J. Herrmann, Niklas Siminski, Markus Junghöfer, Thomas Straube, Dominik Grotegerd, Udo Dannlowski
URN:urn:nbn:de:bvb:20-opus-213430
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Medizinische Fakultät / Klinik und Poliklinik für Psychiatrie, Psychosomatik und Psychotherapie
Sprache der Veröffentlichung:Englisch
Titel des übergeordneten Werkes / der Zeitschrift (Englisch):International Journal of Methods in Psychiatric Research
Erscheinungsjahr:2020
Band / Jahrgang:29
Heft / Ausgabe:2
Aufsatznummer:e1812
Originalveröffentlichung / Quelle:International Journal of Methods in Psychiatric Research (2019) 29:e1812. https://doi.org/10.1002/mpr.1812
DOI:https://doi.org/10.1002/mpr.1812
Allgemeine fachliche Zuordnung (DDC-Klassifikation):6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Freie Schlagwort(e):machine learning; spider phobia; theranostic markers
Datum der Freischaltung:23.12.2020
Datum der Erstveröffentlichung:18.06.2020
Lizenz (Deutsch):License LogoCC BY-NC: Creative-Commons-Lizenz: Namensnennung, Nicht kommerziell