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

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 hypothe...

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Veröffentlicht in:International journal of methods in psychiatric research 2020-06, Vol.29 (2), p.e1812-n/a, Article 1812
Hauptverfasser: Schwarzmeier, Hanna, Leehr, Elisabeth Johanna, Böhnlein, Joscha, Seeger, Fabian Reinhard, Roesmann, Kati, Gathmann, Bettina, Herrmann, Martin J., Siminski, Niklas, Junghöfer, Markus, Straube, Thomas, Grotegerd, Dominik, Dannlowski, Udo
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Sprache:eng
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Zusammenfassung: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 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).
ISSN:1049-8931
1557-0657
DOI:10.1002/mpr.1812