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- Flygare, Oskar
(författare)
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Improving access and outcomes in the treatment of obsessive-compulsive disorder
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Effective psychological treatments exist for obsessive-compulsive disorder (OCD) in the form of cognitive behaviour therapy (CBT), but access is limited and adaptations are needed for groups of patients, for example individuals with co-occurring autism spectrum disorder (ASD), that do not respond well to the standard treatment. Moreover, treatment evaluation is not straightforward with multiple definitions and approaches. Standardised criteria for treatment response and remission have been proposed, but empirically validated operationalisations on self-rated questionnaires are lacking. The goal of this thesis was therefore to improve access and outcomes in the treatment of OCD in four empirical studies. In study I, guided and unguided internet-delivered CBT (ICBT) for OCD were compared to face-to-face CBT in a randomised non-inferiority trial. A total of 120 individuals with a primary diagnosis of OCD participated in the trial, and clinical efficacy as well as costeffectiveness was evaluated. Participants in all three groups improved but the noninferiority results for both ICBT treatments were inconclusive as the confidence intervals for treatment difference included the pre-specified 3-point margin on the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) at primary follow-up. Both therapist-guided and unguided ICBT were cost-effective when compared to face-to-face CBT. Study II evaluated an adapted CBT treatment for 19 adults with co-occurring OCD and ASD in an open trial. After treatment, there were significant reductions in OCD symptoms on the Y-BOCS, and the gains were sustained at 3-month follow-up. However, few patients were treatment responders and treatment engagement was low as the patients completed few exposures and homework assignments relative to the number of treatment sessions. Study III analysed the self-rated Obsessive-Compulsive Inventory–Revised (OCI-R) as a tool to evaluate treatment response and remission after CBT for OCD. The OCI-R was compared to expert consensus criteria using the Y-BOCS and Clinical Global Impression Scale using data from 349 participants in three clinical trials. The optimal cut-off for treatment response was a ≥40% reduction on the OCI-R and the optimal cut-off for remission status was an OCI-R total score of ≤8 points. These empirically validated cut-offs are efficient alternatives to clinician-administered assessments which are not always available in regular clinical practice. Study IV was a pilot trial of the therapist-guided ICBT treatment from study I, implemented in the United Kingdom’s Improving Access to Psychological Therapies (IAPT) programme. A total of 474 consecutively referred patients across three IAPT services with a primary diagnosis of OCD were included in the study. After treatment, there were large improvements in self-rated OCD symptoms (d = 1.77), anxiety (d = 1.55), and depression (d = 0.8). The results indicated that therapist-guided ICBT for OCD is an effective treatment when implemented in the IAPT system, but challenges in implementation were identified and discussed. The studies included in this thesis addressed current issues in the treatment of OCD and evaluations of treatment effects. In summary, the studies showed that ICBT for OCD is an effective treatment when delivered in multiple contexts, and is a cost-effective alternative to face-to-face CBT; that an adapted CBT protocol for adults with OCD and co-occurring ASD is promising but that additional innovations are needed to improve outcomes; and that the self-rated OCI-R can be an efficient tool for treatment evaluation when clinician-rated assessments are unavailable. Directions for future research include further implementation of ICBT for OCD and evaluations of its place in a stepped-care health care model, exploring new intensive treatment options for individuals with OCD and ASD, and externally validating the OCI-R cut-offs in diverse clinical samples.
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| 2. |
- Mataix-Cols, David, et al.
(författare)
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Operational Definitions of Treatment Response and Remission in Obsessive-Compulsive Disorder Capture Meaningful Improvements in Everyday Life
- 2022
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Ingår i: Psychotherapy and Psychosomatics. - : S. Karger AG. - 0033-3190 .- 1423-0348. ; 91:6, s. 424-430
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: The operational definitions of treatment response, partial response, and remission in obsessive-compulsive disorder (OCD) are widely used in clinical trials and regular practice. However, the clinimetric sensitivity of these definitions, that is, whether they identify patients that experience meaningful changes in their everyday life, remains unexplored.Objective: The objective was to examine the clinimetric sensitivity of the operational definitions of treatment response, partial response, and remission in children and adults with OCD.Methods: Pre- and post-treatment data from five clinical trials and three cohort studies of children and adults with OCD (n = 1,528; 55.3% children, 61.1% female) were pooled. We compared (1) responders, partial responders, and non-responders and (2) remitters and non-remitters on self-reported OCD symptoms, clinician-rated general functioning, and self-reported quality of life. Remission was also evaluated against post-treatment diagnostic interviews.Results: Responders and remitters experienced large improvements across validators. Responders had greater improvements than partial responders and non-responders on self-reported OCD symptoms (Cohen’s d 0.65–1.13), clinician-rated functioning (Cohen’s d 0.53–1.03), and self-reported quality of life (Cohen’s d 0.63–0.73). Few meaningful differences emerged between partial responders and non-responders. Remitters had better outcomes across most validators than non-remitters. Remission criteria corresponded well with absence of post-treatment diagnosis (sensitivity/specificity: 93%/83%). Using both the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) and the Clinical Global Impression Scale yielded more conservative results and more robust changes across validators, compared to only using the Y-BOCS.Conclusions: The current definitions of treatment response and remission capture meaningful improvements in the everyday life of individuals with OCD, whereas the concept of partial response has dubious clinimetric sensitivity.
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| 3. |
- Wallert, John, et al.
(författare)
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Predicting remission after internet-delivered psychotherapy in patients with depression using machine learning and multi-modal data
- 2022
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Ingår i: Translational Psychiatry. - : Springer Nature. - 2158-3188. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- This study applied supervised machine learning with multi-modal data to predict remission of major depressive disorder {MDD) after psychotherapy. Genotyped adult patients (n = 894, 65.5% women, age 18-75 years) diagnosed with mild-to-moderate MDD and treated with guided Internet-based Cognitive Behaviour Therapy (ICBT) at the Internet Psychiatry Clinic in Stockholm were included (2008-2016). Predictor types were demographic, clinical, process (e.g., time to complete online questionnaires), and genetic (polygenic risk scores). Outcome was remission status post ICBT (cut-off <= 10 on MADRS-S). Data were split into train (60%) and validation (40%) given ICBT start date. Predictor selection employed human expertise followed by recursive feature elimination. Model derivation was internally validated through cross-validation. The final random forest model was externally validated against a (i) null, (ii) logit, (iii) XGBoost, and {iv) blended meta-ensemble model on the hold-out validation set. Feature selection retained 45 predictors representing all four predictor types. With unseen validation data, the final random forest model proved reasonably accurate at classifying post ICBT remission (Accuracy 0.656 [0.604, 0.705], P vs null model = 0.004; AUC 0.687 [0.631, 0.743]), slightly better vs logit (bootstrap D = 1.730, P = 0.084) but not vs XGBoost (D = 0.463, P = 0.643). Transparency analysis showed model usage of all predictor types at both the group and individual patient level. A new, multi-modal classifier for predicting MDD remission status after ICBT treatment in routine psychiatric care was derived and empirically validated. The multi-modal approach to predicting remission may inform tailored treatment, and deserves further investigation to attain clinical usefulness.
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