INVITED SYMPOSIUM: Personalizing psychotherapy

 

Submission type

Symposium

Scheduled

Parallel Session VI: Graanbeurszaal, 09-06-2018, 13:00 - 14:30

Kernwoorden

Precision medicine, personalized treatment selection.

Onderzoeksgebied

Other

Beknopte samenvatting van de totale bijdrage

Precision medicine, or tailoring treatments to each patient’s individual characteristics, is a major challenge for health care today. We present current developments of precision medicine in psychotherapy. In four presentations, we show recent research findings of personalized treatment selection and adaptation in cognitive behavioral, interpersonal, and psychodynamic therapy.

Auteurs

Which patients benefit specifically from short-term psychodynamic psychotherapy for depression? An individual patient data meta-analysis.

Driessen, E., Fokkema, M., Abbass, A.A., Barber, J.P., Dekker, J.J.M., Town, J.M., Van, H.L., Cuijpers, P.

 

Abstract ID

1071

Submission type

Oral only

Introductie

Short-term psychodynamic psychotherapy (STPP) is an empirically supported treatment that is often used to treat depression. However, it is unclear which patients specifically benefit from STPP. We present an individual participant data (IPD) meta-analysis project aimed at identifying predictors and moderators of STPP efficacy.

Materiaal en methodes

Based on a systematic literature search, we identified studies reporting a) outcomes on standardized measurements of b) depressed c) adult patients d) receiving STPP. We invited the authors of these studies to share the participant-level data of their trials, and combine these data to conduct IPD meta-analyses. The primary outcome measure for this study is post-treatment efficacy as measured by a continuous depression outcome measure. Potential predictors and moderators include all socio-demographic variables, clinical variables, and other patient characteristics that are measured consistently across studies.

Resultaten

The authors of 41 STPP for depression studies, encompassing 3,161 individuals, agreed to share data. We will present preliminary findings regarding which patients benefit specifically from combined treatment of STPP and antidepressant medication versus mono-treatment.

Conclusie

The findings of this study can have important clinical implications, as they can inform expectations of treatment efficacy and help make choices concerning the best treatment for individual patients.

Auteurs

For which patients do cognitive therapy and interpersonal therapy work, and for how long? Personalized treatment selection using predictors from the Maastricht Study on CT and IPT for depression

Huibers, M.J.H., Cohen, Z.D., Lemmens, L.H.J.M., van Bronswijk, S.C., Arntz, A., Peeters, F.P.M.L., Cuijpers, P., DeRubeis, R.J.

 

Abstract ID

1066

Submission type

Oral only

Introductie

Cognitive therapy (CT) and interpersonal therapy (IPT) are different therapies from distinct theoretical backgrounds, which implies they exert their effectiveness through different pathways, and possibly with differential effects in subgroups of patients.

Materiaal en methodes

In the presentation, we focus on the analysis of predictors and moderators in the context of an RCT comparing CT and IPT (n=181).

Resultaten

We found find several moderators that predicted differential response to the two treatments, for both the acute phase of treatment and the long-term (sustained recovery and relapse). We then used the Personalized Advantage Index (PAI), recently developed by DeRubeis and colleagues, to combine these variables into an algorithm that generates actionable treatment recommendations for individual patients. For a majority of the trial participants, a clinical meaningful advantage was predicted in either CT or IPT, compared to the other treatment. Moreover, those who were randomized to their predicted optimal treatment had far better outcomes than those randomized to their predicted non-optimal treatment, directly after treatment and in the longer term.

Auteurs

Lessons Learned (and Still Learning) in the Application of the Personalized Advantage Index Approach to Precision Mental Health

DeRubeis, R.J.

 

Abstract ID

1067

Submission type

Oral only

Introductie

The speaker will describe challenges his team has faced during the development, application, and dissemination of multivariable modeling methods in the context of treatment selection. He will use case examples to illustrate methods that aim to minimize underfitting, overfitting, and double-dipping, common features that can severely constrain the ability of models to generate robust and replicable predictions.

Auteurs

Enhancing outcome in psychotherapy: Personalized predictions and adaptive problem solving in clinical practice.

Lutz, W., Zimmermann, D., Deisenhofer, A.-K., Schwartz, B., Müller, V., Rubel, J.

 

Abstract ID

1068

Submission type

Oral only

Introductie

In this paper a computer based feedback, decision and problem solving tool for clinical practice will be presented, which allows the prediction and tracking of personalized treatment recommendations for psychological treatments.

Materiaal en methodes

The development and validation sample for the computer based tool consisted of 1181 patients treated for at least 10 sessions in Cognitive Behavioral Therapy at the outpatient center of the University of Trier.

Resultaten

Modern statistical techniques for machine learning (e.g. Nearest Neighbor based predictions) were used to develop a decision support tool to derive predictions for each case regarding the early treatment strategy, drop-out and clinical supervision. Furthermore, advanced adaptive modeling tools were developed to identify patients at risk for treatment failure and to indicate the usage of clinical problem solving tools in five risk areas via psychometric feedback: 1. crisis management/suicidality; 2. motivation/treatment goals; 3. therapeutic alliance/interpersonal skills; 4. social support/critical life events; 5. emotion regulation/self-regulation.

Conclusie

The application of this research and the implementation of such tools into clinical practice will be discussed with respect to consequences not only for clinical practice, but also for training and future research.

Auteurs