Cost-Effectiveness of rTMS as a Next Step in Antidepressant Non-Responders: A Randomized Comparison With Current Antidepressant Treatment Approaches.

Background: Although repetitive transcranial magnetic stimulation (rTMS) is an effective and commonly used treatment option for treatment-resistant depression, its cost-effectiveness remains much less studied. In particular, the comparative cost-effectiveness of rTMS and other treatment options, such as antidepressant medication, has not been investigated.

Methods: An economic evaluation with 12 months follow-up was conducted in the Dutch care setting as part of a pragmatic multicenter randomized controlled trial, in which patients with treatment-resistant depression were randomized to treatment with rTMS or treatment with the next pharmacological step according to the treatment algorithm.

Mapping of the health of the Nation Outcomes Scale (HoNOS) and Positive and Negative Symptom Scale (PANSS) to the EQ-5D-3L in psychosis patients using the PHAMOUS study.

Objectives: When health outcomes relevant for economic evaluations are unavailable, algorithms can be developed to map utilities using available clinical outcome measures. This study aims to develop two mapping algorithms estimating EuroQol-5 dimension-3 level (EQ-5D-3 L) utilities using the clinician-rated Health of the Nation Outcome Scores (HoNOS) and Positive and Negative Syndrome Scale (PANNS).

Methods: A dataset with 2,029 observations of patients with psychotic disorders included EQ-5D-3 L, HoNOS, PANSS item scores, and demographics.

Antipsychotic dopamine D affinity and negative symptoms in remitted first episode psychosis patients.

Negative symptoms can be an integral part of schizophrenia spectrum pathology and can be secondary to other psychotic symptoms or caused by antipsychotic medication. As antipsychotic drugs differ in their affinity to dopamine receptors and some antipsychotics have partial agonistic effects, antipsychotic drugs are expected to vary in their ability to cause negative symptoms. The association between negative symptoms and antipsychotic medication divided into partial agonists, or antagonists with high or low D affinity was assessed in 310 remitted first episode psychosis (FEP) patients.

rTMS as a Next Step in Antidepressant Nonresponders: A Randomized Comparison With Current Antidepressant Treatment Approaches.

Objective: Although repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression, little is known about the comparative effectiveness of rTMS and other treatment options, such as antidepressants. In this multicenter randomized controlled trial, rTMS was compared with the next pharmacological treatment step in patients with treatment-resistant depression.

Methods: Patients with unipolar nonpsychotic depression (N=89) with an inadequate response to at least two treatment trials were randomized to treatment with rTMS or to a switch of antidepressants, both in combination with psychotherapy.

Cost-Effectiveness of Digital Mental Health Versus Usual Care During Humanitarian Crises in Lebanon: Pragmatic Randomized Trial.

Background: There is evidence from meta-analyses and systematic reviews that digital mental health interventions for depression, anxiety, and stress-related disorders tend to be cost-effective. However, no such evidence exists for guided digital mental health care in low and middle-income countries (LMICs) facing humanitarian crises, where the needs are highest. Step-by-Step (SbS), a digital mental health intervention for depression, anxiety, and stress-related disorders, proved to be effective for Lebanese citizens and war-affected Syrians residing in Lebanon.

Software with artificial intelligence-derived algorithms for analysing CT brain scans in people with a suspected acute stroke: a systematic review and cost-effectiveness analysis.

Background: Artificial intelligence-derived software technologies have been developed that are intended to facilitate the review of computed tomography brain scans in patients with suspected stroke.

Objectives: To evaluate the clinical and cost-effectiveness of using artificial intelligence-derived software to support review of computed tomography brain scans in acute stroke in the National Health Service setting.

Methods: Twenty-five databases were searched to July 2021.

Health-Economic Evaluation of Psychological Interventions for Anxiety Prevention: A Systematic Review.

Objective: Although evidence supports the effectiveness of psychological interventions for prevention of anxiety, little is known about their cost-effectiveness. The aim of this study was to conduct a systematic review of health-economic evaluations of psychological interventions for anxiety prevention.

Methods: PubMed, PsycInfo, Web of Science, Embase, Cochrane Central Register of Controlled Trials, EconLit, National Health Service (NHS) Economic Evaluations Database, NHS Health Technology Assessment, and OpenGrey databases were searched electronically on December 23, 2022.

Prognostic Information on Progression to Dementia: Quantification of the Impact on Quality of Life.

Background: The increasing interest in early identification of people at risk of developing dementia, has led to the development of numerous models aimed at estimating the likelihood of progression from mild cognitive impairment (MCI) to dementia. It is important to study both the need for and possible outcomes related with such prediction models, including the impact of risk predictions on perceived quality of life (QoL).

Objective: This study aimed to quantify the impact that receiving a risk prediction on progression from MCI to dementia has on QoL.

Risk stratification for treating people at ultra-high risk for psychosis: A cost-effectiveness analysis.

People who are at ultra-high risk (UHR) for psychosis receive clinical care with the aim to prevent first-episode psychosis (FEP), regardless of the risk of conversion to psychosis. An economic model from the Canadian health system perspective was developed to evaluate the cost-effectiveness of treating all with UHR compared to risk stratification over a 15-year time horizon, based on conversion probability, expected quality-of-life and costs. The analysis used a decision tree followed by a Markov model.

Testing the combination of Feeling Safe and peer counselling against formulation-based cognitive behaviour therapy to promote psychological wellbeing in people with persecutory delusions: study protocol for a randomized controlled trial (the Feeling Safe-NL Trial).

Background: Persecutory delusions are strong threat beliefs about others' negative intentions. They can have a major impact on patients' day-to-day life. The Feeling Safe Programme is a new translational cognitive-behaviour therapy that helps patients modify threat beliefs and relearn safety by targeting key psychological causal factors.

Trial-based economic evaluation of mindfulness-based cognitive therapy compared to treatment as usual for bipolar disorder.

Objective: Aim of this study was to assess the cost-effectiveness and cost-utility of mindfulness-based cognitive therapy (MBCT) and treatment as usual (TAU) compared to TAU alone in adults with Bipolar disorder (BD).

Methods: An economic evaluation with a time horizon of 15 months was conducted from a societal perspective. Outcomes were expressed in costs per quality adjusted life years (QALYs) and costs per responder using the inventory of depressive symptomatology clinician rating score.

Predicting Undesired Treatment Outcomes With Machine Learning in Mental Health Care: Multisite Study.

Background: Predicting which treatment will work for which patient in mental health care remains a challenge.

Objective: The aim of this multisite study was 2-fold: (1) to predict patients' response to treatment in Dutch basic mental health care using commonly available data from routine care and (2) to compare the performance of these machine learning models across three different mental health care organizations in the Netherlands by using clinically interpretable models.

Methods: Using anonymized data sets from three different mental health care organizations in the Netherlands (n=6452), we applied a least absolute shrinkage and selection operator regression 3 times to predict the treatment outcome.

Economic evaluations of nonpharmacological treatments for drug-resistant epilepsy: A systematic review.

This study was undertaken to systematically identify and critically appraise all published full economic evaluations assessing the cost-effectiveness of nonpharmacological interventions for patients with drug-resistant epilepsy. The Population, Intervention, Comparison, Outcome, Study criteria was used to design search strategies for the identification and selection of relevant studies. Literature search was performed using the MEDLINE (via PubMed), Embase, International Health Technology Assessment, National Institute for Health Research Economic Evaluation Database, and Cost-Effectiveness Analysis Registry databases to identify articles published between January 2000 and May 2023.

A roadmap for applying machine learning when working with privacy-sensitive data: predicting non-response to treatment for eating disorders.

Objectives: Applying machine-learning methodology to clinical data could present a promising avenue for predicting outcomes in patients receiving treatment for psychiatric disorders. However, preserving privacy when working with patient data remains a critical concern.

Methods: In showcasing how machine-learning can be used to build a clinically relevant prediction model on clinical data, we apply two commonly used machine-learning algorithms (Random Forest and least absolute shrinkage and selection operator) to routine outcome monitoring data collected from 593 patients with eating disorders to predict absence of reliable improvement 12 months after entering outpatient treatment.

Designing and testing of a health-economic Markov model to assess the cost-effectiveness of treatments for Bipolar disorder: TiBipoMod.

Background: Bipolar disorder is an often recurrent mood disorder that is associated with a significant economic and health-related burden. Increasing the availability of health-economic evidence may aid in reducing this burden. The aim of this study is to describe the design of an open-source health-economic Markov model for assessing the cost-effectiveness of interventions in the treatment of Bipolar Disorders type I and II, TiBipoMod.

(Cost)-effectiveness and implementation of integrated community-based care for patients with severe mental illness: a study protocol.

Background: As severe mental illness (SMI) is associated with a high disease burden and persistent nature, patients with SMI are often subjected to long-term mental healthcare and are in need of additional social support services. Community-based care and support services are organized via different providers and institutions, which are often lacking structural communication, resulting in a fragmented approach. To improve the efficiency of care provision and optimize patient wellbeing, an integrated multi-agency approach to community-based mental health and social services has been developed and implemented.

Fenfluramine for Treating Dravet Syndrome: An Evidence Review Group Perspective of a NICE Single Technology Appraisal.

Fenfluramine, tradename Fintepla, was appraised within the National Institute for Health and Care Excellence (NICE) single technology appraisal (STA) process as Technology Appraisal 808. Within the STA process, the company (Zogenix International) provided NICE with a written submission and a mathematical health economic model, summarising the company's estimates of the clinical effectiveness and cost-effectiveness of fenfluramine for patients with Dravet syndrome (DS). This company submission (CS) was reviewed by an evidence review group (ERG) independent of NICE.

Design and testing of a health economic Markov model for treatment of anorexia nervosa.

Objectives: Anorexia Nervosa (AN) is a severe psychiatric disorder and knowledge about the cost-effectiveness of potential interventions is limited. The aim of this paper is to introduce the (AnoMod-TI), a flexible modeling tool for assessing the long-term cost-effectiveness of interventions for AN in late adolescent and adult patients, which could support clinical decision making.

Methods: AnoMod-TI is a state-transition cohort simulation (Markov) model developed from a Dutch societal perspective, which consists of four health states - namely full remission (FR), partial remission (PR), AN and death.