1
|
Mayer SF, Corcoran C, Kennedy L, Leucht S, Bighelli I. Cognitive behavioural therapy added to standard care for first-episode and recent-onset psychosis. Cochrane Database Syst Rev 2024; 3:CD015331. [PMID: 38470162 PMCID: PMC10929366 DOI: 10.1002/14651858.cd015331.pub2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
BACKGROUND Cognitive behavioural therapy (CBT) can be effective in the general population of people with schizophrenia. It is still unclear whether CBT can be effectively used in the population of people with a first-episode or recent-onset psychosis. OBJECTIVES To assess the effects of adding cognitive behavioural therapy to standard care for people with a first-episode or recent-onset psychosis. SEARCH METHODS We conducted a systematic search on 6 March 2022 in the Cochrane Schizophrenia Group's Study-Based Register of Trials, which is based on CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, PubMed, ClinicalTrials.gov, ISRCTN, and WHO ICTRP. SELECTION CRITERIA We included randomised controlled trials (RCTs) comparing CBT added to standard care vs standard care in first-episode or recent-onset psychosis, in patients of any age. DATA COLLECTION AND ANALYSIS Two review authors (amongst SFM, CC, LK and IB) independently screened references for inclusion, extracted data from eligible studies and assessed the risk of bias using RoB2. Study authors were contacted for missing data and additional information. Our primary outcome was general mental state measured on a validated rating scale. Secondary outcomes included other specific measures of mental state, global state, relapse, admission to hospital, functioning, leaving the study early, cognition, quality of life, satisfaction with care, self-injurious or aggressive behaviour, adverse events, and mortality. MAIN RESULTS We included 28 studies, of which 26 provided data on 2407 participants (average age 24 years). The mean sample size in the included studies was 92 participants (ranging from 19 to 444) and duration ranged between 26 and 52 weeks. When looking at the results at combined time points (mainly up to one year after start of the intervention), CBT added to standard care was associated with a greater reduction in overall symptoms of schizophrenia (standardised mean difference (SMD) -0.27, 95% confidence interval (CI) -0.47 to -0.08, 20 RCTs, n = 1508, I2 = 68%, substantial heterogeneity, low certainty of the evidence), and also with a greater reduction in positive (SMD -0.22, 95% CI -0.38 to -0.06, 22 RCTs, n = 1565, I² = 52%, moderate heterogeneity), negative (SMD -0.20, 95% CI -0.30 to -0.11, 22 RCTs, n = 1651, I² = 0%) and depressive symptoms (SMD -0.13, 95% CI -0.24 to -0.01, 18 RCTs, n = 1182, I² = 0%) than control. CBT added to standard care was also associated with a greater improvement in the global state (SMD -0.34, 95% CI -0.67 to -0.01, 4 RCTs, n = 329, I² = 47%, moderate heterogeneity) and in functioning (SMD -0.23, 95% CI -0.42 to -0.05, 18 RCTs, n = 1241, I² = 53%, moderate heterogeneity, moderate certainty of the evidence) than control. We did not find a difference between CBT added to standard care and control in terms of number of participants with relapse (relative risk (RR) 0.82, 95% CI 0.57 to 1.18, 7 RCTs, n = 693, I² = 48%, low certainty of the evidence), leaving the study early for any reason (RR 0.87, 95% CI 0.72 to 1.05, 25 RCTs, n = 2242, I² = 12%, moderate certainty of the evidence), adverse events (RR 1.29, 95% CI 0.85 to 1.97, 1 RCT, n = 43, very low certainty of the evidence) and the other investigated outcomes. AUTHORS' CONCLUSIONS This review synthesised the latest evidence on CBT added to standard care for people with a first-episode or recent-onset psychosis. The evidence identified by this review suggests that people with a first-episode or recent-onset psychosis may benefit from CBT additionally to standard care for multiple outcomes (overall, positive, negative and depressive symptoms of schizophrenia, global state and functioning). Future studies should better define this population, for which often heterogeneous definitions are used.
Collapse
Affiliation(s)
- Susanna Franziska Mayer
- Section for Evidence-Based Medicine in Psychiatry and Psychotherapy, TUM School of Medicine and Health, Technical University of Munich, München, Germany
| | | | - Liam Kennedy
- Department of Old Age Psychiatry, Carew House, St Vincent's Hospital, Dublin, Ireland
| | - Stefan Leucht
- Section for Evidence-Based Medicine in Psychiatry and Psychotherapy, TUM School of Medicine and Health, Technical University of Munich, München, Germany
- German Center for Mental Health (DZPG), Munich, Germany
| | - Irene Bighelli
- Section for Evidence-Based Medicine in Psychiatry and Psychotherapy, TUM School of Medicine and Health, Technical University of Munich, München, Germany
- German Center for Mental Health (DZPG), Munich, Germany
| |
Collapse
|
2
|
Shields GE, Wilberforce M, Clarkson P, Farragher T, Verma A, Davies LM. Factors Limiting Subgroup Analysis in Cost-Effectiveness Analysis and a Call for Transparency. PHARMACOECONOMICS 2022; 40:149-156. [PMID: 34713422 PMCID: PMC8553493 DOI: 10.1007/s40273-021-01108-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/18/2021] [Indexed: 05/03/2023]
Abstract
The use of population averages in cost-effectiveness analysis may hide important differences across subgroups, potentially resulting in suboptimal resource allocation, reduced population health and/or increased health inequalities. We discuss the factors that limit subgroup analysis in cost-effectiveness analysis and propose more thorough and transparent reporting. There are many issues that may limit whether subgroup analysis can be robustly included in cost-effectiveness analysis, including challenges with prespecifying and justifying subgroup analysis, identifying subgroups that can be implemented (identified and targeted) in practice, resource and data requirements, and statistical and ethical concerns. These affect every stage of the design, development and reporting of cost-effectiveness analyses. It may not always be possible to include and report relevant subgroups in cost effectiveness, e.g. due to data limitations. Reasons for not conducting subgroup analysis may be heterogeneous, and the consequences of not acknowledging patient heterogeneity can be substantial. We recommend that when potentially relevant subgroups have not been included in a cost-effectiveness analysis, authors report this and discuss their rationale and the limitations of this. Greater transparency of subgroup reporting should provide a starting point to overcoming these challenges in future research.
Collapse
Affiliation(s)
- Gemma E Shields
- Division of Population Health, Health Services Research, and Primary Care, Faculty of Biology, Medicine and Health, Manchester Centre for Health Economics, School of Health Sciences, University of Manchester, Manchester, UK.
| | - Mark Wilberforce
- Social Policy Research Unit, Department of Social Policy and Social Work, University of York, York, UK
| | - Paul Clarkson
- Social Care and Society, Division of Population Health, Health Services Research, and Primary Care, Faculty of Biology, Medicine and Health, School of Health Sciences, University of Manchester, Manchester, UK
| | - Tracey Farragher
- The Epidemiology and Public Health Group (EPHG), Division of Population Health, Health Services Research, and Primary Care, Faculty of Biology, Medicine and Health, School of Health Sciences, University of Manchester, Manchester, UK
| | - Arpana Verma
- The Epidemiology and Public Health Group (EPHG), Division of Population Health, Health Services Research, and Primary Care, Faculty of Biology, Medicine and Health, School of Health Sciences, University of Manchester, Manchester, UK
- Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Linda M Davies
- Division of Population Health, Health Services Research, and Primary Care, Faculty of Biology, Medicine and Health, Manchester Centre for Health Economics, School of Health Sciences, University of Manchester, Manchester, UK
| |
Collapse
|
3
|
Shields GE, Camacho E, Farragher T, Clarkson P, Verma A, Davies LM. Acknowledging Patient Heterogeneity in Economic Evaluations in Schizophrenia: A Systematic Review. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2022; 25:147-156. [PMID: 35031093 DOI: 10.1016/j.jval.2021.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 05/28/2021] [Accepted: 07/02/2021] [Indexed: 06/14/2023]
Abstract
OBJECTIVES Schizophrenia is a severe mental illness with heterogeneous etiology, range of symptoms, and course of illness. Cost-effectiveness analysis often applies averages from populations, which disregards patient heterogeneity even though there are a range of methods available to acknowledge patient heterogeneity. This review evaluates existing economic evaluations of interventions in schizophrenia to understand how patient heterogeneity is currently reflected in economic evaluation. METHODS Electronic searches of MEDLINE, Embase, and PsycINFO via Ovid and the Health Technology Assessment database were run to identify full economic evaluations of interventions aiming to reduce the symptoms associated with schizophrenia. Two levels of screening were used, and explicit inclusion criteria were applied. Prespecified data extraction and critical appraisal were performed. RESULTS Seventy-six relevant studies were identified. More than half (41 of 76) of the articles acknowledged patient heterogeneity in some way through discussion or methods. There was a range of patient characteristics considered, including demographics and socioeconomic factors (eg, age, educational level, ethnicity), clinical characteristics (eg, symptom severity, comorbidities), and preferences (eg, preferences related to outcomes or symptoms). Subgroup analyses were rarely reported (8 of 76). CONCLUSIONS Patient heterogeneity was frequently mentioned in studies but was rarely thoroughly investigated in the identified economic evaluations. When investigated, included patient characteristics and methods were found to be heterogeneous. Understanding and acknowledging patient heterogeneity may alter the conclusions of cost-effectiveness evaluations; subsequently, we would encourage further research in this area.
Collapse
Affiliation(s)
- Gemma E Shields
- Manchester Centre for Health Economics, Division of Population Health, Health Services Research, and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, England, UK.
| | - Elizabeth Camacho
- Manchester Centre for Health Economics, Division of Population Health, Health Services Research, and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, England, UK
| | - Tracey Farragher
- The Epidemiology and Public Health Group, Division of Population Health, Health Services Research, and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, England, UK
| | - Paul Clarkson
- Social Care and Society, Division of Population Health, Health Services Research, and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, England, UK
| | - Arpana Verma
- The Epidemiology and Public Health Group, Division of Population Health, Health Services Research, and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, England, UK; Manchester Academic Health Science Centre, The University of Manchester, Manchester, England, UK
| | - Linda M Davies
- Manchester Centre for Health Economics, Division of Population Health, Health Services Research, and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, England, UK
| |
Collapse
|
4
|
Chan HY, Wijnen BFM, Hiligsmann M, Smit F, Leenen LAM, Majoie MHJM, Evers SMAA. Assessment of Quality of Life 8-Dimension (AQoL-8D): translation, validation, and application in two Dutch trials in patients with epilepsy and schizophrenia. Expert Rev Pharmacoecon Outcomes Res 2021; 22:795-803. [PMID: 34553651 DOI: 10.1080/14737167.2021.1981861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
BACKGROUND To translate and linguistically validate the Assessment of Quality of Life 8-dimensions (AQoL-8D) for use in the Netherlands and to compare the psychometric properties of AQoL-8D with the EuroQol 5-dimensions 5-levels (EQ-5D-5L) in two patient samples. METHODS AQoL-8D was translated from English into Dutch. The translated AQoL-8D was then administered alongside the EQ-5D-5L at baseline and follow-up of two Dutch randomized controlled trials among patients with epilepsy and schizophrenia. These data were subjected to a post-hoc analysis assessing the psychometric properties of AQol-8D vis-à-vis EQ-5D-5L in terms of known-groups construct validity, responsiveness, and floor/ceiling effects. RESULTS In total, 103 epilepsy patients and 99 schizophrenia patients were included in this study. In both datasets, the two instruments discriminated between known-groups, but in schizophrenia, AQoL-8D showed higher responsiveness than EQ-5D-5L, while both instruments showed equal responsiveness in epilepsy. Ceiling effects were only found for EQ-5D-5L in both epilepsy (26.6%) and schizophrenia (6.1%). CONCLUSION Our results have shown that, among other things, AQoL-8D presents better ability to discriminate between known-groups and shows no ceiling effect. Based on our results, we would recommend the use of AQoL-8D in addition to EQ-5D-5L in trials assessing patient's quality of life in patients with epilepsy or schizophrenia.
Collapse
Affiliation(s)
- Hoi Yau Chan
- Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands
| | - Ben F M Wijnen
- Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands.,Department of Research and Development, Epilepsy Center Kempenhaeghe, Heeze, The Netherlands
| | - Mickaël Hiligsmann
- Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands
| | - Filip Smit
- Center for Economic Evaluation and Machine Learning, Trimbos Institute (Netherlands Institute of Mental Health and Addiction), Utrecht, The Netherlands.,Department of Clinical, Neuro and Developmental Psychology and Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, VU University, Amsterdam, The Netherlands
| | - Loes A M Leenen
- Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands.,Department of Research and Development, Epilepsy Center Kempenhaeghe, Heeze, The Netherlands
| | - Marian H J M Majoie
- Department of Research and Development, Epilepsy Center Kempenhaeghe, Heeze, The Netherlands.,MHeNS, School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Maastricht University Medical Centre, Maastricht, The Netherlands.,School of Health Professions Education, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands.,Department of Neurology, Academic Centre for Epileptology, Epilepsy Centre Kempenhaeghe & Maastricht University Medical Centre, The Netherlands
| | - Silvia M A A Evers
- Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands.,Center for Economic Evaluation and Machine Learning, Trimbos Institute (Netherlands Institute of Mental Health and Addiction), Utrecht, The Netherlands
| |
Collapse
|
5
|
Aceituno D, Pennington M, Iruretagoyena B, Prina AM, McCrone P. Health State Utility Values in Schizophrenia: A Systematic Review and Meta-Analysis. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2020; 23:1256-1267. [PMID: 32940244 DOI: 10.1016/j.jval.2020.05.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 04/03/2020] [Accepted: 05/20/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVES Patient preferences are increasingly important in informing clinical and policy decisions. Health-state utility values (HSUVs) are quantitative measures of people's preferences over different health states. In schizophrenia, there is no clarity about HSUVs across the symptoms' severity spectrum. This meta-analysis aims to synthesize the literature on HSUVs in people with schizophrenia. METHODS We searched Medline, PsycInfo, Embase, EconLit, The Cochrane Library, and specialized databases. The studies reporting HSUVs in people with schizophrenia were selected and pooled in a random-effects meta-analysis. The primary outcome was the mean HSUV obtained from participants. RESULTS A total of 54 studies involving 87 335 participants were included. The pooled estimate using direct elicitation was a mean HSUV of 0.79 (95% CI: 0.70-0.88) for mild symptomatic states, 0.69 (95% CI: 0.54-0.85) in moderate states, and 0.34 (95% CI: 0.13-0.56) in severe states. Studies using indirect techniques resulted in a pooled mean HSUV of 0.73 (95% CI: 0.67-0.78) applying the EuroQol 5-dimension, 0.66 (95% CI: 0.62-0.71) in the Short-Form 6-dimension, and 0.59 (95% CI: 0.57-0.61) using the Quality of Well-Being scale. All the estimates resulted in considerable heterogeneity, partially reduced by meta-regression. CONCLUSION Our findings suggest that the severity of psychotic symptoms has an important effect on HSUVs in schizophrenia, with values mirroring patients with disabling physical conditions such as cancer and stroke. Decision makers should be aware of these results when including people's preferences in trials, models, and policy decisions.
Collapse
Affiliation(s)
- David Aceituno
- Health Service & Population Research Department, Institute of Psychiatry, Psychology and Neuroscience. King's College London, London, United Kingdom; Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
| | - Mark Pennington
- Health Service & Population Research Department, Institute of Psychiatry, Psychology and Neuroscience. King's College London, London, United Kingdom
| | - Barbara Iruretagoyena
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile; Early Intervention Program, J. Horwitz Psychiatric Institute, Santiago, Chile
| | - A Matthew Prina
- Health Service & Population Research Department, Institute of Psychiatry, Psychology and Neuroscience. King's College London, London, United Kingdom
| | - Paul McCrone
- Healthcare Economics, Institute for Lifecourse Development, University of Greenwich, London, United Kingdom
| |
Collapse
|