Background Systematic reviews suggest school-based mindfulness training (SBMT) shows promise in promoting student mental health. Objective The My Resilience in Adolescence (MYRIAD) Trial evaluated the effectiveness and cost-effectiveness of SBMT compared with teaching-as-usual (TAU). Methods MYRIAD was a parallel group, cluster-randomised controlled trial. Eighty-five eligible schools consented and were randomised 1:1 to TAU (43 schools, 4232 students) or SBMT (42 schools, 4144 students), stratified by school size, quality, type, deprivation and region. Schools and students (mean (SD); age range=12.2 (0.6); 11–14 years) were broadly UK population-representative. Forty-three schools (n=3678 pupils; 86.9%) delivering SBMT, and 41 schools (n=3572; 86.2%) delivering TAU, provided primary end-point data. SBMT comprised 10 lessons of psychoeducation and mindfulness practices. TAU comprised standard social-emotional teaching. Participant-level risk for depression, social-emotional-behavioural functioning and well-being at 1 year follow-up were the co-primary outcomes. Secondary and economic outcomes were included. Findings Analysis of 84 schools (n=8376 participants) found no evidence that SBMT was superior to TAU at 1 year. Standardised mean differences (intervention minus control) were: 0.005 (95% CI −0.05 to 0.06) for risk for depression; 0.02 (−0.02 to 0.07) for social-emotional-behavioural functioning; and 0.02 (−0.03 to 0.07) for well-being. SBMT had a high probability of cost-effectiveness (83%) at a willingness-to-pay threshold of £20 000 per quality-adjusted life year. No intervention-related adverse events were observed. Conclusions Findings do not support the superiority of SBMT over TAU in promoting mental health in adolescence. Clinical implications There is need to ask what works, for whom and how, as well as considering key contextual and implementation factors. Trial registration Current controlled trials ISRCTN86619085. This research was funded by the Wellcome Trust (WT104908/Z/14/Z and WT107496/Z/15/Z).
Nine years ago, in my first editorial for EvidenceBased Mental Health (EBMH) as editor in chief, I wrote that ‘EBMH should be seen as a tool to engage new generations of psychiatrists and psychologists to develop and implement the evidencebased approach into daily clinical practice.’ I took the job when I moved to Oxford and one of the main reasons why I accepted the challenge of editing this journal was the name of the journal itself. Evidence is anything presented in support of an assertion. Even if ‘evidence’ is not necessarily ‘evident’, be it strong (ideal scenario) or weak (too often the case), evidence is about data (scientific data, possibly!). Evidence can change over the years, but it is the closest we can get to the truth itself when we deal with healthrelated issues. As a practising psychiatrist, I think that evidence is the only objective starting point that should be used in clinical practice. An evidencebased decision is not ‘a priori’ determined only by the data and it may vary from one patient to another depending on individual clinical circumstances and personal preferences. However, we need data to justify our rational choice in clinical decision making; otherwise, patients will be treated according to mere—and too often, biased—opinions (the recent controversies about COVID19 treatments and vaccines are a clear example of ideology and disinformation). Given the inevitability of errors and inaccuracies in the scientific literature, we have a simple choice: we can either make the best use of the available evidence or dismiss and ignore it. Our journal has always favoured the former approach and rejected nihilism. Valid conclusions can be drawn from a critical and cautious use of the best available, even if flawed, evidence. In 2023, we will celebrate the 25th anniversary of the foundation of EBMH. It is a remarkable achievement. And it is great to see that many of the previous editors and associate editors of the journal are still active as academics and clinicians, practising and disseminating evidencebased mental health across the globe. They should be congratulated for their pioneering vision of ‘harnessing advances in clinical epidemiology, biostatistics and information science to produce a coherent and comprehensive approach’ that allowed ‘clinicians to stay up to date with the most recent publications, and base their practice on the best available evidence.’ However, over the last quarter of a century, EBMH has changed dramatically. The journal started as an international digest of the most relevant studies in mental health and published only commissioned commentaries and opinion pieces. EBMH now has its core in unsolicited original research papers and methodological articles, and has become one of the top 10 mental health journals in the world in terms of impact factor (https:// ebmh.bmj.com/pages/about/). To this success contributed all of our editors, editorial boards, publishers, authors and readers. The point now is where to go next. I think there has to be a change. Or better, an evolution. We need to work harder in the field of evidencebased mental health, both in terms of knowledge and implementation. We need to make all the content of the journal free and open access to readers and researchers. We need to accelerate the pace and put more effort to engage a wider range of stakeholders, especially patients. Evidence synthesis, data science, digital technology and precision mental health are the way forward. The world of scientific journals is crowded, the competition high and, even though mental health is now a priority worldwide, the funding is always limited. Rather than being a limitation, all this is a great opportunity. Opportunity to do better science in psychiatry and psychology, to fill the gap between physical and mental health, to combat stigma and discrimination, to deliver better care and have better outcomes for our patients. To be continued.
ObjectiveA network meta-analysis (NMA) usually assesses multiple outcomes across several treatment comparisons. TheVitruvian plotaims to facilitate communication of multiple outcomes from NMAs to patients and clinicians.MethodsWe developed this tool following the recommendations on the communication of benefit–risk information from the available literature. We collected and implemented feedback from researchers, statisticians, methodologists, clinicians and people with lived experience of physical and mental health issues.ResultsWe present theVitruvian plot, which graphically presents absolute estimates and relative performance of competing interventions against a common comparator for several outcomes of interest. We use two alternative colour schemes to highlight either the strength of statistical evidence or the confidence in the evidence. Confidence in the evidence is evaluated across six domains (within-study bias, reporting bias, indirectness, imprecision, heterogeneity and incoherence) using the Confidence in Network Meta-Analysis (CINeMA) system.ConclusionsTheVitruvian plotallows reporting of multiple outcomes from NMAs, with colourings appropriate to inform credibility of the presented evidence.
Nine years ago, in my first editorial for EvidenceBased Mental Health (EBMH) as editor in chief, I wrote that ‘EBMH should be seen as a tool to engage new generations of psychiatrists and psychologists to develop and implement the evidencebased approach into daily clinical practice.’ I took the job when I moved to Oxford and one of the main reasons why I accepted the challenge of editing this journal was the name of the journal itself. Evidence is anything presented in support of an assertion. Even if ‘evidence’ is not necessarily ‘evident’, be it strong (ideal scenario) or weak (too often the case), evidence is about data (scientific data, possibly!). Evidence can change over the years, but it is the closest we can get to the truth itself when we deal with healthrelated issues. As a practising psychiatrist, I think that evidence is the only objective starting point that should be used in clinical practice. An evidencebased decision is not ‘a priori’ determined only by the data and it may vary from one patient to another depending on individual clinical circumstances and personal preferences. However, we need data to justify our rational choice in clinical decision making; otherwise, patients will be treated according to mere—and too often, biased—opinions (the recent controversies about COVID19 treatments and vaccines are a clear example of ideology and disinformation). Given the inevitability of errors and inaccuracies in the scientific literature, we have a simple choice: we can either make the best use of the available evidence or dismiss and ignore it. Our journal has always favoured the former approach and rejected nihilism. Valid conclusions can be drawn from a critical and cautious use of the best available, even if flawed, evidence. In 2023, we will celebrate the 25th anniversary of the foundation of EBMH. It is a remarkable achievement. And it is great to see that many of the previous editors and associate editors of the journal are still active as academics and clinicians, practising and disseminating evidencebased mental health across the globe. They should be congratulated for their pioneering vision of ‘harnessing advances in clinical epidemiology, biostatistics and information science to produce a coherent and comprehensive approach’ that allowed ‘clinicians to stay up to date with the most recent publications, and base their practice on the best available evidence.’ However, over the last quarter of a century, EBMH has changed dramatically. The journal started as an international digest of the most relevant studies in mental health and published only commissioned commentaries and opinion pieces. EBMH now has its core in unsolicited original research papers and methodological articles, and has become one of the top 10 mental health journals in the world in terms of impact factor (https:// ebmh.bmj.com/pages/about/). To this success contributed all of our editors, editorial boards, publishers, authors and readers. The point now is where to go next. I think there has to be a change. Or better, an evolution. We need to work harder in the field of evidencebased mental health, both in terms of knowledge and implementation. We need to make all the content of the journal free and open access to readers and researchers. We need to accelerate the pace and put more effort to engage a wider range of stakeholders, especially patients. Evidence synthesis, data science, digital technology and precision mental health are the way forward. The world of scientific journals is crowded, the competition high and, even though mental health is now a priority worldwide, the funding is always limited. Rather than being a limitation, all this is a great opportunity. Opportunity to do better science in psychiatry and psychology, to fill the gap between physical and mental health, to combat stigma and discrimination, to deliver better care and have better outcomes for our patients. To be continued.
Background Non-serious adverse events (NSAEs) should be captured and reported because they can have a significant negative impact on patients and treatment adherence. However, the reporting of NSAEs in randomised controlled trials (RCTs) is limited. Objective To identify the most important NSAEs of antidepressants for patients and clinicians, to be evaluated in RCTs and meta-analyses. Methods We conducted online international surveys in English, German and French, including (1) adults prescribed an antidepressant for a depressive episode and (2) healthcare professionals (HCPs) prescribing antidepressants. Participants ranked the 30 most frequent NSAEs reported in the scientific literature. We fitted logit models for sets of ranked items and calculated for each AE the probability to be ranked higher than the least important AE. We also identified additional patient-important AEs not included in the ranking task via open-ended questions. Findings We included 1631 patients from 44 different countries (1290 (79.1%) women, mean age 39.4 (SD 13), 289 (37.1%) with severe depression (PHQ-9 score ≥20)) and 281 HCPs (224 (79.7%) psychiatrists). The most important NSAEs for patients were insomnia (95.9%, 95% CI 95.2% to 96.5%), anxiety (95.2%, 95% CI 94.3% to 95.9%) and fatigue (94.6%, 95% CI 93.6% to 95.4%). The most important NSAEs for HCPs were sexual dysfunction (99.2%, 95% CI 98.5% to 99.6%), weight gain (98.9%, 95% CI 97.7% to 99.4%) and erectile problems (98.8%, 95% CI 97.7% to 99.4%). Participants reported 66 additional NSAEs, including emotional numbing (8.6%), trouble with concentration (7.6%) and irritability (6%). Conclusions These most important NSAEs should be systematically reported in antidepressant trials. Clinical implications The most important NSAEs should contribute to the core outcome set for harms in depression.
Background Behavioural and cognitive interventions remain credible approaches in addressing loneliness and depression. There was a need to rapidly generate and assimilate trial-based data during COVID-19. Objectives We undertook a parallel pilot RCT of behavioural activation (a brief behavioural intervention) for depression and loneliness (Behavioural Activation in Social Isolation, the BASIL-C19 trial ISRCTN94091479 ). We also assimilate these data in a living systematic review (PROSPERO CRD42021298788) of cognitive and/or behavioural interventions. Methods Participants (≥65 years) with long-term conditions were computer randomised to behavioural activation (n=47) versus care as usual (n=49). Primary outcome was PHQ-9. Secondary outcomes included loneliness (De Jong Scale). Data from the BASIL-C19 trial were included in a metanalysis of depression and loneliness. Findings The 12 months adjusted mean difference for PHQ-9 was −0.70 (95% CI −2.61 to 1.20) and for loneliness was −0.39 (95% CI −1.43 to 0.65). The BASIL-C19 living systematic review (12 trials) found short-term reductions in depression (standardised mean difference (SMD)=−0.31, 95% CI −0.51 to −0.11) and loneliness (SMD=−0.48, 95% CI −0.70 to −0.27). There were few long-term trials, but there was evidence of some benefit (loneliness SMD=−0.20, 95% CI −0.40 to −0.01; depression SMD=−0.20, 95% CI −0.47 to 0.07). Discussion We delivered a pilot trial of a behavioural intervention targeting loneliness and depression; achieving long-term follow-up. Living meta-analysis provides strong evidence of short-term benefit for loneliness and depression for cognitive and/or behavioural approaches. A fully powered BASIL trial is underway. Clinical implications Scalable behavioural and cognitive approaches should be considered as population-level strategies for depression and loneliness on the basis of a living systematic review.
Question Amphetamine use is a risk factor for psychosis, which imposes a substantial burden on society. We aimed to investigate the incidence of psychosis associated with illicit amphetamine use and whether rehabilitation treatments could influence the psychosis risk. Study selection and analysis A retrospective cohort study was conducted using the population based Taiwan Illicit Drug Issue Database (TIDID) and the National Health Insurance Research Database (NHIRD), from 2007 to 2016. We identified 74 601 illicit amphetamine users as the amphetamine cohort and 2 98 404 subjects as the non-amphetamine cohort. The incidence rate of newly diagnosed psychosis was the main outcome. Cox proportional hazards models were applied to assess the effects of amphetamine, and the Kaplan-Meier method was used to estimate the cumulative psychosis incidence curves. Findings Illicit amphetamine users were 5.28 times more likely to experience psychosis than those without illicit drug use records. The risk was higher for subjects with multiple arrests for amphetamine use. A greater hazard ratio (HR) magnitude was observed in female patients. We also observed a significant decrease in the risk of psychosis in patients receiving rehabilitation treatments during deferred prosecution (adjusted HR 0.74, 95% CI 0.61 to 0.89). Conclusions Illicit amphetamine use was associated with an increased incidence of psychosis. The risk was identified across all age groups, particularly in women and in those arrested multiple times, and was inversely correlated with rehabilitation treatments for amphetamine misuse.
Background Advances in genetics and digital phenotyping in psychiatry have given rise to testing services targeting young people, which claim to predict psychiatric outcomes before difficulties emerge. These services raise several ethical challenges surrounding data sharing and information privacy. Objectives This study aimed to investigate young people's interest in predictive testing for mental health challenges and their attitudes towards sharing biological, psychosocial and digital data for such purpose. Methods Eighty UK adolescents aged 16-18 years took part in a digital role-play where they played the role of clients of a fictional predictive psychiatry company and chose what sources of personal data they wished to provide for a risk assessment. After the role-play, participants reflected on their choices during a peer-led interview. Findings Participants saw multiple benefits in predictive testing services, but were highly selective with regard to the type of data they were willing to share. Largely due to privacy concerns, digital data sources such as social media or Google search history were less likely to be shared than psychosocial and biological data, including school grades and one's DNA. Participants were particularly reluctant to share social media data with schools (but less so with health systems). Conclusions Emerging predictive psychiatric services are valued by young people; however, these services must consider privacy versus utility trade-offs from the perspective of different stakeholders, including adolescents. Clinical implications Respecting adolescents' need for transparency, privacy and choice in the age of digital phenotyping is critical to the responsible implementation of predictive psychiatric services.
Background Adjunctive metformin is the most well-studied intervention in the pharmacological management of antipsychotic-induced weight gain (AIWG). Although a relatively unaddressed area, among guidelines recommending consideration of metformin, prescribing information that would facilitate its applied use by clinicians, for example, provision of a dose titration schedule is absent. Moreover, recommendations differ regarding metformin’s place in the hierarchy of management options. Both represent significant barriers to the applied, evidence-based use of metformin for this indication. Objective To produce a guideline solely dedicated to the optimised use of metformin in AIWG management, using internationally endorsed guideline methodology. Methods A list of guideline key health questions (KHQs) was produced. It was agreed that individual recommendations would be ‘adopted or adapted’ from current guidelines and/or developed de novo, in the case of unanswered questions. A systematic literature review (2008–2020) was undertaken to identify published guidelines and supporting (or more recent) research evidence. Quality appraisal was undertaken using the Appraisal of Guidelines Research and Evaluation II tool, A Measurement Tool to Assess Systematic Reviews (AMSTAR) assessment,and the Cochrane Risk of Bias 2 tool, where appropriate. Assessment of evidence certainty and recommendation development was undertaken using Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. Findings We confirmed that no published guideline—of appropriate quality, solely dedicated to the use of metformin to manage AIWG was available. Recommendations located within other guidelines inadequately addressed our KHQs. Conclusion All 11 recommendations and 7 supporting good practice developed here were formulated de novo. Clinical implications These recommendations build on the number and quality of recommendations in this area, and facilitate the optimised use of metformin when managing AIWG.
QuestionEffective prevention of suicide requires a comprehensive understanding of risk factors.Study selection and analysisFive databases were systematically searched to identify psychological autopsy studies (published up to February 2022) that reported on risk factors for suicide mortality among adults in the general population. Effect sizes were pooled as odds ratios (ORs) using random-effects models for each risk factor examined in at least three independent samples.FindingsA total of 37 case–control studies from 23 countries were included, providing data on 40 risk factors in 5633 cases and 7101 controls. The magnitude of effect sizes varied substantially both between and within risk factor domains. Clinical factors had the strongest associations with suicide, including any mental disorder (OR=13.1, 95% CI 9.9 to 17.4) and a history of self-harm (OR=10.1, 95% CI 6.6 to 15.6). By comparison, effect sizes were smaller for other domains relating to sociodemographic status, family history, and adverse life events (OR range 2–5).ConclusionsA wide range of predisposing and precipitating factors are associated with suicide among adults in the general population, but with clear differences in their relative strength.PROSPERO registration numberCRD42021232878.
Ostinelli et al developed an interesting visualisation tool, the Vitruvian plot, to present multiple outcomes in network metaanalysis. We write to make some suggestions and potential improvements. First, to present the strength of statistical evidence, the authors colour the sectors according to the p values of a Ztest. According to the Cochran handbook, this could lead to overreliance and misinterpretation of p values, and assertive judgements about imprecision. One solution is to use a partially contextualised approach, according to the guidance of the GRADE working group. This approach also encourages researchers to use absolute values. After choosing reference intervention, researchers need to set thresholds for effects, which classify interventions into those with a trivial, small, moderate or large effect. The specific magnitude of the potential benefit or harm is more conducive to helping readers understand the evidence accurately. Second, in the Vitruvian plot, the increase in absolute event rate is in a 1:1 ratio with the increase in sector radius. Taking into account the general reader’s understanding of statistics, this could lead to misunderstandings. For example, if the radius is doubled, the area will be quadrupled. The sector area cannot accurately represent the corresponding absolute estimates. We suggest that the absolute event rate should be comparable to the ratio of shaded sectors to total sector area, which will avoid misunderstandings by graphically sensitive readers. Third, the original Vitruvian plot cannot show both the specific magnitude of the potential benefit or harm and the certainty of evidence at the same time. Especially when we use effect size to colour the sector, the certainty of evidence could present information of imprecision. We propose improvements to the Vitruvian plot to increase the presentation of the certainty of evidence. This facilitates the user to read the evidence coherently. Based on the original design, we improved the original Vitruvian plot as shown in figure 1. The data presented in the figure are fictitious. For demonstration purposes, we set the same threshold for each outcome. The green and red in the sector represent the two directions of the effect. The ratio of the shaded sector area to the total sector area is consistent with the absolute event rate. The area outside the circle is used to present the certainty of evidence. We find the Vitruvian plot to be very useful and sincerely hope that our suggestions could refine this visualisation tool for multiple outcomes in network metaanalysis.
Question Mindfulness-based programmes (MBPs) are an increasingly popular approach to improving mental health in young people. Our previous meta-analysis suggested that MBPs show promising effectiveness, but highlighted a lack of high-quality, adequately powered randomised controlled trials (RCTs). This updated meta-analysis assesses the-state-of the-art of MBPs for young people in light of new studies. It explores MBP’s effectiveness in active vs passive controls; selective versus universal interventions; and studies that included follow-up. Study selection and analysis We searched for published and unpublished RCTs of MBPs with young people (<19 years) in PubMed Central, PsycINFO, Web of Science, EMBASE, ICTRP, ClinicalTrials.gov, EThOS, EBSCO and Google Scholar. Random-effects meta-analyses were conducted, and standardised mean differences (Cohen’s d) were calculated. Findings Sixty-six RCTs, involving 20 138 participants (9552 receiving an MBP and 10 586 controls), were identified. Compared with passive controls, MBPs were effective in improving anxiety/stress, attention, executive functioning, and negative and social behaviour (d from 0.12 to 0.35). Compared against active controls, MBPs were more effective in reducing anxiety/stress and improving mindfulness (d=0.11 and 0.24, respectively). In studies with a follow-up, there were no significant positive effects of MBPs. No consistent pattern favoured MBPs as a universal versus selective intervention. Conclusions The enthusiasm for MBPs in youth has arguably run ahead of the evidence. While MBPs show promising results for some outcomes, in general, the evidence is of low quality and inconclusive. We discuss a conceptual model and the theory-driven innovation required to realise the potential of MBPs in supporting youth mental health.
BACKGROUND:Previous research suggests that mindfulness training (MT) appears effective at improving mental health in young people. MT is proposed to work through improving executive control in affectively laden contexts. However, it is unclear whether MT improves such control in young people. MT appears to mitigate mental health difficulties during periods of stress, but any mitigating effects against COVID-related difficulties remain unexamined. OBJECTIVE:To evaluate whether MT (intervention) versus psychoeducation (Psy-Ed; control), implemented in after-school classes: (1) Improves affective executive control; and/or (2) Mitigates negative mental health impacts from the COVID-19 pandemic. METHODS:A parallel randomised controlled trial (RCT) was conducted (Registration: https://osf.io/d6y9q/; Funding: Wellcome (WT104908/Z/14/Z, WT107496/Z/15/Z)). 460 students aged 11-16 years were recruited and randomised 1:1 to either MT (N=235) or Psy-Ed (N=225) and assessed preintervention and postintervention on experimental tasks and self-report inventories of affective executive control. The RCT was then extended to evaluate protective functions of MT on mental health assessed after the first UK COVID-19 lockdown. FINDINGS:Results provided no evidence that the version of MT used here improved affective executive control after training or mitigated negative consequences on mental health of the COVID-19 pandemic relative to Psy-Ed. No adverse events were reported. CONCLUSIONS:There is no evidence that MT improves affective control or downstream mental health of young people during stressful periods. CLINICAL IMPLICATIONS:We need to identify interventions that can enhance affective control and thereby young people's mental health.
Background The COVID-19 pandemic has caused an increase in mental ill health compared with prepandemic levels. Longer-term trajectories of depression in adults during the pandemic remain unclear. Objective We used latent growth curve modelling to examine individual trajectories of depression symptoms, and their predictors, beyond the early stage of the pandemic. Methods Data were collected in three waves in May 2020, September/October 2020 and February/March 2021 in four UK cohorts (Millennium Cohort Study, Next Steps cohort, British Cohort and National Child Development Study). We included n=16 978 participants (mean age at baseline: 20, 30, 50 and 62, respectively). Self-reported depressive symptoms were the study outcome. Findings Symptoms of depression were higher in younger compared with older age groups (d=0.7) across all waves. While depressive symptoms remained stable from May 2020 to Autumn 2020 overall (standardized mean difference (SMD)=0.03, 95% CI 0.02 to 0.04), they increased in all age groups from May 2020 to Spring 2021 (SMD=0.12, 95% CI 0.11 to 0.13). Feelings of loneliness were the strongest predictor and concurrent correlate of increasing depressive symptoms across all cohorts, prepandemic mental health problems and having a long-term illness were also significantly associated with an increase in depression symptoms across all ages. By contrast, compliance with social distancing measures did not predict an increase in depression symptoms. Conclusions Feeling lonely and isolated had a large effect on depression trajectories across all generations, while social distancing measures did not. Clinical implications These findings highlight the importance of fostering the feeling of connectedness during COVID-19-related distancing measures.
Question Although mental pain is present in many mental disorders and is a predictor of suicide, it is rarely investigated in research or treated in care. A valid tool to measure it is a necessary first step towards better understanding, predicting and ultimately relieving this pain. Study selection and analysis Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we performed a systematic review to identify all published standardised measures of mental pain. We used qualitative content analysis to evaluate the similarity of each measure, quantified via Jaccard Index scores ranging from no similarity (0) to full similarity (1). Finally, using the Consensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology, we evaluated each measure’s development (assessing 35 features), its content validity (31 features) and if the latter was rated at least adequate, its other psychometric properties. Findings We identified 10 self-reported scales of mental pain in 2658 screened studies relying on diverse definitions of this construct. The highest average similarity coefficient for any given measure was 0.24, indicative of weak similarity (individual pairwise coefficients from 0 to 0.5). Little to no information was provided regarding the development and the content validity of all 10 scales. Therefore, their development and content validity were rated ‘inadequate’ or ‘doubtful’. Conclusions and clinical implications There is not enough evidence of validity to recommend using one measure over others in research or clinical practice. Heterogeneous use of disparate measures across studies limits comparison and combination of their results in meta-analyses. Development by all stakeholders (especially patients) of a consensual patient-reported measure for mental pain is needed. PROSPERO registration number CRD42021242679.
BackgroundPredictors of antidepressant response in older patients with major depressive disorder (MDD) need to be confirmed before they can guide treatment.ObjectiveTo create decision trees for early identification of older patients with MDD who are unlikely to respond to 12 weeks of antidepressant treatment, we analysed data from 454 older participants treated with venlafaxine XR (150–300 mg/day) for up to 12 weeks in the Incomplete Response in Late-Life Depression: Getting to Remission study.MethodsWe selected the earliest decision point when we could detect participants who had not yet responded (defined as >50% symptom improvement) but would do so after 12 weeks of treatment. Using receiver operating characteristic models, we created two decision trees to minimise either false identification of future responders (false positives) or false identification of future non-responders (false negatives). These decision trees integrated baseline characteristics and treatment response at the early decision point as predictors.FindingWe selected week 4 as the optimal early decision point. Both decision trees shared minimal symptom reduction at week 4, longer episode duration and not having responded to an antidepressant previously as predictors of non-response. Test negative predictive values of the leftmost terminal node of the two trees were 77.4% and 76.6%, respectively.ConclusionOur decision trees have the potential to guide treatment in older patients with MDD but they require to be validated in other larger samples.Clinical implicationsOnce confirmed, our findings may be used to guide changes in antidepressant treatment in older patients with poor early response.
Objective There is little evidence for finding optimal antipsychotic treatment for schizophrenia, especially in paediatrics. To evaluate the performance and clinical benefit of several prediction methods for 1-year treatment continuation of antipsychotics. Design and Settings Population-based prognostic study conducting using the nationwide claims database in Korea. Participants 5109 patients aged 2–18 years who initiated antipsychotic treatment with risperidone/aripiprazole for schizophrenia between 2010 and 2017 were identified. Main outcome measures We used the conventional logistic regression (LR) and common six machine-learning methods (least absolute shrinkage and selection operator, ridge, elstic net, randomforest, gradient boosting machine, and superlearner) to derive predictive models for treatment continuation of antipsychotics. The performance of models was assessed using the Brier score (BS), area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC). The clinical benefit of applying these models was also evaluated by comparing the treatment continuation rate between patients who received the recommended medication by models and patients who did not. Results The gradient boosting machine showed the best performance in predicting treatment continuation for risperidone (BS, 0.121; AUROC, 0.686; AUPRC, 0.269). Among aripiprazole models, GBM for BS (0.114), SuperLearner for AUROC (0.688) and random forest for AUPRC (0.317) showed the best performance. Although LR showed lower performance than machine learnings, the difference was negligible. Patients who received recommended medication by these models showed a 1.2–1.5 times higher treatment continuation rate than those who did not. Conclusions All prediction models showed similar performance in predicting the treatment continuation of antipsychotics. Application of prediction models might be helpful for evidence-based decision-making in antipsychotic treatment.
BACKGROUND:Available prediction models of cardiovascular diseases (CVDs) may not accurately predict outcomes among individuals initiating pharmacological treatment for attention-deficit/hyperactivity disorder (ADHD). OBJECTIVE:To improve the predictive accuracy of traditional CVD risk factors for adults initiating pharmacological treatment of ADHD, by considering novel CVD risk factors associated with ADHD (comorbid psychiatric disorders, sociodemographic factors and psychotropic medication). METHODS:The cohort composed of 24 186 adults residing in Sweden without previous CVDs, born between 1932 and 1990, who started pharmacological treatment of ADHD between 2008 and 2011, and were followed for up to 2 years. CVDs were identified using diagnoses according to the International Classification of Diseases, and dispended medication prescriptions from Swedish national registers. Cox proportional hazards regression was employed to derive the prediction model. FINDINGS:The developed model included eight traditional and four novel CVD risk factors. The model showed acceptable overall discrimination (C index=0.72, 95% CI 0.70 to 0.74) and calibration (Brier score=0.008). The Integrated Discrimination Improvement index showed a significant improvement after adding novel risk factors (0.003 (95% CI 0.001 to 0.007), p<0.001). CONCLUSIONS:The inclusion of the novel CVD risk factors may provide a better prediction of CVDs in this population compared with traditional CVD predictors only, when the model is used with a continuous risk score. External validation studies and studies assessing clinical impact of the model are warranted. CLINICAL IMPLICATIONS:Individuals initiating pharmacological treatment of ADHD at higher risk of developing CVDs should be more closely monitored.
BackgroundStudies report an increased risk of self-harm or suicide in people prescribed mirtazapine compared with other antidepressants.ObjectivesTo compare the risk of serious self-harm in people prescribed mirtazapine versus other antidepressants as second-line treatments.Design and settingCohort study using anonymised English primary care electronic health records, hospital admission data and mortality data with study window 1 January 2005 to 30 November 2018.Participants24 516 people diagnosed with depression, aged 18–99 years, initially prescribed a selective serotonin reuptake inhibitor (SSRI) and then prescribed mirtazapine, a different SSRI, amitriptyline or venlafaxine.Main outcome measuresHospitalisation or death due to deliberate self-harm. Age–sex standardised rates were calculated and survival analyses were performed using inverse probability of treatment weighting to account for baseline covariates.ResultsStandardised rates of serious self-harm ranged from 3.8/1000 person-years (amitriptyline) to 14.1/1000 person-years (mirtazapine). After weighting, the risk of serious self-harm did not differ significantly between the mirtazapine group and the SSRI or venlafaxine groups (HRs (95% CI) 1.18 (0.84 to 1.65) and 0.85 (0.51 to 1.41) respectively). The risk was significantly higher in the mirtazapine than the amitriptyline group (3.04 (1.36 to 6.79)) but was attenuated after adjusting for dose.ConclusionsThere was no evidence for a difference in risk between mirtazapine and SSRIs or venlafaxine after accounting for baseline characteristics. The higher risk in the mirtazapine versus the amitriptyline group might reflect residual confounding if amitriptyline is avoided in people considered at risk of self-harm.Clinical implicationsAddressing baseline risk factors and careful monitoring might improve outcomes for people at risk of serious self-harm.
