Combining endpoint and change data did not affect the summary standardised mean difference in pairwise and network meta-analyses: An empirical study in depression.

When studies use different scales to measure continuous outcomes, standardised mean differences (SMD) are required to meta-analyse the data. However, outcomes are often reported as endpoint or change from baseline scores. Combining corresponding SMDs can be problematic and available guidance advises against this practice. We aimed to examine the impact of combining the two types of SMD in meta-analyses of depression severity. We used individual participant data on pharmacological interventions (89 studies, 27,409 participants) and internet-delivered cognitive behavioural therapy (iCBT; 61 studies, 13,687 participants) for depression to compare endpoint and change from baseline SMDs at the study level. Next, we performed pairwise (PWMA) and network meta-analyses (NMA) using endpoint SMDs, change from baseline SMDs, or a mixture of the two. Study-specific SMDs calculated from endpoint and change from baseline data were largely similar, although for iCBT interventions 25% of the studies at 3 months were associated with important differences between study-specific SMDs (median 0.01, IQR -0.10, 0.13) especially in smaller trials with baseline imbalances. However, when pooled, the differences between endpoint and change SMDs were negligible. Pooling only the more favourable of the two SMDs did not materially affect meta-analyses, resulting in differences of pooled SMDs up to 0.05 and 0.13 in the pharmacological and iCBT datasets, respectively. Our findings have implications for meta-analyses in depression, where we showed that the choice between endpoint and change scores for estimating SMDs had immaterial impact on summary meta-analytic estimates. Future studies should replicate and extend our analyses to fields other than depression.

Mortality and adverse events associated with statin use in primary care patients with depression: a real-world, population-based cohort study.

BACKGROUND: New National Institute for Health and Care Excellence (NICE) guidance endorses the prescription of statins in larger population groups for the prevention of cardiovascular and cerebrovascular morbidity and mortality, especially in people with severe mental illness. However, the evidence base for their safety and risk/benefit balance in depression is not established. OBJECTIVES: This study aims to assess the real-world mortality and adverse events of statins in depressive disorders. METHODS: Population-based, nationwide (England), between-subject, cohort study. We used electronic health records (QResearch database) of people aged 18-100 years with first-episode depression, registered with English primary care practices over January 1998-August 2020 for 12(+) months, divided into statin users versus non-users.Primary safety outcomes included all-cause mortality and any adverse event measured at 2, 6 and 12 months. Multivariable logistic regression was employed to control for several potential confounders and calculate adjusted ORs (aORs) with 99% CIs. FINDINGS: From over 1 050 105 patients with depression (42.64% males, mean age 43.23±18.32 years), 21 384 (2.04%) died, while 707 111 (67.34%) experienced at least one adverse event during the 12-month follow-up. Statin use was associated with lower mortality over 12 months (range aOR2-12months 0.66-0.67, range 99% CI 0.60 to 0.73) and with lower adverse events over 6 months (range aOR2-6months 0.90-0.96, range 99% CI 0.91 to 0.99), but not at 1 year (aOR12months 0.99, 99% CI 0.96 to 1.03). No association with any other individual outcome measure (ie, any other neuropsychiatric symptoms) was identified. CONCLUSIONS: We found no evidence that statin use among people with depression increases mortality or other adverse events. CLINICAL IMPLICATIONS: Our findings support the safety of updated NICE guidelines for prescribing statins in people with depressive disorders.

Digital Mental Health for Schizophrenia and Other Severe Mental Illnesses: An International Consensus on Current Challenges and Potential Solutions.

BACKGROUND: Digital approaches may be helpful in augmenting care to address unmet mental health needs, particularly for schizophrenia and severe mental illness (SMI). OBJECTIVE: An international multidisciplinary group was convened to reach a consensus on the challenges and potential solutions regarding collecting data, delivering treatment, and the ethical challenges in digital mental health approaches for schizophrenia and SMI. METHODS: The consensus development panel method was used, with an in-person meeting of 2 groups: the expert group and the panel. Membership was multidisciplinary including those with lived experience, with equal participation at all stages and coproduction of the consensus outputs and summary. Relevant literature was shared in advance of the meeting, and a systematic search of the recent literature on digital mental health interventions for schizophrenia and psychosis was completed to ensure that the panel was informed before the meeting with the expert group. RESULTS: Four broad areas of challenge and proposed solutions were identified: (1) user involvement for real coproduction; (2) new approaches to methodology in digital mental health, including agreed standards, data sharing, measuring harms, prevention strategies, and mechanistic research; (3) regulation and funding issues; and (4) implementation in real-world settings (including multidisciplinary collaboration, training, augmenting existing service provision, and social and population-focused approaches). Examples are provided with more detail on human-centered research design, lived experience perspectives, and biomedical ethics in digital mental health approaches for SMI. CONCLUSIONS: The group agreed by consensus on a number of recommendations: (1) a new and improved approach to digital mental health research (with agreed reporting standards, data sharing, and shared protocols), (2) equal emphasis on social and population research as well as biological and psychological approaches, (3) meaningful collaborations across varied disciplines that have previously not worked closely together, (4) increased focus on the business model and product with planning and new funding structures across the whole development pathway, (5) increased focus and reporting on ethical issues and potential harms, and (6) organizational changes to allow for true communication and coproduction with those with lived experience of SMI. This study approach, combining an international expert meeting with patient and public involvement and engagement throughout the process, consensus methodology, discussion, and publication, is a helpful way to identify directions for future research and clinical implementation in rapidly evolving areas and can be combined with measurements of real-world clinical impact over time. Similar initiatives will be helpful in other areas of digital mental health and similarly fast-evolving fields to focus research and organizational change and effect improved real-world clinical implementation.

Real-world effectiveness of antidepressants, antipsychotics and their combinations in the maintenance treatment of psychotic depression. Evidence from within-subject analyses of two nationwide cohorts.

Psychotic depression (PD) is a severe mental disorder leading to functional disability and high risk of suicide, but very little is known about the comparative effectiveness of medications used in its maintenance treatment. The objective of this study was to investigate the comparative effectiveness of specific antipsychotics and antidepressants, and their combinations, on the risk of psychiatric hospitalization among persons with PD in routine care. Persons aged 16-65 years with a first-time diagnosis of PD were identified from Finnish (years 2000-2018) and Swedish (years 2006-2021) nationwide registers of inpatient care, specialized outpatient care, sickness absence, and disability pension. The main exposures were specific antipsychotics and antidepressants, and the main outcome measure was psychiatric hospitalization as a marker of severe relapse. The risk of hospitalization associated with periods of use vs. non-use of medications (expressed as adjusted hazard ratio, aHR) was assessed by a within-individual design, using each individual as his/her own control, and analyzed with stratified Cox models. The two national cohorts were first analyzed separately, and then combined using a fixed-effect meta-analysis. The Finnish cohort included 19,330 persons (mean age: 39.8±14.7 years; 57.9% women) and the Swedish cohort 13,684 persons (mean age: 41.3±14.0 years; 53.5% women). Individual antidepressants associated with a decreased risk of relapse vs. non-use of antidepressants were bupropion (aHR=0.73, 95% CI: 0.63-0.85), vortioxetine (aHR=0.78, 95% CI: 0.63-0.96) and venlafaxine (aHR=0.92, 95% CI: 0.86-0.98). Any long-acting injectable antipsychotic (LAI) (aHR=0.60, 95% CI: 0.45-0.80) and clozapine (aHR=0.72, 95% CI: 0.57-0.91) were associated with a decreased risk of relapse vs. non-use of antipsychotics. Among monotherapies, only vortioxetine (aHR=0.67, 95% CI: 0.47-0.95) and bupropion (aHR=0.71, 95% CI: 0.56-0.89) were associated with a significantly decreased risk of relapse vs. non-use of both antidepressants and antipsychotics. In an exploratory analysis of antidepressant-antipsychotic combinations, a decreased relapse risk was found for amitriptyline-olanzapine (aHR=0.45, 95% CI: 0.28-0.71), sertraline-quetiapine (aHR=0.79, 95% CI: 0.67-0.93) and venlafaxine-quetiapine (aHR=0.82, 95% CI: 0.73-0.91) vs. non-use of antidepressants and antipsychotics. Benzodiazepines and related drugs (aHR=1.29, 95% CI: 1.24-1.34) and mirtazapine (aHR=1.17, 95% CI: 1.07-1.29) were associated with an increased risk of relapse. These data indicate that, in the maintenance treatment of PD, bupropion, vortioxetine, venlafaxine, any LAI, clozapine, and only few specific antidepressant-antipsychotic combinations are associated with a decreased risk of relapse. These findings challenge the current recommendation by treatment guidelines to combine an antipsychotic with an antidepressant (without further specification) as standard treatment in PD.

Towards precision in the diagnostic profiling of patients: leveraging symptom dynamics as a clinical characterisation dimension in the assessment of major depressive disorder.

BACKGROUND: International guidelines present overall symptom severity as the key dimension for clinical characterisation of major depressive disorder (MDD). However, differences may reside within severity levels related to how symptoms interact in an individual patient, called symptom dynamics. AIMS: To investigate these individual differences by estimating the proportion of patients that display differences in their symptom dynamics while sharing the same overall symptom severity. METHOD: Participants with MDD (n = 73; mean age 34.6 years, s.d. = 13.1; 56.2% female) rated their baseline symptom severity using the Inventory for Depressive Symptomatology Self-Report (IDS-SR). Momentary indicators for depressive symptoms were then collected through ecological momentary assessments five times per day for 28 days; 8395 observations were conducted (average per person: 115; s.d. = 16.8). Each participant's symptom dynamics were estimated using person-specific dynamic network models. Individual differences in these symptom relationship patterns in groups of participants sharing the same symptom severity levels were estimated using individual network invariance tests. Subsequently, the overall proportion of participants that displayed differential symptom dynamics while sharing the same symptom severity was calculated. A supplementary simulation study was conducted to investigate the accuracy of our methodology against false-positive results. RESULTS: Differential symptom dynamics were identified across 63.0% (95% bootstrapped CI 41.0-82.1) of participants within the same severity group. The average false detection of individual differences was 2.2%. CONCLUSIONS: The majority of participants within the same depressive symptom severity group displayed differential symptom dynamics. Examining symptom dynamics provides information about person-specific psychopathological expression beyond severity levels by revealing how symptoms aggravate each other over time. These results suggest that symptom dynamics may be a promising new dimension for clinical characterisation, warranting replication in independent samples. To inform personalised treatment planning, a next step concerns linking different symptom relationship patterns to treatment response and clinical course, including patterns related to spontaneous recovery and forms of disorder progression.

Comparing interventions for early psychosis: a systematic review and component network meta-analysis.

Background: 'Early Intervention in Psychosis' (EIP) services have been associated with improved outcomes for early psychosis. However, these services are heterogeneous and many provide different components of treatment. The impact of this variation on the sustained treatment effects is unknown. Methods: We performed a systematic review and component network meta-analysis (cNMA) of randomised controlled trials (RCTs) that compared specialised intervention services for early psychosis. We searched CENTRAL (published and unpublished), EMBASE, MEDLINE, CINAHL, PsycINFO and Web of Science from inception to February 2023. Primary outcomes were negative and positive psychotic symptoms at 3-month and 1-year follow-up and treatment dropouts. Secondary outcomes were depressive symptoms and social functioning at 1-year follow-up. We registered a protocol for our study in PROSPERO (CRD42017057420). Findings: We identified 37 RCTs including 4599 participants. Participants' mean age was 25.8 years (SD 6.0) and 64.0% were men. We found evidence that psychological interventions (this component grouped all psychological treatment intended to treat, or ameliorate the consequences of, psychotic symptoms) are beneficial for reducing negative symptoms (iSMD -0.24, 95% CI -0.44 to -0.05, p = 0.014) at 3-month follow-up and may be associated with clinically relevant benefits in improving social functioning scores at 1-year follow-up (iSMD -0.52, 95% CI -1.05 to 0.01, p = 0.052). The addition of case management has a beneficial effect on reducing negative symptoms (iSMD -1.17, 95% CI -2.24 to -0.11, p = 0.030) and positive symptoms (iSMD -1.05, 95% CI -2.02 to -0.08, p = 0.033) at 1-year follow-up. Pharmacotherapy was present in all trial arms, meaning it was not possible to examine the specific effects of this component. Interpretation: Our findings suggest psychological interventions and case management in addition to pharmacotherapy as the core components of services for early psychosis to achieve sustained clinical benefits. Our conclusions are limited by the small number of studies and sparsely connected networks. Funding: National Institute for Health and Care Research.

Heterogeneity of outcome measures in depression trials and the relevance of the content of outcome measures to patients: a systematic review.

Research waste occurs when randomised controlled trial (RCT) outcomes are heterogeneous or overlook domains that matter to patients (eg, relating to symptoms or functions). In this systematic review, we reviewed the outcome measures used in 450 RCTs of adult unipolar and bipolar depression registered between 2018 and 2022 and identified 388 different measures. 40% of the RCTs used the same measure (Hamilton Depression Rating Scale [HAMD]). Patients and clinicians matched each item within the 25 most frequently used measures with 80 previously identified domains of depression that matter to patients. Seven (9%) domains were not covered by the 25 most frequently used outcome measures (eg, mental pain and irritability). The HAMD covered a maximum of 47 (59%) of the 80 domains that matter to patients. An interim solution to facilitate evidence synthesis before a core outcome set is developed would be to use the most common measures and choose complementary scales to optimise domain coverage. TRANSLATIONS: For the French and Dutch translations of the abstract see Supplementary Materials section.

Using Electronic Health Records to Facilitate Precision Psychiatry.

The use of clinical prediction models to produce individualized risk estimates can facilitate the implementation of precision psychiatry. As a source of data from large, clinically representative patient samples, electronic health records (EHRs) provide a platform to develop and validate clinical prediction models, as well as potentially implement them in routine clinical care. The current review describes promising use cases for the application of precision psychiatry to EHR data and considers their performance in terms of discrimination (ability to separate individuals with and without the outcome) and calibration (extent to which predicted risk estimates correspond to observed outcomes), as well as their potential clinical utility (weighing benefits and costs associated with the model compared to different approaches across different assumptions of the number needed to test). We review 4 externally validated clinical prediction models designed to predict psychosis onset, psychotic relapse, cardiometabolic morbidity, and suicide risk. We then discuss the prospects for clinically implementing these models and the potential added value of integrating data from evidence syntheses, standardized psychometric assessments, and biological data into EHRs. Clinical prediction models can utilize routinely collected EHR data in an innovative way, representing a unique opportunity to inform real-world clinical decision making. Combining data from other sources (e.g., meta-analyses) or enhancing EHR data with information from research studies (clinical and biomarker data) may enhance our abilities to improve the performance of clinical prediction models.

Shortening the Alzheimer's disease assessment scale cognitive subscale.

BACKGROUND: A short yet reliable cognitive measure is needed that separates treatment and placebo for treatment trials for Alzheimer's disease. Hence, we aimed to shorten the Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS-Cog) and test its use as an efficacy measure. METHODS: Secondary data analysis of participant-level data from five pivotal clinical trials of donepezil compared with placebo for Alzheimer's disease (N = 2,198). Across all five trials, cognition was appraised using the original 11-item ADAS-Cog. Statistical analysis consisted of sample characterization, item response theory (IRT) to identify an ADAS-Cog short version, and mixed models for repeated-measures analysis to examine the effect sizes of ADAS-Cog change on the original and short versions in the placebo versus donepezil groups. RESULTS: Based on IRT, a short ADAS-Cog was developed with seven items and two response options. The original and short ADAS-Cog correlated at baseline and at weeks 12 and 24 at 0.7. Effect sizes based on mixed modeling showed that the short and original ADAS-Cog separated placebo and donepezil comparably (ADAS-Cog original ES = 0.33, 95% CI = 0.29, 0.40, ADAS-Cog short ES = 0.25, 95% CI =0.23, 0.34). CONCLUSIONS: IRT identified a short ADAS-cog version that separated donepezil and placebo, suggesting its clinical potential for assessment and treatment monitoring.

Efficacy and effectiveness of antipsychotics in schizophrenia: network meta-analyses combining evidence from randomised controlled trials and real-world data.

BACKGROUND: There is debate about the generalisability of results from randomised clinical trials (RCTs) to real-world settings. Studying outcomes of treatments for schizophrenia can shed light on this issue and inform treatment guidelines. We therefore compared the efficacy and effectiveness of antipsychotics for relapse prevention in schizophrenia and estimated overall treatment effects using all available RCT and real-world evidence. METHODS: We conducted network meta-analyses using individual participant data from Swedish and Finnish national registries and aggregate data from RCTs. The target population was adults (age >18 and <65 years) with schizophrenia and schizoaffective disorder with stabilised symptoms. We analysed each registry separately to obtain hazard ratios (HRs) and 95% CIs for relapse within 6 months post-antipsychotic initiation as our main outcome. Interventions studied were antipsychotics, no antipsychotic use, and placebo. We compared HRs versus a reference drug (oral haloperidol) between registries, and between registry individuals who would be eligible and ineligible for RCTs, using the ratio of HRs. We synthesised evidence using network meta-analysis and compared results from our network meta-analysis of real-world data with our network meta-analysis of RCT data, including oral versus long-acting injectable (LAI) formulations. Finally, we conducted a joint real-world and RCT network meta-analysis. FINDINGS: We included 90 469 individuals from the Swedish and Finnish registries (mean age 45·9 [SD 14·6] years; 43 025 [47·5%] women and 47 467 [52·5%] men, ethnicity data unavailable) and 10 091 individuals from 30 RCTs (mean age 39·6 years [SD 11·7]; 3724 [36·9%] women and 6367 [63·1%] men, 6022 White [59·7%]). We found good agreement in effectiveness of antipsychotics between Swedish and Finnish registries (HR ratio 0·97, 95% CI 0·88-1·08). Drug effectiveness versus no antipsychotic was larger in RCT-eligible than RCT-ineligible individuals (HR ratio 1·40 [1·24-1·59]). Efficacy versus placebo in RCTs was larger than effectiveness versus no antipsychotic in real-world (HR ratio 2·58 [2·02-3·30]). We found no evidence of differences between effectiveness and efficacy for between-drug comparisons (HR ratio vs oral haloperidol 1·17 [0·83-1·65], where HR ratio >1 means superior effectiveness in real-world to RCTs), except for LAI versus oral comparisons (HR ratio 0·73 [0·53-0·99], indicating superior effectiveness in real-world data relative to RCTs). The real-world network meta-analysis showed clozapine was most effective, followed by olanzapine LAI. The RCT network meta-analysis exhibited heterogeneity and inconsistency. The joint real-world and RCT network meta-analysis identified olanzapine as the most efficacious antipsychotic amongst those present in both RCTs and the real world registries. INTERPRETATION: LAI antipsychotics perform slightly better in the real world than according to RCTs. Otherwise, RCT evidence was in line with real-world evidence for most between-drug comparisons, but RCTs might overestimate effectiveness of antipsychotics observed in routine care settings. Our results further the understanding of the generalisability of RCT findings to clinical practice and can inform preferential prescribing guidelines. FUNDING: None.

Estimating the smallest worthwhile difference of antidepressants: a cross-sectional survey.

BACKGROUND: Approximately 30% of patients experience substantial improvement in depression after 2 months without treatment, and 45% with antidepressants. The smallest worthwhile difference (SWD) refers to an intervention's smallest beneficial effect over a comparison patients deem worthwhile given treatment burdens (harms, expenses and inconveniences), but is undetermined for antidepressants. OBJECTIVE: Estimating the SWD of commonly prescribed antidepressants for depression compared to no treatment. METHODS: The SWD was estimated as a patient-required difference in response rates between antidepressants and no treatment after 2 months. An online cross-sectional survey using Prolific, MQ Mental Health and Amazon Mechanical Turk crowdsourcing services in the UK and USA between October 2022 and January 2023 garnered participants (N=935) that were a mean age of 44.1 (SD=13.9) and 66% women (n=617). FINDINGS: Of 935 participants, 124 reported moderate-to-severe depressive symptoms but were not in treatment, 390 were in treatment and 495 reported absent-to-mild symptoms with or without treatment experiences. The median SWD was a 20% (IQR=10-30%) difference in response rates for people with moderate-to-severe depressive symptoms, not in treatment, and willing to consider antidepressants, and 25% (IQR=10-35%) for the full sample. CONCLUSIONS: Our observed SWDs mean that the current 15% antidepressant benefit over no treatment was sufficient for one in three people to accept antidepressants given the burdens, but two in three expected greater treatment benefits. IMPLICATIONS: While a minority may be satisfied with the best currently available antidepressants, more effective and/or less burdensome medications are needed, with more attention given to patient perspectives.

Treatment Outcomes With Licensed and Unlicensed Stimulant Doses for Adults With Attention-Deficit/Hyperactivity Disorder: A Systematic Review and Meta-Analysis.

Importance: Stimulants (methylphenidate and amphetamines) are often prescribed at unlicensed doses for adults with attention-deficit/hyperactivity disorder (ADHD). Whether dose escalation beyond US Food and Drug Administration recommendations is associated with positive risk benefits is unclear. Objective: To investigate the impact, based on averages, of stimulant doses on treatment outcomes in adults with ADHD and to determine, based on averages, whether unlicensed doses are associated with positive risk benefits compared with licensed doses. Data Sources: Twelve databases, including published (PubMed, Cochrane Library, Embase, Web of Sciences) and unpublished (ClinicalTrials.gov) literature, up to February 22, 2023, without language restrictions. Study Selection: Two researchers independently screened records to identify double-blinded randomized clinical trials of stimulants against placebo in adults (18 years and older) with ADHD. Data Extraction and Synthesis: Aggregate data were extracted and synthesized in random-effects dose-response meta-analyses and network meta-analyses. Main Outcome Measures: Change in ADHD symptoms and discontinuations due to adverse events. Results: A total of 47 randomized clinical trials (7714 participants; mean age, 35 (SD, 11) years; 4204 male [56%]) were included. For methylphenidate, dose-response curves indicated additional reductions of symptoms with increments in doses, but the gains were progressively smaller and accompanied by continued additional risk of adverse events dropouts. Network meta-analyses showed that unlicensed doses were associated with greater reductions of symptoms compared with licensed doses (standardized mean difference [SMD], -0.23; 95% CI, -0.44 to -0.02; very low certainty of evidence), but the additional gain was small and accompanied by increased risk of adverse event dropouts (odds ratio, 2.02; 95% CI, 1.19-3.43; moderate certainty of evidence). For amphetamines, the dose-response curve approached a plateau and increments in doses did not indicate additional reductions of symptoms, but there were continued increments in the risk of adverse event dropouts. Network meta-analysis did not identify differences between unlicensed and licensed doses for reductions of symptoms (SMD, -0.08; 95% CI, -0.24 to 0.08; very low certainty of evidence). Conclusions and Relevance: Based on group averages, unlicensed doses of stimulants may not have positive risk benefits compared with licensed doses for adults with ADHD. In general, practitioners should consider unlicensed doses cautiously. Practitioners may trial unlicensed doses if needed and tolerated but should be aware that there may not be large gains in the response to the medication with those further increments in dose. However, the findings are averages and will not generalize to every patient.

Assessing the Impact of Evidence-Based Mental Health Guidance During the COVID-19 Pandemic: Systematic Review and Qualitative Evaluation.

BACKGROUND: During the COVID-19 pandemic, the Oxford Precision Psychiatry Lab (OxPPL) developed open-access web-based summaries of mental health care guidelines (OxPPL guidance) in key areas such as digital approaches and telepsychiatry, suicide and self-harm, domestic violence and abuse, perinatal care, and vaccine hesitancy and prioritization in the context of mental illness, to inform timely clinical decision-making. OBJECTIVE: This study aimed to evaluate the practice of creating evidence-based health guidelines during health emergencies using the OxPPL guidance as an example. An international network of clinical sites and colleagues (in Australia, New Zealand, and the United Kingdom) including clinicians, researchers, and experts by experience aimed to (1) evaluate the clinical impact of the OxPPL guidance, as an example of an evidence-based summary of guidelines; (2) review the literature for other evidence-based summaries of COVID-19 guidelines regarding mental health care; and (3) produce a framework for response to future global health emergencies. METHODS: The impact and clinical utility of the OxPPL guidance were assessed using clinicians' feedback via an international survey and focus groups. A systematic review (protocol registered on Open Science Framework) identified summaries or syntheses of guidelines for mental health care during and after the COVID-19 pandemic and assessed the accuracy of the methods used in the OxPPL guidance by identifying any resources that the guidance had not included. RESULTS: Overall, 80.2% (146/182) of the clinicians agreed or strongly agreed that the OxPPL guidance answered important clinical questions, 73.1% (133/182) stated that the guidance was relevant to their service, 59.3% (108/182) said that the guidelines had or would have a positive impact on their clinical practice, 42.9% (78/182) that they had shared or would share the guidance, and 80.2% (146/182) stated that the methodology could be used during future health crises. The focus groups found that the combination of evidence-based knowledge, clinical viewpoint, and visibility was crucial for clinical implementation. The systematic review identified 2543 records, of which 2 syntheses of guidelines met all the inclusion criteria, but only 1 (the OxPPL guidance) used evidence-based methodology. The review showed that the OxPPL guidance had included the majority of eligible guidelines, but 6 were identified that had not been included. CONCLUSIONS: The study identified an unmet need for web-based, evidence-based mental health care guidance during the COVID-19 pandemic. The OxPPL guidance was evaluated by clinicians as having a real-world clinical impact. Robust evidence-based methodology and expertise in mental health are necessary, but easy accessibility is also needed, and digital technology can materially help. Further health emergencies are inevitable and now is the ideal time to prepare, including addressing the training needs of clinicians, patients, and carers, especially in areas such as telepsychiatry and digital mental health. For future planning, guidance should be widely disseminated on an international platform, with allocated resources to support adaptive updates.

Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis.

BACKGROUND: The relative treatment effects estimated from network meta-analysis can be employed to rank treatments from the most preferable to the least preferable option. These treatment hierarchies are typically based on ranking metrics calculated from a single outcome. Some approaches have been proposed in the literature to account for multiple outcomes and individual preferences, such as the coverage area inside a spie chart, that, however, does not account for a trade-off between efficacy and safety outcomes. We present the net-benefit standardised area within a spie chart, [Formula: see text] to explore the changes in treatment performance with different trade-offs between benefits and harms, according to a particular set of preferences. METHODS: We combine the standardised areas within spie charts for efficacy and safety/acceptability outcomes with a value λ specifying the trade-off between benefits and harms. We derive absolute probabilities and convert outcomes on a scale between 0 and 1 for inclusion in the spie chart. RESULTS: We illustrate how the treatments in three published network meta-analyses perform as the trade-off λ varies. The decrease of the [Formula: see text] quantity appears more pronounced for some drugs, e.g. haloperidol. Changes in treatment performance seem more frequent when SUCRA is employed as outcome measures in the spie charts. CONCLUSIONS: [Formula: see text] should not be interpreted as a ranking metric but it is a simple approach that could help identify which treatment is preferable when multiple outcomes are of interest and trading-off between benefits and harms is important.

Pharmacological treatments in panic disorder in adults: a network meta-analysis.

BACKGROUND: A panic attack is a discrete period of fear or anxiety that has a rapid onset and reaches a peak within 10 minutes. The main symptoms involve bodily systems, such as racing heart, chest pain, sweating, shaking, dizziness, flushing, churning stomach, faintness and breathlessness. Other recognised panic attack symptoms involve fearful cognitions, such as the fear of collapse, going mad or dying, and derealisation (the sensation that the world is unreal). Panic disorder is common in the general population with a prevalence of 1% to 4%. The treatment of panic disorder includes psychological and pharmacological interventions, including antidepressants and benzodiazepines. OBJECTIVES: To compare, via network meta-analysis, individual drugs (antidepressants and benzodiazepines) or placebo in terms of efficacy and acceptability in the acute treatment of panic disorder, with or without agoraphobia. To rank individual active drugs for panic disorder (antidepressants, benzodiazepines and placebo) according to their effectiveness and acceptability. To rank drug classes for panic disorder (selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), tricyclic antidepressants (TCAs), mono-amine oxidase inhibitors (MAOIs) and benzodiazepines (BDZs) and placebo) according to their effectiveness and acceptability. To explore heterogeneity and inconsistency between direct and indirect evidence in a network meta-analysis. SEARCH METHODS: We searched the Cochrane Common Mental Disorders Specialised Register, CENTRAL, CDSR, MEDLINE, Ovid Embase and PsycINFO to 26 May 2022. SELECTION CRITERIA: We included randomised controlled trials (RCTs) of people aged 18 years or older of either sex and any ethnicity with clinically diagnosed panic disorder, with or without agoraphobia. We included trials that compared the effectiveness of antidepressants and benzodiazepines with each other or with a placebo. DATA COLLECTION AND ANALYSIS: Two authors independently screened titles/abstracts and full texts, extracted data and assessed risk of bias. We analysed dichotomous data and continuous data as risk ratios (RRs), mean differences (MD) or standardised mean differences (SMD): response to treatment (i.e. substantial improvement from baseline as defined by the original investigators: dichotomous outcome), total number of dropouts due to any reason (as a proxy measure of treatment acceptability: dichotomous outcome), remission (i.e. satisfactory end state as defined by global judgement of the original investigators: dichotomous outcome), panic symptom scales and global judgement (continuous outcome), frequency of panic attacks (as recorded, for example, by a panic diary; continuous outcome), agoraphobia (dichotomous outcome). We assessed the certainty of evidence using threshold analyses. MAIN RESULTS: Overall, we included 70 trials in this review. Sample sizes ranged between 5 and 445 participants in each arm, and the total sample size per study ranged from 10 to 1168. Thirty-five studies included sample sizes of over 100 participants. There is evidence from 48 RCTs (N = 10,118) that most medications are more effective in the response outcome than placebo. In particular, diazepam, alprazolam, clonazepam, paroxetine, venlafaxine, clomipramine, fluoxetine and adinazolam showed the strongest effect, with diazepam, alprazolam and clonazepam ranking as the most effective. We found heterogeneity in most of the comparisons, but our threshold analyses suggest that this is unlikely to impact the findings of the network meta-analysis. Results from 64 RCTs (N = 12,310) suggest that most medications are associated with either a reduced or similar risk of dropouts to placebo. Alprazolam and diazepam were associated with a lower dropout rate compared to placebo and were ranked as the most tolerated of all the medications examined. Thirty-two RCTs (N = 8569) were included in the remission outcome. Most medications were more effective than placebo, namely desipramine, fluoxetine, clonazepam, diazepam, fluvoxamine, imipramine, venlafaxine and paroxetine, and their effects were clinically meaningful. Amongst these medications, desipramine and alprazolam were ranked highest. Thirty-five RCTs (N = 8826) are included in the continuous outcome reduction in panic scale scores. Brofaromine, clonazepam and reboxetine had the strongest reductions in panic symptoms compared to placebo, but results were based on either one trial or very small trials. Forty-one RCTs (N = 7853) are included in the frequency of panic attack outcome. Only clonazepam and alprazolam showed a strong reduction in the frequency of panic attacks compared to placebo, and were ranked highest. Twenty-six RCTs (N = 7044) provided data for agoraphobia. The strongest reductions in agoraphobia symptoms were found for citalopram, reboxetine, escitalopram, clomipramine and diazepam, compared to placebo. For the pooled intervention classes, we examined the two primary outcomes (response and dropout). The classes of medication were: SSRIs, SNRIs, TCAs, MAOIs and BDZs. For the response outcome, all classes of medications examined were more effective than placebo. TCAs as a class ranked as the most effective, followed by BDZs and MAOIs. SSRIs as a class ranked fifth on average, while SNRIs were ranked lowest. When we compared classes of medication with each other for the response outcome, we found no difference between classes. Comparisons between MAOIs and TCAs and between BDZs and TCAs also suggested no differences between these medications, but the results were imprecise. For the dropout outcome, BDZs were the only class associated with a lower dropout compared to placebo and were ranked first in terms of tolerability. The other classes did not show any difference in dropouts compared to placebo. In terms of ranking, TCAs are on average second to BDZs, followed by SNRIs, then by SSRIs and lastly by MAOIs. BDZs were associated with lower dropout rates compared to SSRIs, SNRIs and TCAs. The quality of the studies comparing antidepressants with placebo was moderate, while the quality of the studies comparing BDZs with placebo and antidepressants was low. AUTHORS' CONCLUSIONS: In terms of efficacy, SSRIs, SNRIs (venlafaxine), TCAs, MAOIs and BDZs may be effective, with little difference between classes. However, it is important to note that the reliability of these findings may be limited due to the overall low quality of the studies, with all having unclear or high risk of bias across multiple domains. Within classes, some differences emerged. For example, amongst the SSRIs paroxetine and fluoxetine seem to have stronger evidence of efficacy than sertraline. Benzodiazepines appear to have a small but significant advantage in terms of tolerability (incidence of dropouts) over other classes.

Real-world outcomes of concomitant antidepressant and statin use in primary care patients with depression: a population-based cohort study.

BACKGROUND: Antidepressants are licensed for use in depressive disorders, but non-response and poor adherence to treatment affect a considerable number of patients. Pre-clinical and clinical evidence suggest that statins can augment the effects of antidepressants. However, the acceptability and tolerability of combining statins with antidepressants are unclear, and their add-on efficacy has only been shown in small, short-term clinical trials. Observational data can provide complementary information about treatment effects on larger samples over longer follow-ups. In this study, we therefore assessed the real-world acceptability, tolerability, and efficacy of concomitant antidepressant and statin treatment in depression. METHODS: We conducted a population-based cohort study investigating QResearch primary care research database, which comprises the anonymised electronic healthcare records of 35 + million patients over 1574 English general practices. Patients aged 18-100 years, registered between January 1998 and August 2020, diagnosed with a new episode of depression, and commencing an antidepressant were included. Using a between-subject design, we identified two study groups: antidepressant + statin versus antidepressant-only prescriptions. Outcomes of interest included the following: antidepressant treatment discontinuations due to any cause (acceptability) and due to any adverse event (tolerability) and effects on depressive symptoms (efficacy) measured as response, remission, and change in depression score on the Patient Health Questionnaire-9. All outcomes were assessed at 2, 6, and 12 months using multivariable regression analyses, adjusted for relevant confounders, to calculate adjusted odds ratios (aORs) or mean differences (aMDs) with 99% confidence intervals (99% CIs). RESULTS: Compared to antidepressant-only (N 626,335), antidepressant + statin (N 46,482) was associated with higher antidepressant treatment acceptability (aOR2months 0.88, 99% CI 0.85 to 0.91; aOR6months 0.81, 99% CI 0.79 to 0.84; aOR12months 0.78, 99% CI 0.75 to 0.81) and tolerability (aOR2months 0.92, 99% CI 0.87 to 0.98; aOR6months 0.94, 99% CI 0.89 to 0.99, though not long term aOR12 months 1.02, 99% CI 0.97 to 1.06). Efficacy did not differ between groups (range aOR2-12 months 1.00 and 1.02 for response and remission, range aOR2-12 months - 0.01 and - 0.02 for change in depression score). CONCLUSIONS: On real-world data, there is a positive correlation between antidepressant treatment adherence and statin use, partly explained by fewer dropouts due to adverse events. The main limitation of our study is its observational design, which restricts the potential to make causal inferences.

An umbrella review of adverse effects associated with antipsychotic medications: the need for complementary study designs.

Antipsychotic medications are widely prescribed in psychotic illnesses and other mental disorders. Effectiveness is well-established, particularly for reducing symptoms such as delusions and hallucinations, but can be impacted by tolerability. Adverse effects are wide-ranging, and vary between antipsychotics, which is clinically important. This umbrella review aimed to comprehensively summarise the extent and quality of evidence for adverse effects associated with antipsychotic use in people with mental disorders. We included 32 meta-analyses of randomised trials and observational studies. The overall robustness of reported associations was considered in terms of review quality, heterogeneity, excess significance bias, and prediction intervals. Using this approach, endocrine and metabolic, movement-related, and sedation and sleep problems were the clinical domains with strongest evidence. The overall quality of included meta-analyses was low, and individual adverse effects were not typically examined in meta-analyses of both randomised trials and observational study designs. Future reviews should focus on adhering to methodological guidelines, consider the complementary strengths of different study designs, and integrate clinically relevant information on absolute rates and severity of adverse effects.