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.

Comparative efficacy and tolerability of 32 oral and long-acting injectable antipsychotics for the maintenance treatment of adults with schizophrenia: a systematic review and network meta-analysis.

BACKGROUND: Schizophrenia is a common, severe, and usually chronic disorder. Maintenance treatment with antipsychotic drugs can prevent relapse but also causes side-effects. We aimed to compare the efficacy and tolerability of antipsychotics as maintenance treatment for non-treatment resistant patients with schizophrenia. METHODS: In this systematic review and network meta-analysis, we searched, without language restrictions, the Cochrane Schizophrenia Group's specialised register between database inception and April 27, 2020, PubMed from April 1, 2020, to Jan 15, 2021, and the lists of included studies from related systematic reviews. We included randomised controlled trials (RCTs; ≥12 weeks of follow-up) that recruited adult participants with schizophrenia or schizoaffective disorder with stable symptoms who were treated with antipsychotics (monotherapy; oral or long-acting injectable) or placebo. We excluded RCTs of participants with specific comorbidities or treatment resistance. In duplicate, two authors independently selected eligible RCTs and extracted aggregate data. The primary outcome was the number of participants who relapsed and was analysed by random-effects, Bayesian network meta-analyses. The study was registered on PROSPERO, CRD42016049022. FINDINGS: We identified 4157 references through our search, from which 501 references on 127 RCTs of 32 antipsychotics (comprising 18 152 participants) were included. 100 studies including 16 812 participants and 30 antipsychotics contributed to our network meta-analysis of the primary outcome. All antipsychotics had risk ratios (RRs) less than 1·00 when compared with placebo for relapse prevention and almost all had 95% credible intervals (CrIs) excluding no effect. RRs ranged from 0·20 (95% CrI 0·05-0·41) for paliperidone oral to 0·65 (0·16-1·14) for cariprazine oral (moderate-to-low confidence in estimates). Generally, we interpret that there was no clear evidence for the superiority of specific antipsychotics in terms of relapse prevention because most comparisons between antipsychotics included a probability of no difference. INTERPRETATION: As we found no clear differences between antipsychotics for relapse prevention, we conclude that the choice of antipsychotic for maintenance treatment should be guided mainly by their tolerability. FUNDING: The German Ministry of Education and Research and Oxford Health Biomedical Research Centre.

Comparative effects of pharmacological interventions for the acute and long-term management of insomnia disorder in adults: a systematic review and network meta-analysis.

BACKGROUND: Behavioural, cognitive, and pharmacological interventions can all be effective for insomnia. However, because of inadequate resources, medications are more frequently used worldwide. We aimed to estimate the comparative effectiveness of pharmacological treatments for the acute and long-term treatment of adults with insomnia disorder. METHODS: In this systematic review and network meta-analysis, we searched the Cochrane Central Register of Controlled Trials, MEDLINE, PubMed, Embase, PsycINFO, WHO International Clinical Trials Registry Platform, ClinicalTrials.gov, and websites of regulatory agencies from database inception to Nov 25, 2021, to identify published and unpublished randomised controlled trials. We included studies comparing pharmacological treatments or placebo as monotherapy for the treatment of adults (≥18 year) with insomnia disorder. We assessed the certainty of evidence using the confidence in network meta-analysis (CINeMA) framework. Primary outcomes were efficacy (ie, quality of sleep measured by any self-rated scale), treatment discontinuation for any reason and due to side-effects specifically, and safety (ie, number of patients with at least one adverse event) both for acute and long-term treatment. We estimated summary standardised mean differences (SMDs) and odds ratios (ORs) using pairwise and network meta-analysis with random effects. This study is registered with Open Science Framework, https://doi.org/10.17605/OSF.IO/PU4QJ. FINDINGS: We included 170 trials (36 interventions and 47 950 participants) in the systematic review and 154 double-blind, randomised controlled trials (30 interventions and 44 089 participants) were eligible for the network meta-analysis. In terms of acute treatment, benzodiazepines, doxylamine, eszopiclone, lemborexant, seltorexant, zolpidem, and zopiclone were more efficacious than placebo (SMD range: 0·36-0·83 [CINeMA estimates of certainty: high to moderate]). Benzodiazepines, eszopiclone, zolpidem, and zopiclone were more efficacious than melatonin, ramelteon, and zaleplon (SMD 0·27-0·71 [moderate to very low]). Intermediate-acting benzodiazepines, long-acting benzodiazepines, and eszopiclone had fewer discontinuations due to any cause than ramelteon (OR 0·72 [95% CI 0·52-0·99; moderate], 0·70 [0·51-0·95; moderate] and 0·71 [0·52-0·98; moderate], respectively). Zopiclone and zolpidem caused more dropouts due to adverse events than did placebo (zopiclone: OR 2·00 [95% CI 1·28-3·13; very low]; zolpidem: 1·79 [1·25-2·50; moderate]); and zopiclone caused more dropouts than did eszopiclone (OR 1·82 [95% CI 1·01-3·33; low]), daridorexant (3·45 [1·41-8·33; low), and suvorexant (3·13 [1·47-6·67; low]). For the number of individuals with side-effects at study endpoint, benzodiazepines, eszopiclone, zolpidem, and zopiclone were worse than placebo, doxepin, seltorexant, and zaleplon (OR range 1·27-2·78 [high to very low]). For long-term treatment, eszopiclone and lemborexant were more effective than placebo (eszopiclone: SMD 0·63 [95% CI 0·36-0·90; very low]; lemborexant: 0·41 [0·04-0·78; very low]) and eszopiclone was more effective than ramelteon (0.63 [0·16-1·10; very low]) and zolpidem (0·60 [0·00-1·20; very low]). Compared with ramelteon, eszopiclone and zolpidem had a lower rate of all-cause discontinuations (eszopiclone: OR 0·43 [95% CI 0·20-0·93; very low]; zolpidem: 0·43 [0·19-0·95; very low]); however, zolpidem was associated with a higher number of dropouts due to side-effects than placebo (OR 2·00 [95% CI 1·11-3·70; very low]). INTERPRETATION: Overall, eszopiclone and lemborexant had a favorable profile, but eszopiclone might cause substantial adverse events and safety data on lemborexant were inconclusive. Doxepin, seltorexant, and zaleplon were well tolerated, but data on efficacy and other important outcomes were scarce and do not allow firm conclusions. Many licensed drugs (including benzodiazepines, daridorexant, suvorexant, and trazodone) can be effective in the acute treatment of insomnia but are associated with poor tolerability, or information about long-term effects is not available. Melatonin, ramelteon, and non-licensed drugs did not show overall material benefits. These results should serve evidence-based clinical practice. FUNDING: UK National Institute for Health Research Oxford Health Biomedical Research Centre.

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.

Development of a model to predict antidepressant treatment response for depression among Veterans.

BACKGROUND: Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA). METHODS: A 2018-2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample. RESULTS: In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors. CONCLUSIONS: Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.

Placebo and nocebo responses in randomised, controlled trials of medications for ADHD: a systematic review and meta-analysis.

The nature and magnitude of placebo and nocebo responses to ADHD medications and the extent to which response to active medications and placebo are inter-correlated is unclear. To assess the magnitude of placebo and nocebo responses to ADHD and their association with active treatment response. We searched literature until June 26, 2019, for published/unpublished double-blind, randomised placebo-controlled trials (RCTs) of ADHD medication. Authors were contacted for additional data. We assessed placebo effects on efficacy and nocebo effects on tolerability using random effects meta-analysis. We assessed the association of study design and patient features with placebo/nocebo response. We analysed 128 RCTs (10,578 children/adolescents and 9175 adults) and found significant and heterogenous placebo effects for all efficacy outcomes, with no publication bias. The placebo effect was greatest for clinician compared with other raters. We found nocebo effects on tolerability outcomes. Efficacy outcomes from most raters showed significant positive correlations between the baseline to endpoint placebo effects and the baseline to endpoint drug effects. Placebo and nocebo effects did not differ among drugs. Baseline severity and type of rating scale influenced the findings. Shared non-specific factors influence response to both placebo and active medication. Although ADHD medications are superior to placebo, and placebo treatment in clinical practice is not feasible, clinicians should attempt to incorporate factors associated with placebo effects into clinical care. Future studies should explore how such effects influence response to medication treatment. Upon publication, data will be available in Mendeley Data: PROSPERO (CRD42019130292).

Gabapentin and pregabalin in bipolar disorder, anxiety states, and insomnia: Systematic review, meta-analysis, and rationale.

The gabapentinoids, gabapentin, and pregabalin, target the α2δ subunits of voltage-gated calcium channels. Initially licensed for pain and seizures, they have become widely prescribed drugs. Many of these uses are off-label for psychiatric indications, and there is increasing concern about their safety, so it is particularly important to have good evidence to justify this usage. We conducted a systematic review and meta-analysis of the evidence for three of their common psychiatric uses: bipolar disorder, anxiety, and insomnia. Fifty-five double-blind randomised controlled trials (RCTs) and 15 open-label studies were identified. For bipolar disorder, four double-blind RCTs investigating gabapentin, and no double-blind RCTs investigating pregabalin, were identified. A quantitative synthesis could not be performed due to heterogeneity in the study population, design and outcome measures. Across the anxiety spectrum, a consistent but not universal effect in favour of gabapentinoids compared to placebo was seen (standardised mean difference [SMD] ranging between -2.25 and -0.25). Notably, pregabalin (SMD -0.55, 95% CI -0.92 to -0.18) and gabapentin (SMD -0.92, 95% CI -1.32 to -0.52) were more effective than placebo in reducing preoperative anxiety. In insomnia, results were inconclusive. We conclude that there is moderate evidence of the efficacy of gabapentinoids in anxiety states, but minimal evidence in bipolar disorder and insomnia and they should be used for these disorders only with strong justification. This recommendation applies despite the attractive pharmacological and genetic rationale for targeting voltage-gated calcium channels.

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.

Perinatal mental health and COVID-19: Navigating a way forward.

The COVID-19 pandemic and its aftermath have increased pre-existing inequalities and risk factors for mental disorders in general, but perinatal mental disorders are of particular concern. They are already underdiagnosed and undertreated, and this has been magnified by the pandemic. Access to services (both psychiatric and obstetric) has been reduced, and in-person contact has been restricted because of the increased risks. Rates of perinatal anxiety and depressive symptoms have increased. In the face of these challenges, clear guidance in perinatal mental health is needed for patients and clinicians. However, a systematic search of the available resources showed only a small amount of guidance from a few countries, with a focus on the acute phase of the pandemic rather than the challenges of new variants and variable rates of infection. Telepsychiatry offers advantages during times of restricted social contact and also as an additional route for accessing a wide range of digital technologies. While there is a strong evidence base for general telepsychiatry, the particular issues in perinatal mental health need further examination. Clinicians will need expertise and training to navigate a hybrid model, flexibly combining in person and remote assessments according to risk, clinical need and individual patient preferences. There are also wider issues of care planning in the context of varying infection rates, restrictions and vaccination access in different countries. Clinicians will need to focus on prevention, treatment, risk assessment and symptom monitoring, but there will also need to be an urgent and coordinated focus on guidance and planning across all organisations involved in perinatal mental health care.

Community interventions for anxiety and depression in adults and young people: A systematic review.

BACKGROUND: Growing evidence suggests that community-based interventions may be effective for anxiety and depression. This study aimed to describe studies of community interventions delivered to adults and/or young people, either in person or online, evaluated in randomised controlled trials and provide an indication as to their effectiveness, acceptability, quality of data and where possible, mechanisms of action. We included interventions delivered at and/or by museums, art galleries, libraries, gardens, music groups/choirs and sports clubs. METHOD: We developed and followed a preregistered protocol: PROSPERO CRD42020204471. Randomised controlled trials in adults and young people were identified in an extensive search with no date/time, language, document type and publication status limitations. Studies were selected according to predetermined eligibility criteria and data independently extracted and then assessed using Risk of Bias 1. The studies were deemed too heterogeneous for meta-analysis and were therefore reported using a narrative synthesis. RESULTS: Our analysis included 31 studies, with 2898 participants. Community interventions most studied in randomised controlled trials were community music (12 studies, 1432 participants), community exercise (14 studies, 955 participants) and community gardens/gardening (6 studies, 335 participants). The majority of studies were from high-income countries - many were in specific populations (such as those with physical health problems) and were generally of low quality. Dropout rates across the included studies were low (1 participant on average per 100 participants). The inadequate description of interventions limited identification of potential mechanisms of action. DISCUSSION: The uncertainty of the evidence allows only a weak recommendation in support of community interventions for anxiety and depression. The results suggest community engagement is a promising area for wide-reaching interventions to be implemented and evaluated, but more high-quality trials are needed, especially in young people and under-represented communities.

The Impact of the COVID-19 Pandemic and Associated Control Measures on the Mental Health of the General Population : A Systematic Review and Dose-Response Meta-analysis.

BACKGROUND: To what extent the COVID-19 pandemic and its containment measures influenced mental health in the general population is still unclear. PURPOSE: To assess the trajectory of mental health symptoms during the first year of the pandemic and examine dose-response relations with characteristics of the pandemic and its containment. DATA SOURCES: Relevant articles were identified from the living evidence database of the COVID-19 Open Access Project, which indexes COVID-19-related publications from MEDLINE via PubMed, Embase via Ovid, and PsycInfo. Preprint publications were not considered. STUDY SELECTION: Longitudinal studies that reported data on the general population's mental health using validated scales and that were published before 31 March 2021 were eligible. DATA EXTRACTION: An international crowd of 109 trained reviewers screened references and extracted study characteristics, participant characteristics, and symptom scores at each timepoint. Data were also included for the following country-specific variables: days since the first case of SARS-CoV-2 infection, the stringency of governmental containment measures, and the cumulative numbers of cases and deaths. DATA SYNTHESIS: In a total of 43 studies (331 628 participants), changes in symptoms of psychological distress, sleep disturbances, and mental well-being varied substantially across studies. On average, depression and anxiety symptoms worsened in the first 2 months of the pandemic (standardized mean difference at 60 days, -0.39 [95% credible interval, -0.76 to -0.03]); thereafter, the trajectories were heterogeneous. There was a linear association of worsening depression and anxiety with increasing numbers of reported cases of SARS-CoV-2 infection and increasing stringency in governmental measures. Gender, age, country, deprivation, inequalities, risk of bias, and study design did not modify these associations. LIMITATIONS: The certainty of the evidence was low because of the high risk of bias in included studies and the large amount of heterogeneity. Stringency measures and surges in cases were strongly correlated and changed over time. The observed associations should not be interpreted as causal relationships. CONCLUSION: Although an initial increase in average symptoms of depression and anxiety and an association between higher numbers of reported cases and more stringent measures were found, changes in mental health symptoms varied substantially across studies after the first 2 months of the pandemic. This suggests that different populations responded differently to the psychological stress generated by the pandemic and its containment measures. PRIMARY FUNDING SOURCE: Swiss National Science Foundation. (PROSPERO: CRD42020180049).

Implementation of a Web-Based Resilience Enhancement Training for Nurses: Pilot Randomized Controlled Trial.

BACKGROUND: Global workforce challenges faced by health care providers are linked to low levels of job satisfaction, recruitment, retention, and well-being, with detrimental impacts on patient care outcomes. Resilience-building programs can provide support for staff who endure highly stressful environments, enhance resilience, and support recruitment and retention, with web-based formats being key to increasing accessibility. OBJECTIVE: We aimed to examine participants' engagement with a newly developed Resilience Enhancement Online Training for Nurses (REsOluTioN), explore its acceptability, and compare levels of resilience and psychological well-being in nurses who completed REsOluTioN with those who did not. METHODS: We carried out a pilot randomized trial (1:1), conducted at a single site (mental health and community trust in South England) between August 2021 and May 2022. Local research ethics approvals were obtained. Nurses were invited to participate and were randomly assigned to a waitlist group or REsOluTioN group. Training lasted for 4 weeks, consisting of prereading, web-based facilitated sessions, and mentorship support. We evaluated trial engagement, acceptability of training, and pre-post changes in resilience, measured by the Brief Resilience Scale, and psychological well-being, measured by the Warwick Edinburgh Mental Wellbeing Scale. Qualitative participant feedback was collected. Consolidated Standards of Reporting Trials 2010 extension guidelines for reporting pilot and feasibility trials were used. RESULTS: Of 108 participants recruited, 93 completed the study. Participants' mean age was 44 (SD 10.85) years. Most participants were female (n=95, 88.8%), White (n=95, 88.8%), and worked in community settings (n=91, 85.0%). Sixteen facilitated and 150 mentoring sessions took place. Most REsOluTioN program participants reported the sessions helped improve their resilience (n=24, 72.8%), self-confidence (n=24, 72.7%), ability to provide good patient care (n=25, 75.8%), relationships with colleagues (n=24, 72.7%), and communication skills (n=25, 75.8%). No statistically significant differences between training and control groups and time on well-being (F1,91=1.44, P=.23, partial η2=0.02) and resilience scores (F1,91=0.33, P=.57, partial η2=0.004) were revealed; however, there were positive trends toward improvement in both. Nurse participants engaged with the REsOluTioN program and found it acceptable. Most found web-based training and mentoring useful and enjoyed learning, reflection, networking, and participatory sessions. CONCLUSIONS: The REsOluTioN program was acceptable, engaging, perceived as useful, and nurses were keen for it to be implemented to optimize resilience, psychological health, communication, and workplace environments. The study has evidenced that it is acceptable to implement web-based resilience programs with similar design features within busy health care settings, indicating a need for similar programs to be carefully evaluated. Mentorship support may also be a key in optimizing resilience. Trial limitations include small sample size and reduced statistical power; a multicenter randomized controlled trial could test effectiveness of the training on a larger scale. TRIAL REGISTRATION: ClinicalTrials.gov NCT05074563; https://clinicaltrials.gov/ct2/show/NCT05074563. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/37015.

Selective publication of antidepressant trials and its influence on apparent efficacy: Updated comparisons and meta-analyses of newer versus older trials.

BACKGROUND: Valid assessment of drug efficacy and safety requires an evidence base free of reporting bias. Using trial reports in Food and Drug Administration (FDA) drug approval packages as a gold standard, we previously found that the published literature inflated the apparent efficacy of antidepressant drugs. The objective of the current study was to determine whether this has improved with recently approved drugs. METHODS AND FINDINGS: Using medical and statistical reviews in FDA drug approval packages, we identified 30 Phase II/III double-blind placebo-controlled acute monotherapy trials, involving 13,747 patients, of desvenlafaxine, vilazodone, levomilnacipran, and vortioxetine; we then identified corresponding published reports. We compared the data from this newer cohort of antidepressants (approved February 2008 to September 2013) with the previously published dataset on 74 trials of 12 older antidepressants (approved December 1987 to August 2002). Using logistic regression, we examined the effects of trial outcome and trial cohort (newer versus older) on transparent reporting (whether published and FDA conclusions agreed). Among newer antidepressants, transparent publication occurred more with positive (15/15 = 100%) than negative (7/15 = 47%) trials (OR 35.1, CI95% 1.8 to 693). Controlling for trial outcome, transparent publication occurred more with newer than older trials (OR 6.6, CI95% 1.6 to 26.4). Within negative trials, transparent reporting increased from 11% to 47%. We also conducted and contrasted FDA- and journal-based meta-analyses. For newer antidepressants, FDA-based effect size (ESFDA) was 0.24 (CI95% 0.18 to 0.30), while journal-based effect size (ESJournals) was 0.29 (CI95% 0.23 to 0.36). Thus, effect size inflation, presumably due to reporting bias, was 0.05, less than for older antidepressants (0.10). Limitations of this study include a small number of trials and drugs-belonging to a single class-and a focus on efficacy (versus safety). CONCLUSIONS: Reporting bias persists but appears to have diminished for newer, compared to older, antidepressants. Continued efforts are needed to further improve transparency in the scientific literature.

Personalised treatment for cognitive impairment in dementia: development and validation of an artificial intelligence model.

BACKGROUND: Donepezil, galantamine, rivastigmine and memantine are potentially effective interventions for cognitive impairment in dementia, but the use of these drugs has not been personalised to individual patients yet. We examined whether artificial intelligence-based recommendations can identify the best treatment using routinely collected patient-level information. METHODS: Six thousand eight hundred four patients aged 59-102 years with a diagnosis of dementia from two National Health Service (NHS) Foundation Trusts in the UK were used for model training/internal validation and external validation, respectively. A personalised prescription model based on the Recurrent Neural Network machine learning architecture was developed to predict the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores post-drug initiation. The drug that resulted in the smallest decline in cognitive scores between prescription and the next visit was selected as the treatment of choice. Change of cognitive scores up to 2 years after treatment initiation was compared for model evaluation. RESULTS: Overall, 1343 patients with MMSE scores were identified for internal validation and 285 [21.22%] took the drug recommended. After 2 years, the reduction of mean [standard deviation] MMSE score in this group was significantly smaller than the remaining 1058 [78.78%] patients (0.60 [0.26] vs 2.80 [0.28]; P = 0.02). In the external validation cohort (N = 1772), 222 [12.53%] patients took the drug recommended and reported a smaller MMSE reduction compared to the 1550 [87.47%] patients who did not (1.01 [0.49] vs 4.23 [0.60]; P = 0.01). A similar performance gap was seen when testing the model on patients prescribed with AChEIs only. CONCLUSIONS: It was possible to identify the most effective drug for the real-world treatment of cognitive impairment in dementia at an individual patient level. Routine care patients whose prescribed medications were the best fit according to the model had better cognitive performance after 2 years.

Optimal dose of aripiprazole for augmentation therapy of antidepressant-refractory depression: preliminary findings based on a systematic review and dose-effect meta-analysis.

BACKGROUND: Aripiprazole augmentation is proven effective for antidepressant-refractory depression, but its licensed dose range is wide and optimal dosage remains unclear. AIMS: To find the optimal dosage of aripiprazole augmentation. METHOD: Multiple electronic databases were searched (from inception to 16 February 2021) to identify all assessor-masked randomised controlled trials evaluating aripiprazole augmentation therapy in adults (≥18 years old, both genders) with major depressive disorder showing inadequate response to at least one antidepressant treatment. A random-effects, one-stage dose-effect meta-analysis with restricted cubic splines was conducted. Outcomes were efficacy (treatment response: ≥50% reduction in depression severity), tolerability (drop-out due to adverse effects) and acceptability (drop-out for any reason) after 8 weeks of treatment (range 4-12 weeks). RESULTS: Ten studies met the inclusion criteria. All were individually randomised, placebo-controlled, multi-centre, parallel studies including 2625 participants in total. The maximum target dose-efficacy curve showed an increase up to doses between 2 mg (odds ratio OR = 1.46, 95% CI 1.15-1.85) and 5 mg (OR = 1.93, 95% CI 1.33-2.81), and then a non-increasing trend through the higher licensed doses up to 20 mg (OR = 1.90, 95% CI 1.52-2.37). Tolerability showed a similar trend with greater uncertainty. Acceptability showed no significant difference through the examined dose range. Certainty of evidence was low to moderate. CONCLUSIONS: Low-dose aripiprazole as augmentation treatment might achieve the optimal balance between efficacy, tolerability and acceptability in the acute treatment of antidepressant-refractory depression. However, the small number of included studies and the overall moderate to high risk of bias seriously compromise the reliability of the results. Further research is required to investigate the benefits of low versus high dose.

Patient fibroblast circadian rhythms predict lithium sensitivity in bipolar disorder.

Bipolar disorder is a chronic neuropsychiatric condition associated with mood instability, where patients present significant sleep and circadian rhythm abnormalities. Currently, the pathophysiology of bipolar disorder remains elusive, but treatment with lithium continues as the benchmark pharmacotherapy, functioning as a potent mood stabilizer in most, but not all patients. Lithium is well documented to induce period lengthening and amplitude enhancement of the circadian clock. Based on this, we sought to investigate whether lithium differentially impacts circadian rhythms in bipolar patient cell lines and crucially if lithium's effect on the clock is fundamental to its mood-stabilizing effects. We analyzed the circadian rhythms of bipolar patient-derived fibroblasts (n = 39) and their responses to lithium and three further chronomodulators. Here we show, relative to controls (n = 23), patients exhibited a wider distribution of circadian period (p < 0.05), and that patients with longer periods were medicated with a wider range of drugs, suggesting lower effectiveness of lithium. In agreement, patient fibroblasts with longer periods displayed muted circadian responses to lithium as well as to other chronomodulators that phenocopy lithium. These results show that lithium differentially impacts the circadian system in a patient-specific manner and its effect is dependent on the patient's circadian phenotype. We also found that lithium-induced behavioral changes in mice were phenocopied by modulation of the circadian system with drugs that target the clock, and that a dysfunctional clock ablates this response. Thus, chronomodulatory compounds offer a promising route to a novel treatment paradigm. These findings, upon larger-scale validation, could facilitate the implementation of a personalized approach for mood stabilization.

Development and validation of a meta-learner for combining statistical and machine learning prediction models in individuals with depression.

BACKGROUND: The debate of whether machine learning models offer advantages over standard statistical methods when making predictions is ongoing. We discuss the use of a meta-learner model combining both approaches as an alternative. METHODS: To illustrate the development of a meta-learner, we used a dataset of 187,757 people with depression. Using 31 variables, we aimed to predict two outcomes measured 60 days after initiation of antidepressant treatment: severity of depressive symptoms (continuous) and all-cause dropouts (binary). We fitted a ridge regression and a multi-layer perceptron (MLP) deep neural network as two separate prediction models ("base-learners"). We then developed two "meta-learners", combining predictions from the two base-learners. To compare the performance across the different methods, we calculated mean absolute error (MAE, for continuous outcome) and the area under the receiver operating characteristic curve (AUC, for binary outcome) using bootstrapping. RESULTS: Compared to the best performing base-learner (MLP base-learner, MAE at 4.63, AUC at 0.59), the best performing meta-learner showed a 2.49% decrease in MAE at 4.52 for the continuous outcome and a 6.47% increase in AUC at 0.60 for the binary outcome. CONCLUSIONS: A meta-learner approach may effectively combine multiple prediction models. Choosing between statistical and machine learning models may not be necessary in practice.

COVID-19 and substance use disorders: a review of international guidelines for frontline healthcare workers of addiction services.

BACKGROUND: People with substance use disorders may be at a greater risk of contracting COVID-19 infection and developing medical complications. Several institutional and governmental health agencies across the world developed ad hoc guidance for substance use disorder services and care of individuals misusing substances. We aimed to synthesise the best available recommendations on management and care of people with or at risk of substance use disorders during the COVID-19 pandemic from existing guidelines published in UK, USA, Australia, Canada, New Zealand, and Singapore. METHODS: We systematically searched existing guidelines and websites from 28 international institutions and governmental bodies in the context of the COVID-19 pandemic (May 4th 2021). We summarized the extracted data as answers to specific clinical questions. RESULTS: We organised the available recommendations from 19 sources in three sections. First, we focused on general advice and recommendations for people who misuse alcohol or drugs during the COVID-19 pandemic, the design of contingency plans, safeguarding issues for children and families of service users and advice to the public, patients, and carers. Then, we summarised specific guidelines for people who use illicit drugs and related services, such as opioid substitution treatment and needle and syringe programmes. Finally, we provided a synthesis on specific recommendations for services supporting people who misuse alcohol and key topics in the field, such as management of alcohol detoxification and safe transition between supervised and unsupervised consumption. CONCLUSIONS: Available guidance reflected different approaches, ranging from being extremely cautious in providing recommendations other than generic statements to proposing adaptation of previously available guidelines to confront the challenges of the COVID-19 pandemic. After the early phase, guidance focused on reduction of infection transmission and service delivery. Guidance did not provide advice on infection prevention via vaccination programmes and service access strategies tailored to individuals with substance use disorders.

Generating comparative evidence on new drugs and devices after approval.

Certain limitations of evidence available on drugs and devices at the time of market approval often persist in the post-marketing period. Often, post-marketing research landscape is fragmented. When regulatory agencies require pharmaceutical and device manufacturers to conduct studies in the post-marketing period, these studies might remain incomplete many years after approval. Even when completed, many post-marketing studies lack meaningful active comparators, have observational designs, and might not collect patient-relevant outcomes. Regulators, in collaboration with the industry and patients, ought to ensure that the key questions unanswered at the time of drug and device approval are resolved in a timely fashion during the post-marketing phase. We propose a set of seven key guiding principles that we believe will provide the necessary incentives for pharmaceutical and device manufacturers to generate comparative data in the post-marketing period. First, regulators (for drugs and devices), notified bodies (for devices in Europe), health technology assessment organisations, and payers should develop customised evidence generation plans, ensuring that future post-approval studies address any limitations of the data available at the time of market entry impacting the benefit-risk profiles of drugs and devices. Second, post-marketing studies should be designed hierarchically: priority should be given to efforts aimed at evaluating a product's net clinical benefit in randomised trials compared with current known effective therapy, whenever possible, to address common decisional dilemmas. Third, post-marketing studies should incorporate active comparators as appropriate. Fourth, use of non-randomised studies for the evaluation of clinical benefit in the post-marketing period should be limited to instances when the magnitude of effect is deemed to be large or when it is possible to reasonably infer the comparative benefits or risks in settings, in which doing a randomised trial is not feasible. Fifth, efficiency of randomised trials should be improved by streamlining patient recruitment and data collection through innovative design elements. Sixth, governments should directly support and facilitate the production of comparative post-marketing data by investing in the development of collaborative research networks and data systems that reduce the complexity, cost, and waste of rigorous post-marketing research efforts. Last, financial incentives and penalties should be developed or more actively reinforced.

Generating comparative evidence on new drugs and devices before approval.

Fewer than half of new drugs have data on their comparative benefits and harms against existing treatment options at the time of regulatory approval in Europe and the USA. Even when active-comparator trials exist, they might not produce meaningful data to inform decisions in clinical practice and health policy. The uncertainty associated with the paucity of well designed active-comparator trials has been compounded by legal and regulatory changes in Europe and the USA that have created a complex mix of expedited programmes aimed at facilitating faster access to new drugs. Comparative evidence generation is even sparser for medical devices. Some have argued that the current process for regulatory approval needs to generate more evidence that is useful for patients, clinicians, and payers in health-care systems. We propose a set of five key principles relevant to the European Medicines Agency, European medical device regulatory agencies, US Food and Drug Administration, as well as payers, that we believe will provide the necessary incentives for pharmaceutical and device companies to generate comparative data on drugs and devices and assure timely availability of evidence that is useful for decision making. First, labelling should routinely inform patients and clinicians whether comparative data exist on new products. Second, regulators should be more selective in their use of programmes that facilitate drug and device approvals on the basis of incomplete benefit and harm data. Third, regulators should encourage the conduct of randomised trials with active comparators. Fourth, regulators should use prospectively designed network meta-analyses based on existing and future randomised trials. Last, payers should use their policy levers and negotiating power to incentivise the generation of comparative evidence on new and existing drugs and devices, for example, by explicitly considering proven added benefit in pricing and payment decisions.