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

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

Off-label long acting injectable antipsychotics in real-world clinical practice: a cross-sectional analysis of prescriptive patterns from the STAR Network DEPOT study

Introduction: Information on the off-label use of Long-Acting Injectable (LAI) antipsychotics in the real world is lacking. In this study, we aimed to identify the sociodemographic and clinical features of patients treated with on- vs off-label LAIs and predictors of off-label First- or Second-Generation Antipsychotic (FGA vs. SGA) LAI choice in everyday clinical practice. Method: In a naturalistic national cohort of 449 patients who initiated LAI treatment in the STAR Network Depot Study, two groups were identified based on off- or on-label prescriptions. A multivariate logistic regression analysis was used to test several clinically relevant variables and identify those associated with the choice of FGA vs SGA prescription in the off-label group. Results: SGA LAIs were more commonly prescribed in everyday practice, without significant differences in their on- and off-label use. Approximately 1 in 4 patients received an off-label prescription. In the off-label group, the most frequent diagnoses were bipolar disorder (67.5%) or any personality disorder (23.7%). FGA vs SGA LAI choice was significantly associated with BPRS thought disorder (OR = 1.22, CI95% 1.04 to 1.43, p = 0.015) and hostility/suspiciousness (OR = 0.83, CI95% 0.71 to 0.97, p = 0.017) dimensions. The likelihood of receiving an SGA LAI grew steadily with the increase of the BPRS thought disturbance score. Conversely, a preference towards prescribing an FGA was observed with higher scores at the BPRS hostility/suspiciousness subscale. Conclusion: Our study is the first to identify predictors of FGA vs SGA choice in patients treated with off-label LAI antipsychotics. Demographic characteristics, i.e. age, sex, and substance/alcohol use co-morbidities did not appear to influence the choice towards FGAs or SGAs. Despite a lack of evidence, clinicians tend to favour FGA over SGA LAIs in bipolar or personality disorder patients with relevant hostility. Further research is needed to evaluate treatment adherence and clinical effectiveness of these prescriptive patterns

Evidence synthesis, practice guidelines and real-world prescriptions of new generation antidepressants in the treatment of depression: a protocol for cumulative network meta-analyses and meta-epidemiological study. [Protocol]

INTRODUCTION Depressive disorders are the most common, burdensome and costly mental disorders. Their treatments have developed through the past decades and we now have more than a dozen new generation antidepressants, while a series of guidelines have been published to provide recommendations over the years. However, there still may exist important gaps in this evidence synthesis and implementation process. Systematic reviews may not have been conducted in the most unbiased, informative and timely manners; guidelines may not have reflected the most up-to-date evidence; clinicians may not have changed their clinical decision-makings in accordance with the relevant evidence. The aim of this study is to examine the gaps between the ideally synthesised evidence, guideline recommendations and real-world clinical practices in the prescription of new generation antidepressants for major depression through the past three decades. METHODS AND ANALYSIS We will conduct cumulative network meta-analyses (cNMAs) based on the comprehensive systematic review which has identified published and unpublished head-to-head randomised controlled trials comparing the following antidepressants in the acute phase treatment of major depression: agomelatine, amitriptyline, bupropion, citalopram, clomipramine, desvenlafaxine, duloxetine, escitalopram, fluoxetine, fluvoxamine, levomilnacipran, milnacipran, mirtazapine, nefazodone, paroxetine, reboxetine, sertraline, trazodone, venlafaxine, vilazodone and vortioxetine. The primary outcomes will be the proportions of patients who responded (efficacy) and who withdrew from treatment for any reasons (acceptability). We will conduct a random effects cNMA to synthesise evidence and obtain a comprehensive ranking of all new generation antidepressants based on their surface under the cumulative ranking curves. We will identify series of international clinical practice guidelines for the treatment of major depression of adults and summarise their recommendations. We will estimate real-world prescription patterns of antidepressants in the nationally representative samples in USA in the Medical Expenditure Panel Survey. We will compare and evaluate the gaps between the rankings according to cNMAs conducted at 5-year intervals between 1990 and 2015, recommendations in guidelines published in the ensuing 5 years and actual practices thereafter. ETHICS AND DISSEMINATION This review does not require ethical approval. We will disseminate our findings through publications in peer-reviewed journals and presentations at conferences. TRIAL REGISTRATION NUMBER UMIN000031898

Comparing long-acting antipsychotic discontinuation rates under ordinary clinical circumstances: a survival analysis from an observational, pragmatic study

Background: Recent guidelines suggested a wider use of long-acting injectable antipsychotics (LAI) than previously, but naturalistic data on the consequences of LAI use in terms of discontinuation rates and associated factors are still sparse, making it hard for clinicians to be informed on plausible treatment courses. Objective: Our objective was to assess, under real-world clinical circumstances, LAI discontinuation rates over a period of 12 months after a first prescription, reasons for discontinuation, and associated factors. Methods: The STAR Network 'Depot Study' was a naturalistic, multicentre, observational prospective study that enrolled subjects initiating a LAI without restrictions on diagnosis, clinical severity or setting. Participants from 32 Italian centres were assessed at baseline and at 6 and 12 months of follow-up. Psychopathology, drug attitude and treatment adherence were measured using the Brief Psychiatric Rating Scale, the Drug Attitude Inventory and the Kemp scale, respectively. Results: The study followed 394 participants for 12 months. The overall discontinuation rate at 12 months was 39.3% (95% confidence interval [CI] 34.4-44.3), with paliperidone LAI being the least discontinued LAI (33.9%; 95% CI 25.3-43.5) and olanzapine LAI the most discontinued (62.5%; 95% CI 35.4-84.8). The most frequent reason for discontinuation was onset of adverse events (32.9%; 95% CI 25.6-40.9) followed by participant refusal of the medication (20.6%; 95% CI 14.6-27.9). Medication adherence at baseline was negatively associated with discontinuation risk (hazard ratio [HR] 0.853; 95% CI 0.742-0.981; p = 0.026), whereas being prescribed olanzapine LAI was associated with increased discontinuation risk compared with being prescribed paliperidone LAI (HR 2.156; 95% CI 1.003-4.634; p = 0.049). Conclusions: Clinicians should be aware that LAI discontinuation is a frequent occurrence. LAI choice should be carefully discussed with the patient, taking into account individual characteristics and possible obstacles related to the practicalities of each formulation

New living evidence resource of human and non-human studies for early intervention and research prioritisation in anxiety, depression and psychosis

In anxiety, depression and psychosis, there has been frustratingly slow progress in developing novel therapies that make a substantial difference in practice, as well as in predicting which treatments will work for whom and in what contexts. To intervene early in the process and deliver optimal care to patients, we need to understand the underlying mechanisms of mental health conditions, develop safe and effective interventions that target these mechanisms, and improve our capabilities in timely diagnosis and reliable prediction of symptom trajectories. Better synthesis of existing evidence is one way to reduce waste and improve efficiency in research towards these ends. Living systematic reviews produce rigorous, up-to-date and informative evidence summaries that are particularly important where research is emerging rapidly, current evidence is uncertain and new findings might change policy or practice. Global Alliance for Living Evidence on aNxiety, depressiOn and pSychosis (GALENOS) aims to tackle the challenges of mental health science research by cataloguing and evaluating the full spectrum of relevant scientific research including both human and preclinical studies. GALENOS will also allow the mental health community-including patients, carers, clinicians, researchers and funders-to better identify the research questions that most urgently need to be answered. By creating open-access datasets and outputs in a state-of-the-art online resource, GALENOS will help identify promising signals early in the research process. This will accelerate translation from discovery science into effective new interventions for anxiety, depression and psychosis, ready to be translated in clinical practice across the world

New living evidence resource of human and non-human studies for early intervention and research prioritisation in anxiety, depression and psychosis

In anxiety, depression and psychosis, there has been frustratingly slow progress in developing novel therapies that make a substantial difference in practice, as well as in predicting which treatments will work for whom and in what contexts. To intervene early in the process and deliver optimal care to patients, we need to understand the underlying mechanisms of mental health conditions, develop safe and effective interventions that target these mechanisms, and improve our capabilities in timely diagnosis and reliable prediction of symptom trajectories. Better synthesis of existing evidence is one way to reduce waste and improve efficiency in research towards these ends. Living systematic reviews produce rigorous, up-to-date and informative evidence summaries that are particularly important where research is emerging rapidly, current evidence is uncertain and new findings might change policy or practice. Global Alliance for Living Evidence on aNxiety, depressiOn and pSychosis (GALENOS) aims to tackle the challenges of mental health science research by cataloguing and evaluating the full spectrum of relevant scientific research including both human and preclinical studies. GALENOS will also allow the mental health community-including patients, carers, clinicians, researchers and funders-to better identify the research questions that most urgently need to be answered. By creating open-access datasets and outputs in a state-of-the-art online resource, GALENOS will help identify promising signals early in the research process. This will accelerate translation from discovery science into effective new interventions for anxiety, depression and psychosis, ready to be translated in clinical practice across the world

Off-label long acting injectable antipsychotics in real-world clinical practice: a cross-sectional analysis of prescriptive patterns from the STAR Network DEPOT study

Introduction Information on the off-label use of Long-Acting Injectable (LAI) antipsychotics in the real world is lacking. In this study, we aimed to identify the sociodemographic and clinical features of patients treated with on- vs off-label LAIs and predictors of off-label First- or Second-Generation Antipsychotic (FGA vs. SGA) LAI choice in everyday clinical practice. Method In a naturalistic national cohort of 449 patients who initiated LAI treatment in the STAR Network Depot Study, two groups were identified based on off- or on-label prescriptions. A multivariate logistic regression analysis was used to test several clinically relevant variables and identify those associated with the choice of FGA vs SGA prescription in the off-label group. Results SGA LAIs were more commonly prescribed in everyday practice, without significant differences in their on- and off-label use. Approximately 1 in 4 patients received an off-label prescription. In the off-label group, the most frequent diagnoses were bipolar disorder (67.5%) or any personality disorder (23.7%). FGA vs SGA LAI choice was significantly associated with BPRS thought disorder (OR = 1.22, CI95% 1.04 to 1.43, p = 0.015) and hostility/suspiciousness (OR = 0.83, CI95% 0.71 to 0.97, p = 0.017) dimensions. The likelihood of receiving an SGA LAI grew steadily with the increase of the BPRS thought disturbance score. Conversely, a preference towards prescribing an FGA was observed with higher scores at the BPRS hostility/suspiciousness subscale. Conclusion Our study is the first to identify predictors of FGA vs SGA choice in patients treated with off-label LAI antipsychotics. Demographic characteristics, i.e. age, sex, and substance/alcohol use co-morbidities did not appear to influence the choice towards FGAs or SGAs. Despite a lack of evidence, clinicians tend to favour FGA over SGA LAIs in bipolar or personality disorder patients with relevant hostility. Further research is needed to evaluate treatment adherence and clinical effectiveness of these prescriptive patterns

The Role of Attitudes Toward Medication and Treatment Adherence in the Clinical Response to LAIs: Findings From the STAR Network Depot Study

Background: Long-acting injectable (LAI) antipsychotics are efficacious in managing psychotic symptoms in people affected by severe mental disorders, such as schizophrenia and bipolar disorder. The present study aimed to investigate whether attitude toward treatment and treatment adherence represent predictors of symptoms changes over time. Methods: The STAR Network \u201cDepot Study\u201d was a naturalistic, multicenter, observational, prospective study that enrolled people initiating a LAI without restrictions on diagnosis, clinical severity or setting. Participants from 32 Italian centers were assessed at three time points: baseline, 6-month, and 12-month follow-up. Psychopathological symptoms, attitude toward medication and treatment adherence were measured using the Brief Psychiatric Rating Scale (BPRS), the Drug Attitude Inventory (DAI-10) and the Kemp's 7-point scale, respectively. Linear mixed-effects models were used to evaluate whether attitude toward medication and treatment adherence independently predicted symptoms changes over time. Analyses were conducted on the overall sample and then stratified according to the baseline severity (BPRS < 41 or BPRS 65 41). Results: We included 461 participants of which 276 were males. The majority of participants had received a primary diagnosis of a schizophrenia spectrum disorder (71.80%) and initiated a treatment with a second-generation LAI (69.63%). BPRS, DAI-10, and Kemp's scale scores improved over time. Six linear regressions\u2014conducted considering the outcome and predictors at baseline, 6-month, and 12-month follow-up independently\u2014showed that both DAI-10 and Kemp's scale negatively associated with BPRS scores at the three considered time points. Linear mixed-effects models conducted on the overall sample did not show any significant association between attitude toward medication or treatment adherence and changes in psychiatric symptoms over time. However, after stratification according to baseline severity, we found that both DAI-10 and Kemp's scale negatively predicted changes in BPRS scores at 12-month follow-up regardless of baseline severity. The association at 6-month follow-up was confirmed only in the group with moderate or severe symptoms at baseline. Conclusion: Our findings corroborate the importance of improving the quality of relationship between clinicians and patients. Shared decision making and thorough discussions about benefits and side effects may improve the outcome in patients with severe mental disorders