Patient preference for early onset of efficacy of preventive migraine treatments.

OBJECTIVE: The objective of this study was to ascertain to what extent adults with migraine value an early onset of efficacy for preventive migraine treatments. BACKGROUND: In placebo-controlled clinical trials, treatment with eptinezumab resulted in a lower proportion of adults with migraine on the first day following infusion (day 1; 14% point-reduction for chronic migraine [CM] in PROMISE-2 and 8% point-reduction for episodic migraine [EM] in PROMISE-1). METHODS: Adults with migraine completed an online preference-elicitation thresholding exercise to ascertain to what extent they value not having a migraine on day 1 postdosing relative to a clinically relevant reduction in number of migraine days during the first month postdosing (≥2 migraine-free days for CM and ≥1 migraine-free days for EM). RESULTS: One hundred and one participants (mean age, 50.6 ± 12.4 years; 81 [80%] women) were included. In participants with CM, 29 of 50 (58%) considered the eptinezumab-generated reduction in the likelihood of migraine on day 1 postdosing to be at least as important as a clinically relevant reduction in number of migraine days the first month postdosing, whereas 37 of 50 (74%) considered a clinically relevant reduction of migraine days the first month postdosing to have a value equivalent to the eptinezumab-generated reduction in the likelihood of migraine on day 1 postdosing. In participants with EM, 18 of 35 (51%) considered the eptinezumab-generated reduction in the likelihood of migraine on day 1 postdosing to be at least as important as a clinically relevant reduction in migraine days the first month postdosing, whereas 24 of 35 (69%) considered a clinically relevant reduction of migraine days the first month postdosing to have a value equivalent to the eptinezumab-generated reduction in the likelihood of migraine on day 1 postdosing. CONCLUSION: Most participants considered the reduction in the likelihood of migraine offered by eptinezumab on day 1 postdosing to be at least as important as a clinically relevant reduction in migraine days the first month postdosing.

Predicting time to relapse in patients with schizophrenia according to patients' relapse history: a historical cohort study using real-world data in Sweden.

BACKGROUND: For patients with schizophrenia, relapse is a recurring feature of disease progression, often resulting in substantial negative impacts for the individual. Although a patient's relapse history (specifically the number of prior relapses) has been identified as a strong risk factor for future relapse, this relationship has not yet been meticulously quantified. The objective of this study was to use real-world data from Sweden to quantify the relationship of time to relapse in schizophrenia with a patient's history of prior relapses. METHODS: Data from the Swedish National Patient Register and Swedish Prescribed Drug Register were used to study relapse in patients with schizophrenia with a first diagnosis recorded from 2006-2015, using proxy definitions of relapse. The primary proxy defined relapse as a psychiatric hospitalisation of ≥7 days' duration. Hazard ratios (HRs) were calculated for risk of each subsequent relapse, and Aalen-Johansen estimators were used to estimate time to next relapse. RESULTS: 2,994 patients were included, and 5,820 relapse episodes were identified using the primary proxy. As the number of previous relapses increased, there was a general trend of decreasing estimated time between relapses. Within 1.52 years of follow-up, 50% of patients with no history of relapse were estimated to have suffered their first relapse episode. 50% of patients with one prior relapse were estimated to have a second relapse within 1.23 years (HR: 1.84 [1.71-1.99]) and time to next relapse further decreased to 0.89 years (HR: 2.77 [2.53-3.03]) and 0.22 years (HR: 18.65 [15.42-22.56]) for 50% of patients with two or ten prior relapses, respectively. Supplementary analyses using different inclusion/exclusion criteria for the study population and redefined proxies of relapse reflected the pattern observed with the primary analyses of a higher number of prior relapses linked with increased risk of/reduced estimated time to the next relapse. CONCLUSIONS: The results suggested a trend of accelerating disease progression in schizophrenia, each relapse episode predisposing an individual to the next within a shorter time period. These results emphasise the importance of providing early, effective, and tolerable treatments that better meet a patient's individual needs.

Antipsychotic treatment patterns in Alzheimer's disease patients with agitation: a cohort study using the UK clinical practice research datalink.

OBJECTIVES: There is a lack of robust epidemiological evidence on antipsychotic (AP) use in patients with agitation in Alzheimer's disease (AD). Authors studied AP use in patients with AD and agitation and compared their use with patients with other or no neuropsychiatric symptoms (NPS). METHODS: A retrospective cohort study in the UK Clinical Practice Research Datalink, included patients with AD between January 1st, 2015, and December 31st, 2017. AP use was compared between patients with agitation, other types of NPS and no NPS. RESULTS: There were 24,464 patients with AD, median follow-up of 1.1 years (interquartile range [IQR] 0.5-2.1), and median age 83 years (78-88). A larger percentage of patients with agitation (n = 2432) were prescribed APs (38.2%) than other NPS (n = 13,076, 20.4%) and no NPS (n = 11,816, 12.2%). Compared to patients with no NPS, adjusted hazard ratios for AP use were 3.45 (95% CI 2.86-4.17) for patients with agitation and 1.31 (95% CI 1.19-1.44) for patients with other NPS. Among users of APs, the treatment discontinuation rate at six months was 44.8% in patients with agitation (other NPS 57.1%; no NPS 63.5%). CONCLUSIONS: Patients with AD and agitation were frequently prescribed APs and for long periods in routine clinical practice in the UK. The high real-life usage of APs suggests that physicians prefer using APs for the treatment of agitation despite recommendations against their long-term use. These data support a need for AP therapies that better address known safety concerns with currently used APs to treat agitation in elderly patients with AD.

A Noninterventional Cohort Study Assessing Time to All-Cause Treatment Discontinuation After Initiation of Aripiprazole Once Monthly or Daily Oral Atypical Antipsychotic Treatment in Patients With Recent-Onset Schizophrenia.

Introduction: Aripiprazole once-monthly 400 mg (extended-release injectable suspension) is effective in long-term maintenance treatment of schizophrenia based on clinical studies. As study results may not reflect clinical practice, we compared treatment persistence with aripiprazole once-monthly 400 mg versus daily oral atypical antipsychotics in a naturalistic setting.Methods: This was an observational, noninterventional study of patients (aged 18-35 years) with recent-onset schizophrenia (< 5 years post diagnosis) who initiated maintenance treatment with aripiprazole once-monthly 400 mg or any daily oral atypical antipsychotic during a schizophrenia-related hospitalization or within 3 months post hospital discharge (timeframe: July 13, 2017-July 31, 2019). Data were from patient files/obtained during routine visits. Patients were followed for ≤ 12 months or until all-cause treatment discontinuation (including lost to follow-up), whichever came first. Data were analyzed using a sample constructed with inverse probability of treatment weighting (IPTW).Results: Among 357 patients (aripiprazole once-monthly 400 mg: 215, oral atypical antipsychotics: 142), all-cause treatment discontinuation occurred in 87 (41%) of aripiprazole once-monthly 400 mg, 68 (48%) of oral atypical antipsychotic patients over 52 weeks. In the IPTW sample, time to all-cause discontinuation was significantly different between both groups in favor of aripiprazole once-monthly 400 mg (hazard ratio = 1.46; 95% CI, 1.05-2.03; P = .023). Generalizability of results to the overall population with schizophrenia was limited due to incomplete overlap of patient characteristics between cohorts. The primary reason for treatment discontinuation in both groups was voluntary discontinuation by subject (aripiprazole once-monthly 400 mg: 11%; oral atypical antipsychotics: 8%).Conclusions: In a naturalistic setting, younger patients with recent-onset schizophrenia treated with aripiprazole once-monthly 400 mg after hospitalization tended to discontinue treatment later than patients treated with daily oral atypical antipsychotics.Trial Registration: ClinicalTrials.gov identifier: NCT03130465.

Targeted school-based interventions for improving reading and mathematics for students with or at risk of academic difficulties in Grades K-6: A systematic review.

Background: Low levels of numeracy and literacy skills are associated with a range of negative outcomes later in life, such as reduced earnings and health. Obtaining information about effective interventions for children with or at risk of academic difficulties is therefore important. Objectives: The main objective was to assess the effectiveness of interventions targeting students with or at risk of academic difficulties in kindergarten to Grade 6. Search Methods: We searched electronic databases from 1980 to July 2018. We searched multiple international electronic databases (in total 15), seven national repositories, and performed a search of the grey literature using governmental sites, academic clearinghouses and repositories for reports and working papers, and trial registries (10 sources). We hand searched recent volumes of six journals and contacted international experts. Lastly, we used included studies and 23 previously published reviews for citation tracking. Selection Criteria: Studies had to meet the following criteria to be included: Population: The population eligible for the review included students attending regular schools in kindergarten to Grade 6, who were having academic difficulties, or were at risk of such difficulties. Intervention: We included interventions that sought to improve academic skills, were conducted in schools during the regular school year, and were targeted (selected or indicated). Comparison: Included studies used an intervention-control group design or a comparison group design. We included randomised controlled trials (RCT); quasi-randomised controlled trials (QRCT); and quasi-experimental studies (QES). Outcomes: Included studies used standardised tests in reading or mathematics. Setting: Studies carried out in regular schools in an OECD country were included. Data Collection and Analysis: Descriptive and numerical characteristics of included studies were coded by members of the review team. A review author independently checked coding. We used an extended version of the Cochrane Risk of Bias tool to assess risk of bias. We used random-effects meta-analysis and robust-variance estimation procedures to synthesise effect sizes. We conducted separate meta-analyses for tests performed within three months of the end of interventions (short-term effects) and longer follow-up periods. For short-term effects, we performed subgroup and moderator analyses focused on instructional methods and content domains. We assessed sensitivity of the results to effect size measurement, outliers, clustered assignment of treatment, risk of bias, missing moderator information, control group progression, and publication bias. Results: We found in total 24,414 potentially relevant records, screened 4247 of them in full text, and included 607 studies that met the inclusion criteria. We included 205 studies of a wide range of intervention types in at least one meta-analysis (202 intervention-control studies and 3 comparison designs). The reasons for excluding studies from the analysis were that they had too high risk of bias (257), compared two alternative interventions (104 studies), lacked necessary information (24 studies), or used overlapping samples (17 studies). The total number of student observations in the analysed studies was 226,745. There were 93% RCTs among the 327 interventions we included in the meta-analysis of intervention-control contrasts and 86% were from the United States. The target group consisted of, on average, 45% girls, 65% minority students, and 69% low-income students. The mean Grade was 2.4. Most studies included in the meta-analysis had a moderate to high risk of bias.The overall average effect sizes (ES) for short-term and follow-up outcomes were positive and statistically significant (ES = 0.30, 95% confidence interval [CI] = [0.25, 0.34] and ES = 0.27, 95% CI = [0.17, 0.36]), respectively). The effect sizes correspond to around one third to one half of the achievement gap between fourth Grade students with high and low socioeconomic status in the United States and to a 58% chance that a randomly selected score of an intervention group student is greater than the score of a randomly selected control group student.All measures indicated substantial heterogeneity across short-term effect sizes. Follow-up outcomes pertain almost exclusively to studies examining small-group instruction by adults and effects on reading measures. The follow-up effect sizes were considerably less heterogeneous than the short-term effect sizes, although there was still statistically significant heterogeneity.Two instructional methods, peer-assisted instruction and small-group instruction by adults, had large and statistically significant average effect sizes that were robust across specifications in the subgroup analysis of short-term effects (ES around 0.35-0.45). In meta-regressions that adjusted for methods, content domains, and other study characteristics, they had significantly larger effect sizes than computer-assisted instruction, coaching of personnel, incentives, and progress monitoring. Peer-assisted instruction also had significantly larger effect sizes than medium-group instruction. Besides peer-assisted instruction and small-group instruction, no other methods were consistently significant across the analyses that tried to isolate the association between a specific method and effect sizes. However, most analyses showed statistically significant heterogeneity also within categories of instructional methods.We found little evidence that effect sizes were larger in some content domains than others. Fractions had significantly higher associations with effect sizes than all other math domains, but there were only six studies of interventions targeting fractions. We found no evidence of adverse effects in the sense that no method or domain had robustly negative associations with effect sizes.The meta-regressions revealed few other significant moderators. Interventions in higher Grades tend to have somewhat lower effect sizes, whereas there were no significant differences between QES and RCTs, general tests and tests of subdomains, and math tests and reading tests. Authors' Conclusions: Our results indicate that interventions targeting students with or at risk of academic difficulties from kindergarten to Grade 6 have on average positive and statistically significant short-term and follow-up effects on standardised tests in reading and mathematics. Peer-assisted instruction and small-group instruction are likely to be effective components of such interventions.We believe the relatively large effect sizes together with the substantial unexplained heterogeneity imply that schools can reduce the achievement gap between students with or at risk of academic difficulties and not-at-risk students by implementing targeted interventions, and that more research into the design of effective interventions is needed.

Transdiagnostic individualized clinically-based risk calculator for the automatic detection of individuals at-risk and the prediction of psychosis: external replication in 2,430,333 US patients.

The real-world impact of psychosis prevention is reliant on effective strategies for identifying individuals at risk. A transdiagnostic, individualized, clinically-based risk calculator to improve this has been developed and externally validated twice in two different UK healthcare trusts with convincing results. The prognostic performance of this risk calculator outside the UK is unknown. All individuals who accessed primary or secondary health care services belonging to the IBM® MarketScan® Commercial Database between January 2015 and December 2017, and received a first ICD-10 index diagnosis of nonorganic/nonpsychotic mental disorder, were included. According to the risk calculator, age, gender, ethnicity, age-by-gender, and ICD-10 cluster diagnosis at index date were used to predict development of any ICD-10 nonorganic psychotic disorder. Because patient-level ethnicity data were not available city-level ethnicity proportions were used as proxy. The study included 2,430,333 patients with a mean follow-up of 15.36 months and cumulative incidence of psychosis at two years of 1.43%. There were profound differences compared to the original development UK database in terms of case-mix, psychosis incidence, distribution of baseline predictors (ICD-10 cluster diagnoses), availability of patient-level ethnicity data, follow-up time and availability of specialized clinical services for at-risk individuals. Despite these important differences, the model retained accuracy significantly above chance (Harrell's C = 0.676, 95% CI: 0.672-0.679). To date, this is the largest international external replication of an individualized prognostic model in the field of psychiatry. This risk calculator is transportable on an international scale to improve the automatic detection of individuals at risk of psychosis.

Deployment of personnel to military operations: impact on mental health and social functioning.

This Campbell systematic review examines the effects of deployment on mental health. The review summarizes evidence from 185 studies. All studies used observational data to quantify the effect of deployment. This review includes studies that evaluate the effects of deployment on mental health. A total of 185 studies were identified. However, only 40 of these were assessed to be of sufficient methodological quality to be included in the final analysis. The studies spanned the period from 1993 to 2017 and were mostly carried out in the USA, UK and Australia. The studies all had some important methodological weaknesses. None of the included studies used experimental designs (random assignment). Deployment to military operations negatively affects the mental health functioning of deployed military personnel. For assessments taken more than 24 months since exposure, we consistently found adverse effects of deployment on all mental health domains (PTSD, depression, substance abuse/dependence, and common mental disorders), particularly on PTSD. For assessments taken less than 24 months (or a variable number of months since exposure) the evidence was less consistent and in many instances inconclusive. Plain language summary: Deployment to military operations negatively affects the mental health functioning of deployed military personnel: While additional research is needed, the current evidence strongly supports the notion that deployment negatively affects mental health functioning of deployed military personnel.What is this review about?: When military personnel are deployed to military operations abroad they face an increased risk of physical harm, and an increased risk of adverse shocks to their mental health.The primary condition under consideration is deployment to an international military operation. Deployment to a military operation is not a uniform condition; rather, it covers a range of scenarios. Military deployment is defined as performing military service in an operation at a location outside the home country for a limited time period, pursuant to orders.The review included studies that reported outcomes for individuals who had been deployed. This review looked at the effect of deployment on mental health outcomes. The mental health outcomes are: post-traumatic stress disorder (PTSD), major depressive disorder (MDD), common mental disorders (depression, anxiety and somatisation disorders) and substance-related disorders.By identifying the major effects of deployment on mental health and quantifying these effects, the review can inform policy development on deployment and military activity as well as post-deployment support for veterans. In this way the review enables decision-makers to prioritise key areas.What are the main findings of this review?: What studies are included?: This review includes studies that evaluate the effects of deployment on mental health. A total of 185 studies were identified. However, only 40 of these were assessed to be of sufficient methodological quality to be included in the final analysis. The studies spanned the period from 1993 to 2017 and were mostly carried out in the USA, UK and Australia. The studies all had some important methodological weaknesses. None of the included studies used experimental designs (random assignment).Does deployment have an effect on mental health?: Deployment to military operations negatively affects the mental health functioning of deployed military personnel. For assessments taken more than 24 months since exposure, we consistently found adverse effects of deployment on all mental health domains (PTSD, depression, substance abuse/dependence, and common mental disorders), particularly on PTSD. For assessments taken less than 24 months (or a variable number of months since exposure) the evidence was less consistent and in many instances inconclusive.What do the findings of this review mean?: The odds of screening positive for PTSD and depression were consistently high in the longer term. This suggests that efforts should be increased to detect and treat mental disorders, as effects may be long-lasting.Overall the risk of bias in the majority of included studies was high. While it is difficult to imagine a randomised study design to understand how deployment affects mental health, other matters such as changes to personnel policy, or unanticipated shocks to the demand for military personnel, could potentially be a rich source of quasi-experimental variation.How up-to-date is this review?: The review authors searched for studies up to 2017. This Campbell systematic review was published in March 2018. Executive summary: BACKGROUND: When military personnel are deployed to military operations abroad they face an increased risk of physical harm, and an increased risk of adverse shocks to their mental health. Research suggests that the increased risk to mental health is mainly due to the hazards of war, combat exposure: firing weapons, road side bombs, seeing fellow soldiers, friends, civilians, and enemies being injured, maimed or killed. These experiences may lead to severe mental stress. The adverse impact on mental health is the psychological cost of war, and it is of interest to policymakers to learn the magnitude of these effects. This review sets out to synthesise available evidence about the consequences of deployment for deployed military personnel in the mental health and social functioning domains.OBJECTIVES: The objective of this review isto synthesise the consequences of deployment to military operation on the mental health and social functioning of deployed military personnel.SEARCH METHODS: We searched electronic databases, grey literature, and references from primary studies and related reviews. No language or date restrictions were applied to the searches. We searched the following electronic databases: Academic Search Elite, Cochrane Library, EMBASE, ERIC, MEDLINE, PsycINFO, Science Citation Index, Social Science Citation Index, SocINDEX, as well as the Nordic platforms: bibliotek.dk, BIBSYS, and LIBRIS. The conclusions of this review are based on the most recent searches performed. The last search was performed in April 2017.SELECTION CRITERIA: Primary studies had to meet the following inclusion criteria: Participants: The participants should be military personnel.Intervention: The condition should be deployment to a military operation.Comparison: The relevant comparisons were either comparing a) deployed military personnel to non-deployed military personnel, b) deployed military personnel to military personnel deployed elsewhere, for example personnel deployed to non-combat operations, c) military personnel deployed to the same operation but stratified by combat exposure.Outcomes: The study should report on one or more mental health outcomes, and/or social functioning for the deployed participants. In particular studies should report on one or more of the following mental health outcomes: PTSD, major depression, substance abuse or dependence (including alcohol), and common mental disorders (depression and anxiety disorders). The following social functioning outcomes were relevant: employment, and homelessness.Study Designs: Both experimental and quasi-experimental designs with a comparison group were eligible for inclusion in the review. Studies were excluded if they: Reported on deployments taking place before 1989.Used a within group pre-post study design.Did not report on at least one of the mental health or social functioning outcomes. DATA COLLECTION AND ANALYSIS: The total number of potentially relevant studies constituted31,049records. A total of 185 studies met the inclusion criteria and were critically appraised by the review authors. The final selection of 185 studies was from 13 different countries.Forty eight of the 185 studies did not report effect estimates or provide data that would allow the calculation of an effect size and standard error. Fifty four studies were excluded because of overlapping samples. The majority of those studies were from USA but the main reason for not using studies from USA in the synthesis was lack of information to calculate an effect size. Nearly half the studies from the UK could not be used in the synthesis due to overlap of data samples. Forty three studies were judged to have a very high risk of bias (5 on the scale) and, in accordance with the protocol, we excluded these from the data synthesis on the basis that they would be more likely to mislead than inform., Thus a total of 40 studies, from five different countries, were included in the data synthesis.Random effects models were used to pool data across the studies. We used the odds ratio. Pooled estimates were weighted with inverse variance methods, and 95% confidence intervals were calculated. The meta-analyses were carried out by time since exposure (short, medium, long, and other time since exposure) and by type of comparison (deployed versus non-deployed, all deployed but stratified by either combat operations versus non-combat operations, or stratified by combat exposure). We performed single factor subgroup analysis. The assessment of any difference between subgroups was based on 95% confidence intervals. Funnel plots were used to assess the possibility of publication bias. Sensitivity analysis was used to evaluate whether the pooled effect sizes were robust across components of methodological quality.MAIN RESULTS: The findings were mixed, depending on the outcome, the time since exposure and the approach (deployed versus non-deployed termed absolute or stratified by extent of combat termed relative) used to investigate the effect. It was not possible to analyse the outcomes homelessness and employment. All studies that could be used in the data synthesis reported on the impact of deployment on mental health; PTSD, depression, substance use or common mental disorder.For assessments taken less than 24months since exposure the evidence was inconclusive either because too few studies reported results in the short and medium term and/or the degree of heterogeneity between studies was large.For assessments taken at other time points (a variable number of months since exposure) the evidence was inconclusive for the relative comparisons due to either too few studies or a substantial degree of heterogeneity between studies. For the absolute comparison the analysis of common mental disorder was inconclusive, whereas the average effects of PTSD and depression were positive and statistically significant (PTSD odds ratio (OR) was 1.91 (95% confidence interval (CI): 1.28 to 2.85) and OR=1.98 (95% CI: 1.05 to 3.70) for depression). The analysis concerning substance use indicated that deployed participants did not have higher odds of screening positive for substance use compared to non-deployed participants (OR=1.15 (95% CI: 0.98 to 1.36)).For assessments taken more than 24 months post exposure, meta-analyses indicated that the odds of screening positive for PTSD, depression, substance use and common mental disorder were higher for participants in the deployed group compared to participants in the group that were not deployed (PTSD OR=3.31 (95% CI: 2.69 to 4.07), OR=2.19 (95% CI: 1.58 to 3.03) for depression, OR=1.27 (95% CI: 1.15 to 1.39) for substance use, and OR=1.64 (95% CI: 1.38 to 1.96) for common mental disorder). Likewise, participants reporting high combat exposure had higher odds of screening positive for PTSD and depression than participants reporting lower exposure for long term assessments (PTSD OR=3.05 (95% CI: 1.94 to 4.80) and OR=1.81 (95% CI: 1.28 to 2.56) for depression). The analyses of substance use and common mental disorder were inconclusive due to too few studies.On the basis of the prevalence of mental health problems in pre-deployed or non-deployed population based comparison sampleswe would therefore expect the long term prevalence of PTSD in post-deployed samples to be in the range 6.1 - 14.9%, the long term prevalence of depression to be in the range from 7.6% to 18%, the long term prevalence of substance use to be in the range from 2.4% to 17.5% and the prevalence of common mental disorder to be in the range from 10% to 23%.Sensitivity analyses resulted in no appreciable change in effect size, suggesting that the results are robust.It was only possible to assess the impact of two types of personnel characteristics (branch of service and duty/enlistment status) on the mental health outcomes. We found no evidence to suggest that the effect of deployment on any outcomes differ between these two types of personnel characteristics.AUTHORS' CONCLUSIONS: Deployment to military operations negatively affects the mental health functioning of deployed military personnel. We focused on the effect of deployment on PTSD (post-traumatic stress disorder), depression, substance abuse/dependence, and common mental disorders (depression and anxiety disorders). For assessments taken less than 24 months (or a variable number of months since exposure) the evidence was less consistent and in many instances inconclusive. For assessments taken more than 24 months since exposure, we consistently found adverse effects of deployment on all domains, particularly on PTSD. There is increased political awareness of the need to address post deployment mental health problems. The odds of screening positive for PTSD and depression were consistently high in the longer term. This suggests that efforts should be increased to detect and treat mental disorders, as effects may be long lasting. Mental illness is of particular concern in the military for operational reasons, but they may be hard to detect in the military setting because a military career is intimately linked with mental and physical strength.It was not possible to examine a number of factors which we had reason to expect would impact on the magnitude of the effect. This would have been particularly relevant from a policy perspective because these are direct parameters that one could use to optimally "organize" deployment in order to minimize impacts on mental health functioning.While additional research is needed, the current evidence strongly supports the notion that deployment negatively affects mental health functioning of deployed military personnel. The next step is to begin to examine preventive measures and policies for organizing deployment, in order to minimize the effects on mental health.