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Summary: Power analyses are an important aspect of experimental design, because they help determine how experiments are implemented in practice. It is common to specify a desired level of power and compute the sample size necessary to obtain that power. Such calculations are well known for completely randomized experiments, but there can be many benefits to using other experimental designs. For example, it has recently been established that rerandomization, where subjects are randomized until covariate balance is obtained, increases the precision of causal effect estimators. This work establishes the power of rerandomized treatment-control experiments, thereby allowing for sample size calculators. We find the surprising result that, while power is often greater under rerandomization than complete randomization, the opposite can occur for very small treatment effects. The reason is that inference under rerandomization can be relatively more conservative, in the sense that it can have a lower Type-I error at the same nominal significance level, and this additional conservativeness adversely affects power. This surprising result is due to treatment effect heterogeneity, a quantity often ignored in power analyses. We find that heterogeneity increases power for large effect sizes, but decreases power for small effect sizes.

This meta-analysis aimed at investigating the therapeutic effects of probiotics against the symptoms of depression in children and adolescents as well as to identify the potential confounders. Following PRISMA guidelines, major databases were searched for randomized controlled trials focusing on effects of probiotics against the symptoms of depression in children and adolescents to analyze the effect size (ES) for primary outcomes (i.e., improvement in depressive symptoms) expressed as standardized mean difference (SMD) and odds ratios (ORs) for continuous and categorical variables, respectively, with 95% confidence interval (CI). Meta-analysis of five studies (692 participants, mean age = 7.33 years, treatment duration 8–104 weeks) demonstrated no significant improvement in depressive symptoms in subjects receiving probiotics (SMD = 0.04, 95% CI: -0.33 to 0.41, p = 0.84, five studies, 692 participants). Subgroup analysis also showed no significant improvement associated with probiotic use relative to controls in the subgroup of studies focusing on individuals diagnosed with neurodevelopmental disorders (SMD = -0.11, 95% CI: -0.73 to 0.51, p = 0.72, three studies, 452 participants) and that recruiting the general population (SMD = 0.24, 95% CI: -0.43 to 0.91, p = 0.48, two studies, 240 participants). However, high levels of heterogeneity were found in both our primary results (I2 = 77%, p = 0.001) and subgroup analyses for those with neurodevelopmental disorders (I2 = 84%, p = 0.002) and the general population (I2 = 79%, p = 0.03). The results did not support the use of probiotics for relieving depressive symptoms compared with controls in children and adolescents diagnosed with neurodevelopmental disorders or in the general population. Nevertheless, given the high level of heterogeneity across the included trials and a lack of studies focusing on those with diagnoses of anxiety or depression in the current meta-analysis, further large-scale clinical investigations are required to elucidate the therapeutic potential of probiotics against depressive symptoms in these populations, especially in those diagnosed with neurodevelopmental disorders or depression. [ABSTRACT FROM AUTHOR]

Good hand-washing practice is the most important preventive measure to reduce the spread of communicable disease to under-five children. Prior studies on good handwashing practice at critical times among mothers of children under-five age in Ethiopia were extremely varied. Therefore, this meta-analysis aimed to assess the overall proportion of good handwashing practice at critical times and identify the associated factors in Ethiopia. A comprehensive search of relevant studies was performed using distinct databases. Data were extracted using Microsoft Excel spreadsheet, and exported to Stata-MPv-17 for analysis. A random-effect model was used to estimate the overall proportion of good hand-washing practice at critical times. A random or fixed effects model was used to compute the pooled AORs with their 95% Cis, which were presented on a forest plot. I 2 test statistics was used for assessing heterogeneity among the included studies. The funnel plot and Egger's test were used to assess the publication bias. Ten studies were included in this systematic review and meta-analysis. The overall pooled proportion of good hand-washing practice at critical times among mothers of children under-five age in Ethiopia was 43.18% (95% CI = 31.05, 55.31). Insufficient water (AOR = 0.33, 95% CI: 0.13, 0.52), good knowledge (AOR = 1.35, 95% CI = 1.09, 1.61), desirable attitude (AOR = 4.34, 95% CI = 1.84, 6.84) and higher educational level (AOR = 0.17, 95% CI = 0.08, 0.25) were significantly associated with good practice of hand-washing at critical times. The national level of good practice of hand-washing at critical times was low. Hence, to promote good practice of hand-washing, it is essential to increase the accessibility of water and provide hygiene health education and training programs to improve knowledge and desirable attitudes of mothers. [ABSTRACT FROM AUTHOR]

A primary goal in treating obstructive hypertrophic cardiomyopathy (oHCM) is to improve patients' health status: their symptoms, function, and quality of life. The health status benefits of aficamten, a novel cardiac myosin inhibitor, have not been comprehensively described. This study sought to determine the effect of aficamten on patient-reported health status, including symptoms of fatigue, shortness of breath, chest pain, physical and social limitations, and quality of life. SEQUOIA-HCM (Phase 3 Trial to Evaluate the Efficacy and Safety of Aficamten Compared to Placebo in Adults With Symptomatic oHCM) randomized symptomatic adults with oHCM to 24 weeks of aficamten (n = 142) or placebo (n = 140), followed by a 4-week washout. The Kansas City Cardiomyopathy Questionnaire (KCCQ) and Seattle Angina Questionnaire 7-item (SAQ7) were serially administered. Changes in mean KCCQ—Overall Summary Score (KCCQ-OSS) and SAQ7—Summary Score (SAQ7-SS) from baseline to 24 weeks and following treatment withdrawal were compared using linear regression adjusted for baseline scores and randomization strata. Proportions of patients with clinically important changes were compared. Among 282 participants, the mean age was 59 ± 13 years, 115 (41%) were female, and 223 (79%) were White. Baseline KCCQ-OSS (69.3 ± 20.1 vs 67.3 ± 18.8) and SAQ7-SS (72.0 ± 21.0 vs 72.4 ± 18.3) were similar between aficamten and placebo groups. Treatment with aficamten, compared with placebo, improved both the mean KCCQ-OSS (13.3 ± 16.3 vs 6.1 ± 12.6; mean difference: 7.9; 95% CI: 4.8-11.0; P < 0.001) and SAQ7-SS (11.6 ± 17.4 vs 3.8 ± 14.4; mean difference: 7.8; 95% CI: 4.7-11.0; P < 0.001) at 24 weeks, with benefits emerging within 4 weeks. No heterogeneity in treatment effect was found across subgroups. A much larger proportion of participants experienced a very large health status improvement (≥20 points) with aficamten vs placebo (KCCQ-OSS: 29.7% vs 12.4%, number needed to treat: 5.8; SAQ7-SS: 31.2% vs 13.9%, number needed to treat: 5.8). Participants' health status worsened significantly more after withdrawal from aficamten than placebo (KCCQ-OSS: −16.2 ± 19.0 vs −3.0 ± 9.6; P < 0.001; SAQ7-SS: −17.4 ± 21.4 vs −2.5 ± 13.3), further confirming a causal effect of aficamten. In patients with symptomatic oHCM, treatment with aficamten resulted in markedly improved health status, including significant improvement in chest pain-related health status, than placebo. (Phase 3 Trial to Evaluate the Efficacy and Safety of Aficamten Compared to Placebo in Adults With Symptomatic oHCM [SEQUOIA-HCM]; NCT05186818) [Display omitted] [ABSTRACT FROM AUTHOR]

Simple Summary: Pancreatic tumors are increasingly being detected due to widespread use of imaging in healthcare. Pancreatic tumor can be benign, pre-malignant, and malignant. Surgery is the mainstay for malignant and premalignant pancreatic tumors. However, it is invasive and associated with numerous complications. Radiofrequency ablation uses high thermal energy to induce coagulative necrosis of the tissue. Endoscopic ultrasound-guided radiofrequency ablation (EUS-RFA) is a minimally invasive technique that can serve as an alternative to surgery, particularly for patients at high surgical risk or those who refuse surgery. This review article explores the utility of EUS-RFA in the treatment of pancreatic tumors, such as nonfunctional neuroendocrine tumor, insulinoma (up to 2 cm), and premalignant cystic lesion. It also discusses several aspects of EUS-RFA and future perspectives that could be valuable in clinical practice, thereby improving patient outcomes. Endoscopic ultrasound-guided radiofrequency ablation (EUS-RFA) has emerged as an effective and minimally invasive treatment for pancreatic lesions, particularly in patients at high surgical risk. Utilizing thermal energy, RFA induces the coagulative necrosis of the tissue and potentially triggers immunomodulation by releasing intracellular antigens. Numerous studies have confirmed the technical feasibility, safety, and efficacy of EUS-RFA in pancreatic neuroendocrine tumors and premalignant cystic lesions, with an acceptable profile of adverse events. The technique's potential immunomodulatory effects offer intriguing implications for the treatment of advanced pancreatic malignancies, encouraging further evaluation. This review paper aims to highlight the EUS-RFA principles, technology, and clinical applications in various pancreatic lesions and safety, and the future research directions. [ABSTRACT FROM AUTHOR]

Purpose: Disease heterogeneity in coronavirus disease 2019 (COVID-19) may render the current one-size-fits-all treatment approach suboptimal. We aimed to identify and immunologically characterize clinical phenotypes among critically ill COVID-19 patients, and to assess heterogeneity of corticosteroid treatment effect. Methods: We applied consensus k-means clustering on 21 clinical parameters obtained within 24 h after admission to the intensive care unit (ICU) from 13,279 COVID-19 patients admitted to 82 Dutch ICUs from February 2020 to February 2022. Derived phenotypes were reproduced in 6225 COVID-19 ICU patients from Spain (February 2020 to December 2021). Longitudinal immunological characterization was performed in three COVID-19 ICU cohorts from the Netherlands and Germany, and associations between corticosteroid treatment and survival were assessed across phenotypes. Results: We derived three phenotypes: COVIDICU1 (43% of patients) consisted of younger patients with the lowest Acute Physiology And Chronic Health Evaluation (APACHE) scores, highest body mass index (BMI), lowest PaO2/FiO2 ratio, and a 90-day in-hospital mortality rate of 18%. COVIDICU2 patients (37%) had the lowest BMI, were older and had higher APACHE scores and mortality rate (24%) than COVIDICU1. Patients with COVIDICU3 (20%) were the eldest with the most comorbidities, the highest APACHE scores, acute kidney injury and metabolic dysregulations, and the highest mortality rate (47%). These patients also displayed the most pronounced inflammatory response. Corticosteroid therapy started at day 5 [2–9] after ICU admission and administered for 5 [3–7] days was associated with an increased risk for 90-day mortality in patients with the COVIDICU1 and COVIDICU2 phenotypes (hazard ratio [HR] 1.59 [1.09–2.31], p = 0.015 and HR 1.79 [1.42–2.26], p < 0.001, respectively), but not in patients with the COVIDICU3 phenotype (HR 1.08 [0.76–1.54], p = 0.654). Conclusion: Our multinational study identified three distinct clinical COVID-19 phenotypes, each exhibiting marked differences in demographic, clinical, and immunological features, and in the response to late and short-term corticosteroid treatment. [ABSTRACT FROM AUTHOR]

Objectives: The efficacy of interventions targeting lifestyle habits, particularly dietary habits, among postpartum women is well established. However, whether these results can be translated into tangible changes in the care and services provided to this population remains unclear. Therefore, the aim is to examine the implementation outcomes of postpartum nutritional interventions delivered in healthcare, community, or eHealth settings. Methods: A search was conducted in the MEDLINE, EMBASE, Web of Science, CINAHL, and Cochrane Library databases in July 2024, to identify all relevant studies. Included studies had to report at least 1 of the 8 implementation outcomes studied: acceptability, adoption, appropriateness, implementation cost, feasibility, fidelity, penetration, and sustainability. Study selection and data extraction were performed by two independent reviewers. Descriptive analysis of reported outcomes was performed. PROSPERO ID: CRD42022351411. Results: Of the 8907 unique studies identified, 26 interventions (24 publications) were included.There was a great heterogeneity among interventions studied and implementation outcomes reported. Acceptability, feasibility, and fidelity were the most studied implementation outcomes. Overall, postpartum nutritional interventions were found to be acceptable and useful, but improvements were suggested by participants, such as more frequent contacts and longer programs. Recruitment, retention, participation, and penetration rates widely varied across studies. Challenges hindering the delivery of nutritional interventions were reported by participants, such as lack of time and the presence of medical conditions following delivery. Conclusions for Practice: This review demonstrates the potential for the delivery and implementation of nutritional interventions in real-world settings during the postpartum period. Significance: What is Already Known About the Topic?: The efficacy of interventions aiming to modify lifestyle behaviors, especially dietary habits, among postpartum women is well established. Nevertheless, it is still uncertain whether these findings can be translated into healthcare, community, or eHealth settings. What This Study Adds?: This systematic review examines the implementation outcomes of postpartum nutritional interventions delivered in healthcare, community, or eHealth settings. It indicates that postpartum nutritional interventions are deemed acceptable, useful, and feasible. However, adaptation of interventions to the needs of participants is essential to reduce challenges encountered, such as recruitment and retention. [ABSTRACT FROM AUTHOR]

AbstractProbability surveys are a major source of population representative data for policy research and program evaluation. However, the data come with the added complications of being observational and selected with unequal probabilities. Propensity score adjustments have become increasingly popular for inferring causal relationships in non-randomized studies, but when using survey data, estimates of the population level causal effect may be biased if the sampling design is not adequately adjusted for. The current practice of using propensity score estimators with complex surveys is somewhat ad-hoc. We propose a potential-outcome super-population framework to streamline the causal analysis. We also develop propensity-score-and-survey weighted estimators and corresponding variance estimators, as well as their asymptotic properties. Our framework clarifies the confusion regarding the use of survey weighted propensity score in practice. The choice actually depends on the available sampling weights. Various estimators are compared in a simulation study, which shows that the proposed estimators perform better than the competing methods in terms of bias and confidence interval coverage when treatment effects are heterogeneous. To address an important public health issue, we evaluate the impact of e-cigarette use on future tobacco use intention in teens, using a large nationally representative survey in the United States. [ABSTRACT FROM AUTHOR]

Purpose: Delaying high school start times prolongs weekday sleep. However, it is not clear if longer sleep reduces depression symptoms and if the impact of such policy change is the same across groups of adolescents. Methods: We examined how gains in weekday sleep impact depression symptoms in 2,134 high school students (mean age 15.16 ± 0.35 years) from the Minneapolis metropolitan area. Leveraging a natural experiment design, we used the policy change to delay school start times as an instrument to estimate the effect of a sustained gain in weekday sleep on repeatedly measured Kandel-Davies depression symptoms. We also evaluated whether allocating the policy change to subgroups with expected benefit could improve the impact of the policy. Results: Over 2 years, a sustained half-hour gain in weekday sleep expected as a result of the policy change to delay start times decreased depression symptoms by 0.78 points, 95%CI (-1.32,-0.28), or 15.6% of a standard deviation. The benefit was driven by a decrease in fatigue and sleep-related symptoms. While symptoms of low mood, hopelessness, and worry were not affected by the policy on average, older students with greater daily screen use and higher BMI experienced greater improvements in mood symptoms than would be expected on average, signaling heterogeneity. Nevertheless, universal implementation outperformed prescriptive strategies. Conclusion: High school start time delays are likely to universally decrease fatigue and overall depression symptoms in adolescents. Students who benefit most with respect to mood are older, spend more time on screens and have higher BMI. [ABSTRACT FROM AUTHOR]

Background: The average treatment effect (ATE) reported by most randomised clinical trials provides estimates of treatment effects for the theoretical, non‐existent average patient. However, ATE may not accurately reflect the outcomes for all subsets of the trial population; some individuals may benefit from the intervention, while others experience worse outcomes or no effect at all. Heterogeneity of treatment effect (HTE) is the non‐random and explainable variation in the magnitude or direction of a treatment effect among individuals within a population. Predictive approaches to HTE seek to provide estimates of which treatment of choice is better suited for the individual patient, using regression and/or machine learning techniques. This scoping review aims to investigate the extent to which such predictive approaches to HTE are applied to data from trials on sepsis or septic shock as well as the results of these analyses. Methods: The planned review will be conducted in accordance with the PRISMA extension for scoping reviews. We will search Medline, EMBASE, Central, Cinahl and Google Scholar for studies on sepsis or septic shock in which HTE was analysed using predictive approaches. We plan to chart data regarding trial characteristics, patient demographics, disease severity, interventions, outcomes of interest and ATEs, type of predictive approach for the HTE analysis, results from HTE analysis and whether HTE analysis would change an ATE‐based trial conclusion. Results: Studies included in the scoping review will be presented as narrative summaries, supplemented with descriptive statistics of quantitative data. Conclusion: The planned scoping review will systematically investigate, summarise and delineate the existing evidence of analysis of HTE in trials on sepsis or septic shock patients as well as their findings, when performed using predictive approaches. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Multiregional trials are designed under the assumption that treatment effect applies to the entire target population, yet several factors may introduce geographic heterogeneity in treatment effect. We explored whether such variations exist in trials assessing the efficacy of glucagon-like peptide 1 receptor agonists (GLP-1RAs) in major cardiovascular events (MACE) in type 2 diabetes. RESEARCH DESIGN AND METHODS: A systematic search of Medline and the Cochrane Library was conducted from inception until 30 June 2020. We included international randomized controlled trials comparing any GLP-1RA versus placebo, with MACE as a primary end point. Individual participant data were subsequently requested from the sponsor or through data sharing platforms. For each trial, we calculated hazard ratios (HRs) and their 95% CIs for MACE, subgrouped by region. We then performed a random-effects meta-analysis and conducted meta-regressions to assess the influence of predetermined variables of interest on treatment effect. RESULTS: We included six trials including 45,426 patients. Baseline risk of MACE ranged from 2.9 per 100 patient-years in Southern Asia to 7.4 per 100 patient-years in Sub-Saharan Africa. HRs for MACE ranged between 0.25 (95% CI 0.05, 1.12) in Northern Africa to 0.98 (0.79, 1.22) in Western Europe. There was no significant subgroup difference across regions (P = 0.70). Baseline risk of MACE and indexes of development status (i.e., Human Development Index, gross domestic product) were independently associated with GLP-1RA efficacy. CONCLUSIONS: This study does not suggest any regional heterogeneity of GLP-1RA efficacy in MACE. However, a higher baseline risk and lower development status were associated with a greater benefit of these drugs. [ABSTRACT FROM AUTHOR]

Mental health conditions such as anxiety, depression, aggression, and inattention are common in autistic youth and are challenging to treat by community providers. We aim to parse the heterogeneity of autism based on dimensions of executive function and determine whether specific executive function profiles are differentially related to psychiatric symptoms. Parents of 397 well-characterized 8–14-year-old autistic children without an intellectual disability reported on their child's executive function skills and psychiatric symptoms. We applied a data-driven, graph theory-based, community-detection approach to a common executive function measure, revealing three distinct executive function profile subgroups. Despite having similar social challenges, the executive function subgroups differed on anxiety, aggression, affect, and inattention symptoms. Results support the need for more intensive subtyping with autistic youth to develop appropriate, individualized mental health treatments and supports. Characterizing youth through neurocognitive strengths and challenges can guide the development of precision medicine, allowing for more meaningful, specialized treatment. Many autistic people struggle with mental health problems like anxiety, depression, inattention, and aggression, which can be challenging to treat. Executive function challenges, which impact many autistic individuals, may serve as a risk factor for mental health problems or make treating mental health conditions more difficult. While some people respond well to medication or therapy, others do not. This study tried to understand if there are different subgroups of autistic young people who may have similar patterns of executive function strengths and challenges—like flexibility, planning, self-monitoring, and emotion regulation. Then, we investigated whether executive function subgroups were related to mental health problems in autistic youth. We found three different types of executive function subgroups in autistic youth, each with different patterns of mental health problems. This helps us identify specific profiles of executive function strengths and challenges that may be helpful with identifying personalized supports, services, and treatment strategies for mental health conditions. [ABSTRACT FROM AUTHOR]

Service performance is a main concern in public administration. This study uses the staggered adoption of participatory budgeting in New York City to test the hypothesis that participatory budgeting improves service performance, indicated by fewer 311 complaint rates. It applies the difference-in-differences estimator that is robust to heterogeneous treatment effects across groups and over time and finds that participatory budgeting declines the total complaint rates, which implies an improvement in public service performance. However, there is no evidence that participatory budgeting affects more specific types of complaints such as school maintenance, potholes, and new trees. [ABSTRACT FROM AUTHOR]

Digital tools are increasingly being used in welfare programmes to reduce corruption and increase transparency. Banerjee et al. (2020, E‐governance, accountability, and leakage in public programmes: experimental evidence from a financial management reform in India. American Economic Journal: Applied Economics. https://doi.org/10.1257/app.20180302) evaluate the effectiveness of one such intervention. In a later section of their paper, they use a Two‐Way Fixed Effects (TWFE) specification to examine the consequences of the nationwide scale of an electronic funds management system in India's workfare programme, and report that it reduced expenditures by 19%. The present paper extends its analysis by (a) exploiting the recent literature that disaggregates the TWFE coefficient in the presence of staggered treatment timing to pinpoint sources of identifying variation and (b) attempting to uncover heterogeneity in treatment effects. We find that certain problematic comparisons have a large weight in the TWFE coefficient. Further, an event study analysis of the six constituent and valid comparisons shows that there is no support for parallel trends, so lag coefficients cannot be vested with causal interpretation. Our results imply that large‐scale evaluations, because of the very diversity they encompass, need to explicitly account for the factors that are responsible for programme effectiveness. [ABSTRACT FROM AUTHOR]

Rationale: Although recent evidence suggested that glucagon-like peptide 1 receptor agonists (GLP1RAs) might reduce the risk of asthma exacerbations, it remains unclear which subpopulations might derive the most benefit from GLP1RA treatment. Objectives: To identify characteristics of patients with asthma that predict who might benefit the most from GLP1RA treatment using real-world data. Methods: We implemented an active-comparator, new-user design analysis using commercially ensured patients 18–65 years of age from MarketScan data for 2007–2019 and identified two cohorts: GLP1RAs versus thiazolidinediones and GLP1RAs versus sulfonylureas. The outcome was acute exacerbation of asthma (hospital admission or emergency department visit for asthma) within 180 days after initiation. We applied iterative causal forest, a novel causal machine learning subgrouping algorithm, to assess heterogeneous treatment effects. In identified subgroups, we predicted propensity score, conducted propensity score trimming, and then estimated adjusted risk differences for the effect of GLP1RAs relative to comparators on asthma exacerbation using inverse probability treatment weighting in the propensity score–trimmed subpopulation. Results: Among 10,989 patients initiating GLP1RAs or thiazolidinediones and 17,088 patients initiating GLP1RAs versus sulfonylurea, GLP1RA initiators had fewer exacerbations, with adjusted risk differences of −0.5% (95% confidence interval [CI], −1.1% to 0.1%) and −1.6% (95% CI, −2.2% to −1.1%), respectively. In the GLP1RA versus sulfonylurea cohort, in which we observed a beneficial effect, our iterative causal forest analysis identified five subgroups with different treatment effects, defined by the number of emergency department visits, the number of prescriptions for short-acting β2-agonists, the number of prescriptions for inhaled steroids and long-acting β-agonists (either combination therapy or concurrent use), and age ≥ 50 years. Among these, patients with two or more emergency department visits during the 12-month baseline period had the largest absolute exacerbation risk reduction, with a decrease of 2.8% for GLP1RAs (95% CI, −4.8% to −0.9%). Conclusions: GLP1RAs demonstrated a beneficial effect on reducing asthma exacerbation relative to sulfonylureas. Patients with asthma with two or more emergency department visits (a proxy for disease severity) benefit most from GLP1RAs. Emergency department visit frequency, the number of maintenance and reliever inhalers, and age might help individualize prediction of the short-term benefit of GLP1RAs on asthma exacerbation. [ABSTRACT FROM AUTHOR]

Air quality information disclosure has emerged as a popular policy tool to reduce emissions, yet its impact on both environmental and economic performance remains ambiguous. This study employs a comprehensive measure of environmental-economic efficiency, the Green Total Factor Productivity (GTFP), to investigate the effect of China's mandated air quality disclosure program from 2003 to 2016. Using a difference-in-differences approach, we find that cities subject to disclosure experienced an average decline of 8% in GTFP. To further explore the heterogeneity in the treatment effect, we apply causal forest, a state-of-the-art causal machine learning technique for estimating individual treatment effects. The analysis uncovers substantial variation in the impact of information disclosure across cities, suggesting that the negative average effect may be partially attributed to mistargeting. We identify financial constraints, industrial composition, and urban scale as key moderators of the disclosure program's effectiveness. Moreover, our findings indicate that disclosing negative information, such as severe pollution levels or low environmental rankings, has a more pronounced impact compared to neutral content. By identifying key moderators and differential impacts of disclosure content, this study provides a foundation for targeted policy design to enhance the effectiveness of environmental information regulations. [ABSTRACT FROM AUTHOR]

We propose spatial difference-in-differences (DID) models that are able to incorporate treatment effect spillovers through modeling spatial interactions in the response and spatial correlations in treatment status among individuals. We first explore the ways in which combinations of spatial interaction and spatial correlation bias the conventional DID estimator, and then we develop spatial DID models, estimators, and specification tests that allow for a flexible order of local spatial structures. We consider both simultaneous and dynamic treatment. The local spatial DID models with a flexible order of spatial structure allow for different types of heterogeneity in the treatment effects. Monte Carlo simulations support our discussions of the bias in the conventional DID model under spatial interaction and correlation, and demonstrate the finite sample performance of our proposed models, estimators, and tests. [ABSTRACT FROM AUTHOR]

Evaluation of the heterogeneous treatment effect (HTE) allows for the assessment of the causal effect of a therapy or intervention while considering heterogeneity in individual factors within a population. Machine learning (ML) methods have previously been employed for HTE evaluation, addressing the limitations associated with modelling complex systems. In this work, three tree-based ML algorithms, causal random forest (CRF), causal Bayesian additive regression trees (CBART), and causal rule ensemble (CRE), are used to analyze the potential causation of benzene exposure to cause childhood acute myeloid leukemia (AML). Data for this analysis is generated by drawing samples from a previously developed model that estimates AML probability given as input demographic information and benzene exposure. Comparison is drawn between the three tree-based algorithms in terms of the predicted average treatment effect (ATE), the regression coefficient of determination, and the computational time of each algorithm. Minimal difference is reported between the three tree-based algorithms in terms of the ATE, as well as the regression coefficient of determination. However, CRF outperforms CBART in terms of algorithm computational time. Moreover, CRF allows for both continuous and binary treatment variables, as opposed to CBART and CRE, making it better suited to environmental health studies, where exposure levels of pollutants shall be considered continuous. Following the comparison of all three algorithms, the influence of adding Gaussian noise to the treatment and outcome variables, as well as outliers, is investigated using CRF. A set of considerations is drawn to guide researchers in using these algorithms. These considerations detail the simulation settings, applications, and results interpretation and aim to provide prompt information in decision-making surrounding the establishment of pollutant exposure thresholds in environmental risk assessments. [ABSTRACT FROM AUTHOR]

Background: Cluster randomized trials (CRTs) are increasingly important for evaluating interventions embedded in health care systems. An essential parameter in sample size calculation to detect both overall and heterogeneous treatment effects for CRTs is the intra-cluster correlation coefficient (ICC) of both outcome and covariates of interest. However, obtaining advance estimates for the ICC can be challenging. When trial outcomes will be obtained from routinely collected data sources, there is an opportunity to obtain reliable ICC estimates in advance of the trial. Using USA national Medicare data, we estimated ICCs for a range of outcomes to inform the design of CRTs for people living with Alzheimer's and related dementias (ADRD). Method: Data from 2018 Medicare Fee-for-Service beneficiaries, specifically, 1,898,812 individuals (≥ 65 years) with diagnosis of ADRD within 3436 hospital service areas (treated as clusters) and 306 hospital referral regions (treated as fixed strata), were used to calculate unadjusted and adjusted ICC estimates for three outcomes: death, any hospitalizations, and any emergency department (ED) visits and three covariates: age, race and sex. We present both overall and stratum-specific ICC estimates. We illustrate their use in sample size calculations for overall treatment effects as well as detecting treatment effect heterogeneity. Results: The unadjusted overall ICCs for death, hospitalizations, and ED visits were 0.001, 0.010, and 0.017 respectively. Stratum-specific ICCs varied widely across the 306 HRRs: median 0.001, 0.010 and 0.025 for death, hospitalizations, and ED visits respectively and 0.007, 0.001, and 0.080 for age, sex and race. An interactive R Shiny app is provided that allows users to retrieve estimates overlayed on a map of the USA. Conclusions: We presented both adjusted and unadjusted ICCs for outcomes as well as unadjusted ICCs for covariates of potential interest from population-level data in the USA and demonstrated how the estimates may be used in sample size calculations for CRTs in ADRD. [ABSTRACT FROM AUTHOR]

AbstractMultiregional clinical trials (MRCTs) have become increasingly common in recent years. Detecting underlying regional heterogeneity is a critical issue for these trials. Existing methods for assessing treatment effect heterogeneity across regions have ignored the incomparability of baseline extrinsic risk factors of the randomized patients from different regions. In this paper, a calibration weighting method is proposed to calibrate the distribution of these extrinsic risk factors between multiple regions. We establish the consistency and the asymptotic normality of the calibration weighting estimator. Simulation studies confirm the finite sample properties of the proposed estimator as well as its superior performance over naive methods and the inverse probability weighting method. The proposed method is illustrated using a randomized clinical trial of adjuvant chemotherapy for resected non-small-cell lung cancer. [ABSTRACT FROM AUTHOR]

Objectives: Numerous studies have investigated the predictive significance of the platelet-to-lymphocyte ratio (PLR) in oral squamous cell carcinoma(OSCC). However, the results of studies on its prognostic value remain controversial. This study aims to evaluate the prognostic significance of the PLR in patients with OSCC. Materials and methods: We conducted a comprehensive search of PubMed, Embase, the Cochrane Library, and Web of Science databases for all studies investigating the association between PLR and prognosis in OSCC, from the inception of each database up to November 2023. The outcome measures included overall survival (OS), disease-free survival (DFS) and disease-specific survival (DSS). To identify potential sources of heterogeneity, sensitivity and subgroup analyses were performed, alongside an assessment of publication bias. The analyses in this study were conducted using RevMan and Stata software. Results: According to the inclusion criteria, 20 articles were included, including 5,714 patients.The meta-analysis revealed that an elevated PLR adversely affects OS (HR = 1.58; 95% CI: 1.29–1.94; p < 0.0001), DFS (HR = 1.71; 95% CI: 1.20–2.42; p < 0.003), and DSS (HR = 2.41; 95% CI: 1.79–3.25; p < 0.00001). The results of the subgroup analysis showed that a preoperative high PLR was associated with reduced OS when the PLR threshold was ≤ 150 (HR = 1.49, P = 0.0003).When the PLR threshold was > 150, Preoperative PLR was not significantly associated with the prediction of overall survival (OS) in OSCC. (P > 0.05). Conclusion: The prognostic significance of PLR in patients with oral cancer is evident in terms of OS, DSS, and DFS. Nonetheless, it is crucial to note that the predictive value of PLR might depend on specific threshold values. [ABSTRACT FROM AUTHOR]

We empirically investigate the effectiveness of 17 macroprudential policy (MPP) instruments on financial and macroeconomic stability for 98 emerging market and 36 advanced economies between 1990 and 2020. We use Difference-in-Difference estimators with heterogeneous treatment effects which are robust in estimating treatment effects as compared to time and group fixed effects estimators. We find that while in short-term MPP instruments stabilize capital & other investment flows, in longer term, the regulations may increase fluctuations. Further we find that the MPP regulation reduces leverage growth in short-term, however, it may increase leverage growth in longer term. Our results show that broadly, tightening MPP instruments has a stabilizing impact on financial variables. However, the results indicate that MPP may have negative spill-over effects on real GDP growth. The impact on real effective exchange rate depreciation is mixed. [ABSTRACT FROM AUTHOR]

Rationale: Pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH) cause right ventricular dysfunction, which can impact other solid organs. However, the profiles and consequences of hepatic injury resulting from PAH and CTEPH have not been well studied. Objectives: We aimed to identify underlying patterns of liver injury in a cohort of patients with PAH and CTEPH enrolled in 15 randomized clinical trials conducted between 1998 and 2014. Methods: We used unsupervised machine learning to identify liver injury clusters in 13 trials and validated the findings in two additional trials. We then determined whether these liver injury clusters were associated with clinical outcomes or treatment effect heterogeneity. Measurements and Main Results: Our training dataset included 4,219 patients and our validation dataset included 1,756 patients with serum total bilirubin, alkaline phosphatase, aspartate aminotransferase, alanine aminotransferase, and albumin data. Using k-means clustering, we identified phenotypes with no liver injury, hepatocellular injury, cholestatic injury, and combined injury patterns. Patients in the cholestatic injury liver cluster had the shortest time to clinical worsening and the highest risk of mortality. The cholestatic injury group also experienced the greatest placebo-corrected treatment effect on 6-minute-walk distance. Randomization to the experimental arm transitioned patients to a healthier liver status. Conclusions: Liver injury was associated with adverse outcomes in patients with PAH and CTEPH. Randomization to active treatment had beneficial effects on liver health compared with placebo. The role of liver disease (often subclinical) in determining outcomes warrants prospective studies. [ABSTRACT FROM AUTHOR]

Background: Drug-resistant tuberculosis (DR-TB) significantly increases the risk of depression, yet research on mental health in this population remains limited. Aim: This meta-analysis aimed to evaluate the prevalence of depression among multidrug-resistant TB (MDR-TB) patients, emphasizing the necessity for integrated mental health care. Methods: A systematic search across PubMed, Cochrane, EBSCOhost, and Google Scholar identified 536 articles, which were screened for eligibility after removing duplicates. Prevalence data were analyzed using R programming, with back-transformation applied to enhance accuracy. The methodological quality of the included studies was assessed with the JBI Critical Appraisal Checklist, and the study protocol is registered in PROSPERO (CRD42023449156). Results: Ultimately, twelve studies involving 3,258 participants were included in the analysis. The pooled prevalence of depression among MDR-TB patients was found to be 54% (95% CI: 42%-65%). Although substantial heterogeneity was noted (I² = 72%; P < 0.01), excluding one study (Walker et al.) due to high Cook's distance revised the prevalence to 55% (95% CI: 43%-68%), with reduced heterogeneity (I² = 68%; P < 0.01). Subgroup analyses indicated minimal variability among studies using the Hamilton Depression Rating Scale (52%, 95% CI: 40%-64%) and substantial variability among those employing the Patient Health Questionnaire (54%, 95% CI: 30%-79%). Funnel plot analysis and Egger's test revealed no significant publication bias (P = 0.2105). Conclusion: This study highlights a high prevalence of depression among MDR-TB patients, underscoring the urgent need for integrated mental health care strategies tailored for this vulnerable population. Further research is essential to refine these strategies effectively. [ABSTRACT FROM AUTHOR]

The article discusses the long-term outcomes of nutrition trials in critical care patients. Survivors of critical illness often experience physical, cognitive, and mental disorders after leaving the hospital, leading to a lower quality of life. Various interventions, including nutrition therapy, have been studied to mitigate these adverse outcomes. The article focuses on the results of the EPaNIC trial, which examined the effects of early parenteral nutrition on mortality and functional outcomes. The study found no significant differences between the early and late parenteral nutrition groups in terms of mortality or physical functioning. The article emphasizes the importance of patient-centered outcomes and suggests that future research should focus on other aspects of nutrition therapy and long-term functional domains. [Extracted from the article]

Purpose: In critically ill adults, withholding parenteral nutrition until 1 week after intensive care admission (Late-PN) facilitated recovery as compared with early supplementation of insufficient enteral nutrition with parenteral nutrition (Early-PN). However, the impact on long-term mortality and functional outcome, in relation to the estimated nutritional risk, remains unclear. Methods: In this prospective follow-up study of the multicenter EPaNIC randomized controlled trial, we investigated the impact of Late-PN on 2-year mortality (N = 4640) and physical functioning, assessed by the 36-Item Short Form Health Survey (SF-36; in 3292 survivors, responding 819 [738–1058] days post-randomization). To account for missing data, we repeated the analyses in two imputed models. To identify potential heterogeneity of treatment effects, we investigated the impact of Late-PN in different nutritional risk subgroups as defined by Nutritional Risk Screening-2002-score, modified NUTrition Risk in the Critically Ill-score, and age (above/below 70 years), and we evaluated whether there was statistically significant interaction between classification to a nutritional risk subgroup and the effect of the randomized intervention. Secondary outcomes were SF-36-derived physical and mental component scores (PCS & MCS). Results: Two-year mortality (20.5% in Late-PN, 19.8% in Early-PN; P = 0.54) and physical functioning (70 [40–90] in both study-arms; P = 0.99) were similar in both groups, also after imputation of missing physical functioning data. Likewise, Late-PN had no impact on 2-year mortality and physical functioning in any nutritional risk subgroup. PCS and MCS were similar in both groups. Conclusion: Late-PN did not alter 2-year survival and physical functioning in adult critically ill patients, independent of anticipated nutritional risk. [ABSTRACT FROM AUTHOR]

To improve the validity of self-report measures, researchers should control for response style (RS) effects, which can be achieved with IRTree models. A traditional IRTree model considers a response as a combination of distinct decision-making processes, where the substantive trait affects the decision on response direction, while decisions about choosing the middle category or extreme categories are largely determined by midpoint RS (MRS) and extreme RS (ERS). One limitation of traditional IRTree models is the assumption that all respondents utilize the same set of RS in their response strategies, whereas it can be assumed that the nature and the strength of RS effects can differ between individuals. To address this limitation, we propose a mixture multidimensional IRTree (MM-IRTree) model that detects heterogeneity in response strategies. The MM-IRTree model comprises four latent classes of respondents, each associated with a different set of RS traits in addition to the substantive trait. More specifically, the class-specific response strategies involve (1) only ERS in the "ERS only" class, (2) only MRS in the "MRS only" class, (3) both ERS and MRS in the "2RS" class, and (4) neither ERS nor MRS in the "0RS" class. In a simulation study, we showed that the MM-IRTree model performed well in recovering model parameters and class memberships, whereas the traditional IRTree approach showed poor performance if the population includes a mixture of response strategies. In an application to empirical data, the MM-IRTree model revealed distinct classes with noticeable class sizes, suggesting that respondents indeed utilize different response strategies. [ABSTRACT FROM AUTHOR]

Background: Endovascular recanalization (ER) has demonstrated efficacy as a treatment modality for patients presenting with acute ischemic stroke (AIS) caused by large-vessel occlusion (LVO) within a 24-hour timeframe. Nevertheless, the safety and effectiveness of ER in patients with a time of onset exceeding 24 h remain uncertain. Objective: To evaluate the safety and efficacy of ER treatment for mild ischemic stroke beyond 24-h from symptom onset. Methods: A retrospectively maintained database of mild AIS due to LVO from March2018 to September 2022 at a comprehensive stroke center was screened. Patients received ER or standard medical therapies (SMT) for anterior circulation AIS due to LVO > 24-h were selected. Results: We included 47 LVO patients with mild AIS beyond 24-h who suffered neurological deterioration (ND). 34 of these patients underwent ER, the other 13 received SMT. The technical success rate of recanalization was 82.4% (28/34). Patients received ER had significantly lower NIHSS score at discharge and 90-day mRS score (p = 0.028, p = 0.037, respectively) compared to SMT. In addition, they had significantly lower 90-day recurrence of ischemic stroke and lower incidence of moderate-severe stroke (with a NIHSS score at least 5) (p = 0.037, p = 0.033). There were 4 patients (11.7%) had perioperative complications, and no symptomatic intracranial hemorrhage occurred. Conclusion: ER treatment for mild AIS due to LVO encountered ND was generally safe and effective, even beyond 24-h, and resulted in a good prognosis and lower 90-day recurrence compared to SMT. STRENGTHS AND LIMITATIONS OF THIS STUDY: ER for mild anterior stroke might be safe and feasible, even exceeding 24-h; The proposed protocol could be used for individualized treatment decision making; Modelling for heterogeneity of treatment effect. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases (CVDs) are the leading causes of global mortality. Modifiable behavioural and metabolic risk factors significantly contribute to the burden of CVD. Given the vast socio-demographic and health outcome heterogeneity in Latin America, similar southern Latin American countries (Argentina, Chile, and Uruguay) were analysed as a distinct group to describe the CVD death rates related to metabolic and behavioural risk factors. An ecological study was performed using data from the Global Burden of Disease Study 2019. Metabolic and behavioural risk factors-related CVD death were examined by analysing age-standardised rates per 100,000 individuals in the three countries between 1990 and 2019. While exposure to behavioural risk is decreasing, an upwards trend was observed in metabolic risks. Among the assessed risk factors, metabolic factors emerged as the primary contributors to deaths. High fasting plasma glucose exhibited a remarkable increase in relative importance across most studied contexts. Dietary risks stood out among behavioural factors due to their complexity and substantial changes observed. Although mortality rates have declined for overall CVD, peripheral artery disease mortality is rising. Modifiable behavioural and metabolic risk factors significantly influence CVD mortality in Southern Latin America. Despite the increasing exposure to metabolic risks, advancements in prevention and treatment are evidenced in the decline of mortality rates for most CVD. These findings emphasise the need for targeted interventions and comprehensive strategies to address their impact on cardiovascular health, advocating for healthy lifestyle behaviours to mitigate the progression and CVD development. • What is the cardiovascular disease burden from modifiable behavioural and metabolic risk factors in Southern Latin America? • Metabolic risks drove cardiovascular deaths: blood pressure was most significant and fasting glucose increased the most. • Focused prevention and treatment strategies targeting these factors can enhance life quality and expectancy. [ABSTRACT FROM AUTHOR]

Multisite cluster randomized trials (MCRTs), in which, the intermediate-level clusters (e.g., classrooms) are randomly assigned to the treatment or control condition within each site (e.g., school), are among the most commonly used experimental designs across a broad range of disciplines. MCRTs often align with the theory that programs are delivered at a cluster-level (e.g., teacher professional development) and provide opportunities to explore treatment effect heterogeneity across sites. In designing experimental studies, a critical step is the statistical power analysis and sample size determination. However, the statistical tools for power analysis of moderator effects in three-level MCRTs are not available. In this study, we derived formulas for calculating the statistical power and the minimum detectable effect size difference (MDESD) with confidence intervals for investigating the effects of various moderators in three-level MCRTs. We considered the levels of the moderators (level-1, −2, and −3), the scales of the moderators (binary and continuous), and random and nonrandomly varying slopes of the (moderated) treatment effects. We validated our formulas through Monte Carlo simulations. Finally, we conclude with directions for future work. [ABSTRACT FROM AUTHOR]

Psychologists are increasingly interested in whether treatment effects vary in randomized controlled trials. A number of tests have been proposed in the causal inference literature to test for such heterogeneity, which differ in the sample statistic they use (either using the variance terms of the experimental and control group, their empirical distribution functions, or specific quantiles), and in whether they make distributional assumptions or are based on a Fisher randomization procedure. In this manuscript, we present the results of a simulation study in which we examine the performance of the different tests while varying the amount of treatment effect heterogeneity, the type of underlying distribution, the sample size, and whether an additional covariate is considered. Altogether, our results suggest that researchers should use a randomization test to optimally control for type 1 errors. Furthermore, all tests studied are associated with low power in case of small and moderate samples even when the heterogeneity of the treatment effect is substantial. This suggests that current tests for treatment effect heterogeneity require much larger samples than those collected in current research. [ABSTRACT FROM AUTHOR]

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When upstream suppliers are VAT-exempted, overclaiming by fictional invoices becomes easier. This paper examines the effect of the presumed input VAT deduction reform on VAT evasion among VAT-exempted transactions in China. In the reform, firms are required to claim the presumed input refund of VAT based on downstream sales volume instead of on purchasing cost recorded on self-issued purchased invoices. We find that the reform reduced firms' VAT evasion since taxpayers have little incentive to use spurious invoices. Furthermore, the reform demonstrated more pronounced policy effects when taxpayers are low in tax-compliance and local economy contains a higher share of tax-noncompliant firms with poor accounting records. Results survive a battery of robustness checks as well as treatment effect heterogeneity. The presumed input VAT method would be a complementary tax enforcement tool to avoid VAT evasion in low tax capacity and high-informality settings under the context of credit-invoice VAT collection system. [ABSTRACT FROM AUTHOR]

The editorial "Using the difference-in-differences design with panel data in international business research: progress, potential issues, and practical suggestions" by Jiatao Li and Han Jiang discusses the popular design of causal inference in social science research known as Difference-in-Differences (DID) design. The article highlights the importance of identifying a particular event that influences some subjects but not others and compares the differences in outcomes before and after the treatment. The text emphasizes the need for caution when applying DID design with panel data, as violations of key assumptions can lead to biased estimations. Practical recommendations are provided to enhance the rigor of future research using DID design with panel data in the field of international business. [Extracted from the article]

Background: Precision medicine has led to the development of targeted treatment strategies tailored to individual patients based on their characteristics and disease manifestations. Although precision medicine often focuses on a single health outcome for individualized treatment decision rules (ITRs), relying only on a single outcome rather than all available outcomes information leads to suboptimal data usage when developing optimal ITRs. Methods: To address this limitation, we propose a Bayesian multivariate hierarchical model that leverages the wealth of correlated health outcomes collected in clinical trials. The approach jointly models mixed types of correlated outcomes, facilitating the "borrowing of information" across the multivariate outcomes, and results in a more accurate estimation of heterogeneous treatment effects compared to using single regression models for each outcome. We develop a treatment benefit index, which quantifies the relative benefit of the experimental treatment over the control treatment, based on the proposed multivariate outcome model. Results: We demonstrate the strengths of the proposed approach through extensive simulations and an application to an international Coronavirus Disease 2019 (COVID-19) treatment trial. Simulation results indicate that the proposed method reduces the occurrence of erroneous treatment decisions compared to a single regression model for a single health outcome. Additionally, the sensitivity analyses demonstrate the robustness of the model across various study scenarios. Application of the method to the COVID-19 trial exhibits improvements in estimating the individual-level treatment efficacy (indicated by narrower credible intervals for odds ratios) and optimal ITRs. Conclusion: The study jointly models mixed types of outcomes in the context of developing ITRs. By considering multiple health outcomes, the proposed approach can advance the development of more effective and reliable personalized treatment. [ABSTRACT FROM AUTHOR]

Appropriately managing working hours is at the core of the policy on teachers’ working conditions. We analyzed the impact of long working hours on teachers’ well-being using data on Japanese teachers from TALIS 2018. We applied a novel identification strategy that does not require panel data, forcing variables, or instrumental variables. The findings revealed a substantial negative impact of long working hours on teachers’ well-being, which may have been underestimated in extant research. Furthermore, the effects of long working hours are highly heterogeneous, and amplified by individual and contextual factors. [ABSTRACT FROM AUTHOR]

In this paper, we study the impairment in monetary policy caused by different forms of global financial cycles. We find that while both equity inflows and outflows cycles do exert influence over monetary policy, the bond inflows cycle does not have a significant impact. Further, we discuss the role of macroprudential policies in mitigating this impairment by using Difference-in-Difference with heterogeneous treatment effects which is robust to presence of heterogeneity across both time periods and groups. We find that FX-based policies such as Capital Restrictions on Foreign Exchange positions and Limits on Foreign Exposure alongside SIFIs and Loan Loss Provisioning are effective in reducing the impairment. [ABSTRACT FROM AUTHOR]

Background: Previous research on the risk of dementia associated with education attainment, smoking status, and alcohol use disorder (AUD) has yielded inconsistent results, indicating potential heterogeneous treatment effects (HTEs) of these factors on dementia risk. Thus, this study aimed to identify the important variables that may contribute to HTEs of these factors in older adults. Methods: Using 2005–2021 data from the National Alzheimer's Coordinating Center (NACC), we included older adults (≥ 65 years) with normal cognition at the first visit. The exposure of interest included college education or above, current smoking, and AUD and the outcome was all-cause dementia. We applied doubly robust learning to estimate risk differences (RD) and 95% confidence intervals (CI) between exposed and unexposed groups in the overall cohort and subgroups identified through a decision tree model. Results: Of 10,062 participants included, 929 developed all-cause dementia over a median 4.4-year follow-up. College education or above was associated with a lower risk of all-cause dementia in the overall population (RD, -1.5%; 95%CI, -2.8 to -0.3), especially among the subpopulations without hypertension, regardless of the APOE4 status. Current smoking was not related to increased dementia risk overall (2.8%; -1.5 to 7.2) but was significantly associated with increased dementia risk among men with (21.1%, 3.1 to 39.1) and without (8.4%, 0.9 to 15.8) cerebrovascular disease. AUD was not related to increased dementia risk overall (2.0%; -7.7 to 11.7) but was significantly associated with increased dementia risk among men with neuropsychiatric disorders (31.5%; 7.4 to 55.7). Conclusions: Our studies identified important factors contributing to HTEs of education, smoking, and AUD on risk of all-cause dementia, suggesting an individualized approach is needed to address dementia disparities. [ABSTRACT FROM AUTHOR]

Background: Guidelines by the National Institute for Health and Care Excellence recommend an angiotensin receptor blocker (ARB) rather than an angiotensin-converting enzyme inhibitor (ACEi) for the treatment of hypertension for people of African and Caribbean descent, due to an increased risk of angioedema associated with ACEi use observed in US trials. However, the effectiveness and risk of these drugs in Black populations in UK routine care is unknown. Methods and findings: We applied a reference trial emulation approach to UK Clinical Practice Research Datalink Aurum data (linked with data from Hospital Episode Statistics and Office for National Statistics) to study the comparative effectiveness of ARB and ACEi in ethnic minority groups in England, after benchmarking results against the ONTARGET trial. Approximately 17,593 Black, 30,805 South Asian, and 524,623 White patients receiving a prescription for ARB/ACEi between 1 January 2001 and 31 July 2019 were included with a median follow-up of 5.2 years. The primary composite outcome was cardiovascular-related death, myocardial infarction, stroke, or hospitalisation for heart failure with individual components studied as secondary outcomes. Angioedema was a safety endpoint. We assessed outcomes using an inverse-probability—weighted Cox proportional hazards model for ARB versus ACEi with heterogeneity by ethnicity assessed on the relative and absolute scale. For the primary outcome, 27,327 (18.0%) events were recorded in the ARB group (event rate: 25% per 5.5 person-years) and 80,624 (19.1%) events (event rate: 26% per 5.5 person-years) in the ACEi group. We benchmarked results against ONTARGET and observed hazard ratio (HR) 0.96 (95% CI: 0.95, 0.98) for the primary outcome, with an absolute incidence rate difference (IRD)% of -1.01 (95% CI: -1.42, -0.60) per 5.5 person-years. We found no evidence of treatment effect heterogeneity by ethnicity for the primary outcome on the multiplicative (Pint = 0.422) or additive scale (Pint = 0.287). Results were consistent for most secondary outcomes. However, for cardiovascular-related death, which occurred in 37,554 (6.6%) people, there was strong evidence of heterogeneity on the multiplicative (Pint = 0.002) and additive scale (Pint < 0.001). Compared to ACEi, ARB were associated with more events in Black individuals (HR 1.20 (95% CI: 1.02, 1.40); IRD% 1.07 (95% CI: 0.10, 2.04); number-needed-to-harm (NNH): 93) and associated with fewer events in White individuals (HR 0.91 (95% CI: 0.88, 0.93); IRD% -0.87 (95% CI: -1.10, -0.63); number-needed-to-treat (NNT): 115), and no differences in South Asian individuals (HR 0.97 (95% CI: 0.86, 1.09); IRD% -0.17 (95% CI: -0.87, 0.53)). For angioedema, HR 0.56 (95% CI: 0.46, 0.67) with no heterogeneity for ARB versus ACEi on the multiplicative scale (Pint = 0.306). However, there was heterogeneity on the additive scale (Pint = 0.023). Absolute risks were higher in Black individuals (IRD% -0.49 (95% CI: -0.79, -0.18); NNT: 204) compared with White individuals (IRD% -0.06 (95% CI: -0.09, -0.03); NNT: 1667) and no difference among South Asian individuals (IRD% -0.05 (95% CI: -0.15, 0.05) for ARB versus ACEi. Conclusions: These results demonstrate variation in drug effects of ACEi and ARB for some outcomes by ethnicity and suggest the potential for adverse consequences from current UK guideline recommendations for ARB in preference to ACEi for Black individuals. Leveraging data form the UK CPRD Aurum, Paris Jade Baptiste and colleagues apply target trial emulation methods to a cohort of >570,000 participants to explore the effectiveness and risk of ACE-inhibitors and ARB according to ethnicity. Author summary: Why was this study done?: UK hypertension treatment guidelines, which include ethnicity (Black versus non-Black) as a determinant of treatment choice are based on evidence from dated randomised controlled trials (RCTs) often arising from US populations, with conclusions extrapolated to ethnic minority groups in the UK. Despite an increased risk of hypertension and cardiovascular disease among South Asian patients in the UK, little is known about comparative treatment effectiveness and risk of angiotensin receptor blocker (ARB) and angiotensi-converting enzyme inhibitor (ACEi). Using reference trial emulation (considering study design and benchmarking against an existing RCT), followed by analysis of effects in trial-underrepresented groups can add confidence to findings of observational research and bridge gaps in evidence, allowing us to explore the "real-world" generalisability of the ONTARGET trial. What did the researchers do and find?: The researchers used a reference trial emulation approach, applied to self-reported Black, South Asian, and White patients at high risk of cardiovascular disease in primary care data from England, applied trial eligibility criteria, and benchmarked findings against the ONTARGET trial, which compared ARB versus ACEi on cardiovascular outcomes. Our results support the generalisability of the ONTARGET trial results to ethnic minority populations being prescribed an ARB or ACEi in England. Results suggest for cardiovascular death, treatment with ACEi might be associated with fewer events in people who are Black and ARB with fewer events in people who are White. Relative risks of angioedema for ARB versus ACEi were similar across all ethnic groups but because of the increased incidence in Black patients, there was a marked difference in the number needed to harm for ARB compared to ACEi use. There was no difference in cardiovascular outcomes or angioedema between the ARB versus ACEi in South Asian patients. What do these findings mean?: Unlike traditional RCTs, the reference trial emulation design provides an opportunity to study effects in large, diverse samples with the possibility to identify subgroup effects among trial-underrepresented groups, including South Asian and Black patients. Our results suggest variation in drug effects of ACEi and ARB by ethnicity for some outcomes and suggest the potential for adverse consequences from current UK guideline recommendations for ARB in preference to ACEi for Black individuals. Limitions include a risk of chance findings due to multiple testing by repeating all outcomes of ONTARGET. Despite taking measures to address confounding, unmeasured confounding could remain due to the nature of the study design. Without replication, it is uncertain to what extent our finding of differences in outcomes for ARB versus ACEi by ethnicity should influence current guidelines that recommend ARB over ACEi for Black individuals. [ABSTRACT FROM AUTHOR]

Purpose To familiarize clinicians with the emerging concepts in critical care research of Bayesian thinking and personalized medicine through phenotyping and explain their clinical relevance by highlighting how they address the issues of frequent negative trials and heterogeneity of treatment effect. Summary The past decades have seen many negative (effect-neutral) critical care trials of promising interventions, culminating in calls to improve the field's research through adopting Bayesian thinking and increasing personalization of critical care medicine through phenotyping. Bayesian analyses add interpretive power for clinicians as they summarize treatment effects based on probabilities of benefit or harm, contrasting with conventional frequentist statistics that either affirm or reject a null hypothesis. Critical care trials are beginning to include prospective Bayesian analyses, and many trials have undergone reanalysis with Bayesian methods. Phenotyping seeks to identify treatable traits to target interventions to patients expected to derive benefit. Phenotyping and subphenotyping have gained prominence in the most syndromic and heterogenous critical care disease states, acute respiratory distress syndrome and sepsis. Grouping of patients has been informative across a spectrum of clinically observable physiological parameters, biomarkers, and genomic data. Bayesian thinking and phenotyping are emerging as elements of adaptive clinical trials and predictive enrichment, paving the way for a new era of high-quality evidence. These concepts share a common goal, sifting through the noise of heterogeneity in critical care to increase the value of existing and future research. Conclusion The future of critical care medicine will inevitably involve modification of statistical methods through Bayesian analyses and targeted therapeutics via phenotyping. Clinicians must be familiar with these systems that support recommendations to improve decision-making in the gray areas of critical care practice. [ABSTRACT FROM AUTHOR]

A Japanese clinical trial (JGOG3016) showed that dose‐dense weekly paclitaxel in combination with carboplatin extensively prolonged overall survival (OS) in patients with advanced ovarian cancer. However, in other clinical trials, dose‐dense paclitaxel regimens were not superior to triweekly paclitaxel regimens. In this study, causal tree analysis was applied to explore subpopulations with different treatment effects of dose‐dense paclitaxel in a data‐driven approach. The 587 participants with stage II–IV ovarian cancer in the JGOG3016 trial were used for model development. The primary endpoint was treatment effect in terms of 3‐year OS in patients receiving dose‐dense vs. conventional paclitaxel therapies. In patients <50 years, the 3‐year OS was similar in both groups; however, it was higher in the dose‐dense group in patients ≥50 years. Dose‐dense paclitaxel showed strong positive treatment effects in patients ≥50 years with stage II/III disease, BMI <23 kg/m2, non‐CC/MC, and residual tumor ≥1 cm. In contrast, although there was no significant difference in OS; the 3‐year OS rate was 23% lower in dose‐dense paclitaxel than conventional paclitaxel in patients ≥60 years with stage IV cancer. Patients in this group had a particularly lower performance status than other groups. Our causal tree analysis suggested that poor prognosis groups represented by residual tumor tissue ≥1 cm benefit from dose‐dense paclitaxel, whereas elderly patients with advanced disease and low‐performance status are negatively impacted by dose‐dense paclitaxel. These subpopulations will be of interest to future validation studies. Personalized treatments based on clinical features are expected to improve advanced ovarian cancer prognosis. [ABSTRACT FROM AUTHOR]

Dual antiplatelet therapy (DAPT) for 12 months is the standard of care after coronary stenting in patients with acute coronary syndrome (ACS). The aim of this individual patient-level meta-analysis was to summarise the evidence comparing DAPT de-escalation to ticagrelor monotherapy versus continuing DAPT for 12 months after coronary drug-eluting stent implantation. A systematic review and individual patient data (IPD)-level meta-analysis of randomised trials with centrally adjudicated endpoints was performed to evaluate the comparative efficacy and safety of ticagrelor monotherapy (90 mg twice a day) after short-term DAPT (from 2 weeks to 3 months) versus 12-month DAPT in patients undergoing percutaneous coronary intervention with a coronary drug-eluting stent. Randomised trials comparing P2Y 12 inhibitor monotherapy with DAPT after coronary revascularisation were searched in Ovid MEDLINE, Embase, and two websites (www.tctmd.com and www.escardio.org) from database inception up to May 20, 2024. Trials that included patients with an indication for long-term oral anticoagulants were excluded. The risk of bias was assessed using the revised Cochrane risk-of-bias tool. The principal investigators of the eligible trials provided IPD by means of an anonymised electronic dataset. The three ranked coprimary endpoints were major adverse cardiovascular or cerebrovascular events (MACCE; a composite of all-cause death, myocardial infarction, or stroke) tested for non-inferiority in the per-protocol population; and Bleeding Academic Research Consortium (BARC) 3 or 5 bleeding and all-cause death tested for superiority in the intention-to-treat population. All outcomes are reported as Kaplan–Meier estimates. The non-inferiority was tested using a one-sided α of 0·025 with the prespecified non-inferiority margin of 1·15 (hazard ratio [HR] scale), followed by the ranked superiority testing at a two-sided α of 0·05. This study is registered with PROSPERO (CRD42024506083). A total of 8361 unique citations were screened, of which 610 records were considered potentially eligible during the screening of titles and abstracts. Of these, six trials that randomly assigned patients to ticagrelor monotherapy or DAPT were identified. De-escalation took place a median of 78 days (IQR 31–92) after intervention, with a median duration of treatment of 334 days (329−365). Among 23 256 patients in the per-protocol population, MACCE occurred in 297 (Kaplan–Meier estimate 2·8%) with ticagrelor monotherapy and 332 (Kaplan–Meier estimate 3·2%) with DAPT (HR 0·91 [95% CI 0·78–1·07]; p=0·0039 for non-inferiority; τ2<0·0001). Among 24 407 patients in the intention-to-treat population, the risks of BARC 3 or 5 bleeding (Kaplan–Meier estimate 0·9% vs 2·1%; HR 0·43 [95% CI 0·34–0·54]; p<0·0001 for superiority; τ2=0·079) and all-cause death (Kaplan–Meier estimate 0·9% vs 1·2%; 0·76 [0·59–0·98]; p=0·034 for superiority; τ2<0·0001) were lower with ticagrelor monotherapy. Trial sequential analysis showed strong evidence of non-inferiority for MACCE and superiority for bleeding among the overall and ACS populations (the z-curve crossed the monitoring boundaries or the required information size without crossing the futility boundaries or approaching the null). The treatment effects were heterogeneous by sex for MACCE (p interaction=0·041) and all-cause death (p interaction=0·050), indicating a possible benefit in women with ticagrelor monotherapy, and by clinical presentation for bleeding (p interaction=0·022), indicating a benefit in ACS with ticagrelor monotherapy. Our study found robust evidence that, compared with 12 months of DAPT, de-escalation to ticagrelor monotherapy does not increase ischaemic risk and reduces the risk of major bleeding, especially in patients with ACS. Ticagrelor monotherapy might also be associated with a mortality benefit, particularly among women, which warrants further investigation. Cardiocentro Ticino Institute, Ente Ospedaliero Cantonale. [ABSTRACT FROM AUTHOR]

The article explores the use of difference-in-differences (DID) designs in health systems research, specifically in assessing the effectiveness of health system interventions. It emphasizes the importance of establishing core assumptions and addressing potential biases in order to determine causal relationships. The article also discusses the need for clear assumptions, statistical assessments, and contextualization to enhance the quality of evaluations. It mentions the increasing acceptance of causal claims in observational studies by medical journals. [Extracted from the article]

Mechanistically targeted behavioral interventions are a much-needed strategy for improving outcomes in depression, especially for vulnerable populations with comorbidities such as obesity. Such interventions may change behavior and outcome by changing underlying neural circuit function. However, it is unknown how these circuit-level modifications unfold over intervention and how individual differences in early circuit-level modifications may explain the heterogeneity of treatment effects. We addressed this need within a clinical trial of problem-solving therapy for participants with depression symptoms and comorbid obesity, focusing on the cognitive control circuit as a putative neural mechanism of action. Functional magnetic resonance imaging was applied to measure the cognitive control circuit activity at five time points over 24 months. Compared with participants who received usual care, those receiving problem-solving therapy showed that attenuations in cognitive control circuit activity were associated with enhanced problem-solving ability, which suggests that this circuit plays a key role in the mechanisms of problem-solving therapy. Attenuations in circuit activity were also associated with improved depression symptoms. Changes in cognitive control circuit activity at 2 months better predicted changes in problem-solving ability and depression symptoms at 6, 12, and 24 months, with predictive improvements ranging from 17.8 to 104.0%, exceeding baseline demographic and symptom characteristics. Our findings suggest that targeting the circuit mechanism of action could enhance the prediction of treatment outcomes, warranting future model refinement and improvement to pave the way for its clinical application. Editor's summary: Behavioral intervention therapies can improve symptoms of depression but do not work for all patients. To identify brain circuit changes that might underlie treatment response, Zhang et al. performed a longitudinal fMRI imaging study on patients with depression and comorbid obesity who received either problem-solving therapy (I-CARE) or usual care (U-CARE). They found that decreased cognitive control circuit activity measured at different time points over 24 months correlated with better treatment outcomes. A predictive model based on control circuit changes at 2 months outperformed a standard model based on demographic and clinical parameters. These results suggest an approach that could support treatment outcome predictions for depression, but further optimization and validation are needed. —Daniela Neuhofer [ABSTRACT FROM AUTHOR]

Objective: Evidence for necrotising otitis externa (NOE) diagnosis and management is limited, and outcome reporting is heterogeneous. International best practice guidelines were used to develop consensus diagnostic criteria and a core outcome set (COS). Methods: The study was pre-registered on the Core Outcome Measures in Effectiveness Trials (COMET) database. Systematic literature review identified candidate items. Patient-centred items were identified via a qualitative study. Items and their definitions were refined by multidisciplinary stakeholders in a two-round Delphi exercise and subsequent consensus meeting. Results: The final COS incorporates 36 items within 12 themes: Signs and symptoms; Pain; Advanced Disease Indicators; Complications; Survival; Antibiotic regimes and side effects; Patient comorbidities; Non-antibiotic treatments; Patient compliance; Duration and cessation of treatment; Relapse and readmission; Multidisciplinary team management. Consensus diagnostic criteria include 12 items within 6 themes: Signs and symptoms (oedema, otorrhoea, granulation); Pain (otalgia, nocturnal otalgia); Investigations (microbiology [does not have to be positive], histology [malignancy excluded], positive CT and MRI); Persistent symptoms despite local and/or systemic treatment for at least two weeks; At least one risk factor for impaired immune response; Indicators of advanced disease (not obligatory but mut be reported when present at diagnosis). Stakeholders were unanimous that there is no role for secondary, graded, or optional diagnostic items. The consensus meeting identified themes for future research. Conclusion: The adoption of consensus-defined diagnostic criteria and COS facilitates standardised research reporting and robust data synthesis. Inclusion of patient and professional perspectives ensures best practice stakeholder engagement. [ABSTRACT FROM AUTHOR]

Simple Summary: Immune checkpoint inhibitors (ICIs) are a common and growing type of cancer treatment, but they can cause side effects. This study aims to understand these side effects in patients with kidney cancer and bladder cancer. We compared the types and severity of side effects between these two groups to determine if there are differences. We also compared them to other tumor types to see if there is a unique pattern. The findings will help doctors better predict and manage side effects. This will hopefully lead to improving patient care for those receiving ICI treatment. Background: Immune checkpoint inhibitors (ICIs) have become common lines of therapy for genitourinary cancers (GUcs). Given their widespread use, understanding the risk factors, comparative profiles, and timing of immune-related adverse events (irAEs) is essential. Methods: We created an IRB-approved retrospective registry of all patients who received at least one dose of an ICI for any indication between 1 February 2011 and 7 April 2022 at a comprehensive cancer center and its outreach clinics. Dichotomous outcomes were modeled using multivariable logistic regression. Survival outcomes were compared using multivariable Cox regression. Results: Among 3101 patients, 196 had renal cell carcinoma (RCC) and 170 had urothelial tumors. RCC patients were more likely to experience irAEs (OR 1.78; 95% CI 1.32–2.39), whereas urothelial carcinoma patients were not (OR 1.22; 95% CI 0.88–1.67). RCC patients were more prone to dermatitis, thyroiditis, acute kidney injury, and myocarditis, compared to other tumors, while urothelial carcinoma patients were not. The impact of irAEs on survival was not significantly different for GUcs compared to other tumors. Conclusions: RCC primaries have a significantly different irAE profile than most tumors, as opposed to urothelial primaries. Further, RCC was more likely to experience any irAEs. Heterogeneity of survival benefits by irAEs was not seen. [ABSTRACT FROM AUTHOR]

Psychotherapy has been proven to be effective on average, though patients respond very differently to treatment. Understanding which characteristics are associated with treatment effect heterogeneity can help to customize therapy to the individual patient. In this tutorial, we describe different meta-learners, which are flexible algorithms that can be used to estimate personalized treatment effects. More specifically, meta-learners decompose treatment effect estimation into multiple prediction tasks, each of which can be solved by any machine learning model. We begin by reviewing necessary assumptions for interpreting the estimated treatment effects as causal, and then give an overview over key concepts of machine learning. Throughout the article, we use an illustrative data example to show how the different meta-learners can be implemented in R. We also point out how current popular practices in psychotherapy research fit into the meta-learning framework. Finally, we show how heterogeneous treatment effects can be analyzed, and point out some challenges in the implementation of meta-learners. [ABSTRACT FROM AUTHOR]

Objectives: To determine the effects of prophylactic urethrectomy (PU) on oncological and perioperative outcomes in patients with bladder cancer (BC) undergoing radical cystectomy (RC). Methods: This retrospective study analyzed data on 1976 evaluable patients with BC who underwent RC. Patients were drawn from 36 institutions within the Japanese Urological Oncology Group. Oncological outcomes were compared using restricted mean survival times (RMSTs) based on inverse probability of treatment weighting (IPTW)‐adjusted Kaplan–Meier curves for non‐urinary tract recurrence‐free survival (NUTRFS), cancer‐specific survival (CSS), and overall survival (OS). Interaction terms within IPTW‐adjusted Cox regression models were examined to assess the heterogeneity of treatment effect based on the risk of urethral recurrence (UR). The association between PU, estimated blood loss (EBL), and the incidence of severe postoperative surgical complications (SPSCs) (Clavien‐Dindo grade 3 or higher) was analyzed. Results: Of 1976 patients, 1448 (73.3%) received PU. IPTW adjustment was used to balance baseline characteristics between the treatment groups. Within the 107‐month window of patient monitoring, PU showed no survival benefits (NUTRFS difference: 0.2 months [95% confidence interval: −6.8 to 7.3]; CSS, 1.2 [−4.9 to 7.3]; OS, 0 [−6.5 to 6.5]). No significant interactions were observed with factors associated with UR, and PU was associated with unfavorable perioperative outcomes (EBL, 1179 mL vs. 983 mL; SPSC, 14.6% vs. 7.0%). Conclusions: This study showed that (1) PU was not associated with survival in patients with BC undergoing RC, regardless of UR‐associated factors, and (2) PU was associated with unfavorable perioperative outcomes. [ABSTRACT FROM AUTHOR]

Critical care trials evaluate the effect of interventions in patients with diverse personal histories and causes of illness, often under the umbrella of heterogeneous clinical syndromes, such as sepsis or acute respiratory distress syndrome. Given this variation, it is reasonable to expect that the effect of treatment on outcomes may differ for individuals with variable characteristics. However, in randomized controlled trials, efficacy is typically assessed by the average treatment effect (ATE), which quantifies the average effect of the intervention on the outcome in the study population. Importantly, the ATE may hide variations of the treatment's effect on a clinical outcome across levels of patient characteristics, which may erroneously lead to the conclusion that an intervention does not work overall when it may in fact benefit certain patients. In this review, we describe methodological approaches for assessing heterogeneity of treatment effect (HTE), including expert-derived subgrouping, data-driven subgrouping, baseline risk modeling, treatment effect modeling, and individual treatment rule estimation. Next, we outline how insights from HTE analyses can be incorporated into the design of clinical trials. Finally, we propose a research agenda for advancing the field and bringing HTE approaches to the bedside. [ABSTRACT FROM AUTHOR]

To review the literature on the effects of vestibular training on motor function and balance in children and youth with cerebral palsy. Eight databases (MEDLINE-PubMed, PEDro, Cochrane Library, OTSeeker, Web of Science, Scopus Database, CINAHL and SPORTDiscus.) were searched up to May 15th, 2023. Studies comparing vestibular training with other types of interventions. The DerSimonian and Laird method was employed using random effects models to calculate the pooled estimate of the effect size with confidence intervals of 95%. The risk of bias was assessed with the Cochrane Collaboration's tool and the Grading of Recommendations Assessment, Development and Evaluation approach was used to judge the certainty of the evidence for all outcomes. Eight studies were included comprising 226 participants with cerebral palsy. The meta-analyses demonstrated significant standardized mean differences in favor of vestibular training program compared to other technique(s) for Gross Motor Function Measure (−0.471; 95% confidence intervals: −0.919 to −0.023) and balance (−0.546; 95% confidence intervals: −0.916 to −0.176). Vestibular training has potential benefits in the short-term as a therapeutic approach for improving gross motor function and the balance in children and youth with cerebral palsy, but further research is needed. [ABSTRACT FROM AUTHOR]