Frequentist Framework Research Articles

Functional language lateralization during sentence completion in the healthy brain is not associated with the quantitative estimate of familial sinistrality.

Familial sinistrality (left-handedness) has been suggested as a proxy for functional language lateralization in the healthy adult brain. Previous studies show that individuals with familial sinistrality tend to have less lateralized language-related brain activation, while individuals without familial sinistrality show greater left-hemispheric lateralization for language. However, familial sinistrality trait has always been treated as a binary categorical variable. In this study a more sensitive quantitative estimate of familial sinistrality (LH load) has been modelled in 39 participants with different direction and degree of handedness by applying a standard genetic multifactorial model. This LH load was tested for an association with functional language lateralization based on an fMRI sentence completion task. Using frequentist and Bayesian statistical frameworks, the association between LH load and language lateralization was not confirmed. The findings of the present research suggest that a quantitative measure of familial sinistrality is not related to individual language representation in the brain measured by a sentence completion fMRI paradigm. However, considering the context of our study and previous research we suggest that familial sinistrality being related to personal handedness could drive functional language lateralization through it.

The impact of high versus standard enteral protein provision on functional recovery following intensive care admission: A pre-planned Bayesian analysis of the PRECISe trial.

The impact of high versus standard enteral protein provision on functional recovery following intensive care admission: A pre-planned Bayesian analysis of the PRECISe trial.

Immunotherapy and PARP inhibitors as first-line treatment in endometrial cancer: A systematic review and network meta-analysis.

Immunotherapy and PARP inhibitors as first-line treatment in endometrial cancer: A systematic review and network meta-analysis.

Efficacy of interventions for the treatment of irritable bowel syndrome, functional abdominal pain-not otherwise specified, and abdominal migraine in children: a systematic review and network meta-analysis.

Efficacy of interventions for the treatment of irritable bowel syndrome, functional abdominal pain-not otherwise specified, and abdominal migraine in children: a systematic review and network meta-analysis.

Antipsychotic drug dosing and study discontinuation in schizophrenia: A systematic review and dose-response meta-analysis.

Antipsychotic drug dosing and study discontinuation in schizophrenia: A systematic review and dose-response meta-analysis.

Clinical Benefits and Risks of Antiamyloid Antibodies in Sporadic Alzheimer Disease: Systematic Review and Network Meta-Analysis With a Web Application.

Despite the increasing approval of antiamyloid antibodies for Alzheimer disease (AD), their clinical relevance and risk-benefit profile remain uncertain. The heterogeneity of AD and the limited availability of long-term clinical data make it difficult to establish a clear rationale for selecting one treatment over another. The aim of this work was to assess and compare the efficacy and safety of antiamyloid antibodies through an interactive online meta-analytic approach by performing conventional pair-wise meta-analyses and frequentist and Bayesian network meta-analyses of phase II and III clinical trial results. To achieve this, we developed AlzMeta.app 2.0, a freely accessible web application that enables researchers and clinicians to evaluate the relative and absolute risks and benefits of these therapies in real time, incorporating different prior choices and assumptions of baseline risks of disease progression and adverse events. We adhered to PRISMA-NMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for reporting of systematic reviews with network meta-analysis) and GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) guidelines for reporting and rating the certainty of evidence. Clinical trial reports (until September 30, 2024) were retrieved from PubMed, Google Scholar, and clinical trial databases (including ClinicalTrials.gov). Studies with <20 sporadic AD patients and a modified Jadad score <3 were excluded. Risk of bias was assessed with the RoB-2 tool. Relative risks and benefits have been expressed as risk ratios and standardized mean differences, with confidence, credible, and prediction intervals calculated for all outcomes. For significant results, the intervention effects were ranked in frequentist and Bayesian frameworks, and their clinical relevance was determined by the absolute risk per 1000 people and number needed to treat (NNT) for a wide range of control responses. Among 7 treatments tested in 21,236 patients (26 studies with low risk of bias or with some concerns), donanemab was the best-ranked treatment on cognitive and functional measures, and it was almost 2 times more effective than aducanumab and lecanemab and significantly more beneficial than other treatments on the global (cognitive and functional) Clinical Dementia Rating Scale-Sum of Boxes (NNT=10, 95% CI 8-16). Special caution is required regarding cerebral edema and microbleeding due to the clinically relevant risks of edema for donanemab (NNT=8, 95% CI 5-16), aducanumab (NNT=10, 95% CI 6-17), and lecanemab (NNT=14, 95% CI 7-31), which may outweigh the benefits. Our results showed that donanemab is more effective and has a safety profile similar to aducanumab and lecanemab, highlighting the need for treatment options with improved safety. Potential bias may have been introduced in the included trials due to unblinding caused by frequent cerebral edema and microbleeds, as well as the impact of the COVID-19 pandemic.

Improving Guideline Development Processes: Integrating Evidence Estimation and Decision-Analytical Frameworks.

Despite using state-of-the-art methodologies like Grades of Recommendation, Assessment, Development and Evaluation (GRADE), current guideline development frameworks still rely heavily on panellists' intuitive integration of evidence related to the benefits and harms/burdens of health interventions. This leads to the 'black-box' and 'integration' problems, highlighting the lack of transparency in guideline decision-making. Combined with humans' limited capacity to process the large volumes of information presented in Summary of Findings (SoF) tables-the primary output of systematic reviews that underpin guideline recommendations-this reliance on non-explicit processes raises concerns about the trustworthiness of clinical practice guidelines. SoF tables provide the best available evidence, derived from frequentist or Bayesian estimation frameworks. Decision analysis, which integrates both types of estimates but considers intervention consequences, is the only analytical approach that combines multiple outcomes (benefits, harms and costs) into a single metric to support decision-making. Such analysis seeks to identify the optimal decision by balancing harms, benefits and uncertainties. This paper leverages the PICO format (Population, Intervention, Comparison(s), Outcome) as a conceptual basis for deriving SoF tables. Subsequently, we propose a solution to GRADE's "black-box" and "integration" problems by matching PICO-based SoF with decision models. We succeeded in connecting the PICO framework to simple decision-analytical models, restricted to time frames supported by empirically verifiable evidence, to calculate which competing intervention offers the greatest benefit (net differences in expected utility; ΔEU). The single metric [ΔEU] enabled a simple, transparent and easy-to-understand assessment of the superiority of competing management strategies across multiple outcomes (considering both benefits and harms), addressing the 'black-box' and 'integration' problems. Completing a SoF-based decision model takes about 10 min. Not surprisingly, the recommendations based on ΔEU may differ from the intuitive recommendations of panels. We propose that incorporating the straightforward and transparent modelling into guideline panels' decision-making processes will enhance their intuitive judgements, resulting in more trustworthy recommendations. Given the simplicity of calculating ΔEU, we advocate for its immediate inclusion in systematic reviews and SoF tables.

Statistical primer: an introduction into the principles of Bayesian statistical analyses in clinical trials.

Trials in cardiac surgery are often hampered at the design level by small sample sizes and ethical considerations. The conventional analytical approach, combining frequentist statistics with null hypothesis significance testing, has known limitations and its associated P-values are often misinterpreted, leading to dichotomous conclusions of trial results. The Bayesian statistical framework may overcome these limitations through probabilistic reasoning and is subsequently introduced in this Primer. The Bayesian framework combines prior beliefs and currently obtained data (the likelihood), resulting in updated beliefs, also known as posterior distributions. These distributions subsequently facilitate probabilistic interpretations. Several previous cardiac surgery trials have been performed under a Bayesian framework and this Primer enhances the understanding of their basic concepts by linking results to graphical presentations. Furthermore, contemporary trials that were initially analysed under a frequentist framework, are re-analysed within a Bayesian framework to demonstrate several interpretative advantages.

Searches for signatures of ultralight axion dark matter in polarimetry data of the European Pulsar Timing Array

Ultralight axionlike particles (ALPs) can be a viable solution to the dark matter problem. The scalar field associated with ALPs, coupled to the electromagnetic field acts as an active birefringent medium, altering the polarization properties of light through which it propagates. In particular, oscillations of the axionic field induce monochromatic variations of the plane of linearly polarized radiation of astrophysical signals. The radio emission of millisecond pulsars provides an excellent tool to search for such manifestations, given their high fractional linear polarization and negligible fluctuations of their polarization properties. We have searched for evidence of ALPs in polarimetry measurements of pulsars collected and preprocessed for the European Pulsar Timing Array (EPTA) campaign. Focusing on the twelve brightest sources in linear polarization, we searched for an astrophysical signal from axions using both frequentist and Bayesian statistical frameworks. For the frequentist analysis, which uses Lomb-Scargle periodograms at its core, no statistically significant signal has been found. The model used for the Bayesian analysis has been adjusted to accommodate multiple deterministic systematics that may be present in the data. A statistically significant signal has been found in the dataset of multiple pulsars with common frequencies between 10−8 and 2×10−8 Hz, which can most likely be explained by the residual Faraday rotation in the terrestrial ionosphere. Strong bounds on the coupling constant gaγ, in the same ballpark as other searches, have been obtained in the mass range between 6×10−24 and 5×10−21 eV. We conclude by discussing the problems that can limit the sensitivity of our search for ultralight axions in the polarimetry data of pulsars, and possible ways to resolve them. Published by the American Physical Society 2025

Approaches for thoracoabdominal oesophagectomy for oesophageal cancer: a network meta-analysis – study protocol

IntroductionOesophageal cancer is the seventh most frequently diagnosed cancer and the sixth leading cause of cancer-related deaths worldwide. Oesophagectomy remains the main curative treatment option. The effect of different surgical...

Adjuvant endocrine treatment strategies for non-metastatic breast cancer: a network meta-analysis.

Adjuvant endocrine treatment strategies for non-metastatic breast cancer: a network meta-analysis.

Efficacy of Myopia Prevention in At-Risk Children: A Systematic Review and Network Meta-Analysis.

Objectives: To evaluate the efficacy of myopia prevention methods in children without pre-existing myopia. Methods: A network meta-analysis was conducted following the PRISMA-NMA guidelines. Comprehensive searches were performed in PubMed, Embase, and Cochrane CENTRAL databases. The analysis focused on randomized controlled trials evaluating myopia prevention strategies in children without prior myopia. Primary outcomes included annual changes in refraction and axial length, while secondary outcomes encompassed myopia incidence and adverse events. Effect sizes were reported as risk ratios (RR) or mean differences (MD) with 95% confidence intervals (CIs). Data synthesis utilized a random-effects model under a frequentist framework, with intervention efficacy ranked by P-scores. Study quality was assessed using the Cochrane risk-of-bias tool, and robustness was ensured via sensitivity and consistency analyses. Results: Low-level red light therapy and low-dose atropine were the most effective interventions for reducing refractive progression (MD: 0.48 D, 95% CI: 0.38-0.59 D; MD: 0.33 D, 95% CI: 0.23-0.43 D) and axial elongation (MD: -0.23 mm, 95% CI: -0.27 to -0.19 mm; MD: -0.12 mm, 95% CI: -0.16 to -0.08 mm). In addition, both significantly lowered myopia incidence (RR: 0.59, 95% CI: 0.45-0.79; RR: 0.55, 95% CI: 0.41-0.75). Outdoor activities and myopia awareness programs demonstrated moderate efficacy. Adverse events, including photophobia and dry eyes, were minor and self-limiting, with no serious complications reported. Conclusions: Low-level red light therapy and low-dose atropine are the most effective, generally safe strategies for preventing myopia in at-risk children without myopia, while a non-invasive approach, outdoor activities, provides moderate benefits.

Bayes factors for two-group comparisons in Cox regression with an application for reverse-engineering raw data from summary statistics

The use of Cox proportional hazards regression to analyze time-to-event data is ubiquitous in biomedical research. Typically, the frequentist framework is used to draw conclusions about whether hazards are different between patients in an experimental and a control condition. We offer a procedure to compute Bayes factors for simple Cox models, both for the scenario where the full data are available and for the scenario where only summary statistics are available. The procedure is implemented in our ‘baymedr’ R package. The usage of Bayes factors remedies some shortcomings of frequentist inference and has the potential to save scarce resources.

Long-Term Timing Analysis of PSR J1741—3016: Efficient Noise Characterization Using PINT

The stable rotation of young pulsars is often interrupted by two non-deterministic phenomena: glitches and red timing noise. Timing noise provides insights into plasma and nuclear physics under extreme conditions. The framework leverages rotational symmetry in pulsar spin-down models and temporal symmetry in noise processes to achieve computational efficiency, aligning with the journal’s focus on symmetry principles in physical systems. In this paper, we apply a novel frequentist framework developed within the PINT software package (v0.9.8) to analyze single-pulsar noise processes. Using 17.5 years of pulse time-of-arrival (TOA) data for the young pulsar PSR J1741—3016, observed with the Nanshan 26 m radio telescope, we investigate its timing properties. In this study, we employed the Downhill Weighted Least-Squares Fitter to estimate the pulsar’s spin parameters and position. The Akaike Information Criterion (AIC) was used for model parameter selection. The results obtained with PINT were compared to those from ENTERPRISE and TEMPONEST, two Bayesian-based frameworks. We demonstrate that PINT achieves comparable results with significantly reduced computational costs. Additionally, the adequacy of the noise model can be readily verified through visual inspection tools. Future research will utilize this framework to analyze timing noise across a large sample of young pulsars.

Machine perfusion strategies in liver transplantation: A systematic review, pairwise, and network meta-analysis of randomized controlled trials.

Machine perfusion (MP), including hypothermic oxygenated machine perfusion (HOPE), dual HOPE, normothermic machine perfusion (NMP), NMP ischemia-free liver transplantation (NMP-ILT), and controlled oxygenated rewarming (COR), is increasingly being investigated to improve liver graft quality from extended criteria donors and donors after circulatory death and expand the donor pool. This network meta-analysis investigates the comparative efficacy and safety of various liver MP strategies versus traditional static cold storage (SCS). We searched PubMed, Scopus, Web of Science, and Cochrane Controlled Register of Trials for randomized controlled trials comparing liver transplantation outcomes between SCS and MP techniques. The primary outcome was the incidence of early allograft dysfunction. Secondary endpoints included 1-year graft survival, the incidence of graft failure/loss, post-reperfusion syndrome, biliary complications, the need for renal replacement therapy, graft-related patient mortality, and the length of intensive care unit and hospital stay. R-software was used to conduct a network meta-analysis using a frequentist framework (PROSPERO ID: CRD42024549254). We included 12 randomized controlled trials involving 1628 patients undergoing liver transplantation (801 in the liver MP groups and 832 in the SCS group). Compared to SCS, HOPE/dHOPE, but not other MP strategies, was associated with a significantly lower risk of early allograft dysfunction (RR: 0.53, 95% CI [0.37, 0.74], p =0.0002), improved 1-year graft survival rate (RR: 1.07, 95% CI [1.01, 1.14], p =0.02), decreased graft failure/loss (RR: 0.38, 95% CI [0.16, 0.90], p =0.03), and reduced the risk of biliary complications (RR: 0.52, 95% CI [0.43, 0.75], p < 0.0001). Compared to SCS, NMP (RR: 0.49, 95% CI [0.24, 0.96]) and NMP-ILT (RR: 0.15, 95% CI [0.04, 0.57]), both significantly reduced the risk of postperfusion syndrome. There is no difference between SCS and MP groups in the risk of renal replacement therapy, graft-related patient mortality, and intensive care unit and hospital stay length. Our meta-analysis showed that HOPE/dual-HOPE is a promising alternative to SCS for donor liver preservation. These new techniques can help expand the donor pool with similar or even better post-liver transplantation outcomes.

Improving the Effectiveness of Sample Size Re-Estimation: An Operating Characteristic Focused, Hybrid Frequentist-Bayesian Approach.

Sample size re-estimation (SSR) is perhaps the most used adaptive procedure in both frequentist and Bayesian adaptive designs for clinical trials. The primary focus of all current frequentist and Bayesian SSR procedures is type I error control. We propose a hybrid frequentist-Bayesian SSR approach that focuses on optimizing operating characteristics (OC), which uses simulations to investigate the associated OC and adjusts accordingly. The hybrid approach incorporates the Bayesian predictive power into the frequentist framework of SSR. Simulations show that the hybrid approach can substantially outperform popular frequentist type error-focused SSR procedure. The hybrid approach can substantially improve the effectiveness of SSR using Bayesian predictive power.

Bayesian views of generalized additive modelling

Abstract Generalized additive models (GAMs) are a frequently used, flexible framework applied to many problems in statistical ecology. They are commonly used to incorporate smooth effects into models via splines, including spatial components in species distribution models. GAMs are often considered to be a purely frequentist framework (‘generalized linear models with wiggly bits’), however links between frequentist and Bayesian approaches to these models were highlighted early‐on in the literature. From a practical perspective, Bayesian thinking underlies many parts of the implementation in the popular R package mgcv, so understanding these underpinnings can be informative during model building and assessment. This article aims to highlight useful links (and differences) between Bayesian and frequentist approaches to smoothing, as detailed in the statistical literature, in accessible way, with a focus on the mgcv implementation. By harnessing these links we can expand the set of modelling tools we have at our disposal, as well as our understanding of how existing methods work. Two important topics for quantitative ecologists are covered in detail: model term selection and uncertainty estimation. Taking Bayesian viewpoints for these problems makes them much more tractable in many applied settings. Examples are given using data from the NOAA Alaska Fisheries Science Center's groundfish assessment program.

Non-pharmacological Interventions for Preoperative Anxiety in Children: A Systematic Review and Network Meta-Analysis.

This study aimed to compare the efficacy of non-pharmacological interventions in children with preoperative anxiety. It is estimated that preoperative anxiety affects up to 60% of children which is associated with both immediate and long-term adverse outcomes. Several non-pharmacological interventions have been demonstrated to be effective, but further research is necessary to determine which is the most effective. This study was conducted and reported in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 checklist. We searched randomised controlled trials in twelve databases from which inception to March 31, 2024. The primary outcome was the severity of preoperative anxiety change from the baseline to the endpoint which is usually before the anaesthesia induction. Within the frequentist framework, a random-effects network meta-analysis (NMA) was used to compare the primary outcomes. The surface under the cumulative ranking curve (SUCRA) was used to rank each intervention separately. Subgroup and sensitivity analyses were carried out for the primary outcomes. A total of 36 randomised controlled trials (RCTs) with 3182 paediatric patients were included. Based on the results, psychological + digital health intervention was significantly more effective than control groups and ranked highest. Combined parental presence during induction anaesthesia and video games (PPIA + VG) had significant benefits compared to almost all other interventions with the highest rank. Psychological + digital health interventions, especially PPIA + VG, may be the most effective non-pharmacological interventions for reducing preoperative anxiety in children. It is necessary to conduct more RCTs to evaluate the efficacy of different non-pharmacological interventions. Non-pharmacological interventions can effectively improve preoperative anxiety in children. No patient or public contribution applies to this work. PROSPERO CRD42024509512 (https://www.crd.york.ac.uk/PROSPERO/).

Exploring the relationship between income inequality and crime in Toronto using frequentist and Bayesian models: Examining different crime types and spatial scales

Income inequality, which refers to the uneven distribution of income in a population, has been linked to many societal problems, including crime. Although environmental criminology theories, such as rational choice theory, suggest a positive association between income inequality and crime, previous empirical studies have reported divergent results based on different crime types, statistical models, and spatial units of analysis. This study employs non-spatial and spatial regression models using frequentist and Bayesian modelling frameworks to explore the impacts of within-area and across-area income inequality on five types of major crimes in the City of Toronto at the census tract and dissemination area scales. The use of spatial regression models improves the model fit in both frequentist and Bayesian frameworks. The Bayesian shared component model, which accounts for the interactions between different types of crimes, further enhances model performance. Results obtained from the best-fitting frequentist and Bayesian models are inconsistent but do not conflict in terms of the relationship between crime and income inequality, where within-area income inequality generally increases major crime rates, while across-area income inequality has varying effects dependent on crime type and spatial scale. The discrepancies between spatial scales are a manifestation of the modifiable areal unit problem (MAUP).

Comparative efficacy and safety of dipeptidyl peptidase-4 inhibitors in adults with type 2 diabetes mellitus: A network meta-analysis.

We have compiled updated evidence on the benefits and drawbacks of dipeptidyl peptidase-4 (DPP-4) inhibitors in treating type 2 diabetes mellitus. We systematically searched PubMed, Embase, Cochrane Library, and ClinicalTrials.gov (as of 20 May 2024). Effect estimates were calculated using network meta-analysis under the frequentist framework. The P-score established the ranking of competing treatments. The authors incorporated 58 studies containing data from a substantial sample size of 21 332 patients. Based on evidence of high and moderate certainty, respectively, teneligliptin and vildagliptin were found to be superior to all other DPP-4 inhibitors in lowering haemoglobin A1c (mean difference [MD] -0.81%, 95% CI -1.03, -0.60) and fasting blood glucose (MD -1.18 mmol/L, 95% CI -1.56, -0.81) compared to placebo. The absence of conclusive differences between interventions for serious adverse events was supported by evidence, which was interpreted with low to very low certainty. In adults with type 2 diabetes, teneligliptin was most effective for HbA1c control, and vildagliptin for fasting blood glucose. No significant differences in serious adverse events were noted among DPP-4 inhibitors compared to placebo. Given the therapeutic significance of these findings, more studies are needed to explore this issue more thoroughly.