Bilateral data are frequently occur in medical research. Asymptotic approaches are traditionally used to construct confidence intervals for proportion difference. However, they are often have ...unsatisfactory performance with regards to coverage, with the actual coverage below the nominal level or being too conservative. For these reasons, we propose developing exact one-sided limits for proportion difference in a parallel study with bilateral data to guarantee the coverage probability when sample size is small to medium. A statistical quantity has to be used for sample space ordering in the exact limit calculation. Four asymptotic limits are utilized as statistical quantities: the Wald limits under the independence or dependence assumptions for variance estimates, the Wald limits with the difference estimate under the dependence assumption, and the bootstrap percentile limits. We compare the performance of these exact limits with regards to average length and the limits of all possible samples. A real example from a randomized clinical trial in otolaryngology is used to illustrate the application of the proposed exact limits.
To examine the characteristics of those who fulfil the recent National Institute of Neurological Disease and Stroke (NINDS) Consensus Diagnostic Criteria for Traumatic Encephalopathy Syndrome (TES) ...and test whether they show differences in MRI-based regional brain volumes, cognitive domains, and certain plasma biomarkers.
Professional fighters 35 years of age or older and/or retired were included. Participants were categorised as either having TES (TES+) or not (non-TES). TES+ participants were further subtyped by their cognitive profile. Multiple linear regression models were used to compare MRI-based regional brain volumes, cognitive performance, plasma tau and neurofilament light levels between TES- and TES+ groups.
176 participants (110 boxers and 66 MMA) were included in the analysis. 72 (41%)/176 were categorised as having TES, the likelihood of TES increasing with age. TES+ participants tended to be boxers, started fighting at a younger age, had more professional fights and knocked out more frequently. The TES+ group had lower regional brain volumes including both grey and white matter structures. TES+ also had lower scores on simple and choice reaction time, psychomotor speed and Trails A .
The new TES criteria does distinguish a group of fighters with differences in regional brain volumes and reduced cognitive function. Our findings support the use of the NINDS criteria for TES in further research of the long-term effects of repetitive head impacts.
The aim of this study is to evaluate longitudinal change in plasma neurofilament light (NF-L) and tau levels in relationship to clinical and radiological measures in professional fighters. ...Participants (active and retired professional fighters and control group) underwent annual blood sampling, 3-Tesla magnetic resonance imaging (MRI) brain imaging, computerized cognitive testing, and assessment of exposure to traumatic brain injury. Plasma tau and NF-L concentrations were measured using Simoa assays. Multiple linear regression models were used to compare the difference across groups in regard to baseline measurements, whereas mixed linear models was used for the longitudinal data with multiple measurements for each participant. Plasma samples were available on 471 participants. Baseline NF-L measures differed across groups (F
= 6.99; p = 0.0001), with the active boxers having the highest levels. Higher NF-L levels at baseline were correlated with lower baseline MRI regional volumes and lower cognitive scores. The number of sparring rounds completed by the active fighters was correlated with NF-L (95% confidence interval, 0.0116-0.4053; p = 0.0381), but not tau, levels. Among 126 subjects having multiple yearly samples, there was a significant difference in average yearly percentage change in tau across groups (F
= 3.87; p = 0.0121). We conclude that plasma NF-L and tau behave differently in a group of active and retired fighters; NF-L better reflects acute exposure whereas the role of plasma tau levels in signifying chronic change in brain structure over time requires further study.
For this reason, the exact conditional approach may not be appropriate to compute sample size for this type of study. Two exact unconditional approaches will be introduced in this letter, and we will ...use them for the sample size determination. ...we would recommend the ExactM approach for use in practice to determine the sample size for a study with paired binary data. Table 1Sample size comparison among the seven approaches to attain 80% power at α = 0.05 where P2 = P1 − 0.1 for a two-sided testing problem r P1 GEE-W GEE-S AsyU AsyC ExactC ExactM ExactEM 0.1 0.2 188 178 183 175 195 178 178 0.1 0.3 269 262 268 263 283 267 267 0.1 0.4 324 318 324 320 340 325 324 0.1 0.5 351 347 352 349 370 354 351 0.3 0.2 148 140 146 135 159 141 141 0.3 0.3 210 205 210 203 223 207 206 0.3 0.4 252 248 253 248 269 253 252 0.3 0.5 273 270 275 271 291 274 273 0.5 0.2 108 103 108 91 114 99 99 0.5 0.3 151 147 152 142 166 148 147 0.5 0.4 180 177 183 175 195 178 178 0.5 0.5 195...
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Survival endpoint is frequently used in early phase clinical trials as the primary endpoint to assess the activity of a new treatment. Existing two-stage optimal designs with survival endpoint either ...over estimate the sample size or compute power outside the alternative hypothesis space.
We propose a new single-arm two-stage optimal design with survival endpoint by using the one-sample log rank test based on exact variance estimates. This proposed design with survival endpoint is analogous to Simon's two-stage design with binary endpoint, having restricted follow-up.
We compare the proposed design with the existing two-stage designs, including the two-stage design with survival endpoint based on the nonparametric Nelson-Aalen estimate, and Simon's two-stage designs with or without interim accrual. The new design always performs better than these competitors with regards to the expected total study length, and requires a smaller expected sample size than Simon's design with interim accrual.
The proposed two-stage minimax and optimal designs with survival endpoint are recommended for use in practice to shorten the study length of clinical trials.
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Amyloid-Formula: see text (AFormula: see text) is the target in many clinical trials for Alzheimer's disease (AD). Preclinical AD patients are heterogeneous with regards to different backgrounds and ...diagnosis. Accurately predicting AFormula: see text status of participants by using machine learning (ML) models based on easily accessible data, could improve the effectiveness of AD clinical trials. We will develop optimal ML models for each subpopulation stratified by sex and disease stages using sub scores from screening neurological tests. Data from the AD Neuroimaging Initiative (ADNI) were used to build the ML models, for three groups: individuals with significant memory concern, early mild cognitive impairment (MCI), and late MCI. Data were further separated into 6 groups by disease stage (3 levels) and sex (2 categories). The outcome was defined as the AFormula: see text status confirmed by the PET imaging, and the features include demographic data, newly identified risk factors, screening tests, and the domain scores from screening tests. Monte Carlo simulation studies were used together with k-fold cross-validation technique to compute model performance metric. We also develop a new feature selection method based on the stochastic ordering to avoiding searching all possible combinations of features. Accuracy of the identified optimal model for SMC male was over 90% by using domain scores, and accuracy for LMCI female was above 86%. Domain scores can improve the ML model prediction as compared to the total scores. Accurate ML prediction models can identify the proper population for AD clinical trials.
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Exact Statistical Inference for Categorical Data discusses the way asymptotic approaches have been often used in practice to make statistical inference. This book introduces both conditional and ...unconditional exact approaches for the data in 2 by 2, or 2 by k contingency tables, and is an ideal reference for users who are interested in having the convenience of applying asymptotic approaches, with less computational time. In addition to the existing conditional exact inference, some efficient, unconditional exact approaches could be used in data analysis to improve the performance of the testing procedure. * Demonstrates how exact inference can be used to analyze data in 2 by 2 tables * Discusses the analysis of data in 2 by k tables using exact inference * Explains how exact inference can be used in genetics
For paired binary data, the hybrid method and the score method are often recommended for use to calculate the confidence interval for risk difference. These asymptotic intervals do not control the ...coverage probability. We propose to develop a new score interval with continuity correction to further improve the performance of the existing intervals. The traditional correction value may be too large which leads to a wide interval. For that reason, we propose three different correction values to identify the optimal correction interval with balanced coverage probability and interval width. From simulation studies, we find that a small correction value for the score interval has good performance. In addition, we derive the non-iterative solutions for the developed continuity correction score intervals.
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Background
Guidelines for pneumonia recommend empiric dual antipseudomonal therapy in patients with specific risk factors. However, there is lack of consensus on when to use dual antipseudomonal ...therapy as the recommendations are rated as weak, based on low‐quality evidence.
Objectives
The objectives of this study were to develop combination antibiograms to assess the susceptibility of Pseudomonas aeruginosa (P. aeruginosa) in respiratory cultures to combinations of empiric antibiotics and to use combination antibiograms to delineate the impact of specific risk factors for which guidelines recommend dual antipseudomonal therapy.
Methods
A retrospective cohort study was conducted of adults hospitalized with pneumonia with positive respiratory cultures for P. aeruginosa between September 2014 and September 2018. Data collected included demographics, antimicrobial susceptibility results, and risk factors for which guidelines recommend dual antipseudomonal therapy. Combination antibiograms were developed and logistic regression was performed to identify risk factors for nonsusceptibility to beta‐lactams.
Results
Eight hundred nineteen patients were included and 72% received antibiotics. Beta‐lactam susceptibility ranged from 58% to 69% and addition of a fluoroquinolone or aminoglycoside resulted in statistically significant increases in susceptibility. However, only addition of tobramycin or amikacin provided susceptibility rates approaching or exceeding 90% stratified by pneumonia type and risk factors. Presence of guideline‐based risk factors generally resulted in reduced susceptibility rates. Logistic regression identified three risk factors associated with nonsusceptibility to beta‐lactams: intravenous antibiotics in the previous 90 days, nursing home residence, and mechanical ventilation at onset. The cumulative presence of each additional risk factor affected beta‐lactam susceptibility rates, which were 93% in the absence of any risk factors and 39% when all three risk factors co‐existed.
Conclusions
Risk factors necessitating dual antipseudomonal therapy for pneumonia should be locally validated. When dual antipseudomonal therapy is indicated, tobramycin or amikacin have the best likelihood of providing adequate in vitro activity.
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