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Using Bayesian statistics in confirmatory clinical trials in the regulatory setting: a tutorial review
Bayesian statistics plays a pivotal role in advancing medical science by enabling healthcare companies, regulators, and stakeholders to assess the...
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Bayesian statistics in anesthesia practice: a tutorial for anesthesiologists
This narrative review intends to provide the anesthesiologist with the basic knowledge of the Bayesian concepts and should be considered as a...
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Bayesian parametric models for survival prediction in medical applications
BackgroundEvidence-based treatment decisions in medicine are made founded on population-level evidence obtained during randomized clinical trials. In...
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Frailty’s influence on 30-day mortality in old critically ill ICU patients: a bayesian analysis evaluating the clinical frailty scale
IntroductionFrailty is widely acknowledged as influencing health outcomes among critically ill old patients. Yet, the traditional understanding of...
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Informed Bayesian survival analysis
BackgroundWe provide an overview of Bayesian estimation, hypothesis testing, and model-averaging and illustrate how they benefit parametric survival...
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Goal-Directed Learning Deficits in Patients with OCD: A Bayesian Analysis
IntroductionDual system learning theories posit an overreliance characterizes obsessive–compulsive disorder on habitual decision-making at the...
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Interpreting frequentist hypothesis tests: insights from Bayesian inference
Randomized controlled trials are one of the best ways of quantifying the effectiveness of medical interventions. Therefore, when the authors of a...
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Bayesian methods: a potential path forward for sepsis trials
BackgroundGiven the success of recent platform trials for COVID-19, Bayesian statistical methods have become an option for complex, heterogenous...
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A Bayesian network perspective on neonatal pneumonia in pregnant women with diabetes mellitus
ObjectiveTo predict the influencing factors of neonatal pneumonia in pregnant women with diabetes mellitus using a Bayesian network model. By...
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Territorial gaps on quality of causes of death statistics over the last forty years in Spain
BackgroundThe quality of the statistics on causes of death (CoD) does not present consolidated indicators in literature further than the coding group...
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A Bayesian approach to pilot-pivotal trials for bioequivalence assessment
BackgroundTo demonstrate bioequivalence between two drug formulations, a pilot trial is often conducted prior to a pivotal trial to assess...
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Detailed statistical analysis plan for a secondary Bayesian analysis of the SafeBoosC-III trial: a multinational, randomised clinical trial assessing treatment guided by cerebral oximetry monitoring versus usual care in extremely preterm infants
BackgroundExtremely preterm infants have a high mortality and morbidity. Here, we present a statistical analysis plan for secondary Bayesian analyses...
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Prediction model of gleason score upgrading after radical prostatectomy based on a bayesian network
ObjectiveTo explore the clinical value of the Gleason score upgrading (GSU) prediction model after radical prostatectomy (RP) based on a Bayesian...
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Assessing the survival time of women with breast cancer in Northwestern Ethiopia: using the Bayesian approach
BackgroundDespite the significant weight of difficulty, Ethiopia's survival rate and mortality predictors have not yet been identified. Finding out...
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Application of Bayesian methods to accelerate rare disease drug development: scopes and hurdles
BackgroundDesign and analysis of clinical trials for rare and ultra-rare disease pose unique challenges to the practitioners. Meeting conventional...
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Bayesian networks for Risk Assessment and postoperative deficit prediction in intraoperative neurophysiology for brain surgery
PurposeTo this day there is no consensus regarding evidence of usefulness of Intraoperative Neurophysiological Monitoring (IONM). Randomized...
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Does climate change affect the transmission of COVID-19? A Bayesian regression analysis
AimCoronavirus is an airborne and infectious disease and it is crucial to check the impact of climatic risk factors on the transmission of COVID-19....
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Bayesian statistics in the design and analysis of cluster randomised controlled trials and their reporting quality: a methodological systematic review
BackgroundIn a cluster randomised controlled trial (CRCT), randomisation units are “clusters” such as schools or GP practices. This has...
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Treatment of missing data in Bayesian network structure learning: an application to linked biomedical and social survey data
BackgroundAvailability of linked biomedical and social science data has risen dramatically in past decades, facilitating holistic and systems-based...
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Flexible Bayesian semiparametric mixed-effects model for skewed longitudinal data
BackgroundIn clinical trials and epidemiological research, mixed-effects models are commonly used to examine population-level and subject-specific...
