Clinical significance not statistical significance: a simple Bayesian alternative to p values

2024 Revision of the level of evidence grading system for ESC clinical practice guideline recommendations I: therapy and prevention

The level of evidence (LOE) grading system for ESC Clinical Practice Guidelines classifies the quality of the evidence supporting a recommendation. However, the current taxonomy does not fully consider the optimal study design necessary to establish evidence for such recommendations. Therefore, two separate taskforces of clinical and methodological experts were appointed by the Clinical Practice Guidelines Committee, with the first tasked with updating the LOE grading system for therapy and prevention, and the second responsible for developing a LOE grading system for diagnosis and prediction. The updated system for therapy and prevention presented here maintains the three-level grading structure but uses revised definitions. Level of evidence A represents conclusive evidence usually from ≥2 adequately powered randomized controlled trials (RCTs) free from major bias, with substantial evidence against the play of chance when combined in a meta-analysis (e.g. P < .005 for superiority). Additional criteria are specified to define substantial evidence against the play of chance in case of non-inferiority, equivalence, and harm. Level of evidence B is now subdivided into B1 and B2. Level of evidence B1 represents suggestive evidence usually from ≥1 adequately powered RCT free from major bias, or a meta-analysis of such RCTs, with some evidence against the play of chance (e.g. P < .05 for superiority). Level of evidence B2 represents limited evidence from ≥2 adequately powered non-randomized studies with careful control of major sources of bias or from a meta-analysis of small, underpowered RCTs. Level of evidence C represents preliminary evidence from either non-randomized studies without careful control of major sources of bias, a single small, underpowered RCT, or expert consensus.

Brain oxygenation monitoring during neonatal stabilization and resuscitation and its potential for improving preterm infant outcomes: a systematic review and meta-analysis with Bayesian analysis

Neonatal stabilization and resuscitation in preterm infants are critical interventions. Cerebral tissue oxygen saturation (CrSO2) measured with near-infrared spectroscopy monitoring offers potential benefits by providing real-time information on brain oxygenation. This systematic review aimed to determine if CrSO2-monitoring to guide neonatal resuscitation after birth can improve survival without cerebral injury. A systematic search of MEDLINE, Google Scholar, EMBASE, the Cumulative Index of Nursing and Allied Health Literature, Clinical Trials.gov, and the Cochrane Central Register of Controlled Trials was performed through December 2024. We included only human studies that investigated CrSO2-guided interventions during neonatal resuscitation after birth in preterm infants. A meta-analysis was performed using individual patient data and the Bayesian method. The main outcome assessed was survival without cerebral injury (Study registration:PROSPERO CRD42024512148). Two studies were identified, including a total of 667 preterm infants with less than 34 weeks of gestation, describing CrSO2-guided interventions during neonatal resuscitation. The meta-analysis revealed a high probability of treatment superiority for NIRS-guided interventions that demonstrated improved outcomes compared to standard care, with a 4.5% increase in the rate of survival without cerebral injury (93% probability) and 4.2% reduction of IVH of any grade (94% probability). The risk of bias can be described as low.

CONCLUSION

This meta-analysis suggests that CrSO2-guided interventions may offer a meaningful advantage in preterm infant resuscitation after birth, improving survival without brain injury. The analysis indicates a high probability of a clinically important benefit. This warrants consideration in clinical practice.

WHAT IS KNOWN

• Studies have shown that near-infrared spectroscopy can monitor brain oxygenation in preterm infants immediately after birth.

WHAT IS NEW

• This is the first meta-analysis to examine the impact of near-infrared spectroscopy based interventions on neonatal resuscitation outcomes. • Interventions based on monitoring preterm infants' cerebral oxygenation may improve their chances of surviving without severe brain injury, compared to standard care.

Increase in colonic PRopionate as a method of prEVENTing weight gain over 12 months in adults aged 20-40 years (iPREVENT): a multi-centre, double-blind, randomised, parallel-group trial

Background

Obesity drives metabolic disease development. Preventing weight gain during early adulthood could mitigate later-life chronic disease risk. Increased dietary fibre intake, leading to enhanced colonic microbial fermentation and short-chain fatty acid (SCFA) production, is associated with lower body weight. Despite national food policy recommendations to consume 30 g of dietary fibre daily, only 9% of adults achieve this target. Inulin-propionate ester (IPE) selectively increases the production of the SCFA propionate in the colon. In previous studies, IPE has prevented weight gain in middle-aged adults over 6 months, compared with the inulin control. IPE is a novel food ingredient that can be added to various commonly consumed foods with a potential health benefit. This 12-month study aimed to determine whether using IPE to increase colonic propionate prevents further weight gain in overweight younger adults.

Methods

This multi-centre randomised-controlled, double-blind trial was conducted in London and Glasgow, UK. Recruited participants were individuals at risk of weight gain, aged between 20 and 40 years and had an overweight body mass index. Sealed Envelope Software was used to randomise participants to consume 10 g of IPE or inulin (control), once per day for 12 months. The primary outcome was the weight gained from baseline to 12 months, analysed by an 'Intention to Treat' strategy. The safety profile and tolerability of IPE were monitored through adverse events and compliance. This study is registered with the International Standard Randomised Controlled Trials (ISRCT) Database (ISRCT number: 16299902).

Findings

Participants (n = 135 per study arm) were recruited from July 2019 to October 2021. At 12 months, there was no significant difference in baseline-adjusted mean weight gain for IPE compared with control (1.02 kg, 95% CI: -0.37 to 2.41; p = 0.15; n = 226). Neither the IPE (+1.22 kg) nor the control arm (+0.07 kg) unadjusted mean gains in body weight reached the expected 2 kg threshold. In the IPE arm, fat-free mass was greater by 1.07 kg (95% CI: 0.21-1.93), and blood glucose elevated by 0.11 mmol/L (95% CI: 0.01-0.21). Compliance, determined by intake of ≥50% sachets, was reached by 63% of IPE participants. There were no unexpected adverse events or safety concerns.

Interpretation

Our study indicates that at 12 months, IPE did not differentially affect weight gain, compared with the inulin control, in adults between 20 and 40 years of age, at risk of obesity.

Funding

NIHR EME Programme (15/185/16).

A smoking cessation smartphone app that delivers real-time 'context aware' behavioural support: the Quit Sense feasibility RCT

Background

During a quit attempt, cues from a smoker's environment are a major cause of brief smoking lapses, which increase the risk of relapse. Quit Sense is a theory-guided Just-In-Time Adaptive Intervention smartphone app, providing smokers with the means to learn about their environmental smoking cues and provides 'in the moment' support to help them manage these during a quit attempt.

Objective

To undertake a feasibility randomised controlled trial to estimate key parameters to inform a definitive randomised controlled trial of Quit Sense.

Design

A parallel, two-arm randomised controlled trial with a qualitative process evaluation and a 'Study Within A Trial' evaluating incentives on attrition. The research team were blind to allocation except for the study statistician, database developers and lead researcher. Participants were not blind to allocation.

Setting

Online with recruitment, enrolment, randomisation and data collection (excluding manual telephone follow-up) automated through the study website.

Participants

Smokers (323 screened, 297 eligible, 209 enrolled) recruited via online adverts on Google search, Facebook and Instagram.

Interventions

Participants were allocated to 'usual care' arm (n = 105; text message referral to the National Health Service SmokeFree website) or 'usual care' plus Quit Sense (n = 104), via a text message invitation to install the Quit Sense app.

Main outcome measures

Follow-up at 6 weeks and 6 months post enrolment was undertaken by automated text messages with an online questionnaire link and, for non-responders, by telephone. Definitive trial progression criteria were met if a priori thresholds were included in or lower than the 95% confidence interval of the estimate. Measures included health economic and outcome data completion rates (progression criterion #1 threshold: ≥ 70%), including biochemical validation rates (progression criterion #2 threshold: ≥ 70%), recruitment costs, app installation (progression criterion #3 threshold: ≥ 70%) and engagement rates (progression criterion #4 threshold: ≥ 60%), biochemically verified 6-month abstinence and hypothesised mechanisms of action and participant views of the app (qualitative).

Results

Self-reported smoking outcome completion rates were 77% (95% confidence interval 71% to 82%) and health economic data (resource use and quality of life) 70% (95% CI 64% to 77%) at 6 months. Return rate of viable saliva samples for abstinence verification was 39% (95% CI 24% to 54%). The per-participant recruitment cost was £19.20, which included advert (£5.82) and running costs (£13.38). In the Quit Sense arm, 75% (95% CI 67% to 83%; 78/104) installed the app and, of these, 100% set a quit date within the app and 51% engaged with it for more than 1 week. The rate of 6-month biochemically verified sustained abstinence, which we anticipated would be used as a primary outcome in a future study, was 11.5% (12/104) in the Quit Sense arm and 2.9% (3/105) in the usual care arm (estimated effect size: adjusted odds ratio = 4.57, 95% CIs 1.23 to 16.94). There was no evidence of between-arm differences in hypothesised mechanisms of action. Three out of four progression criteria were met. The Study Within A Trial analysis found a £20 versus £10 incentive did not significantly increase follow-up rates though reduced the need for manual follow-up and increased response speed. The process evaluation identified several potential pathways to abstinence for Quit Sense, factors which led to disengagement with the app, and app improvement suggestions.

Limitations

Biochemical validation rates were lower than anticipated and imbalanced between arms. COVID-19-related restrictions likely limited opportunities for Quit Sense to provide location tailored support.

Conclusions

The trial design and procedures demonstrated feasibility and evidence was generated supporting the efficacy potential of Quit Sense.

Future work

Progression to a definitive trial is warranted providing improved biochemical validation rates.

Trial registration

This trial is registered as ISRCTN12326962.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR award ref: 17/92/31) and is published in full in Public Health Research; Vol. 12, No. 4. See the NIHR Funding and Awards website for further award information.

Pathological perspectives in pilocytic astrocytomas: Extent of resection as the sole critical factor for recurrence-free survival, and the challenge of evaluating conclusions derived from limited data

Introduction: Pilocytic astrocytoma (PA) is one of the most common primary intracranial neoplasms in childhood with an overall favorable prognosis. Despite decades of experience, there are still diagnostic and treatment challenges and unresolved issues regarding risk factors associated with recurrence, most often due to conclusions of publications with limited data. We analyzed 499 patients with PA diagnosed in a single institution over 30 years in order to provide answers to some of the unresolved issues. Materials and Methods: We identified pilocytic astrocytomas diagnosed at the University of California, San Francisco, between 1989 and 2019, confirmed the diagnoses using the WHO 2021 essential and desirable criteria, and performed a retrospective review of the demographic and clinical features of the patients and the radiological, pathologic and molecular features of the tumors. Results: Among the patients identified from pathology archives, 499 cases fulfilled the inclusion criteria. Median age at presentation was 12 years (range 3.5 months - 73 years) and the median follow-up was 78.5 months. Tumors were predominantly located in the posterior fossa (52.6%). There were six deaths, but there were confounding factors that prevented a clear association of death to tumor progression. Extent of resection was the only significant factor for recurrence-free survival. Recurrence-free survival time was 321.0 months for gross total resection, compared to 160.9 months for subtotal resection (log rank, p <0.001). Conclusion: Multivariate analysis was able to identify extent of resection as the only significant variable to influence recurrence-free survival. We did not find a statistically significant association between age, NF1 status, tumor location, molecular alterations, and outcome. Smaller series with apparently significant results may have suffered from limited sample size, limited variables, acceptance of univariate analysis findings as well as a larger p value for biological significance. PA still remains a predominantly surgical disease and every attempt should be made to achieve gross total resection since this appears to be the most reliable predictor of recurrence-free survival.

Effects of whey protein on skeletal muscle microvascular and mitochondrial plasticity following 10 weeks of exercise training in men with type 2 diabetes

Skeletal muscle microvascular dysfunction and mitochondrial rarefaction feature in type 2 diabetes mellitus (T2DM) linked to low tissue glucose disposal rate (GDR). Exercise training and milk protein supplementation independently promote microvascular and metabolic plasticity in muscle associated with improved nutrient delivery, but combined effects are unknown. In a randomised-controlled trial, 24 men (55.6 y, SD 5.7) with T2DM ingested whey protein drinks (protein/carbohydrate/fat: 20/10/3 g; WHEY) or placebo (carbohydrate/fat: 30/3 g; CON) before/after 45 mixed-mode intense exercise sessions over 10 weeks, to study effects on insulin-stimulated (hyperinsulinemic clamp) skeletal-muscle microvascular blood flow (mBF) and perfusion (near-infrared spectroscopy), and histological, genetic, and biochemical markers (biopsy) of microvascular and mitochondrial plasticity. WHEY enhanced insulin-stimulated perfusion (WHEY-CON 5.6%; 90% CI -0.1, 11.3), while mBF was not altered (3.5%; -17.5, 24.5); perfusion, but not mBF, associated (regression) with increased GDR. Exercise training increased mitochondrial (range of means: 40%-90%) and lipid density (20%-30%), enzyme activity (20%-70%), capillary:fibre ratio (∼25%), and lowered systolic (∼4%) and diastolic (4%-5%) blood pressure, but without WHEY effects. WHEY dampened PGC1α -2.9% (90% compatibility interval: -5.7, -0.2) and NOS3 -6.4% (-1.4, -0.2) expression, but other messenger RNA (mRNA) were unclear. Skeletal muscle microvascular and mitochondrial exercise adaptations were not accentuated by whey protein ingestion in men with T2DM. ANZCTR Registration Number: ACTRN12614001197628. Novelty: Chronic whey ingestion in T2DM with exercise altered expression of several mitochondrial and angiogenic mRNA. Whey added no additional benefit to muscle microvascular or mitochondrial adaptations to exercise. Insulin-stimulated perfusion increased with whey but was without impact on glucose disposal.

Bayesian Statistics for Surgical Decision Making

Background: Application of clinical study findings to surgical decision making requires accurate interpretation of the results, integration of the findings within the context of pre-existing knowledge and use of statistics to answer clinically relevant questions. Bayesian analyses are optimally suited for interpretation of study findings, supporting translation to the bedside. Discussion: Surgical decision making is a complex process that draws on an individual clinician's medical knowledge, experience, data, and the patient's unique characteristics and preferences. Subjective and objective knowledge may be merged to derive a probability of benefit or harm of a treatment under consideration. Bayesian reasoning complements the clinical decision-making process by incorporating known evidence and data from a new study to determine the probability of an outcome of interest. Bayesian analyses are statistically robust and intuitive when translating findings of a study into clinical care. In contrast, frequentist statistics are poorly suited to translate study findings to clinical application. This review aims to highlight the benefits of incorporating Bayesian analyses into clinical research. Conclusion: Bayesian analyses offer clinically relevant information including the probability of benefit or harm of a treatment under consideration while accounting for uncertainty. This information may be incorporated easily and accurately into surgical decision making.

Bayesian Methods in the Field of Rehabilitation

Bayesian techniques, as an alternative method of statistical analysis in rehabilitation studies, have some advantages such as handling small sample sizes, allowing incorporation of previous experience of the researchers or clinicians, being suitable for different kinds of studies, and managing highly complex models. These characteristics are important in rehabilitation research. In the present article, the Bayesian approach is displayed through three examples in previously analyzed data with traditional or frequentist methods. The studies used as examples have small sample sizes and show that the Bayesian procedures enhance the statistical information of the results. The Bayesian credibility interval includes the true value of the corresponding parameter diminishing uncertainty about the treatment effect. In addition, the Bayes factor value quantifies the evidence provided by the data in favor of the alternative hypothesis as opposed to the null hypothesis. Bayesian inference could be an interesting and adaptable alternative statistical method for physical medicine and rehabilitation applications.

Thiazide Use and Fracture Risk: An updated Bayesian Meta-Analysis

The association between thiazide use and fracture risk is still controversial. We conducted an updated meta-analysis on the association between thiazide use and fracture risk. We systematically searched PubMed, Embase, and Cochrane library databases for all types of human studies, including observational and experimental studies that were published up until July 2019. We also manually searched the reference lists of relevant studies. The pooled relative risks (RRs) with 95% credible interval (CrI) were calculated using a Bayesian hierarchical random effect model. A total of 19 case-control (N = 496,568 subjects) and 21 cohort studies (N = 4,418,602 subjects) were included in this meta-analysis. The pooled RR for fractures associated with thiazide use was 0.87 (95% CrI: 0.70–0.99) in case-control and 0.95 (95% CrI: 0.85–1.08) in cohort studies. The probabilities that thiazide use reduces any fracture risk by more than 0% were 93% in case-control studies and 72% in cohort studies. Significant heterogeneity was found for both case-control (p < 0.001, I² = 75%) and cohort studies (p < 0.001, I² = 97.2%). Thiazide use was associated with reduced fracture risk in case-control studies, but not in cohort studies. The associations demonstrated in case-control studies might be driven by inherent biases, such as selection bias and recall bias. Thus, thiazide use may not be a protective factor for fractures.

Applied Bayesian Methods in the Rheumatic Diseases

The use of applied Bayesian methods is increasing in rheumatology. Using the Bayes theorem, past evidence is updated with new data. Preexisting data are expressed as a prior probability distribution or prior. New observations are expressed as a likelihood. Through explicit incorporation of preexisting data and new data, this process informs how this new information should change the way we think. In this article, the authors highlight the use of applied Bayesian methods in the study of rheumatic diseases.

Enhancing the understanding of clinically meaningful results: A clinical research perspective

Published research often address aspects related to "statistical significance" but fail to address the clinical and practical importance and meaning of results. Our main objectives in this article are to investigate the merit of common measures of Effect Size in statistical research and to highlight the importance of the simple Relative Risk ratio. In this article we present data where we consider two widely utilized effect size measures (Cohen's d and Pearson's r) in relations to relative risk. We conclude that probability analyses of risk surpass the most commonly used statistical approach used in clinical trials today and should thus be the preferred compared to the misuse and misunderstanding of reporting for instance p-values alone.

Factors Associated With Bites to a Child From a Dog Living in the Same Home: A Bi-National Comparison

We conducted a veterinary clinic-based retrospective cohort study aimed at identifying child-, dog-, and home-environment factors associated with dog bites to children aged 5–15 years old living in the same home as a dog in Kingston, Jamaica (236) and San Francisco, USA (61). Secondarily, we wished to compare these factors to risk factors for dog bites to the general public. Participant information was collected via interviewer-administered questionnaire using proxy respondents. Data were analyzed using log-binomial regression to estimate relative risks and associated 95% confidence intervals (CIs) for each exposure–dog bite relationship. Exploiting the correspondence between X% confidence intervals and X% Bayesian probability intervals obtained using a uniform prior distribution, for each exposure, we calculated probabilities of the true (population) RRs ≥ 1.25 or ≤0.8, for positive or negative associations, respectively. Boys and younger children were at higher risk for bites, than girls and older children, respectively. Dogs living in a home with no yard space were at an elevated risk (RR = 2.97; 95% CI: 1.06–8.33) of biting a child living in the same home, compared to dogs that had yard space. Dogs routinely allowed inside for some portion of the day (RR = 3.00; 95% CI: 0.94–9.62) and dogs routinely allowed to sleep in a family member’s bedroom (RR = 2.82; 95% CI: 1.17–6.81) were also more likely to bite a child living in the home than those that were not. In San Francisco, but less so in Kingston, bites were inversely associated with the number of children in the home. While in Kingston, but not in San Francisco, smaller breeds and dogs obtained for companionship were at higher risk for biting than larger breeds and dogs obtained for protection, respectively. Overall, for most exposures, the observed associations were consistent with population RRs of practical importance (i.e., RRs ≥ 1.25 or ≤0.8). Finally, we found substantial consistency between risk factors for bites to children and previously reported risk factors for general bites.

Nil Whey Protein Effect on Glycemic Control after Intense Mixed-Mode Training in Type 2 Diabetes

Although intense endurance and resistance exercise training and whey protein supplementation have both been shown to independently improve glycemic control, no known studies have examined the effect of high-intensity mixed-mode interval training (MMIT) and whey supplementation in adults with Type 2 diabetes (T2D).

PURPOSE

This study aimed to determine if peritraining whey protein supplementation combined with MMIT can improve glycemic control.

METHODS

In a double-blind, randomized, placebo-controlled trial, 24 men (55.7 ± 5.6 yr) with T2D performed MMIT with whey (20 g) or placebo control for 10 wk. Glycemic control was assessed via glucose disposal rate during a euglycemic insulin clamp, fasting blood glucose concentration, and homeostatic model assessment of insulin resistance. Changes in peak oxygen consumption, 1-repetition maximum strength, vastus lateralis muscle, and subcutaneous adipose thicknesses, and waist circumference were also assessed.

RESULTS

Ten weeks of MMIT substantially improved glucose disposal rate by 27.5% (90% confidence interval, 1.2%-60.7%) and 24.8% (-5.4% to 64.8%) in the whey and control groups, respectively. There were likely and possible reductions in fasting blood glucose by -17.4% (-30.6% to -1.6%) and homeostatic model assessment of insulin resistance by -14.1% (-25.3% to 1.08%) in the whey group; however, whey effects were not clearly beneficial to glycemic outcomes relative to the control. MMIT also clearly substantially improved 1-repetition maximum by 20.6% (16.3%-24.9%) and 22.7% (18.4%-27.2%), peak oxygen consumption by 22.6% (12.0%-26.2%) and 18.5% (10.5%-27.4%), and vastus lateralis muscle thickness by 18.9% (12.0%-26.2%) and 18.6% (10.5%-27.4%) and possibly reduced waist circumference by -2.1% (-3.1% to -1.0%) and -1.9% (-3.7% to -0.1%) in the control and whey groups, respectively, but the whey-control outcome was trivial or unclear.

CONCLUSIONS

A clinically meaningful enhancement in glycemic control after 10 wk of MMIT was not clearly advanced with peritraining whey protein supplementation in middle-age men with T2D.

Antimicrobials for the treatment of drug-resistant Acinetobacter baumannii pneumonia in critically ill patients: a systemic review and Bayesian network meta-analysis

BACKGROUND

An optimal therapy for the treatment of pneumonia caused by drug-resistant Acinetobacter baumannii remains unclear. This study aims to compare various antimicrobial strategies and to determine the most effective therapy for pneumonia using a network meta-analysis.

METHODS

Systematic search and quality assessment were performed to select eligible studies reporting one of the following outcomes: all-cause mortality, clinical cure, and microbiological eradication. The primary outcome was all-cause mortality. A network meta-analysis was conducted with a Bayesian approach. Antimicrobial treatments were ranked based on surface under the cumulative ranking curve (SUCRA) value along with estimated median outcome rate and corresponding 95% credible intervals (CrIs). Two treatments were considered significantly different if a posterior probability of superiority (P) was greater than 97.5%.

RESULTS

Twenty-three studies evaluating 15 antimicrobial treatments were included. Intravenous colistin monotherapy (IV COL) was selected as a common comparator, serving as a bridge for developing the network. Five treatments ranked higher than IV COL (SUCRA, 57.1%; median all-cause mortality 0.45, 95% CrI 0.41-0.48) for reducing all-cause mortality: sulbactam monotherapy (SUL, 100.0%; 0.18, 0.04-0.42), high-dose SUL (HD SUL, 85.7%; 0.31, 0.07-0.71), fosfomycin plus IV COL (FOS + IV COL, 78.6%; 0.34, 0.19-0.54), inhaled COL plus IV COL (IH COL + IV COL, 71.4%; 0.39, 0.32-0.46), and high-dose tigecycline (HD TIG, 71.4%; 0.39, 0.16-0.67). Those five treatments also ranked higher than IV COL (SUCRA, 45.5%) for improving clinical cure (72.7%, 72.7%, 63.6%, 81.8%, and 90.9%, respectively). Among the five treatments, SUL (P = 98.1%) and IH COL + IV COL (P = 99.9%) were significantly superior to IV COL for patient survival and clinical cure, respectively. In terms of microbiological eradication, FOS + IV COL (P = 99.8%) and SUL (P = 98.9%) were significantly superior to IV COL.

CONCLUSIONS

This Bayesian network meta-analysis demonstrated the comparative effectiveness of fifteen antimicrobial treatments for drug-resistant A. baumannii pneumonia in critically ill patients. For survival benefit, SUL appears to be the best treatment followed by HD SUL, FOS + IV COL, IH COL + IV COL, HD TIG, and IV COL therapy, in numerical order.

Current Research and Statistical Practices in Sport Science and a Need for Change

Current research ideologies in sport science allow for the possibility of investigators producing statistically significant results to help fit the outcome into a predetermined theory. Additionally, under the current Neyman-Pearson statistical structure, some argue that null hypothesis significant testing (NHST) under the frequentist approach is flawed, regardless. For example, a p-value is unable to measure the probability that the studied hypothesis is true, unable to measure the size of an effect or the importance of a result, and unable to provide a good measure of evidence regarding a model or hypothesis. Many of these downfalls are key questions researchers strive to answer following an investigation. Therefore, a shift towards a magnitude-based inference model, and eventually a fully Bayesian framework, is thought to be a better fit from a statistical standpoint and may be an improved way to address biases within the literature. The goal of this article is to shed light on the current research and statistical shortcomings the field of sport science faces today, and offer potential solutions to help guide future research practices.

The role of splenic angioembolization as an adjunct to nonoperative management of blunt splenic injuries: A systematic review and meta-analysis

BACKGROUND

Nonoperative management (NOM) of hemodynamically normal patients with blunt splenic injury (BSI) is the standard of care. Guidelines recommend additional splenic angioembolization (SAE) in patients with American Association for the Surgery of Trauma (AAST) Grade IV and Grade V BSI, but the role of SAE in Grade III injuries is unclear and controversial. The aim of this systematic review was to compare the safety and effectiveness of SAE as an adjunct to NOM versus NOM alone in adults with BSI.

METHODS

A systematic literature search (Medline, Embase, and CINAHL) was performed to identify original studies that compared outcomes in adult BSI patients treated with SAE or NOM alone. Primary outcome was failure of NOM. Secondary outcomes included morbidity, mortality, hospital length of stay, and transfusion requirements. Bayesian meta-analyses were used to calculate an absolute (risk difference) and relative (risk ratio [RR]) measure of treatment effect for each outcome.

RESULTS

Twenty-three studies (6,684 patients) were included. For Grades I to V combined, there was no difference in NOM failure rate (SAE, 8.6% vs NOM, 7.7%; RR, 1.09 [0.80-1.51]; p = 0.28), mortality (SAE, 4.8% vs NOM, 5.8%; RR, 0.82 [0.45-1.31]; p = 0.81), hospital length of stay (11.3 vs 9.5 days; p = 0.06), or blood transfusion requirements (1.8 vs 1.7 units; p = 0.47) between patients treated with SAE and those treated with NOM alone. However, morbidity was significantly higher in patients treated with SAE (SAE, 38.1% vs NOM, 18.6%; RR, 1.83 [1.20-2.66]; p < 0.01). When stratified by grade of splenic injury, SAE significantly reduced the failure rate of NOM in patients with Grade IV and Grade V splenic injuries but had minimal effect in those with Grade I to Grade III injuries.

CONCLUSION

Splenic angioembolization should be strongly considered as an adjunct to NOM in patients with AAST Grade IV and Grade V BSI but should not be routinely recommended in patients with AAST Grade I to Grade III injuries.

LEVEL OF EVIDENCE

Systematic review and meta-analysis, level III.

A randomised controlled trial of three very brief interventions for physical activity in primary care

Background

Very brief interventions (VBIs) for physical activity are promising, but there is uncertainty about their potential effectiveness and cost. We assessed potential efficacy, feasibility, acceptability, and cost of three VBIs in primary care, in order to select the most promising intervention for evaluation in a subsequent large-scale RCT.

Methods

Three hundred and ninety four adults aged 40–74 years were randomised to a Motivational (n = 83), Pedometer (n = 74), or Combined (n = 80) intervention, delivered immediately after a preventative health check in primary care, or control (Health Check only; n = 157). Potential efficacy was measured as the probability of a positive difference between an intervention arm and the control arm in mean physical activity, measured by accelerometry at 4 weeks.

Results

For the primary outcome the estimated effect sizes (95 % CI) relative to the Control arm for the Motivational, Pedometer and Combined arms were respectively: +20.3 (−45.0, +85.7), +23.5 (−51.3, +98.3), and −3.1 (−69.3, +63.1) counts per minute. There was a73% probability of a positive effect on physical activity for each of the Motivational and Pedometer VBIs relative to control, but only 46 % for the Combined VBI. Only the Pedometer VBI was deliverable within 5 min. All VBIs were acceptable and low cost.

Conclusions

Based on the four criteria, the Pedometer VBI was selected for evaluation in a large-scale trial.

Trial registration

Current Controlled Trials ISRCTN02863077. Retrospectively registered 05/10/2012.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-016-3684-7) contains supplementary material, which is available to authorized users.

Novel Form of Curcumin Improves Endothelial Function in Young, Healthy Individuals: A Double-Blind Placebo Controlled Study

Curcumin, a turmeric extract, may protect against cardiovascular diseases by enhancing endothelial function. In this randomized controlled double-blind parallel prospective study, fifty-nine healthy adults were assigned to placebo, 50 mg (50 mg), or 200 mg (200 mg) curcumin, for 8 weeks. The higher curcumin (200 mg) supplementation produced a dose-mediated improvement in endothelial function measured by flow-mediated dilation (FMD). The outcome was a clinically substantial 3.0% increase (90% CI 0.7 to 5.3%, p = 0.032; benefit : harm odds ratio 546 : 1) with the 200 mg dose, relative to placebo. The 50 mg dose also increased FMD relative to placebo by 1.7% (-0.6 to 4.0%, p = 0.23; 25 : 1), but the outcome was not clinically decisive. In apparently healthy adults, 8 weeks of 200 mg oral curcumin supplementation resulted in a clinically meaningful improvement in endothelial function as measured by FMD. Oral curcumin supplementation may present a simple lifestyle strategy for decreasing the risk of cardiovascular diseases. This trial was registered at ISRCTN registry (ISRCTN90184217).

Bayesian Estimation of Small Effects in Exercise and Sports Science

The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a 'magnitude-based inference' approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.

Adolescent Pornography Use and Dating Violence among a Sample of Primarily Black and Hispanic, Urban-Residing, Underage Youth

This cross-sectional study was designed to characterize the pornography viewing preferences of a sample of U.S.-based, urban-residing, economically disadvantaged, primarily Black and Hispanic youth (n = 72), and to assess whether pornography use was associated with experiences of adolescent dating abuse (ADA) victimization. The sample was recruited from a large, urban, safety net hospital, and participants were 53% female, 59% Black, 19% Hispanic, 14% Other race, 6% White, and 1% Native American. All were 16–17 years old. More than half (51%) had been asked to watch pornography together by a dating or sexual partner, and 44% had been asked to do something sexual that a partner saw in pornography. Adolescent dating abuse (ADA) victimization was associated with more frequent pornography use, viewing pornography in the company of others, being asked to perform a sexual act that a partner first saw in pornography, and watching pornography during or after marijuana use. Approximately 50% of ADA victims and 32% of non-victims reported that they had been asked to do a sexual act that their partner saw in pornography (p = 0.15), and 58% did not feel happy to have been asked. Results suggest that weekly pornography use among underage, urban-residing youth may be common, and may be associated with ADA victimization.

Relative efficacy and safety of simeprevir and telaprevir in treatment-naïve hepatitis C-infected patients in a Japanese population: A Bayesian network meta-analysis

AIM

Simeprevir (SMV) is an oral, once-daily protease inhibitor for the treatment of chronic hepatitis C virus (HCV) genotype 1 infection. In phase II/III randomized controlled trials (RCT) conducted in Japan, SMV, in combination with peginterferon-α and ribavirin (PEG IFN/RBV), demonstrated potent efficacy in HCV genotype 1-infected patients relative to PEG IFN/RBV and was generally well tolerated. Telaprevir (TVR) in combination with PEG IFN/RBV is licensed for the treatment of HCV in Japan. In the absence of head-to-head comparisons of TVR and SMV in a Japanese population, we undertook a network meta-analysis (NMA) to examine the relative efficacy and safety of SMV and TVR in combination with PEG IFN/RBV.

METHODS

A systematic review identified SMV and TVR RCT in Japanese treatment-naïve patients. Bayesian NMA was performed assuming fixed study effects.

RESULTS

Three studies met our inclusion criteria: two SMV and one TVR. SMV showed a higher mean odds ratio (OR) of achieving SVR versus TVR (OR, 1.68 (95% credible interval 0.66-4.26)). SMV showed a lower mean OR of discontinuation: overall, 0.35 (0.12-1.00); and due to AE, 0.87 (0.23-3.34) versus TVR. SMV showed a lower mean OR of experiencing anemia 0.20 (0.07-0.56) and rash 0.41 (0.17-0.99) but a higher mean OR of experiencing pruritus 1.26 (0.46-3.47) versus TVR.

CONCLUSION

In this indirect treatment comparison, SMV, in combination with PEG IFN/RBV, showed a favorable risk-benefit profile compared with TVR with PEG IFN/RBV in Japanese treatment-naïve HCV patients.

Meta-analysis of prognostic factors for amputation following surgical repair of lower extremity vascular trauma

Background

Lower extremity vascular trauma (LEVT) is a major cause of amputation. A clear understanding of prognostic factors for amputation is important to inform surgical decision-making, patient counselling and risk stratification. The aim was to develop an understanding of prognostic factors for amputation following surgical repair of LEVT.

Methods

A systematic review was conducted to identify potential prognostic factors. Bayesian meta-analysis was used to calculate an absolute (pooled proportion) and relative (pooled odds ratio, OR) measure of the amputation risk for each factor.

Results

Forty-five studies, totalling 3187 discrete LEVT repairs, were included. The overall amputation rate was 10·0 (95 per cent credible interval 7·4 to 13·1) per cent. Significant prognostic factors for secondary amputation included: associated major soft tissue injury (26 versus 8 per cent for no soft tissue injury; OR 5·80), compartment syndrome (28 versus 6 per cent; OR 5·11), multiple arterial injuries (18 versus 9 per cent; OR 4·85), duration of ischaemia exceeding 6 h (24 versus 5 per cent; OR 4·40), associated fracture (14 versus 2 per cent; OR 4·30), mechanism of injury (blast 19 per cent, blunt 16 per cent, penetrating 5 per cent), anatomical site of injury (iliac 18 per cent, popliteal 14 per cent, tibial 10 per cent, femoral 4 per cent), age over 55 years (16 versus 9 per cent; OR 3·03) and sex (men 7 per cent versus women 8 per cent; OR 0·64). Shock and nerve or venous injuries were not significant prognostic factors for secondary amputation.

Conclusion

A significant proportion of patients who undergo lower extremity vascular trauma repair will require secondary amputation. This meta-analysis describes significant prognostic factors needed to inform surgical judgement, risk assessment and patient counselling.

Bayesian methodology for the design and interpretation of clinical trials in critical care medicine: a primer for clinicians

OBJECTIVES

To review Bayesian methodology and its utility to clinical decision making and research in the critical care field.

DATA SOURCE AND STUDY SELECTION

Clinical, epidemiological, and biostatistical studies on Bayesian methods in PubMed and Embase from their inception to December 2013.

DATA SYNTHESIS

Bayesian methods have been extensively used by a wide range of scientific fields, including astronomy, engineering, chemistry, genetics, physics, geology, paleontology, climatology, cryptography, linguistics, ecology, and computational sciences. The application of medical knowledge in clinical research is analogous to the application of medical knowledge in clinical practice. Bedside physicians have to make most diagnostic and treatment decisions on critically ill patients every day without clear-cut evidence-based medicine (more subjective than objective evidence). Similarly, clinical researchers have to make most decisions about trial design with limited available data. Bayesian methodology allows both subjective and objective aspects of knowledge to be formally measured and transparently incorporated into the design, execution, and interpretation of clinical trials. In addition, various degrees of knowledge and several hypotheses can be tested at the same time in a single clinical trial without the risk of multiplicity. Notably, the Bayesian technology is naturally suited for the interpretation of clinical trial findings for the individualized care of critically ill patients and for the optimization of public health policies.

CONCLUSIONS

We propose that the application of the versatile Bayesian methodology in conjunction with the conventional statistical methods is not only ripe for actual use in critical care clinical research but it is also a necessary step to maximize the performance of clinical trials and its translation to the practice of critical care medicine.

Modeling to optimize terminal stem cell differentiation

Embryonic stem cell (ESC), iPCs, and adult stem cells (ASCs) all are among the most promising potential treatments for heart failure, spinal cord injury, neurodegenerative diseases, and diabetes. However, considerable uncertainty in the production of ESC-derived terminally differentiated cell types has limited the efficiency of their development. To address this uncertainty, we and other investigators have begun to employ a comprehensive statistical model of ESC differentiation for determining the role of intracellular pathways (e.g., STAT3) in ESC differentiation and determination of germ layer fate. The approach discussed here applies the Baysian statistical model to cell/developmental biology combining traditional flow cytometry methodology and specific morphological observations with advanced statistical and probabilistic modeling and experimental design. The final result of this study is a unique tool and model that enhances the understanding of how and when specific cell fates are determined during differentiation. This model provides a guideline for increasing the production efficiency of therapeutically viable ESCs/iPSCs/ASC derived neurons or any other cell type and will eventually lead to advances in stem cell therapy.

Association between beta-blockers and fracture risk: a Bayesian meta-analysis

BACKGROUND

The association between beta-blockers (BB) and fracture risk is controversial, due largely to conflicting findings from previous studies. The present study sought to evaluate the effect of BB on fracture risk by using a Bayesian meta-analysis approach.

METHODS AND RESULTS

We systematically retrieved 13 observational studies on the association between BB use and fracture risk. This meta-analysis involved more than 907,000 men and women with mean/median age of individual studies ranging from 43 to 81 years. We used a hierarchical Bayesian random effects model to synthesize the results. BB use was associated with an average 17% reduction in the risk of any fracture (risk ratio [RR] 0.83; 95% credible interval [CrI]: 0.71-0.93), hip fracture (RR 0.83; 95% CrI: 0.70-0.92) and vertebral fracture (RR 0.81; 95% CrI: 0.61-0.99). The probability that BB use reduces fracture risk by at least 10% was 0.91.

CONCLUSIONS

Beta-blockers are associated with reduced risk of fracture in older adults, but the effect size is likely to be modest.

Warfarin in systemic sclerosis-associated and idiopathic pulmonary arterial hypertension. A Bayesian approach to evaluating treatment for uncommon disease

OBJECTIVE

Warfarin is recommended in systemic sclerosis-associated pulmonary arterial hypertension (SSc-PAH) and idiopathic PAH (IPAH) to improve survival. There is no evidence to support this in SSc-PAH and the evidence in IPAH is conflicting. We evaluated the ability of warfarin to improve survival using 2 large SSc-PAH and IPAH cohorts.

METHODS

The effect of warfarin on all-cause mortality was evaluated. Bayesian propensity scores (PS) were used to adjust for baseline differences between patients exposed and not exposed to warfarin, and to assemble a matched cohort. Bayesian Cox proportional hazards models were constructed using informative priors based on international PAH expert elicitation.

RESULTS

Review of 1138 charts identified 275 patients with SSc-PAH (n = 78; 28% treated with warfarin) and 155 patients with IPAH (n = 91; 59% treated with warfarin). Baseline differences in PAH severity and medications were resolved using PS matching. In the matched cohort of 98 patients with SSc-PAH (49 treated with warfarin), the posterior median hazard ratio (HR) was 1.06 [95% credible interval (CrI) 0.70, 1.63]. In the matched cohort of 66 patients with IPAH (33 treated with warfarin), the posterior median HR was 1.07 (95% CrI 0.57, 1.98). The probability that warfarin improves median survival by 6 months or more is 23.5% in SSc-PAH and 27.7% in IPAH. Conversely, there is a > 70% probability that warfarin provides no significant benefit or is harmful.

CONCLUSION

There is a low probability that warfarin improves survival in SSc-PAH and IPAH. Given the availability of other PAH therapies with demonstrable benefits, there is little reason to use warfarin to improve survival for these patients.

Continuous safety monitoring for randomized controlled clinical trials with blinded treatment information. Part 2: Statistical considerations

If the primary objective of a trial is to learn about the ability of a new treatment to help future patients without sacrificing the safe and effective treatment of the current patients, then a Bayesian design with frequent assessments of the accumulating data should be considered. Unfortunately, Bayesian analyses typically do not have standard approaches, and because of the subjectivity of prior probabilities and the possibility for introducing bias, statisticians have developed other methods for statistical inference that only depend on deductive probabilities. However, these frequentist probabilities are just theories about how certain relative frequencies will develop over time. They have no real meaning in a single experiment. Designed to work well in the long run, p-values become hard to explain for individual experiments. Fortunately, the controversy surrounding Bayes' theorem comes, not from the representation of evidence, but from the use of probabilities to measure belief. A prior distribution is not necessary. The likelihood function contains all of the information in a trial relevant for making inferences about the parameters. Monitoring clinical trials is a dynamic process which requires flexibility to respond to unforeseen developments. Likelihood ratios allow the data to speak for themselves, without regard for the probability of observing weak or misleading evidence, and decisions to stop, or continue, a trial can be made at any time, with all of the available information. A likelihood based method is needed.

Bayesian analysis of a mastitis control plan to investigate the influence of veterinary prior beliefs on clinical interpretation

The fundamental objective for health research is to determine whether changes should be made to clinical decisions. Decisions made by veterinary surgeons in the light of new research evidence are known to be influenced by their prior beliefs, especially their initial opinions about the plausibility of possible results. In this paper, clinical trial results for a bovine mastitis control plan were evaluated within a Bayesian context, to incorporate a community of prior distributions that represented a spectrum of clinical prior beliefs. The aim was to quantify the effect of veterinary surgeons’ initial viewpoints on the interpretation of the trial results.

A Bayesian analysis was conducted using Markov chain Monte Carlo procedures. Stochastic models included a financial cost attributed to a change in clinical mastitis following implementation of the control plan. Prior distributions were incorporated that covered a realistic range of possible clinical viewpoints, including scepticism, enthusiasm and uncertainty. Posterior distributions revealed important differences in the financial gain that clinicians with different starting viewpoints would anticipate from the mastitis control plan, given the actual research results. For example, a severe sceptic would ascribe a probability of 0.50 for a return of <£5 per cow in an average herd that implemented the plan, whereas an enthusiast would ascribe this probability for a return of >£20 per cow. Simulations using increased trial sizes indicated that if the original study was four times as large, an initial sceptic would be more convinced about the efficacy of the control plan but would still anticipate less financial return than an initial enthusiast would anticipate after the original study. In conclusion, it is possible to estimate how clinicians’ prior beliefs influence their interpretation of research evidence. Further research on the extent to which different interpretations of evidence result in changes to clinical practice would be worthwhile.

Effect of vegetarian diets on bone mineral density: a Bayesian meta-analysis

BACKGROUND

The association between vegetarian diets and bone mineral density (BMD) is controversial because of conflicting findings from previous studies.

OBJECTIVE

The aim of this study was to estimate the effect of vegetarian diets on BMD by using a meta-analytic approach.

DESIGN

A systematic electronic literature search was conducted to identify all relevant articles on the association between vegetarian diet and BMD. Nine studies of 2749 subjects (1880 women and 869 men) were included in the analysis. Traditional and Bayesian methods of meta-analysis were applied to synthesize the data.

RESULTS

Overall, BMD was approximately 4% lower in vegetarians than in omnivores (95% CI: 2%, 7%) at both the femoral neck and the lumbar spine. Compared with omnivores, vegans had a significantly lower lumbar spine BMD (6% lower; 95% CI: 2%, 9%), which was more pronounced than in lactoovovegetarians (2% lower; 95% CI: 1%, 4%). The probability that BMD was > or =5% lower in vegetarians than in omnivores (or approximately 0.3 SD) was 42% for the femoral neck and 32% for the lumbar spine. There was no evidence of publication bias. There was a moderate degree of between-study heterogeneity; the coefficient of heterogeneity varied between 46% and 51%.

CONCLUSION

The results suggest that vegetarian diets, particularly vegan diets, are associated with lower BMD, but the magnitude of the association is clinically insignificant.

The long-term effects of breastfeeding on asthma and atopic disease

In this review, the primary objective is to assess the evidence of whether breastfeeding protects against asthma and atopic disease for the long-term (long-term is defined here as >5 years of age). Two main types of observational epidemiological studies have been used to test this hypothesis. These are cohort studies of random samples of children and cohort studies of children with a family history of asthma or atopy. In each study type, exposure and outcome data are collected either prospectively or retrospectively. The 12 criteria for assessing the adequate measurement of exposure, outcome and statistics of cohort studies in this context are given in Table 17-1.

Shifting Our Thinking About Uncommon Disease Trials: The Case of Methotrexate in Scleroderma

Objective.

Randomized trials for uncommon diseases suffer from methodological challenges: difficulty in recruiting sufficient numbers of patients and low power to detect important treatment effects. Using traditional (frequentist) analysis, p values > 0.05 mean investigators are unable to reject the null hypothesis (of no treatment effect). The medical community often labels trials with p values > 0.05 as “negative.” Our study demonstrates how Bayesian analysis conveys more relevant information to clinicians — using the example of methotrexate (MTX) in systemic sclerosis (SSc).

Methods.

Data from 71 patients with diffuse SSc (n = 35 MTX, n = 36 placebo) in the trial were reanalyzed using Bayesian models. We examined 3 primary outcomes: modified Rodnan skin score (MRSS), University of California Los Angeles (UCLA) skin score, and physician global assessment of overall disease activity. Using noninformative prior probability distributions, the probability of beneficial treatment effects for each outcome and the probability of simultaneous benefit in outcomes were computed.

Results.

The probability that treatment with MTX results in better mean outcomes than placebo was 94% for MRSS, 96% for UCLA skin score, and 88% for physician global assessment. There was 96% probability that at least 2 of 3 primary outcomes were better on treatment.

Conclusion.

Bayesian analysis of uncommon disease trials allows for more flexible and clinically relevant interpretations of the data. From the trial data, clinicians can infer that MTX has a high probability of beneficial effects on skin score and global assessment.

Bayesian statistical inference enhances the interpretation of contemporary randomized controlled trials

OBJECTIVE

Randomized trials generally use "frequentist" statistics based on P-values and 95% confidence intervals. Frequentist methods have limitations that might be overcome, in part, by Bayesian inference. To illustrate these advantages, we re-analyzed randomized trials published in four general medical journals during 2004.

STUDY DESIGN AND SETTING

We used Medline to identify randomized superiority trials with two parallel arms, individual-level randomization and dichotomous or time-to-event primary outcomes. Studies with P<0.05 in favor of the intervention were deemed "positive"; otherwise, they were "negative." We used several prior distributions and exact conjugate analyses to calculate Bayesian posterior probabilities for clinically relevant effects.

RESULTS

Of 88 included studies, 39 were positive using a frequentist analysis. Although the Bayesian posterior probabilities of any benefit (relative risk or hazard ratio<1) were high in positive studies, these probabilities were lower and variable for larger benefits. The positive studies had only moderate probabilities for exceeding the effects that were assumed for calculating the sample size. By comparison, there were moderate probabilities of any benefit in negative studies.

CONCLUSION

Bayesian and frequentist analyses complement each other when interpreting the results of randomized trials. Future reports of randomized trials should include both.

Why are clinicians not embracing the results from pivotal clinical trials in severe sepsis? A bayesian analysis

BACKGROUND

Five pivotal clinical trials (Intensive Insulin Therapy; Recombinant Human Activated Protein C [rhAPC]; Low-Tidal Volume; Low-Dose Steroid; Early Goal-Directed Therapy [EGDT]) demonstrated mortality reduction in patients with severe sepsis and expert guidelines have recommended them to clinical practice. Yet, the adoption of these therapies remains low among clinicians.

OBJECTIVES

We selected these five trials and asked: Question 1--What is the current probability that the new therapy is not better than the standard of care in my patient with severe sepsis? Question 2--What is the current probability of reducing the relative risk of death (RRR) of my patient with severe sepsis by meaningful clinical thresholds (RRR >15%; >20%; >25%)?

METHODS

Bayesian methodologies were applied to this study. Odds ratio (OR) was considered for Question 1, and RRR was used for Question 2. We constructed prior distributions (enthusiastic; mild, moderate, and severe skeptic) based on various effective sample sizes of other relevant clinical trials (unfavorable evidence). Posterior distributions were calculated by combining the prior distributions and the data from pivotal trials (favorable evidence).

MAIN FINDINGS

Answer 1--The analysis based on mild skeptic prior shows beneficial results with the Intensive Insulin, rhAPC, and Low-Tidal Volume trials, but not with the Low-Dose Steroid and EGDT trials. All trials' results become unacceptable by the analyses using moderate or severe skeptic priors. Answer 2--If we aim for a RRR>15%, the mild skeptic analysis shows that the current probability of reducing death by this clinical threshold is 88% for the Intensive Insulin, 62-65% for the Low-Tidal Volume, rhAPC, EGDT trials, and 17% for the Low-Dose Steroid trial. The moderate and severe skeptic analyses show no clinically meaningful reduction in the risk of death for all trials. If we aim for a RRR >20% or >25%, all probabilities of benefits become lower independent of the degree of skepticism.

CONCLUSIONS

Our clinical threshold analysis offers a new bedside tool to be directly applied to the care of patients with severe sepsis. Our results demonstrate that the strength of evidence (statistical and clinical) is weak for all trials, particularly for the Low-Dose Steroid and EGDT trials. It is essential to replicate the results of each of these five clinical trials in confirmatory studies if we want to provide patient care based on scientifically sound evidence.

How many patients with severe sepsis are needed to confirm the efficacy of drotrecogin alfa activated? A Bayesian design

OBJECTIVES

Controversies concerning the pivotal trial and negative results from other Drotrecogin alfa activated (DAA) trials have raised questions about its efficacy in severe sepsis patients. Based on all available evidence, our study aimed to respond to: (1) What is the current probability that DAA is not better than the control? If the current probability is not small, e.g. greater than 0.05, then (2) How many patients will be needed for the DAA confirmatory trial?

DESIGN

We applied the Bayesian methodology to all randomized trials which tested anti-thrombotic therapies for severe sepsis. Prior distributions were defined as severe skeptic (all anti-thrombotic trials or DAA trials); moderate skeptic (anti-thrombotic trials with high risk of death); mild skeptic (DAA trials only); enthusiastic (DAA trials with high risk of death).

RESULTS

The total study sample includes 7,683 patients: DAA (N = 3,143); Anti-thrombin-III (N = 2,581); tissue factor pathway inhibitor (N = 1,959). Answer 1: All current probabilities that DAA is not better than the control (except for the enthusiastic analysis) range from 0.14 to 0.48, which strongly suggest the need for a confirmatory trial. Answer 2: The number of patients necessary for the DAA confirmatory trial ranges up to 8,350 for the severe skeptic; 730-810 for moderate skeptic; 550-685 for mild skeptic; and zero for enthusiastic analysis.

CONCLUSIONS

A confirmatory trial with approximately 600 patients with severe sepsis and high risk of death can provide a convincing answer for both the mild and moderate skeptic physicians concerning the efficacy of DAA in severe sepsis.

On the association between statin and fracture: a Bayesian consideration

BACKGROUND

The association between statin use and fracture risk is controversial, due to conflicting findings from previous studies. This study utilized the Bayesian approach to combine existing evidence and update the association with consideration of potential bias.

METHODS

Data on the association between statin use and fracture incidence from 11 observational studies and 4 RCTs were synthesized by both empirical Bayesian analysis and fully Bayesian random-effects meta-analysis models.

RESULTS

Empirical Bayesian analysis showed that statin use was associated with a reduction in hip fracture risk (OR=0.57, 95% credible interval (CrI): 0.46-0.71) and for non-vertebral (OR=0.69, 95% CrI, 0.63-0.74). These results were comparable with results from the fully Bayesian random-effects meta-analysis only for hip fracture (OR 0.56, 95% CrI, 0.42-0.73), but not for non-vertebral fracture (OR 0.77, 95% CrI, 0.58-1.03). The probability that statin use reduces fracture risk by at least 20% was 0.995 for hip fracture and 0.61 for non-vertebral fracture. Under the assumption that bias over-estimates the true OR by 20%, there is still a probability of 0.97 that statin use reduces hip fracture risk by at least 20%; however, the effect on non-vertebral fracture was much less robust with a probability of 0.27.

CONCLUSIONS

Results of this Bayesian consideration are highly consistent with the hypothesis that statin use reduces hip fracture, but the association between statin use and non-vertebral fracture remains uncertain. The Bayesian approach presented here has the ability to help updating existing evidence as new data becomes available.

Lifting a veil on diversity: a Bayesian approach to fitting relative-abundance models

Bayesian methods incorporate prior knowledge into a statistical analysis. This prior knowledge is usually restricted to assumptions regarding the form of probability distributions of the parameters of interest, leaving their values to be determined mainly through the data. Here we show how a Bayesian approach can be applied to the problem of drawing inference regarding species abundance distributions and comparing diversity indices between sites. The classic log series and the lognormal models of relative- abundance distribution are apparently quite different in form. The first is a sampling distribution while the other is a model of abundance of the underlying population. Bayesian methods help unite these two models in a common framework. Markov chain Monte Carlo simulation can be used to fit both distributions as small hierarchical models with shared common assumptions. Sampling error can be assumed to follow a Poisson distribution. Species not found in a sample, but suspected to be present in the region or community of interest, can be given zero abundance. This not only simplifies the process of model fitting, but also provides a convenient way of calculating confidence intervals for diversity indices. The method is especially useful when a comparison of species diversity between sites with different sample sizes is the key motivation behind the research. We illustrate the potential of the approach using data on fruit-feeding butterflies in southern Mexico. We conclude that, once all assumptions have been made transparent, a single data set may provide support for the belief that diversity is negatively affected by anthropogenic forest disturbance. Bayesian methods help to apply theory regarding the distribution of abundance in ecological communities to applied conservation.