Biomedical subjects

Alexander J Sutton

Publications and source records attributed to Alexander J Sutton.

9 recordsLinked to original sources

PubMed2007

Evidence-based sample size calculations based upon updated meta-analysis.

Meta-analyses of randomized controlled trials (RCTs) provide the highest level of evidence regarding the effectiveness of interventions and as such underpin much of evidence-based medicine. Despite this, meta-analyses are usually produced as observational by-products of the existing literature, with no formal consideration of future meta-analyses when individual trials are being designed. Basing the sample size of a new trial on the results of an updated meta-analysis which will include it, may sometimes make more sense than powering the trial in isolation. A framework for sample size calculation for a future RCT based on the results of a meta-analysis of the existing evidence is presented. Both fixed and random effect approaches are explored through an example. Bayesian Markov Chain Monte Carlo simulation modelling is used for the random effects model since it has computational advantages over the classical approach. Several criteria on which to base inference and hence power are considered. The prior expectation of the power is averaged over the prior distribution for the unknown true treatment effect. An extension to the framework allowing for consideration of the design for a series of new trials is also presented. Results suggest that power can be highly dependent on the statistical model used to meta-analyse the data and even very large studies may have little impact on a meta-analysis when there is considerable between study heterogeneity. This raises issues regarding the appropriateness of the use of random effect models when designing and drawing inferences across a series of studies.

Anti-Bacterial Agents↗

PubMed2007

Bivariate random-effects meta-analysis and the estimation of between-study correlation.

BACKGROUND: When multiple endpoints are of interest in evidence synthesis, a multivariate meta-analysis can jointly synthesise those endpoints and utilise their correlation. A multivariate random-effects meta-analysis must incorporate and estimate the between-study correlation (rhoB). METHODS: In this paper we assess maximum likelihood estimation of a general normal model and a generalised model for bivariate random-effects meta-analysis (BRMA). We consider two applied examples, one involving a diagnostic marker and the other a surrogate outcome. These motivate a simulation study where estimation properties from BRMA are compared with those from two separate univariate random-effects meta-analyses (URMAs), the traditional approach. RESULTS: The normal BRMA model estimates rhoB as -1 in both applied examples. Analytically we show this is due to the maximum likelihood estimator sensibly truncating the between-study covariance matrix on the boundary of its parameter space. Our simulations reveal this commonly occurs when the number of studies is small or the within-study variation is relatively large; it also causes upwardly biased between-study variance estimates, which are inflated to compensate for the restriction on rhoB. Importantly, this does not induce any systematic bias in the pooled estimates and produces conservative standard errors and mean-square errors. Furthermore, the normal BRMA is preferable to two normal URMAs; the mean-square error and standard error of pooled estimates is generally smaller in the BRMA, especially given data missing at random. For meta-analysis of proportions we then show that a generalised BRMA model is better still. This correctly uses a binomial rather than normal distribution, and produces better estimates than the normal BRMA and also two generalised URMAs; however the model may sometimes not converge due to difficulties estimating rhoB. CONCLUSION: A BRMA model offers numerous advantages over separate univariate synthesises; this paper highlights some of these benefits in both a normal and generalised modelling framework, and examines the estimation of between-study correlation to aid practitioners.

CD4 Lymphocyte Count↗

PubMed2007

Predicting costs over time using Bayesian Markov chain Monte Carlo methods: an application to early inflammatory polyarthritis.

This article focuses on the modelling and prediction of costs due to disease accrued over time, to inform the planning of future services and budgets. It is well documented that the modelling of cost data is often problematic due to the distribution of such data; for example, strongly right skewed with a significant percentage of zero-cost observations. An additional problem associated with modelling costs over time is that cost observations measured on the same individual at different time points will usually be correlated. In this study we compare the performance of four different multilevel/hierarchical models (which allow for both the within-subject and between-subject variability) for analysing healthcare costs in a cohort of individuals with early inflammatory polyarthritis (IP) who were followed-up annually over a 5-year time period from 1990/1991. The hierarchical models fitted included linear regression models and two-part models with log-transformed costs, and two-part model with gamma regression and a log link. The cohort was split into a learning sample, to fit the different models, and a test sample to assess the predictive ability of these models. To obtain predicted costs on the original cost scale (rather than the log-cost scale) two different retransformation factors were applied. All analyses were carried out using Bayesian Markov chain Monte Carlo (MCMC) simulation methods.

Adult↗

PubMed2006

Mixed comparison of stroke prevention treatments in individuals with nonrheumatic atrial fibrillation.

BACKGROUND: We aimed to identify different stroke prevention treatments for atrial fibrillation assessed in randomized controlled trials and to compare them within a single evidence synthesis framework. METHODS: We updated the Cochrane review on anticoagulants and antiplatelet therapy for nonrheumatic atrial fibrillation to include randomized controlled trials published between January 2000 and March 2005 identified via the CENTRAL database and MEDLINE. A mixed-treatment comparison method was used to combine direct within-trial, between-treatment comparisons with indirect trial evidence while maintaining randomization. RESULTS: Data were combined from 19 clinical trials that included 17 833 patients randomized to 9 treatment strategies, including placebo. For prevention of ischemic stroke, adjusted standard-dose warfarin sodium (relative rate [RR], 0.35; 95% credible interval [CrI], 0.24 to 0.52), adjusted low-dose warfarin (RR, 0.35; 95% CrI, 0.19 to 0.60), ximelagatran (RR, 0.34; 95% CrI, 0.18 to 0.61), and aspirin (RR, 0.64; 95% CrI, 0.44 to 0.88) were all associated with a significantly lower rate of ischemic stroke compared with placebo. For major and fatal bleeding episodes, there was some evidence of an increased risk for all treatments but none were statistically significant. Assuming a baseline risk of 51 ischemic stroke events per 1000 person-years, it can be estimated that adjusted standard-dose warfarin could prevent 28 (95% CrI, -37 to -19) ischemic strokes at the expense of 11 (95% CrI, -1 to +39) major or fatal bleeding episodes. In comparison, aspirin could prevent 16 (95% CrI, -26 to -5) ischemic strokes at the expense of 6 (95% CrI, -3 to +27) major or fatal bleeding episodes. CONCLUSIONS: A lower rate of ischemic stroke and a higher rate of major bleeding episodes were found to be associated with oral anticoagulants compared with aspirin, and both anticoagulants and aspirin were found to be associated with a reduction in the rate of stroke compared with placebo.

Anticoagulants↗

PubMed2005

Role of multivitamins and mineral supplements in preventing infections in elderly people: systematic review and meta-analysis of randomised controlled trials.

OBJECTIVE: To evaluate the effectiveness of multivitamins and mineral supplements in reducing infections in an elderly population. DESIGN: Systematic review and meta-analysis of randomised controlled trials. DATA SOURCES: Medline and other databases. Reference lists of identified articles were inspected for further relevant articles. SELECTION OF STUDIES: Trials were included if they evaluated the effect of multivitamins and mineral supplements on infections in an elderly population. REVIEW METHODS: Studies were assessed for the methodological quality by using the Jadad instrument. If the data required for the analyses were not available from the published articles we requested them from the original study authors. Meta-analysis was undertaken on three outcomes: the mean difference in number of days spent with infection, the odds ratio of at least one infection in the study period, and the incidence rate ratio for the difference in infection rates. Data on adverse events were also extracted. RESULTS: Eight trials met our inclusion criteria. Owing to inconsistency in the outcomes reported, only a proportion of the trials could be included in each meta-analysis. Multivitamins and mineral supplements were found to reduce the mean annual number of days spent with infection (three studies) by 17.5 (95% confidence interval 11 to 24, P < 0.001). The odds ratio for at least one infection in the study period (three studies) was 1.10 (0.81 to 1.50, P = 0.53). The infection rate ratio (four studies) was 0.89 (0.78 to 1.03, P = 0.11). Reporting of adverse events was poor. CONCLUSION: The evidence for routine use of multivitamin and mineral supplements to reduce infections in elderly people is weak and conflicting. Study results are heterogeneous, and this is partially confounded by outcome measure.

Aged↗

PubMed2005

A Bayesian approach to evaluating net clinical benefit allowed for parameter uncertainty.

BACKGROUND AND OBJECTIVE: Although randomized controlled trials (RCTs) are conducted to establish whether novel interventions work on average in the patient population, there is a growing desire to move to a more individualized approach to evaluation. The potential benefits and harms of a treatment policy may differ between individuals. If these benefits and harms are not evaluated distinctly, and in a quantitative framework, transparency can be lost in the decision-making process. METHODS: Glasziou and Irwig have outlined the concept of net clinical treatment benefit for identifying the patients for whom the potential benefits of treatment outweigh the possible side effects. This study revisits the decision whether to use warfarin to treat atrial fibrillation. In this analysis, RCT and various sorts of observational data are synthesized. RESULTS: This reanalysis brings into question the conclusions of the original analysis on who would benefit from warfarin; however, caution is advised, due to limitations in the quality of life data available. CONCLUSION: A fully realized Bayesian implementation of the model is presented. This provides a framework for including uncertainty related to the estimation of all model parameters, and permits both direct probability statements and credible intervals for specific patient groups to be expressed.

Anticoagulants↗

PubMed2004

What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data.

OBJECTIVES: To compare the performance of different meta-analysis methods for pooling odds ratios when applied to sparse event data with emphasis on the use of continuity corrections. BACKGROUND: Meta-analysis of side effects from RCTs or risk factors for rare diseases in epidemiological studies frequently requires the synthesis of data with sparse event rates. Combining such data can be problematic when zero events exist in one or both arms of a study as continuity corrections are often needed, but, these can influence results and conclusions. METHODS: A simulation study was undertaken comparing several meta-analysis methods for combining odds ratios (using various classical and Bayesian methods of estimation) on sparse event data. Where required, the routine use of a constant and two alternative continuity corrections; one based on a function of the reciprocal of the opposite group arm size; and the other an empirical estimate of the pooled effect size from the remaining studies in the meta-analysis, were also compared. A number of meta-analysis scenarios were simulated and replicated 1000 times, varying the ratio of the study arm sizes. RESULTS: Mantel-Haenszel summary estimates using the alternative continuity correction factors gave the least biased results for all group size imbalances. Logistic regression was virtually unbiased for all scenarios and gave good coverage properties. The Peto method provided unbiased results for balanced treatment groups but bias increased with the ratio of the study arm sizes. The Bayesian fixed effect model provided good coverage for all group size imbalances. The two alternative continuity corrections outperformed the constant correction factor in nearly all situations. The inverse variance method performed consistently badly, irrespective of the continuity correction used. CONCLUSIONS: Many routinely used summary methods provide widely ranging estimates when applied to sparse data with high imbalance between the size of the studies' arms. A sensitivity analysis using several methods and continuity correction factors is advocated for routine practice.

Bayes Theorem↗

PubMed2003

Effectiveness of neuraminidase inhibitors in treatment and prevention of influenza A and B: systematic review and meta-analyses of randomised controlled trials.

OBJECTIVE: To review the clinical effectiveness of oseltamivir and zanamivir for the treatment and prevention of influenza A and B. DESIGN: Systematic review and meta-analyses of randomised controlled trials. DATA SOURCES: Published studies were retrieved from electronic bibliographic databases; supplementary data were obtained from the manufacturers. SELECTION OF STUDIES: Randomised controlled, double blind trials that were published in English, had data available before 31 December 2001, evaluated treatment or prevention of naturally occurring influenza with zanamivir or oseltamivir (if given using the formulation and dosage licensed for clinical use), and reported at least one end point of relevance. REVIEW METHODS: The main outcome measures were the median time to the alleviation of symptoms (for treatment trials) and number of flu episodes avoided (for prevention trials). Three population groups were defined: children aged 12 years and under; otherwise healthy individuals aged 12 to 65 years; and "high risk" individuals (those with certain chronic medical conditions or aged 65 years and older). RESULTS: Seventeen treatment trials and seven prevention trials identified met the inclusion criteria. All trials included compared one of the drugs against placebo or standard care. Treatment of children, otherwise healthy individuals, and high risk populations with zanamivir reduced the median duration of symptoms in days respectively by 1.0 (95% confidence interval 0.5 to 1.5), 0.8 (0.3 to 1.3), and 0.9 (-0.1 to 1.9) for the intention to treat population. The corresponding results, in days, for oseltamivir were 0.9 (0.3 to 1.5), 0.9 (0.3 to 1.4), and 0.4 (-0.7 to 1.4). The effect of giving zanamivir and oseltamivir prophylactically resulted in a relative reduction of 70-90% in the odds of developing flu, depending on the strategy adopted and the population studied. CONCLUSIONS: Evidence from randomised controlled trials consistently supports the view that both oseltamivir and zanamivir are clinically effective for treating and preventing flu. However, evidence is limited for the treatment of certain populations and for all prevention strategies.

Acetamides↗

PubMed2002

Generalized synthesis of evidence and the threat of dissemination bias. the example of electronic fetal heart rate monitoring (EFM).

Assessment of the potential impact of dissemination bias is necessary for meta-analysis. When evidence is available from studies of different designs, the different study types may be affected by dissemination bias to differing degrees. The evidence relating to electronic fetal heart rate monitoring (EFM) for preventing perinatal mortality is used to explore the feasibility of carrying out a dissemination bias assessment in a generalized synthesis of evidence (gse) framework. Visual inspection of funnel plots, statistical tests, and methods to "adjust" the results of a meta-analysis are all used in an extensive sensitivity analysis. The potential impact of dissemination bias on gse models synthesizing all the evidence together is also reported. Detailed consideration is given to the influence of meta-analysis model choice, and outcome scale used. Using the risk difference scale, funnel plots of the observational studies appeared highly asymmetric. However, further explorations show these conclusions are not robust over use of different outcome measures or different meta-analysis models. Researchers should be aware that dissemination bias may affect different sources of evidence differently. Although assessments such as those described here are recommended, awareness of their lack of robustness to outcome scale and model choice is important. Further research into methods to assess dissemination bias that are invariant to these factors is needed.

Cardiotocography↗