How to Conduct a Bayesian Network Meta-Analysis.
Ontology highlight
ABSTRACT:
SUBMITTER: Hu D
PROVIDER: S-EPMC7248597 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Publications
How to Conduct a Bayesian Network Meta-Analysis.
Hu Dapeng D O'Connor Annette M AM Wang Chong C Sargeant Jan M JM Winder Charlotte B CB
Frontiers in veterinary science 20200519
Network meta-analysis is a general approach to integrate the results of multiple studies in which multiple treatments are compared, often in a pairwise manner. In this tutorial, we illustrate the procedures for conducting a network meta-analysis for binary outcomes data in the Bayesian framework using example data. Our goal is to describe the workflow of such an analysis and to explain how to generate informative results such as ranking plots and treatment risk posterior distribution plots. The ...[more]
Similar Datasets
Project description:BackgroundSeveral reviews have noted shortcomings regarding the quality and reporting of network meta-analyses (NMAs). We suspect that this issue may be partially attributable to limitations in current NMA software which do not readily produce all of the output needed to satisfy current guidelines.ResultsTo better facilitate the conduct and reporting of NMAs, we have created an R package called "BUGSnet" (Bayesian inference Using Gibbs Sampling to conduct a Network meta-analysis). This R package relies upon Just Another Gibbs Sampler (JAGS) to conduct Bayesian NMA using a generalized linear model. BUGSnet contains a suite of functions that can be used to describe the evidence network, estimate a model and assess the model fit and convergence, assess the presence of heterogeneity and inconsistency, and output the results in a variety of formats including league tables and surface under the cumulative rank curve (SUCRA) plots. We provide a demonstration of the functions contained within BUGSnet by recreating a Bayesian NMA found in the second technical support document composed by the National Institute for Health and Care Excellence Decision Support Unit (NICE-DSU). We have also mapped these functions to checklist items within current reporting and best practice guidelines.ConclusionBUGSnet is a new R package that can be used to conduct a Bayesian NMA and produce all of the necessary output needed to satisfy current scientific and regulatory standards. We hope that this software will help to improve the conduct and reporting of NMAs.
| S-EPMC6805536 | biostudies-literature
Project description:BackgroundNetwork meta-analysis (NMA) provides a powerful tool for the simultaneous evaluation of multiple treatments by combining evidence from different studies, allowing for direct and indirect comparisons between treatments. In recent years, NMA is becoming increasingly popular in the medical literature and underlying statistical methodologies are evolving both in the frequentist and Bayesian framework. Traditional NMA models are often based on the comparison of two treatment arms per study. These individual studies may measure outcomes at multiple time points that are not necessarily homogeneous across studies.MethodsIn this article we present a Bayesian model based on B-splines for the simultaneous analysis of outcomes across time points, that allows for indirect comparison of treatments across different longitudinal studies.ResultsWe illustrate the proposed approach in simulations as well as on real data examples available in the literature and compare it with a model based on P-splines and one based on fractional polynomials, showing that our approach is flexible and overcomes the limitations of the latter.ConclusionsThe proposed approach is computationally efficient and able to accommodate a large class of temporal treatment effect patterns, allowing for direct and indirect comparisons of widely varying shapes of longitudinal profiles.
| S-EPMC7574305 | biostudies-literature
Project description:BACKGROUND:Aerosolized antibiotics have been proposed as a novel and promising treatment option for the treatment of ventilator-associated pneumonia (VAP). However, the optimum aerosolized antibiotics for VAP remain uncertain. METHODS:We included studies from two systematic reviews and searched PubMed, EMBASE, and Cochrane databases for other studies. Eligible studies included randomized controlled trials and observational studies. Extracted data were analyzed by pairwise and network meta-analysis. RESULTS:Eight observational and eight randomized studies were identified for this analysis. By pairwise meta-analysis using intravenous antibiotics as the reference, patients treated with aerosolized antibiotics were associated with significantly higher rates of clinical recovery (risk ratio (RR) 1.21, 95% confidence interval (CI) 1.09-1.34; P?=?0.001) and microbiological eradication (RR 1.42, 95% CI 1.22-1.650; P?<?0.0001). There were no significant differences in the risks of mortality (RR 0.88, 95% CI 0.74-1.04; P?=?0.127) or nephrotoxicity (RR 1.00, 95% CI 0.72-1.39; P?=?0.995). Using network meta-analysis, clinical recovery benefits were seen only with aerosolized tobramycin and colistin (especially tobramycin), and microbiological eradication benefits were seen only with colistin. Aerosolized tobramycin was also associated with significantly lower mortality when compared with aerosolized amikacin and colistin and intravenous antibiotics. The assessment of rank probabilities indicated aerosolized tobramycin presented the greatest likelihood of having benefits for clinical recovery and mortality, and aerosolized colistin presented the best benefits for microbiological eradication. CONCLUSIONS:Aerosolized antibiotics appear to be a useful treatment for VAP with respect to clinical recovery and microbiological eradication, and do not increase mortality or nephrotoxicity risks. Our network meta-analysis in patients with VAP suggests that clinical recovery benefits are associated with aerosolized tobramycin and colistin (especially tobramycin), microbiological eradication with aerosolized colistin, and survival with aerosolized tobramycin, mostly based on observational studies. Due to the low levels of evidence, definitive recommendations cannot be made before additional, large randomized studies are carried out.
| S-EPMC6238320 | biostudies-other
Project description:In this paper we suggest a new Bayesian approach to network meta-analysis for the case of discrete multiple outcomes. The joint distribution of the discrete outcomes is modeled through a Gaussian copula with binomial marginals. The remaining elements of the hierarchial random effects model are specified in a standard way, with the logit of the success probabilities given by the sum of a baseline log-odds and random effects comparing the log-odds of each treatment against the reference and having a Gaussian distribution centered at the vector of pooled effects. An adaptive Markov Chain Monte Carlo algorithm is devised for running posterior inference. The model is applied to two datasets from Cochrane reviews, already analysed in two papers so to assess and compare its performance. We implemented the model in a freely available R package called netcopula.
| S-EPMC7188248 | biostudies-literature
Project description:OBJECTIVES:Dental research typically targets multiple outcomes. Interdental cleaning devices such as interdental brushes (IB) and water jet devices (WJ) share a sizable portion of the medical device market. However, recommendations for device selection are limited by the conflicting evidence from multiple outcomes in available studies and the lack of an appropriate synthesis approach to summarize evidences taken from multiple outcomes. In particular, both pairwise meta-analyses and single-outcome network meta-analyses can give discordant results. The purpose of this multioutcome, Bayesian network meta-analysis is to introduce this innovative method to the dental research community using data from interdental cleaning device studies for illustrative purposes. METHODS:We reanalyzed a network meta-analysis of interproximal oral hygiene methods in the reduction of clinical indices of inflammation, which included 22 trials assessing 10 interproximal oral hygiene aids. We focused on the primary outcome of gingival inflammation, which was measured by 2 correlated outcome variables, the Gingival Index (GI) and bleeding on probing (BOP). RESULTS:In our previous single-outcome analysis, we concluded that IB and WJ rank high for reducing gingival inflammation while toothpick and flossing rank last. In this multioutcome Bayesian network meta-analysis with equal weight on GI and BOP, the surface under the cumulative ranking curve was 0.87 for WJ and 0.85 for IB. WJ and IB remained ranked as the 2 best devices across different sets of weightings for the GI and BOP. CONCLUSION:In conclusion, multioutcome Bayesian network meta-analysis naturally takes the correlations among multiple outcomes into account, which in turn can provide more comprehensive evidence.
| S-EPMC7211186 | biostudies-literature
Project description:The optimal treatment of recurrent glioblastoma (GBM) remains controversial. Therefore, our study aimed to compare and rank active therapies in recurrent GBM. We performed a systematic review and a Bayesian network meta-analysis. We obtained a treatment hierarchy using the surface under the cumulative ranking curve and mean ranks. A cluster analysis was conducted to aggregate the separated results of three outcomes. The protocol was registered in PROSPERO (CRD42019146794). A total of 1,667 citations were identified, and 15 eligible articles with 17 treatments remained in the final network meta-analysis. Pairwise comparison showed no significant difference on the 6-month progression-free survival (6-m PFS) rate, objective response rate (ORR), and overall survival (OS). Among the reports, cediranib plus lomustine (CCNU) corresponded to the highest rates of grade 3-4 adverse events. Ranking and cluster analysis indicated that bevacizumab (BEV) plus CCNU and regorafenib had a higher efficacy on the ORR, 6-m PFS rate and OS, and that BEV monotherapy or BEV combined with active drug therapies was advantageous for the ORR and 6-m PFS rate. Additionally, tumor treatment fields (TTF) plus BEV showed a relatively higher SUCRA value in OS. According to ranking and cluster analysis, BEV plus CCNU and regorafenib are the primary recommendations for treatment. BEV monotherapy alone or combined with active drug therapies are recommended in patients with severe neurological symptoms. Advanced therapy, such as TTF and immunotherapy, remain to be investigated in future studies.
| S-EPMC8039381 | biostudies-literature
Project description:Network meta-analysis (NMA) is a popular tool to synthesize direct and indirect evidence for simultaneously comparing multiple treatments, while evidence inconsistency greatly threatens its validity. One may use the inconsistency degrees of freedom (ICDF) to assess the potential that an NMA might suffer from inconsistency. Multi-arm studies provide intrinsically consistent evidence and complicate the ICDF's calculation; they commonly appear in NMAs. The existing ICDF measure may not feasibly handle multi-arm studies. Motivated from the effective numbers of parameters of Bayesian hierarchical models, we propose new ICDF measures in generic NMAs that may contain multi-arm studies. Under the fixed- or random-effects setting, the new ICDF measure is the difference between the effective numbers of parameters of the consistency and inconsistency NMA models. We used artificial NMAs created based on an illustrative example and 39 empirical NMAs to evaluate the performance of the existing and new measures. In NMAs with two-arm studies only, the proposed ICDF measure under the fixed-effects setting was nearly the same with the existing measure. Among the empirical NMAs, 27 (69%) contained at least one multi-arm study. The existing measure was not applicable to them, while the proposed measures led to interpretable ICDFs in all NMAs.
| S-EPMC8122016 | biostudies-literature
Project description:BackgroundNetwork meta-analysis (NMA) is a widely used tool to compare multiple treatments by synthesizing different sources of evidence. Measures such as the surface under the cumulative ranking curve (SUCRA) and the P-score are increasingly used to quantify treatment ranking. They provide summary scores of treatments among the existing studies in an NMA. Clinicians are frequently interested in applying such evidence from the NMA to decision-making in the future. This prediction process needs to account for the heterogeneity between the existing studies in the NMA and a future study.MethodsThis article introduces the predictive P-score for informing treatment ranking in a future study via Bayesian models. Two NMAs were used to illustrate the proposed measure; the first assessed 4 treatment strategies for smoking cessation, and the second assessed treatments for all-grade treatment-related adverse events. For all treatments in both NMAs, we obtained their conventional frequentist P-scores, Bayesian P-scores, and predictive P-scores.ResultsIn the two examples, the Bayesian P-scores were nearly identical to the corresponding frequentist P-scores for most treatments, while noticeable differences existed for some treatments, likely owing to the different assumptions made by the frequentist and Bayesian NMA models. Compared with the P-scores, the predictive P-scores generally had a trend to converge toward a common value of 0.5 due to the heterogeneity. The predictive P-scores' numerical estimates and the associated plots of posterior distributions provided an intuitive way for clinicians to appraise treatments for new patients in a future study.ConclusionsThe proposed approach adapts the existing frequentist P-score to the Bayesian framework. The predictive P-score can help inform medical decision-making in future studies.
| S-EPMC8520624 | biostudies-literature
Project description:IntroductionCorticosteroid-induced osteoporosis (CIO) is the most common type of secondary osteoporosis, leading to fractures, and increased morbidity and mortality.Source of dataPubmed, EMBASE, Scopus and Google Scholar databases.Areas of agreementProlonged glucocorticoids administration leads to secondary osteoporosis.Areas of controversyThe optimal management for CIO is controversial.Growing pointsThe present study compared bone mineral density, fractures and adverse events in patients undergoing treatment with risedronate, alendronate, zoledronate, denosumab or etidronate for CIO.Areas timely for developing researchFor selected patients with CIO, alendronate performed better overall. These results must be interpreted within the limitations of the present study.Level of evidenceI, Bayesian network meta-analysis of randomized clinical trials.
| S-EPMC9494254 | biostudies-literature
Project description:Several concerns regarding the safety of face masks use have been propounded in public opinion. The objective of this review is to examine if these concerns find support in the literature by providing a comprehensive overview of physiological responses to the use of face masks. We have performed a systematic review, pairwise and network meta-analyses to investigate physiological responses to the use of face masks. The study has been registered with PROSPERO (C RD42020224791). Obtained results were screened using our exclusion and inclusion criteria. Meta-analyses were performed using the GeMTC and meta R packages. We have identified 26 studies meeting our inclusion and exclusion criteria, encompassing 751 participants. The use of face masks was not associated with significant changes in pulsoxymetrically measured oxygen saturation, even during maximal-effort exercises. The only significant physiological responses to the use of face masks during low-intensity activities were a slight increase in heart rate, mildly elevated partial pressure of carbon dioxide (not meeting criteria for hypercarbia), increased temperature of facial skin covered by the mask, and subsequent increase of the score in the rating of heat perception, with N95 filtering facepiece respirators having a greater effect than surgical masks. In high-intensity conditions, the use of face masks was associated with decreased oxygen uptake, ventilation, and RR. Face masks are safe to use and do not cause significant alterations in human physiology. The increase in heart rate stems most likely from increased respiratory work required to overcome breathing resistance. The increase in carbon dioxide is too small to be clinically relevant. An increased rating of heat perception when using face masks results from higher temperature of facial skin covered by the mask.
| S-EPMC8985742 | biostudies-literature