Network meta-analysis-highly attractive but more methodological research is needed

Network meta-analysis, in the context of a systematic review, is a meta-analysis in which multiple treatments (that is, three or more) are being compared using both direct comparisons of interventions within randomized controlled trials and indirect comparisons across trials based on a common comparator. To ensure validity of findings from network meta-analyses, the systematic review must be designed rigorously and conducted carefully. Aspects of designing and conducting a systematic review for network meta-analysis include defining the review question, specifying eligibility criteria, searching for and selecting studies, assessing risk of bias and quality of evidence, conducting a network meta-analysis, interpreting and reporting findings. This commentary summarizes the methodologic challenges and research opportunities for network meta-analysis relevant to each aspect of the systematic review process based on discussions at a network meta-analysis methodology meeting we hosted in May 2010 at the Johns Hopkins Bloomberg School of Public Health. Since this commentary reflects the discussion at that meeting, it is not intended to provide an overview of the field

Long-acting inhaled therapy (beta-agonists, anticholinergics and steroids) for COPD: a network meta-analysis.

BACKGROUND: Pharmacological therapy for chronic obstructive pulmonary disease (COPD) is aimed at relieving symptoms, improving quality of life and preventing or treating exacerbations.Treatment tends to begin with one inhaler, and additional therapies are introduced as necessary. For persistent or worsening symptoms, long-acting inhaled therapies taken once or twice daily are preferred over short-acting inhalers. Several Cochrane reviews have looked at the risks and benefits of specific long-acting inhaled therapies compared with placebo or other treatments. However for patients and clinicians, it is important to understand the merits of these treatments relative to each other, and whether a particular class of inhaled therapies is more beneficial than the others. OBJECTIVES: To assess the efficacy of treatment options for patients whose chronic obstructive pulmonary disease cannot be controlled by short-acting therapies alone. The review will not look at combination therapies usually considered later in the course of the disease.As part of this network meta-analysis, we will address the following issues.1. How does long-term efficacy compare between different pharmacological treatments for COPD?2. Are there limitations in the current evidence base that may compromise the conclusions drawn by this network meta-analysis? If so, what are the implications for future research? SEARCH METHODS: We identified randomised controlled trials (RCTs) in existing Cochrane reviews by searching the Cochrane Database of Systematic Reviews (CDSR). In addition, we ran a comprehensive citation search on the Cochrane Airways Group Register of trials (CAGR) and checked manufacturer websites and reference lists of other reviews. The most recent searches were conducted in September 2013. SELECTION CRITERIA: We included parallel-group RCTs of at least 6 months' duration recruiting people with COPD. Studies were included if they compared any of the following treatments versus any other: long-acting beta2-agonists (LABAs; formoterol, indacaterol, salmeterol); long-acting muscarinic antagonists (LAMAs; aclidinium, glycopyrronium, tiotropium); inhaled corticosteroids (ICSs; budesonide, fluticasone, mometasone); combination long-acting beta2-agonist (LABA) and inhaled corticosteroid (LABA/ICS) (formoterol/budesonide, formoterol/mometasone, salmeterol/fluticasone); and placebo. DATA COLLECTION AND ANALYSIS: We conducted a network meta-analysis using Markov chain Monte Carlo methods for two efficacy outcomes: St George's Respiratory Questionnaire (SGRQ) total score and trough forced expiratory volume in one second (FEV1). We modelled the relative effectiveness of any two treatments as a function of each treatment relative to the reference treatment (placebo). We assumed that treatment effects were similar within treatment classes (LAMA, LABA, ICS, LABA/ICS). We present estimates of class effects, variability between treatments within each class and individual treatment effects compared with every other.To justify the analyses, we assessed the trials for clinical and methodological transitivity across comparisons. We tested the robustness of our analyses by performing sensitivity analyses for lack of blinding and by considering six- and 12-month data separately. MAIN RESULTS: We identified 71 RCTs randomly assigning 73,062 people with COPD to 184 treatment arms of interest. Trials were similar with regards to methodology, inclusion and exclusion criteria and key baseline characteristics. Participants were more often male, aged in their mid sixties, with FEV1 predicted normal between 40% and 50% and with substantial smoking histories (40+ pack-years). The risk of bias was generally low, although missing information made it hard to judge risk of selection bias and selective outcome reporting. Fixed effects were used for SGRQ analyses, and random effects for Trough FEV1 analyses, based on model fit statistics and deviance information criteria (DIC). SGRQ SGRQ data were available in 42 studies (n = 54,613). At six months, 39 pairwise comparisons were made between 18 treatments in 25 studies (n = 27,024). Combination LABA/ICS was the highest ranked intervention, with a mean improvement over placebo of -3.89 units at six months (95% credible interval (CrI) -4.70 to -2.97) and -3.60 at 12 months (95% CrI -4.63 to -2.34). LAMAs and LABAs were ranked second and third at six months, with mean differences of -2.63 (95% CrI -3.53 to -1.97) and -2.29 (95% CrI -3.18 to -1.53), respectively. Inhaled corticosteroids were ranked fourth (MD -2.00, 95% CrI -3.06 to -0.87). Class differences between LABA, LAMA and ICS were less prominent at 12 months. Indacaterol and aclidinium were ranked somewhat higher than other members of their classes, and formoterol 12 mcg, budesonide 400 mcg and formoterol/mometasone combination were ranked lower within their classes. There was considerable overlap in credible intervals and rankings for both classes and individual treatments. Trough FEV1 Trough FEV1 data were available in 46 studies (n = 47,409). At six months, 41 pairwise comparisons were made between 20 treatments in 31 studies (n = 29,271). As for SGRQ, combination LABA/ICS was the highest ranked class, with a mean improvement over placebo of 133.3 mL at six months (95% CrI 100.6 to 164.0) and slightly less at 12 months (mean difference (MD) 100, 95% CrI 55.5 to 140.1). LAMAs (MD 103.5, 95% CrI 81.8 to 124.9) and LABAs (MD 99.4, 95% CrI 72.0 to 127.8) showed roughly equivalent results at six months, and ICSs were the fourth ranked class (MD 65.4, 95% CrI 33.1 to 96.9). As with SGRQ, initial differences between classes were not so prominent at 12 months. Indacaterol and salmeterol/fluticasone were ranked slightly better than others in their class, and formoterol 12, aclidinium, budesonide and formoterol/budesonide combination were ranked lower within their classes. All credible intervals for individual rankings were wide. AUTHORS' CONCLUSIONS: This network meta-analysis compares four different classes of long-acting inhalers for people with COPD who need more than short-acting bronchodilators. Quality of life and lung function were improved most on combination inhalers (LABA and ICS) and least on ICS alone at 6 and at 12 months. Overall LAMA and LABA inhalers had similar effects, particularly at 12 months. The network has demonstrated the benefit of ICS when added to LABA for these outcomes in participants who largely had an FEV1 that was less than 50% predicted, but the additional expense of combination inhalers and any potential for increased adverse events (which has been established by other reviews) require consideration. Our findings are in keeping with current National Institute for Health and Care Excellence (NICE) guidelines

A threshold analysis assessed the credibility of conclusions from network meta-analysis

Objective: To assess the reliability of treatment recommendations based on network meta-analysis (NMA)Study design: We consider evidence in an NMA to be potentially biased. Taking each pair-wise contrast in turn we use a structured series of threshold analyses to ask: (a) “How large would the bias in this evidence-base have to be before it changed our decision?” and (b) “If the decision changed, what is the new recommendation?” We illustrate the method via two NMAs in which a GRADE assessment for NMAs has been implemented: weight-loss and osteoporosis.Results. Four of the weight-loss NMA estimates were assessed as “low” and 6 as “moderate” quality by GRADE; for osteoporosis 6 were “low”, 9 “moderate” and 1 “high”. The threshold analysis suggests plausible bias in 3 of 10 estimates in the weight-loss network could have changed the treatment recommendation. For osteoporosis plausible bias in 6 of 16 estimates could change the recommendation. There was no relation between plausible bias changing a treatment recommendation and the original GRADE assessments.Conclusions. Reliability judgements on individual NMA contrasts do not help decision makers understand whether a treatment recommendation is reliable. Threshold analysis reveals whether the final recommendation is robust against plausible degrees of bias in the data

Inhaled drugs to reduce exacerbations in patients with chronic obstructive pulmonary disease: a network meta-analysis

BACKGROUND: Most patients with chronic obstructive pulmonary disease (COPD) receive inhaled long-acting bronchodilators and inhaled corticosteroids. Conventional meta-analyses established that these drugs reduce COPD exacerbations when separately compared with placebo. However, there are relatively few head-to-head comparisons and conventional meta-analyses focus on single comparisons rather than on a simultaneous analysis of competing drug regimens that would allow rank ordering of their effectiveness. Therefore we assessed, using a networkmeta analytic technique, the relative effectiveness of the common inhaled drug regimes used to reduce exacerbations in patients with COPD. METHODS: We conducted a systematic review and searched existing systematic reviews and electronic databases for randomized trials of >=4 weeks' duration that assessed the effectiveness of inhaled drug regimes on exacerbations in patients with stable COPD. We extracted participants and intervention characteristics from included trials and assessed their methodological quality. For each treatment group we registered the proportion of patients with >=1 exacerbation during follow-up. We used treatment-arm based logistic regression analysis to estimate the absolute and relative effects of inhaled drug treatments while preserving randomization within trials. RESULTS: We identified 35 trials enrolling 26,786 patients with COPD of whom 27% had >=1 exacerbation. All regimes reduced exacerbations statistically significantly compared with placebo (odds ratios ranging from 0.71 (95%confidence interval [CI] 0.64 to 0.80) for long-acting anticholinergics to 0.78 (95% CI 0.70 to 0.86) for inhaled corticosteroids). Compared with long-acting bronchodilators alone, combined treatment was not more effective (comparison with long-acting beta-agonists: odds ratio 0.93 [95% CI 0.84 to 1.04] and comparison with long-acting anticholinergics: odds ratio 1.02 [95% CI 0.90 to 1.16], respectively). If FEV1 was 40% predicted. This effect modification was significant for inhaled corticosteroids (P=0.02 for interaction) and combination treatment (P=0.01) but not for long-acting anticholinergics (P=0.46). A limitation of this analysis is its exclusive focus on exacerbations and lack of FEV1 data for individual patients. CONCLUSIONS: We found no evidence that one single inhaled drug regimen is more effective than another in reducing exacerbations. Inhaled corticosteroids when added to long-acting beta-agonists reduce exacerbations only in patients with COPD with FEV1<=40%

Network meta-analysis with integrated nested Laplace approximations

Analyzing the collected evidence of a systematic review in form of a network meta-analysis (NMA) enjoys increasing popularity and provides a valuable instrument for decision making. Bayesian inference of NMA models is often propagated, especially if correlated random effects for multiarm trials are included. The standard choice for Bayesian inference is Markov chain Monte Carlo (MCMC) sampling, which is computationally intensive. An alternative to MCMC sampling is the recently suggested approximate Bayesian method of integrated nested Laplace approximations (INLA) that dramatically saves computation time without any substantial loss in accuracy. We show how INLA apply to NMA models for summary level as well as trial-arm level data. Specifically, we outline the modeling of multiarm trials and inference for functional contrasts with INLA. We demonstrate how INLA facilitate the assessment of network inconsistency with node-splitting. Three applications illustrate the use of INLA for a NMA