Methods used to conduct and report Bayesian mixed treatment comparisons published in the medical literature: a systematic review

Prophylactic Antibiotics Delivered Via the Respiratory Tract to Reduce Ventilator-Associated Pneumonia: A Systematic Review, Network Meta-Analysis, and Trial Sequential Analysis of Randomized Controlled Trials

OBJECTIVES

To assess the effects of antibiotics delivered via the respiratory tract in preventing ventilator-associated pneumonia (VAP).

DATA SOURCES

We searched PubMed, Scopus, the Cochrane Library, and ClinicalTrials.gov for studies published in English up to October 25, 2023.

STUDY SELECTION

Adult patients with mechanical ventilation of over 48 h and receiving inhaled or instilled antibiotics (with control group) to prevent VAP were included.

DATA EXTRACTION

Two independent groups screened studies, extracted the data, and assessed the risk of bias. The Grading of Recommendations Assessment, Development, and Evaluation approach was used to assess the certainty/quality of the evidence. Results of a random-effects model were reported for overall and predefined subgroup meta-analyses. The analysis was primarily conducted on randomized controlled trials, and observational studies were used for sensitivity analyses.

DATA SYNTHESIS

Seven RCTs with 1445 patients were included, of which six involving 1283 patients used nebulizers to deliver antibiotics. No obvious risk of bias was found among the included RCTs for the primary outcome. Compared with control group, prophylactic antibiotics delivery via the respiratory tract significantly reduced the risk of VAP (risk ratio [RR], 0.69 [95% CI, 0.53-0.89]), particularly in subgroups where aminoglycosides (RR, 0.67 [0.47-0.97]) or nebulization (RR, 0.64 [0.49-0.83]) were used as opposed to other antibiotics (ceftazidime and colistin) or intratracheal instillation. No significant differences were observed in mortality, mechanical ventilation duration, ICU and hospital length of stay, duration of systemic antibiotics, need for tracheostomy, and adverse events between the two groups. Results were confirmed in sensitivity analyses.

CONCLUSIONS

In adult patients with mechanical ventilation for over 48 h, prophylactic antibiotics delivered via the respiratory tract reduced the risk of VAP, particularly for those treated with nebulized aminoglycosides.

The Bayesian simulation study (BASIS) framework for simulation studies in statistical and methodological research

Statistical simulation studies are becoming increasingly popular to demonstrate the performance or superiority of new computational procedures and algorithms. Despite this status quo, previous surveys of the literature have shown that the reporting of statistical simulation studies often lacks relevant information and structure. The latter applies in particular to Bayesian simulation studies, and in this paper the Bayesian simulation study framework (BASIS) is presented as a step towards improving the situation. The BASIS framework provides a structured skeleton for planning, coding, executing, analyzing, and reporting Bayesian simulation studies in biometrical research and computational statistics. It encompasses various features of previous proposals and recommendations in the methodological literature and aims to promote neutral comparison studies in statistical research. Computational aspects covered in the BASIS include algorithmic choices, Markov-chain-Monte-Carlo convergence diagnostics, sensitivity analyses, and Monte Carlo standard error calculations for Bayesian simulation studies. Although the BASIS framework focuses primarily on methodological research, it also provides useful guidance for researchers who rely on the results of Bayesian simulation studies or analyses, as current state-of-the-art guidelines for Bayesian analyses are incorporated into the BASIS.

The reporting quality and transparency of orthopaedic studies using Bayesian analysis requires improvement: A systematic review

Background

Bayesian methods are being used more frequently in orthopaedics. To advance the use and transparent reporting of Bayesian studies, reporting guidelines have been recommended. There is currently little known about the use or applications of Bayesian analysis in orthopedics including adherence to recommended reporting guidelines. The objective is to investigate the reporting of Bayesian analysis in orthopedic surgery studies; specifically, to evaluate if these papers adhere to reporting guidelines.

Methods

We searched PUBMED to December 2nd, 2020. Two reviewers independently identified studies and full-text screening. We included studies that focused on one or more orthopaedic surgical interventions and used Bayesian methods.

Results

After full-text review, 100 articles were included. The most frequent study designs were meta-analysis or network meta-analysis (56%, 95% CI 46-65) and cohort studies (25%, 95% CI 18-34). Joint replacement was the most common subspecialty (33%, 95% CI 25-43). We found that studies infrequently reported key concepts in Bayesian analysis including, specifying the prior distribution (37-39%), justifying the prior distribution (18%), the sensitivity to different priors (7-8%), and the statistical model used (22%). In contrast, general methodological items on the checklists were largely well reported.

Conclusions

There is an opportunity to improve reporting quality and transparency of orthopaedic studies using Bayesian analysis by encouraging adherence to reporting guidelines such as ROBUST, JASP, and BayesWatch. There is an opportunity to better report prior distributions, sensitivity analyses, and the statistical models used.

Systematic review with network meta-analysis on the treatments for latent tuberculosis infection in children and adolescents

BACKGROUND

We aimed to synthesize the evidence on the efficacy and safety of different treatment regimens for latent tuberculosis infection (LTBI) in children and adolescents.

METHODS

A systematic review with network meta-analysis was performed (CRD142933). Searches were conducted in Pubmed and Scopus (Nov-2021). Randomized controlled trials comparing treatments for LTBI (patients up to 15 years), and reporting data on the incidence of the disease, death or adverse events were included. Networks using the Bayesian framework were built for each outcome of interest. Results were reported as odds ratio (OR) with 95% credibility intervals (CrI). Rank probabilities were calculated via the surface under the cumulative ranking analysis (SUCRA) (Addis-v.1.16.8). GRADE approach was used to rate evidence's certainty.

RESULTS

Seven trials (n = 8696 patients) were included. Placebo was significantly associated with a higher incidence of tuberculosis compared to all active therapies. Combinations of isoniazid (15-25 mg/kg/week) plus rifapentine (300-900 mg/week), followed by isoniazid plus rifampicin (10 mg/kg/day) were ranked as best approaches with lower probabilities of disease incidence (10% and 19.5%, respectively in SUCRA) and death (20%). Higher doses of isoniazid monotherapy were significantly associated to more deaths (OR 18.28, 95% ICr [1.02, 48.60] of 4-6 mg/kg/day vs. 10 mg/kg/3x per week).

CONCLUSIONS

Combined therapies of isoniazid plus rifapentine or rifampicin for short-term periods should be used as the first-line approach for treating LTBI in children and adolescents. The use of long-term isoniazid as monotherapy and at higher doses should be avoided for this population.

Efficacy of Anti-fungal Agents for Invasive Fungal Infection prophylaxis in Liver Transplant Recipients: A Network Meta-Analysis

At present, there is still a lack of effective invasive fungal prophylaxis therapy in liver transplant recipients (LTRs). This study aimed to analysis the latest evidence on efficacy of current prophylactic anti-fungal therapy, and systematically compare between anti-fungal agents and placebo by a fixed-effects meta-analysis in all randomized controlled trials. A network meta-analysis was performed for invasive fungal infection (IFI) among different agents in 14 randomized controlled trials, in which 10 anti-fungal approaches were identified. Overall, anti-fungal prophylaxis reduced the rate of IFI (RR 0.30, 95% CI 0.18-0.52) and proven IFI (RR 0.27, 95% CI 0.14-0.53) when compared to placebo. In the network meta-analysis, an equivalent reduction in the rate of IFI was observed in fluconazole (OR 4.70, 95% CI 1.22-18.10), itraconazole (OR 5.82, 95% CI 1.10-30.71) and Liposomal amphotericin B (LAmB, OR 5.74, 95% CI 1.29-25.58) groups when compared with placebo. Anidulafungin might be the most effective agents in IFI prevention, however, this superiority did not meet statistically significance. Our study indicated that fluconazole, echinocandins and LAmB are equivalent in efficacy. Of which, fluconazole is recommended for the prevention of IFI in LTRs due to its efficacy, economics and compliance.

Comparison of the Effectiveness of Various Drug Interventions to Prevent Etomidate-Induced Myoclonus: A Bayesian Network Meta-Analysis

Background

Myoclonic movement is a very common but undesirable phenomenon during the induction of general anesthesia using etomidate. Such movement may cause unnecessary problems. Currently, there is an increasing number of drugs for preventing etomidate-induced myoclonus (EM). However, direct comparisons of various drugs are lacking, and this interferes with clinical decision-making. Our network meta-analysis (NMA) aimed to compare the efficacy of different drugs for the prevention of moderate-to-severe general myoclonus.

Methods

Using several biomedical databases, randomized controlled trials (RCTs) published in English from inception to August 22, 2021 were searched. Among the various interventions, we selected nine types of intervention drugs (dexmedetomidine, etomidate, lidocaine, NMDA receptor antagonist, κ opioid receptor agonist, μ opioid receptor agonist, muscle relaxant, gabapentin, and midazolam) for comparison, according to the number of studies. Bayesian NMA was performed using STATA16 and R softwares. The relative risk of EM was assessed using risk ratios (RRs) and the corresponding 95% confidence intervals (CI).

Results

A total of 31 RCTs (3209 patients) were included. NMA results showed that, compared with a placebo, etomidate (RR 4.0, 95%CI 2.1–7.8), κ opioid receptor agonist (RR 2.9, 95%CI 1.9–4.6), μ opioid receptor agonist (RR 3.1, 95%CI 2.3–4.3), NMDA receptor antagonist (RR 1.7, 95%CI 1.0–2.8), dexmedetomidine (RR 2.4, 95%CI 1.5–3.9), lidocaine (RR 2.1, 95%CI 1.2–3.9), and midazolam (RR 2.2, 95%CI 1.5–3.2) can significantly reduce the risk of EM. In contrast, the effects of muscle relaxants (RR 2.1, 95%CI 0.81–5.3) and gabapentin (RR 2.8, 95%CI 0.92–9.3) were inconclusive. Further subgroup analyses showed that preoperative low-dose etomidate, μ-opioid receptor agonist, and κ-opioid receptor agonist were significantly better than other interventions in the prevention of moderate to severe EM.

Conclusion

Preoperative use of small doses of etomidate or opioids may be the most effective way to avoid EM, especially moderate and severe EM, which makes anesthesia induction safer, more stable, and aligns better with the requirements of comfortable medicine.

Systematic Review Registration

[https://www.crd.york.ac.uk/prospero/], [CRD4202127706].

Challenges of modelling approaches for network meta-analysis of time-to-event outcomes in the presence of non-proportional hazards to aid decision making: Application to a melanoma network

BACKGROUND

Synthesis of clinical effectiveness from multiple trials is a well-established component of decision-making. Time-to-event outcomes are often synthesised using the Cox proportional hazards model assuming a constant hazard ratio over time. However, with an increasing proportion of trials reporting treatment effects where hazard ratios vary over time and with differing lengths of follow-up across trials, alternative synthesis methods are needed.

OBJECTIVES

To compare and contrast five modelling approaches for synthesis of time-to-event outcomes and provide guidance on key considerations for choosing between the modelling approaches.

METHODS

The Cox proportional hazards model and five other methods of estimating treatment effects from time-to-event outcomes, which relax the proportional hazards assumption, were applied to a network of melanoma trials reporting overall survival: restricted mean survival time, generalised gamma, piecewise exponential, fractional polynomial and Royston-Parmar models.

RESULTS

All models fitted the melanoma network acceptably well. However, there were important differences in extrapolations of the survival curve and interpretability of the modelling constraints demonstrating the potential for different conclusions from different modelling approaches.

CONCLUSION

The restricted mean survival time, generalised gamma, piecewise exponential, fractional polynomial and Royston-Parmar models can accommodate non-proportional hazards and differing lengths of trial follow-up within a network meta-analysis of time-to-event outcomes. We recommend that model choice is informed using available and relevant prior knowledge, model transparency, graphically comparing survival curves alongside observed data to aid consideration of the reliability of the survival estimates, and consideration of how the treatment effect estimates can be incorporated within a decision model.

Bayesian Analysis Reporting Guidelines

Previous surveys of the literature have shown that reports of statistical analyses often lack important information, causing lack of transparency and failure of reproducibility. Editors and authors agree that guidelines for reporting should be encouraged. This Review presents a set of Bayesian analysis reporting guidelines (BARG). The BARG encompass the features of previous guidelines, while including many additional details for contemporary Bayesian analyses, with explanations. An extensive example of applying the BARG is presented. The BARG should be useful to researchers, authors, reviewers, editors, educators and students. Utilization, endorsement and promotion of the BARG may improve the quality, transparency and reproducibility of Bayesian analyses.

Haematological adverse events associated with tyrosine kinase inhibitors in chronic myeloid leukaemia: A network meta-analysis

AIMS

Despite their overall favourable safety profile, tyrosine kinase inhibitors (TKIs) are related to severe adverse events including haematological toxicities such as anaemia, leucopenia, neutropenia and thrombocytopenia. We designed a systematic review and network meta-analysis of randomised controlled trials to compare safety among TKIs (bosutinib, dasatinib, imatinib, nilotinib, ponatinib and radotinib) used by patients diagnosed with chronic myeloid leukaemia.

METHODS

We obtained data from the PubMed, Scopus, Web of Science, and SciELO databases. The Bayesian approach was used for direct and indirect comparisons, and the treatments were ranked by the surface under the cumulative ranking curve (SUCRA).

RESULTS

Seventeen studies were included in the network meta-analysis. Our data show that dasatinib was generally considered worse than the other TKIs, with SUCRA values ​​for 140 mg dasatinib of 90.3% for anaemia, 87.4% for leucopenia, 90.6% for neutropenia and 97.2% for thrombocytopenia. In addition, nilotinib was shown to be safer, with SUCRA values ​​for 600 and 800 mg doses of 21.9 and 35.8% for anaemia, 23.8 and 14.6% for leucopenia, 33.0 and 17.7% for neutropenia, and 28.7 and 32.6% for thrombocytopenia, respectively.

CONCLUSION

Dasatinib appeared as the least safe drug for chronic myeloid leukaemia, probably because it binds to multiple key kinase targets, being more prone to cause serious haematological adverse events. Nilotinib demonstrated a safer profile, mostly due to its selective binding capacity.

Medical Treatments for Acromegaly: A Systematic Review and Network Meta-Analysis

BACKGROUND

Acromegaly results from the hypersecretion of growth hormone. Because of the low incidence rates of this disease worldwide, few clinical trials evaluating drug treatments have been conducted.

OBJECTIVES

To conduct the first network meta-analysis simultaneously comparing all available drugs used in acromegaly treatment so as to provide more robust evidence in this field.

METHODS

A systematic review was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Cochrane Collaboration recommendations (PROSPERO database under the registration number CRD42017059880). The electronic searches were conducted in PubMed (MEDLINE), Scopus, and Web of Science databases. Randomized controlled trials comparing any drug for the treatment of acromegaly head-to-head or versus placebo were included. Outcomes concerning the efficacy and safety of treatments were evaluated. The statistical analyses were performed using Aggregate Data Drug Information System version 1.16.8 (drugis.org, Groningen, The Netherlands).

RESULTS

The initial search retrieved 2059 articles. Of these, 10 randomized controlled trials were included in a qualitative analysis and 7 in a quantitative analysis. The network meta-analysis for the efficacy outcome (number of patients achieving insulinlike growth factor 1 control) showed that pegvisomant and lanreotide autogel were statistically superior to placebo (odds ratio [95% credible interval] 0.06 [0.00-0.55] and 0.09 [0.01-0.88]). No further differences were found. The probability rank indicated that pegvisomant and pasireotide have the highest probabilities (33% and 34%, respectively) of being the best therapeutic options. No major side effects were noted.

CONCLUSIONS

Pegvisomant is still a good option for acromegaly treatment, but pasireotide seems to be a promising alternative. Nevertheless, other important key factors such as drug costs and effectiveness (real-world results) should be taken into account when selecting acromegaly treatment.

The best strategy for RAS wild-type metastatic colorectal cancer patients in first-line treatment: A classic and Bayesian meta-analysis

BACKGROUND

At present, there is uncertainty on the best systemic treatment in first-line setting for RAS wild-type (WT) metastatic colorectal cancer (mCRC) patients. Indeed, several chemotherapy and biologics combinations showed an improvement on survival. We performed a systematic review with a pair-wise and bayesan meta-analysis to rank the best strategy for these patients.

METHODS

A systematic literature search through March 2017 was performed to evaluate the association between several treatment combinations and overall survival (OS), progression-free survival (PFS), overall response rate (ORR) and toxicity rate (TR) in RAS WT mCRC patients. Data were extracted from studies and pooled using the random-effect model for pair-wise meta-analyses and bayesan model for network meta-analysis (NMA).

RESULTS

Eight studies with a total of 2518 individuals were included in the meta-analyses. Pooled analyses for subgroups stratified by type of schedule and tumor location demonstrated that anti-EGFR + doublet had the best OS when compared to doublet ± bevacizumab (0.767; 95%CI, 0.695-0.846; P < 0.0001). This benefit is limited to LSCC when compared to a doublet-based schedule and doublet + bevacizumab (HRs, 0.692; 95%CI, 0.596-0.804; P < 0.001; 0.706; 95%CI, 0.584-0.854; P < 0.001; respectively). No significant differences are detected in PFS, whereas the cetuximab-based regimens showed the highest ORR and TR. In NMA our ranking showed the best performance for FOLFOX + panitumumab.

CONCLUSIONS

Our study indicates that FOLFOX + panitumumab has the major probability to provide an improvement of survival with a good safety profile in patients with RAS WT mCRC with an added value from selection based on sidedness.

Bayesian one-step IPD network meta-analysis of time-to-event data using Royston-Parmar models

Network meta‐analysis (NMA) combines direct and indirect evidence from trials to calculate and rank treatment estimates. While modelling approaches for continuous and binary outcomes are relatively well developed, less work has been done with time‐to‐event outcomes. Such outcomes are usually analysed using Cox proportional hazard (PH) models. However, in oncology with longer follow‐up time, and time‐dependent effects of targeted treatments, this may no longer be appropriate. Network meta‐analysis conducted in the Bayesian setting has been increasing in popularity. However, fitting the Cox model is computationally intensive, making it unsuitable for many datasets. Royston‐Parmar models are a flexible alternative that can accommodate time‐dependent effects. Motivated by individual participant data (IPD) from 37 cervical cancer trials (5922 women) comparing surgery, radiotherapy, and chemotherapy, this paper develops an IPD Royston‐Parmar Bayesian NMA model for overall survival. We give WinBUGS code for the model. We show how including a treatment‐ln(time) interaction can be used to conduct a global test for PH, illustrate how to test for consistency of direct and indirect evidence, and assess within‐design heterogeneity. Our approach provides a computationally practical, flexible Bayesian approach to NMA of IPD survival data, which readily extends to include additional complexities, such as non‐PH, increasingly found in oncology trials.

Fluconazole Doses Used for Prophylaxis of Invasive Fungal Infection in Neonatal Intensive Care Units: A Network Meta-Analysis

OBJECTIVES

To evaluate the safety and efficacy of different doses of fluconazole used for invasive prophylaxis of fungal infection in neonates.

STUDY DESIGN

A systematic search was conducted with PubMed, Scopus, and Web of Science. A manual search was performed as well. Only randomized controlled trials of neonates in a neonatal intensive care unit (NICU) who received fluconazole prophylaxis for invasive fungal infection, regardless of the dose or therapeutic regimen, were included in this review. Data on baseline characteristics, outcomes incidence of proven invasive Candida infection, overall mortality, and invasive Candida infection-related mortality were extracted.

RESULTS

Eleven studies were included in the review, with fluconazole doses of 3, 4, or 6?mg/kg. When the incidence of invasive Candida and invasive Candida-related mortality were considered as outcomes, the 3 and 6?mg/kg fluconazole doses were found to be statistically superior to placebo (OR, 5.48 [95% credible interval, 1.81-18.94] and 2.63 [1.18-7.02], respectively, and 15.32 [1.54-54.31] and 9.14 [1.26-142.7], respectively), but data for the 3 doses were not statistically significantly different.

CONCLUSIONS

Use of the lowest fluconazole dose (3?mg/kg) should be recommended for Candida prophylaxis in neonates, given that increasing the fluconazole dose is not associated with higher efficacy and has greater potential for toxicity and increased cost.

Network meta-analysis: a technique to gather evidence from direct and indirect comparisons

Systematic reviews and pairwise meta-analyses of randomized controlled trials, at the intersection of clinical medicine, epidemiology and statistics, are positioned at the top of evidence-based practice hierarchy. These are important tools to base drugs approval, clinical protocols and guidelines formulation and for decision-making. However, this traditional technique only partially yield information that clinicians, patients and policy-makers need to make informed decisions, since it usually compares only two interventions at the time. In the market, regardless the clinical condition under evaluation, usually many interventions are available and few of them have been studied in head-to-head studies. This scenario precludes conclusions to be drawn from comparisons of all interventions profile (e.g. efficacy and safety). The recent development and introduction of a new technique – usually referred as network meta-analysis, indirect meta-analysis, multiple or mixed treatment comparisons – has allowed the estimation of metrics for all possible comparisons in the same model, simultaneously gathering direct and indirect evidence. Over the last years this statistical tool has matured as technique with models available for all types of raw data, producing different pooled effect measures, using both Frequentist and Bayesian frameworks, with different software packages. However, the conduction, report and interpretation of network meta-analysis still poses multiple challenges that should be carefully considered, especially because this technique inherits all assumptions from pairwise meta-analysis but with increased complexity. Thus, we aim to provide a basic explanation of network meta-analysis conduction, highlighting its risks and benefits for evidence-based practice, including information on statistical methods evolution, assumptions and steps for performing the analysis.

A scoping review of indirect comparison methods and applications using individual patient data

BACKGROUND

Several indirect comparison methods, including network meta-analyses (NMAs), using individual patient data (IPD) have been developed to synthesize evidence from a network of trials. Although IPD indirect comparisons are published with increasing frequency in health care literature, there is no guidance on selecting the appropriate methodology and on reporting the methods and results.

METHODS

In this paper we examine the methods and reporting of indirect comparison methods using IPD. We searched MEDLINE, Embase, the Cochrane Library, and CINAHL from inception until October 2014. We included published and unpublished studies reporting a method, application, or review of indirect comparisons using IPD and at least three interventions.

RESULTS

We identified 37 papers, including a total of 33 empirical networks. Of these, only 9 (27 %) IPD-NMAs reported the existence of a study protocol, whereas 3 (9 %) studies mentioned that protocols existed without providing a reference. The 33 empirical networks included 24 (73 %) IPD-NMAs and 9 (27 %) matching adjusted indirect comparisons (MAICs). Of the 21 (64 %) networks with at least one closed loop, 19 (90 %) were IPD-NMAs, 13 (68 %) of which evaluated the prerequisite consistency assumption, and only 5 (38 %) of the 13 IPD-NMAs used statistical approaches. The median number of trials included per network was 10 (IQR 4-19) (IPD-NMA: 15 [IQR 8-20]; MAIC: 2 [IQR 3-5]), and the median number of IPD trials included in a network was 3 (IQR 1-9) (IPD-NMA: 6 [IQR 2-11]; MAIC: 2 [IQR 1-2]). Half of the networks (17; 52 %) applied Bayesian hierarchical models (14 one-stage, 1 two-stage, 1 used IPD as an informative prior, 1 unclear-stage), including either IPD alone or with aggregated data (AD). Models for dichotomous and continuous outcomes were available (IPD alone or combined with AD), as were models for time-to-event data (IPD combined with AD).

CONCLUSIONS

One in three indirect comparison methods modeling IPD adjusted results from different trials to estimate effects as if they had come from the same, randomized, population. Key methodological and reporting elements (e.g., evaluation of consistency, existence of study protocol) were often missing from an indirect comparison paper.

GetReal in network meta-analysis: a review of the methodology

Pairwise meta-analysis is an established statistical tool for synthesizing evidence from multiple trials, but it is informative only about the relative efficacy of two specific interventions. The usefulness of pairwise meta-analysis is thus limited in real-life medical practice, where many competing interventions may be available for a certain condition and studies informing some of the pairwise comparisons may be lacking. This commonly encountered scenario has led to the development of network meta-analysis (NMA). In the last decade, several applications, methodological developments, and empirical studies in NMA have been published, and the area is thriving as its relevance to public health is increasingly recognized. This article presents a review of the relevant literature on NMA methodology aiming to pinpoint the developments that have appeared in the field. Copyright © 2016 John Wiley & Sons, Ltd.

An assessment of the methodological quality of published network meta-analyses: a systematic review

OBJECTIVE

To assess the methodological quality of published network meta-analysis.

DESIGN

Systematic review.

METHODS

We searched the medical literature for network meta-analyses of pharmaceuticals. We assessed general study characteristics, study transparency and reproducibility, methodological approach, and reporting of findings. We compared studies published in journals with lower impact factors with those published in journals with higher impact factors, studies published prior to January 1st, 2013 with those published after that date, and studies supported financially by industry with those supported by non-profit institutions or that received no support.

RESULTS

The systematic literature search identified 854 citations. Three hundred and eighteen studies met our inclusion criteria. The number of network meta-analyses has grown rapidly, with 48% of studies published since January 2013. The majority of network meta-analyses were supported by a non-profit institution or received no support (68%). We found considerable inconsistencies among reviewed studies. Eighty percent reported search terms, 61% a network diagram, 65% sufficient data to replicate the analysis, and 90% the characteristics of included trials. Seventy percent performed a risk of bias assessment of included trials, 40% an assessment of model fit, and 56% a sensitivity analysis. Among studies with a closed loop, 69% examined the consistency of direct and indirect evidence. Sixty-four percent of studies presented the full matrix of head-to-head treatment comparisons. For Bayesian studies, 41% reported the probability that each treatment was best, 31% reported treatment ranking, and 16% included the model code or referenced publicly-available code. Network meta-analyses published in higher impact factors journals and those that did not receive industry support performed better across the assessment criteria. We found few differences between older and newer studies.

CONCLUSIONS

There is substantial variation in the network meta-analysis literature. Consensus among guidelines is needed improve the methodological quality, transparency, and consistency of study conduct and reporting.

Gastrointestinal and renal side effects of bisphosphonates: differentiating between no proof of difference and proof of no difference

BACKGROUND

This study was aimed at comparing the safety of bisphosphonates in women with osteoporosis by application of equivalence testing.

METHODS

Gastrointestinal and renal side effects were evaluated based on information published in randomized controlled trials.

RESULTS

The data on gastrointestinal side effects (47 trials) indicated that alendronate, risedronate etidronate, and zolendronate have similar rates of the adverse effects; application of Bayesian network meta-analysis showed that equivalence was demonstrated according to margins around ±10%. The data on renal safety were more sparse and suffered from the use of different outcome measures; hence, a single trial could be evaluated. This trial showed a similar effect of alendronate and risedronate on renal function at 12 months; equivalence was based on differences between the two agents in renal function with margins of less than ±10.4 ml/min.

CONCLUSION

Our study provided quantitative information to determine to what extent bisphosphonates can be considered equivalent in terms of gastrointestinal and renal side effects.

Simultaneous Comparison of Efficacy and Tolerability of Second-Generation Antipsychotics in Schizophrenia: Mixed-Treatment Comparison Analysis Based on Head-to-Head Trial Data

OBJECTIVE

Second-generation antipsychotics have been repeatedly shown to be superior to placebo. However, the comparative efficacy among these drugs has not been systematically evaluated. In this study, we used Mixed Treatment Comparison (MTC) procedures to elucidate the comparative efficacy and tolerability of second-generation antipsychotics.

METHODS

Seven antipsychotics were selected based on the availability of the relevant data. Data were gathered from a series of review article published by the Cochrane Collaboration. Six outcome measures were analyzed: 1) percentage of no clinically important response as defined by the original authors, 2) PANSS total score change from baseline to endpoint, 3) percentage of akathisia, 4) percentage of antiparkinson medication use, 5) percentage of total body weight increase more than 7%, and 6) percentage of drop-out due to any reasons.

RESULTS

All the second-generation antipsychotics included in this study showed fairly similar efficacy but widely different tolerability. In terms of efficacy, amisulpride, clozapine and olanzapine were ranked higher than aripiprazole, quetiapine and ziprasidone. Clozapine and olanzapine were superior in terms of akathisia and extrapyramidal symptom risk, but, far more prone to induce clinically important weight gain.

CONCLUSION

Using MTC methodology, we could line up the second generation antipsychotics according to their hierarchical superiority in terms of efficacy and tolerability. Though the wide overlap among the confidence intervals and the inconsistency between the direct and indirect comparison results may limit the validity of these results, it may still allow the important insights into the relative merits of the available drugs.

[Basic concepts for network meta-analysis]

Las revisiones sistemáticas y los metaanálisis se han consolidado como una herramienta fundamental para la práctica clínica basada en la evidencia. Inicialmente, el metaanálisis fue propuesto como una técnica que podría mejorar la precisión y la potencia estadística de la investigación procedente de estudios individuales con pequeño tamaño muestral. Sin embargo, uno de sus principales inconvenientes es que suelen comparar no más de 2 intervenciones alternativas a la vez. Los «metaanálisis en red» utilizan técnicas novedosas de análisis que permiten incorporar la información procedente de comparaciones directas e indirectas a partir de una red de estudios que examina los efectos de diversos tratamientos de una manera más completa. Pese a sus potenciales limitaciones, su aplicación en epidemiología clínica podría ser potencialmente útil en situaciones en las que existen varios tratamientos que se han comparado frente a un comparador común.

Además, estas técnicas pueden ser relevantes ante una pregunta clínica o de investigación cuando existen múltiples tratamientos que deben ser considerados, o cuando se dispone tanto de información directa como indirecta en el cuerpo de la evidencia.

The quality of reporting methods and results in network meta-analyses: an overview of reviews and suggestions for improvement

INTRODUCTION

Some have suggested the quality of reporting of network meta-analyses (a technique used to synthesize information to compare multiple interventions) is sub-optimal. We sought to review information addressing this claim.

OBJECTIVE

To conduct an overview of existing evaluations of quality of reporting in network meta-analyses and indirect treatment comparisons, and to compile a list of topics which may require detailed reporting guidance to enhance future reporting quality.

METHODS

An electronic search of Medline and the Cochrane Registry of methodologic studies (January 2004-August 2013) was performed by an information specialist. Studies describing findings from quality of reporting assessments were sought. Screening of abstracts and full texts was performed by two team members. Descriptors related to all aspects of reporting a network meta-analysis were summarized.

RESULTS

We included eight reports exploring the quality of reporting of network meta-analyses. From past reviews, authors found several aspects of network meta-analyses were inadequately reported, including primary information about literature searching, study selection, and risk of bias evaluations; statement of the underlying assumptions for network meta-analysis, as well as efforts to verify their validity; details of statistical models used for analyses (including information for both Bayesian and Frequentist approaches); completeness of reporting of findings; and approaches for summarizing probability measures as additional important considerations.

CONCLUSIONS

While few studies were identified, several deficiencies in the current reporting of network meta-analyses were observed. These findings reinforce the need to develop reporting guidance for network meta-analyses. Findings from this review will be used to guide next steps in the development of reporting guidance for network meta-analysis in the format of an extension of the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analysis) Statement.

Reporting of results from network meta-analyses: methodological systematic review

OBJECTIVE

To examine how the results of network meta-analyses are reported.

DESIGN

Methodological systematic review of published reports of network meta-analyses.

DATA SOURCES

Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Medline, and Embase, searched from inception to 12 July 2012.

STUDY SELECTION

All network meta-analyses comparing the clinical efficacy of three or more interventions in randomised controlled trials were included, excluding meta-analyses with an open loop network of three interventions.

DATA EXTRACTION AND SYNTHESIS

The reporting of the network and results was assessed. A composite outcome included the description of the network (number of interventions, direct comparisons, and randomised controlled trials and patients for each comparison) and the reporting of effect sizes derived from direct evidence, indirect evidence, and the network meta-analysis.

RESULTS

121 network meta-analyses (55 published in general journals; 48 funded by at least one private source) were included. The network and its geometry (network graph) were not reported in 100 (83%) articles. The effect sizes derived from direct evidence, indirect evidence, and the network meta-analysis were not reported in 48 (40%), 108 (89%), and 43 (36%) articles, respectively. In 52 reports that ranked interventions, 43 did not report the uncertainty in ranking. Overall, 119 (98%) reports of network meta-analyses did not give a description of the network or effect sizes from direct evidence, indirect evidence, and the network meta-analysis. This finding did not differ by journal type or funding source.

CONCLUSIONS

The results of network meta-analyses are heterogeneously reported. Development of reporting guidelines to assist authors in writing and readers in critically appraising reports of network meta-analyses is timely.

Characteristics of networks of interventions: a description of a database of 186 published networks

Systematic reviews that employ network meta-analysis are undertaken and published with increasing frequency while related statistical methodology is evolving. Future statistical developments and evaluation of the existing methodologies could be motivated by the characteristics of the networks of interventions published so far in order to tackle real rather than theoretical problems. Based on the recently formed network meta-analysis literature we aim to provide an insight into the characteristics of networks in healthcare research. We searched PubMed until end of 2012 for meta-analyses that used any form of indirect comparison. We collected data from networks that compared at least four treatments regarding their structural characteristics as well as characteristics of their analysis. We then conducted a descriptive analysis of the various network characteristics. We included 186 networks of which 35 (19%) were star-shaped (treatments were compared to a common comparator but not between themselves). The median number of studies per network was 21 and the median number of treatments compared was 6. The majority (85%) of the non-star shaped networks included at least one multi-arm study. Synthesis of data was primarily done via network meta-analysis fitted within a Bayesian framework (113 (61%) networks). We were unable to identify the exact method used to perform indirect comparison in a sizeable number of networks (18 (9%)). In 32% of the networks the investigators employed appropriate statistical methods to evaluate the consistency assumption; this percentage is larger among recently published articles. Our descriptive analysis provides useful information about the characteristics of networks of interventions published the last 16 years and the methods for their analysis. Although the validity of network meta-analysis results highly depends on some basic assumptions, most authors did not report and evaluate them adequately. Reviewers and editors need to be aware of these assumptions and insist on their reporting and accuracy.