The effects of excluding treatments from network meta-analyses: survey

Vibration of effects resulting from treatment selection in mixed-treatment comparisons: a multiverse analysis on network meta-analyses of antidepressants in major depressive disorder

OBJECTIVE

It is frequent to find overlapping network meta-analyses (NMAs) on the same topic with differences in terms of both treatments included and effect estimates. We aimed to evaluate the impact on effect estimates of selecting different treatment combinations (ie, network geometries) for inclusion in NMAs.

DESIGN

Multiverse analysis, covering all possible NMAs on different combinations of treatments.

SETTING

Data from a previously published NMA exploring the comparative effectiveness of 22 treatments (21 antidepressants and a placebo) for the treatment of acute major depressive disorder.

PARTICIPANTS

Cipriani et al explored a dataset of 116 477 patients included in 522 randomised controlled trials.

MAIN OUTCOME MEASURES

For each possible treatment selection, we performed an NMA to estimate comparative effectiveness on treatment response and treatment discontinuation for the treatments included (231 between-treatment comparisons). The distribution of effect estimates of between-treatment comparisons across NMAs was computed, and the direction, magnitude and statistical significance of the 1st and 99th percentiles were compared.

RESULTS

4 116 254 different NMAs concerned treatment response. Among possible network geometries, 172/231 (74%) pairwise comparisons exhibited opposite effects between the 1st and 99th percentiles, 57/231 (25%) comparisons exhibited statistically significant results in opposite directions, 118 of 231 (51%) comparisons derived results that were both significant and non-significant at 5% risk and 56/231 (24%) treatment pairs obtained consistent results with only significant differences (or only non-significant differences) at 5% risk. Comparisons based on indirect evidence only were associated with greater variability in effect estimates. Comparisons with small absolute values observed in the complete NMA more frequently obtained statistically significant results in opposite directions. Similar results were observed for treatment discontinuation.

CONCLUSION

In this multiverse analysis, we observed that the selection of treatments to be included in an NMA could have considerable consequences on treatment effect estimations.

TRIAL REGISTRATION

https://osf.io/mb5dy.

Bayesian network meta-analysis of head-to-head trials for complete resolution of nail psoriasis

BACKGROUND

Almost 50% of patients with skin psoriasis have concomitant nail involvement. The comparative effectiveness of the available biologics for nail psoriasis (NP) is still an area of contention because of limited data on nails.

OBJECTIVES

We conducted a systematic review and network meta-analysis (NMA) to compare the efficacy of biologics in achieving complete resolution of NP.

METHODS

We identified studies in PubMed, EMBASE and Scopus. The eligibility criteria included randomized controlled trial (RCTs) or cohort studies for psoriasis or psoriatic arthritis with at least two arms of active comparator of biologic reporting at least one efficacy outcome of interest: that is the Nail Psoriasis Severity Index (NAPSI), the modified NAPSI or the Physician's Global Assessment of Fingernail Psoriasis with a score of 0.

RESULTS

Fourteen studies comprising seven treatments met the inclusion criteria, and were included in the NMA. The NMA showed the odds of complete NP resolution were superior with ixekizumab [risk ratio (RR) 1.4, 95% confidence interval (CI) 0.73-3.10] compared with the treatment of reference (adalimumab). Brodalumab (RR 0.92, 95% CI 0.14-7.40), guselkumab (RR 0.81, 95% CI 0.40-1.80), infliximab (RR 0.90, 95% CI 0.19-4.60) and ustekinumab (RR 0.33, 95% CI 0.08-1.60) demonstrated worse therapeutic effect compared with adalimumab. According to the surface under the cumulative ranking curve, ixekizumab 80 mg every 4 weeks had the highest probability of being the best treatment.

CONCLUSIONS

The interleukin-17A inhibitor ixekizumab has the highest rate of complete nail clearance and it can be considered the best-ranked therapy from the present evidence. This study is relevant to daily practice as it facilitates the decision when choosing between the wide variety of available biologics in patients for whom clearance of nail symptoms is the first concern.

A systematic review and network meta-analysis of antimanic drugs for the treatment of acute mania used in Japan

This review aimed to clarify whether antimanic agents used in Japan are superior to placebo for the treatment of acute mania, based on reports of randomized controlled trials (RCTs) conducted in Japan and other East Asian countries. A literature search was conducted using the MEDLINE, PubMed, and Ichushi databases from their dates of inception to July 31, 2021, for studies written in English or Japanese with a primary diagnosis of bipolar I disorder, comparing any of the following active drugs to treat acute mania in adults: aripiprazole, carbamazepine, chlorpromazine, haloperidol, lithium, olanzapine, sultopride, timiperone, and zotepine. A random-effects network meta-analysis was performed within a frequentist framework. The quality of each included study was evaluated using the revised Cochrane risk-of-bias tool for randomized trials. The outcomes adopted were the response rate for efficacy and dropout rate for tolerability during 3 weeks from baseline. Eleven RCTs, totaling 1148 participants, were reviewed. The pooled odds ratio (OR) (±95% confidence interval [CI]) was calculated. Timiperone (OR = 4.53, CI 1.09-18.80), sultopride (OR = 3.76, CI 1.08-13.05), and aripiprazole (OR = 1.99, CI 1.22-3.24) were significantly more effective than placebo. Olanzapine (OR = 0.51, CI 0.29-0.90) was significantly superior in acceptability to placebo. The results showed no significant differences from placebo for carbamazepine, chlorpromazine, haloperidol, lithium, and olanzapine. These results suggest that noninferiority trials alone cannot always confirm the antimanic drug efficacy and that direct placebo-controlled trials are necessary to verify the antimanic efficacy of the drugs.

Introducing the Treatment Hierarchy Question in Network Meta-Analysis

Comparative effectiveness research using network meta-analysis can present a hierarchy of competing treatments, from the most to the least preferable option. However, in published reviews, the research question associated with the hierarchy of multiple interventions is typically not clearly defined. Here we introduce the novel notion of a treatment hierarchy question that describes the criterion for choosing a specific treatment over one or more competing alternatives. For example, stakeholders might ask which treatment is most likely to improve mean survival by at least 2 years, or which treatment is associated with the longest mean survival. We discuss the most commonly used ranking metrics (quantities that compare the estimated treatment-specific effects), how the ranking metrics produce a treatment hierarchy, and the type of treatment hierarchy question that each ranking metric can answer. We show that the ranking metrics encompass the uncertainty in the estimation of the treatment effects in different ways, which results in different treatment hierarchies. When using network meta-analyses that aim to rank treatments, investigators should state the treatment hierarchy question they aim to address and employ the appropriate ranking metric to answer it. Following this new proposal will avoid some controversies that have arisen in comparative effectiveness research.

Empirical Comparisons of 12 Meta-analysis Methods for Synthesizing Proportions of Binary Outcomes

BACKGROUND

Meta-analysis is increasingly used to synthesize proportions (e.g., disease prevalence). It can be implemented with widely used two-step methods or one-step methods, such as generalized linear mixed models (GLMMs). Existing simulation studies have shown that GLMMs outperform the two-step methods in some settings. It is, however, unclear whether these simulation settings are common in the real world. We aim to compare the real-world performance of various meta-analysis methods for synthesizing proportions.

METHODS

We extracted datasets of proportions from the Cochrane Library and applied 12 two-step and one-step methods to each dataset. We used Spearman's ρ and the Bland-Altman plot to assess their results' correlation and agreement. The GLMM with the logit link was chosen as the reference method. We calculated the absolute difference and fold change (ratio of estimates) of the overall proportion estimates produced by each method vs. the reference method.

RESULTS

We obtained a total of 43,644 datasets. The various methods generally had high correlations (ρ > 0.9) and agreements. GLMMs had computational issues more frequently than the two-step methods. However, the two-step methods generally produced large absolute differences from the GLMM with the logit link for small total sample sizes (< 50) and crude event rates within 10-20% and 90-95%, and large fold changes for small total event counts (< 10) and low crude event rates (< 20%).

CONCLUSIONS

Although different methods produced similar overall proportion estimates in most datasets, one-step methods should be considered in the presence of small total event counts or sample sizes and very low or high event rates.

Antioxidant micronutrient supplements for adult critically ill patients: A bayesian multiple treatment comparisons meta-analysis

BACKGROUND & AIMS

Antioxidant micronutrients (AxMs) have been administered to critically ill adults attempting to counteract the oxidative stress imposed during critical illness. However, results are conflicting and relative effectiveness of AxMs regimens is unknown. We conducted a Bayesian multi-treatment comparison (MTC) meta-analysis to identify the best AxM treatment regimen that will improve clinical outcomes.

METHODS

PubMed, EMBASE, Web of Science and Cochrane databases were searched from the inception of databases through August 2020. Randomized controlled trials (RCT) comparing AxMs supplementations with placebo among critically ill adults were included. Two authors assessed trial quality using Cochrane risk of bias tool and assessed certainty of evidence (CoE). A random effect model, non-informative priors Bayesian MTC meta-analysis using gemtc package in R version 3.6.2 was performed. AxMs treatment effect on clinical outcomes (mortality, infection rates, intensive care unit (ICU) and hospital stays and ventilator days) were represented by absolute risk differences (ARD) for dichotomous outcomes and mean differences (MD) for continuous outcomes. Prior to final analysis, we repeated the search through January 2021.

RESULTS

37 RCT (4905 patients) were included with 16 direct comparisons. With respect to mortality, the ARD for "vitamin E" compared with placebo was centred at -0.19 [95%CrI: -0.54,0.16; very low CoE] and was ranked the best treatment for mortality reduction as per surface under the cumulative ranking curve (SUCRA 0.71, 95%CrI: 0.07,1.00). A combination of "selenium, zinc and copper" was ranked the best for lowest ICU stay [-9.40, 95% CrI: -20.0,1.50; low CoE]. A combination of "selenium, zinc, copper and vitamin E" was ranked the best treatment for infection risk reduction [-0.22, 95% CrI: -0.61,0.17; very low CoE]. Ventilator days were least with a combination of "selenium, zinc and manganese" [2.80, 95% CrI: -6.30,0.89; low CoE]. Hospital stay was the lowest using a combination of "selenium, zinc and copper" [-13.00, 95% CrI: -38.00,13.00; very low CoE]. There is substantial uncertainty present in the rankings due to wide and overlapping 95% CrIs of SUCRA scores for the treatments.

CONCLUSIONS

Studies on critically ill adult patients have suggested a possible beneficial effects of certain AxM supplementations over and above the recommended dietary allowance. However, evidence does not support their use in clinical practice due to the low confidence in the estimates. Current studies evaluating specific AxMs or their combinations are limited with small sample sizes.

REGISTRATION

PROSPERO, CRD42020210199.

TAKE-HOME MESSAGE

Evidence suggesting a potential benefit of AxMs use more than recommended doses in critically ill adults is weak, indicating that there is no justification for this practice.

Overlapping network meta-analyses on psoriasis systemic treatments: an overview, quantity does not make quality

BACKGROUND

Network Meta-analyses (NMAs) have become successful in addressing gaps in the comparative effectiveness of systemic treatments in moderate-to-severe psoriasis. However, their increasing number carries both a risk of overlap and reproducibility issues that can hamper clinical decision-making. In this overview, we aimed to assess redundancy across these NMAs and to describe their characteristics.

METHODS

We considered all systematic reviews with NMAs of randomized controlled trials that included adult patients with moderate-to-severe psoriasis and that evaluated the efficacy and/or safety of systemic treatments compared with placebo or with an active comparator. PubMed/MEDLINE, Epistemonikos, PROSPERO and the Evidence Update of the Centre of Evidence-Based Dermatology of the University of Nottingham were searched up to 25 February 2021. Our main outcome was the number per year of redundant NMAs and the extent of their overlap. We also described their features, especially, the confidence in the results of the reviews, the studies' funding and the presence of spin (a description that overstates efficacy and/or understates harm), reporting issues and methodological characteristics.

RESULTS

In total, 47 redundant NMAs were included. Only 2/47 (4%) included all available treatments. Both efficacy and safety were evaluated in 14/47 (30%) NMAs and both short and long-term evaluations were assessed in 5/47 (11 %). Confidence in the results was critically low for 39/47 (83%) NMAs and only 10/47 (23 %) registered a protocol. 26/47 NMAs (55%) received pharmaceutical funding. CROs were involved in 19/47 (40%) NMAs. Reporting was poor across most of the NMAs' abstracts and spin was present in all of the abstracts. Almost half of the NMA failed to consider important limitations such as heterogeneity (32%) or consistency (66%).

DISCUSSION

In addition to a duplication of efforts, our overview showed heterogeneous methods and poor confidence in the results in a majority of the included NMAs, further distorted by reporting issues and spin. Clinicians need to interpret NMAs with caution when looking for the most reliable and comprehensive evidence.

Network Meta-Analysis Techniques for Synthesizing Prevention Science Evidence

Network meta-analysis is a popular statistical technique for synthesizing evidence from studies comparing multiple interventions. Benefits of network meta-analysis, over more traditional pairwise meta-analysis approaches, include evaluating efficacy/safety of interventions within a single framework, increased precision, comparing pairs of interventions that have never been directly compared in a trial, and providing a hierarchy of interventions in terms of their effectiveness. Network meta-analysis is relatively underutilized in prevention science. This paper therefore presents a primer of network meta-analysis for prevention scientists who wish to apply this method or to critically appraise evidence from publications using the method. We introduce the key concepts and assumptions of network meta-analysis, namely, transitivity and consistency, and demonstrate their applicability to the field of prevention science. We then illustrate the method using a network meta-analysis examining the comparative effectiveness of brief alcohol interventions for preventing hazardous drinking among college students. We provide data and code for all examples. Finally, we discuss considerations that are particularly relevant in network meta-analyses in the field of prevention, such as including non-randomized evidence.

Comparative efficacy and acceptability of different antihypertensive drug classes for cardiovascular disease prevention: protocol for a systematic review and network meta-analysis

INTRODUCTION

Clinical practice guidelines differ in their recommendations on first-line antihypertensive drug classes. No adequately powered randomised controlled trial have assessed all major drug classes against each other, and previous meta-analyses have mainly relied on pairwise meta-analyses for treatment comparisons.

METHODS AND ANALYSIS

A systematic review and network meta-analysis will be carried out to assess the efficacy and acceptability of all major antihypertensive drug classes. PubMed and CENTRAL were searched on 21 February 2020 to identify randomised controlled trials with at least 1000 person-years of follow-up, assessing any antihypertensive agent against other agents or placebo. All trials fulfilling the inclusion criteria will be assessed for risk of bias using the second version of Cochrane's risk of bias assessment tool. The study selection process, risk of bias assessment and data extraction are done by two authors in duplicate. Relative risks from individual trials will be combined in pairwise meta-analyses; in the absence of important intransitivity, random-effects network meta-analysis will be performed. The primary outcome for efficacy will be major adverse cardiovascular events, whereas the primary acceptability outcome will be treatment discontinuation for any reason. Additional outcomes include all-cause mortality, cardiovascular mortality, stroke, myocardial infarction, heart failure and acute renal failure. The impact of differences within drug classes will be explored through alternative networks, including analysing thiazide-like and thiazide-type diuretics separately.

ETHICS AND DISSEMINATION

This review will only process aggregated study level data and does not require ethical approval. The findings will be published in a peer-reviewed medical journal.

PROSPERO REGISTRATION NUMBER

CRD42020205482.

Network meta-analysis results against a fictional treatment of average performance: Treatment effects and ranking metric

BACKGROUND

Network meta-analysis (NMA) produces complex outputs as many comparisons between interventions are of interest. The estimated relative treatment effects are usually displayed in a forest plot or in a league table and several ranking metrics are calculated and presented.

METHODS

In this article, we estimate relative treatment effects of each competing treatment against a fictional treatment of average performance using the "deviation from the means" coding that has been used to parametrize categorical covariates in regression models. We then use this alternative parametrization of the NMA model to present a ranking metric (PreTA: Preferable Than Average) interpreted as the probability that a treatment is better than a fictional treatment of average performance.

RESULTS

We illustrate the alternative parametrization of the NMA model using two networks of interventions, a network of 18 antidepressants for acute depression and a network of four interventions for heavy menstrual bleeding. We also use these two networks to highlight differences among PreTA and existing ranking metrics. We further examine the agreement between PreTA and existing ranking metrics in 232 networks of interventions and conclude that their agreement depends on the precision with which relative effects are estimated.

CONCLUSIONS

A forest plot with NMA relative treatment effects using "deviation from means" coding could complement presentation of NMA results in large networks and in absence of an obvious reference treatment. PreTA is a viable alternative to existing probabilistic ranking metrics that naturally incorporates uncertainty.

Comparison of Antifungal Prophylaxis Drugs in Patients With Hematological Disease or Undergoing Hematopoietic Stem Cell Transplantation: A Systematic Review and Network Meta-analysis

IMPORTANCE

Several antifungal drugs are available for antifungal prophylaxis in patients with hematological disease or who are undergoing hematopoietic stem cell transplantation (HSCT).

OBJECTIVE

To summarize the evidence on the efficacy and adverse effects of antifungal agents using an integrated comparison.

DATA SOURCES

Medline, EMBASE, and the Cochrane Central Register of Controlled Clinical Trials were searched to collect all relevant evidence published in randomized clinical trials that assessed antifungal prophylaxis in patients with hematological disease. Sources were search from inception up to October 2019.

STUDY SELECTION

Studies that compared any antifungal agent with a placebo, no antifungal agent, or another antifungal agent among patients with hematological disease or undergoing HSCT were included. Of 39 709 studies identified, 69 met the criteria for inclusion.

DATA EXTRACTION AND SYNTHESIS

The outcome from each study was estimated using the relative risk (RR) with 95% CIs. The Mantel-Haenszel random-effects model was used. The reliability and validity of the networks were estimated by addressing inconsistencies in the evidence from comparative studies of different treatments. Data were analyzed from December 2019 to February 2020. Reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses for Network Meta-analysis (PRISMA-NMA) guideline.

MAIN OUTCOMES AND MEASURES

The primary outcomes were invasive fungal infections (IFIs) and mortality. The secondary outcomes were fungal infections, proven IFIs, invasive candidiasis, invasive aspergillosis, fungi-related death, and withdrawal owing to adverse effects of the drug.

RESULTS

We identified 69 randomized clinical trials that reported comparisons of 12 treatments with at total of 14 789 patients. Posaconazole was the treatment associated with the best probability of success against IFIs (surface under the cumulative ranking curve, 86.7%; mean rank, 2.5). Posaconazole treatment was associated with a significant reduction in IFIs (RR, 0.57; 95% CI, 0.42-0.79) and invasive aspergillosis (RR, 0.36; 95% CI, 0.15-0.85) compared with placebo. Voriconazole was associated with a significant reduction in invasive candidiasis (RR, 0.15; 95% CI, 0.09-0.26) compared with placebo. However, posaconazole was associated with a higher incidence of withdrawal because of the adverse effects of the drug (surface under the cumulative ranking curve, 17.5%; mean rank, 9.2). In subgroup analyses considering efficacy and tolerance, voriconazole might be the best choice for patients undergoing HSCT, especially allogenic HSCT; however, posaconazole was ranked as the best choice for patients with acute myeloid leukemia or myelodysplastic syndrome.

CONCLUSIONS AND RELEVANCE

These findings suggest that voriconazole may be the best prophylaxis option for patients undergoing HSCT, and posaconazole may be the best prophylaxis option for patients with acute myeloid leukemia or myelodysplastic syndrome.

Vibration of effects from diverse inclusion/exclusion criteria and analytical choices: 9216 different ways to perform an indirect comparison meta-analysis

BACKGROUND

Different methodological choices such as inclusion/exclusion criteria and analytical models can yield different results and inferences when meta-analyses are performed. We explored the range of such differences, using several methodological choices for indirect comparison meta-analyses to compare nalmefene and naltrexone in the reduction of alcohol consumption as a case study.

METHODS

All double-blind randomized controlled trials (RCTs) comparing nalmefene to naltrexone or one of these compounds to a placebo in the treatment of alcohol dependence or alcohol use disorders were considered. Two reviewers searched for published and unpublished studies in MEDLINE (August 2017), the Cochrane Library, Embase, and ClinicalTrials.gov and contacted pharmaceutical companies, the European Medicines Agency, and the Food and Drug Administration. The indirect comparison meta-analyses were performed according to different inclusion/exclusion criteria (based on medical condition, abstinence of patients before inclusion, gender, somatic and psychiatric comorbidity, psychological support, treatment administered and dose, treatment duration, outcome reported, publication status, and risk of bias) and different analytical models (fixed and random effects). The primary outcome was the vibration of effects (VoE), i.e. the range of different results of the indirect comparison between nalmefene and naltrexone. The presence of a "Janus effect" was investigated, i.e. whether the 1st and 99th percentiles in the distribution of effect sizes were in opposite directions.

RESULTS

Nine nalmefene and 51 naltrexone RCTs were included. No study provided a direct comparison between the drugs. We performed 9216 meta-analyses for the indirect comparison with a median of 16 RCTs (interquartile range = 12-21) included in each meta-analysis. The standardized effect size was negative at the 1st percentile (- 0.29, favouring nalmefene) and positive at the 99th percentile (0.29, favouring naltrexone). A total of 7.1% (425/5961) of the meta-analyses with a negative effect size and 18.9% (616/3255) of those with a positive effect size were statistically significant (p < 0.05).

CONCLUSIONS

The choice of inclusion/exclusion criteria and analytical models for meta-analysis can result in entirely opposite results. VoE evaluations could be performed when overlapping meta-analyses on the same topic yield contradictory result.

TRIAL REGISTRATION

This study was registered on October 19, 2016, in the Open Science Framework (OSF, protocol available at https://osf.io/7bq4y/ ).

Empirical evaluation of SUCRA-based treatment ranks in network meta-analysis: quantifying robustness using Cohen's kappa

OBJECTIVE

To provide a framework for quantifying the robustness of treatment ranks based on Surface Under the Cumulative RAnking curve (SUCRA) in network meta-analysis (NMA) and investigating potential factors associated with lack of robustness.

METHODS

We propose the use of Cohen's kappa to quantify the agreement between SUCRA-based treatment ranks estimated through NMA of a complete data set and a subset of it. We illustrate our approach using five published NMA data sets, where robustness was assessed by removing studies one at a time.

RESULTS

Overall, SUCRA-based treatment ranks were robust to individual studies in the five data sets we considered. We observed more incidences of disagreement between ranks in the networks with larger numbers of treatments. Most treatments moved only one or two ranks up or down. The lowest quadratic weighted kappa estimate observed across all networks was in the network with the smallest number of treatments (4), where weighted kappa=40%. In the network with the largest number of treatments (12), the lowest observed quadratic weighted kappa=89%, reflecting a small shift in this network's treatment ranks overall. Preliminary observations suggest that a study's size, the number of studies making a treatment comparison, and the agreement of a study's estimated treatment effect(s) with those estimated by other studies making the same comparison(s) may explain the overall robustness of treatment ranks to studies.

CONCLUSIONS

Investigating robustness or sensitivity in an NMA may reveal outlying rank changes that are clinically or policy-relevant. Cohen's kappa is a useful measure that permits investigation into study characteristics that may explain varying sensitivity to individual studies. However, this study presents a framework as a proof of concept and further investigation is required to identify potential factors associated with the robustness of treatment ranks using more extensive empirical evaluations.

Bayesian inference for network meta-regression using multivariate random effects with applications to cholesterol lowering drugs

Low-density lipoprotein cholesterol (LDL-C) has been identified as a causative factor for atherosclerosis and related coronary heart disease, and as the main target for cholesterol- and lipid-lowering therapy. Statin drugs inhibit cholesterol synthesis in the liver and are typically the first line of therapy to lower elevated levels of LDL-C. On the other hand, a different drug, Ezetimibe, inhibits the absorption of cholesterol by the small intestine and provides a different mechanism of action. Many clinical trials have been carried out on safety and efficacy evaluation of cholesterol lowering drugs. To synthesize the results from different clinical trials, we examine treatment level (aggregate) network meta-data from 29 double-blind, randomized, active, or placebo-controlled statins +/$-$ Ezetimibe clinical trials on adult treatment-naïve patients with primary hypercholesterolemia. In this article, we propose a new approach to carry out Bayesian inference for arm-based network meta-regression. Specifically, we develop a new strategy of grouping the variances of random effects, in which we first formulate possible sets of the groups of the treatments based on their clinical mechanisms of action and then use Bayesian model comparison criteria to select the best set of groups. The proposed approach is especially useful when some treatment arms are involved in only a single trial. In addition, a Markov chain Monte Carlo sampling algorithm is developed to carry out the posterior computations. In particular, the correlation matrix is generated from its full conditional distribution via partial correlations. The proposed methodology is further applied to analyze the network meta-data from 29 trials with 11 treatment arms.

Effectiveness of stop smoking interventions among adults: protocol for an overview of systematic reviews and an updated systematic review

BACKGROUND

Tobacco smoking is the leading cause of cancer, preventable death, and disability. Smoking cessation can increase life expectancy by nearly a decade if achieved in the third or fourth decades of life. Various stop smoking interventions are available including pharmacotherapies, electronic cigarettes, behavioural support, and alternative therapies. This protocol outlines an evidence review which will evaluate the benefits and harms of stop smoking interventions in adults.

METHODS

The evidence review will consist of two stages. First, an overview of systematic reviews evaluating the benefits and harms of various stop smoking interventions delivered in or referred from the primary care setting will be conducted. The second stage will involve updating a systematic review on electronic cigarettes identified in the overview; randomized controlled trials will be considered for outcomes relating to benefits while randomized controlled trials, non-randomized controlled trials, and comparative observational studies will be considered for evaluating harms. Search strategies will be developed and peer-reviewed by medical information specialists. The search strategy for the updated review on e-cigarettes will be developed using that of the candidate systematic review. The MEDLINE®, PsycINFO, Embase, and the Cochrane Library electronic databases will be searched as of 2008 for the overview of reviews and from the last search date of the selected review for the updated review. Organizational websites and trial registries will be searched for unpublished or ongoing reviews/studies. Two reviewers will independently screen the title and abstracts of citations using the liberal accelerated method. Full-text screening will be performed independently by two reviewers. Extracted data will be verified by a second reviewer. Disagreements regarding full-text screening and data extraction will be resolved by consensus or third-party adjudication. The methodological quality of systematic reviews, risk of bias of randomized and non-randomized trials, and methodological quality of cohort studies will be evaluated using AMSTAR 2, the Cochrane risk of bias tool, and a modified version of the Scottish Intercollegiate Guidelines Network critical appraisal tool, respectively. The GRADE framework will be used to assess the quality of the evidence for outcomes.

DISCUSSION

The evidence review will evaluate the benefits and harms of various stop smoking interventions for adults. Findings will be used to inform a national tobacco cessation guideline by the Canadian Task Force on Preventive Health Care.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO (CRD42018099691, CRD42018099692).

Defining the process to literature searching in systematic reviews: a literature review of guidance and supporting studies

BACKGROUND

Systematic literature searching is recognised as a critical component of the systematic review process. It involves a systematic search for studies and aims for a transparent report of study identification, leaving readers clear about what was done to identify studies, and how the findings of the review are situated in the relevant evidence. Information specialists and review teams appear to work from a shared and tacit model of the literature search process. How this tacit model has developed and evolved is unclear, and it has not been explicitly examined before. The purpose of this review is to determine if a shared model of the literature searching process can be detected across systematic review guidance documents and, if so, how this process is reported in the guidance and supported by published studies.

METHOD

A literature review. Two types of literature were reviewed: guidance and published studies. Nine guidance documents were identified, including: The Cochrane and Campbell Handbooks. Published studies were identified through 'pearl growing', citation chasing, a search of PubMed using the systematic review methods filter, and the authors' topic knowledge. The relevant sections within each guidance document were then read and re-read, with the aim of determining key methodological stages. Methodological stages were identified and defined. This data was reviewed to identify agreements and areas of unique guidance between guidance documents. Consensus across multiple guidance documents was used to inform selection of 'key stages' in the process of literature searching.

RESULTS

Eight key stages were determined relating specifically to literature searching in systematic reviews. They were: who should literature search, aims and purpose of literature searching, preparation, the search strategy, searching databases, supplementary searching, managing references and reporting the search process.

CONCLUSIONS

Eight key stages to the process of literature searching in systematic reviews were identified. These key stages are consistently reported in the nine guidance documents, suggesting consensus on the key stages of literature searching, and therefore the process of literature searching as a whole, in systematic reviews. Further research to determine the suitability of using the same process of literature searching for all types of systematic review is indicated.

Comparison among adjuvant treatments for primary pterygium: a network meta-analysis

PURPOSE

Pterygium is a frequent ocular disease, where the major challenge is the high level of recurrence after its surgical removal. We performed a network meta-analysis to identify, among several adjuvant treatments for primary pterygium, which is the best to prevent recurrence.

METHODS

A search was conducted using PubMed, Scientific Electronic Library Online, Latin American and Caribbean Centre on Health Sciences and Cochrane Eyes and Vision Group Trials Register between 1993 and 2015 for randomisedclinical trials (RCTs) comparing adjuvant treatments following primary pterygium surgery.

RESULTS

24 RCTs that studied 1815 eyes of 1668 patients were included and allowed direct and indirect comparison among 14 interventions through network meta-analysis. The rank from the best to worse treatment to prevent recurrence is: conjunctival autograft + ciclosporin 0.05% eye drops, bare sclera + intraoperativemitomycin C (MMC) <0.02%, bare sclera + beta therapy (2500 cGy single dose), conjunctival autograft + beta therapy (1000 cGy single dose), bare sclera + MMC 0.02% eye drops, conjunctival autograft, bare sclera + intraoperative MMC >0.02%, bare sclera + ciclosporin 0.05% eye drops, bare sclera + intraoperative 5-fluorouracil 5%, amniotic membrane transplantation, bare sclera + intraoperative MMC 0.02%, conjunctival autograft + bevacizumab 0.05% eye drops, bare sclera + bevacizumab 0.05% eye drops and bare sclera alone.

CONCLUSION

The best adjuvant treatment to prevent recurrence after primary pterygium surgery is the association of conjunctival autograft and ciclosporin 0.05% eye drops. Bare sclera technique alone should be discontinued since it is associated with high recurrence rates.

Second-generation drug-eluting stents versus drug-coated balloons for the treatment of coronary in-stent restenosis: A systematic review and meta-analysis

PURPOSE

The benefit of drug-eluting stents (DES) versus drug-coated balloons (DCB) in coronary artery in-stent restenosis (ISR) for the prevention of target lesion revascularization (TLR), stent thrombosis, and mortality remains uncertain. Our aim was to synthesize the available evidence from randomized clinical trials (RCTs) and observational studies that directly compare second-generation drug-eluting stents (SG-DES) and DCB for the treatment of coronary ISR.

METHODS

Medline, Embase, and Cochrane Central were searched for RCTs or observational studies, published up to March 15, 2017. A random effects model meta-analysis investigating clinical and angiographic outcomes was conducted for RCTs and observational studies that compared SG-DES versus DCB for the treatment of ISR.

RESULTS

Ten studies and 2,173 patients were included in this meta-analysis. The two treatment strategies were proven equal with regards to TLR, myocardial infarction, stent thrombosis, and cardiac mortality in both randomized and observational studies. No difference was found among RCTs for all-cause mortality, while in observational studies, patients who were treated with SG-DES had a lower mortality compared to DCB (OR: 0.47; 95% CI: 0.27-0.83). In the pooled analysis also (RCTs and observational studies), SG-DES were associated with lower all-cause mortality compared to DCB. Patients treated with SG-DES were also superior in terms of minimal lumen diameter (standardized mean difference: 0.39; 95% CI: 0.12-0.66).

CONCLUSIONS

The two treatment strategies are equal for the treatment of ISR, while the difference in all-cause mortality might be potentially explained by baseline differences in the two groups among real-world studies.

Bayesian hierarchical models for network meta-analysis incorporating nonignorable missingness

Network meta-analysis expands the scope of a conventional pairwise meta-analysis to simultaneously compare multiple treatments, synthesizing both direct and indirect information and thus strengthening inference. Since most of trials only compare two treatments, a typical data set in a network meta-analysis managed as a trial-by-treatment matrix is extremely sparse, like an incomplete block structure with significant missing data. Zhang et al. proposed an arm-based method accounting for correlations among different treatments within the same trial and assuming that absent arms are missing at random. However, in randomized controlled trials, nonignorable missingness or missingness not at random may occur due to deliberate choices of treatments at the design stage. In addition, those undertaking a network meta-analysis may selectively choose treatments to include in the analysis, which may also lead to missingness not at random. In this paper, we extend our previous work to incorporate missingness not at random using selection models. The proposed method is then applied to two network meta-analyses and evaluated through extensive simulation studies. We also provide comprehensive comparisons of a commonly used contrast-based method and the arm-based method via simulations in a technical appendix under missing completely at random and missing at random.

Common pitfalls and mistakes in the set-up, analysis and interpretation of results in network meta-analysis: what clinicians should look for in a published article

OBJECTIVE

Several tools have been developed to evaluate the extent to which the findings from a network meta-analysis would be valid; however, applying these tools is a time-consuming task and often requires specific expertise. Clinicians have little time for critical appraisal, and they need to understand the key elements that help them select network meta-analyses that deserve further attention, optimising time and resources. This paper is aimed at providing a practical framework to assess the methodological robustness and reliability of results from network meta-analysis.

METHODS

As a working example, we selected a network meta-analysis about drug treatments for generalised anxiety disorder, which was published in 2011 in the British Medical Journal. The same network meta-analysis was previously used to illustrate the potential of this methodology in a methodological paper published in JAMA.

RESULTS

We reanalysed the 27 studies included in this network following the methods reported in the original article and compared our findings with the published results. We showed how different methodological approaches and the presentation of results can affect conclusions from network meta-analysis. We divided our results into three sections, according to the specific issues that should always be addressed in network meta-analysis: (1) understanding the evidence base, (2) checking the statistical analysis and (3) checking the reporting of findings.

CONCLUSIONS

The validity of the results from network meta-analysis depends on the plausibility of the transitivity assumption. The risk of bias introduced by limitations of individual studies must be considered first and judgement should be used to infer about the plausibility of transitivity. Inconsistency exists when treatment effects from direct and indirect evidence are in disagreement. Unlike transitivity, inconsistency can be always evaluated statistically, and it should be specifically investigated and reported in the published paper. Network meta-analysis allows researchers to list treatments in preferential order; however, in this paper we demonstrated that rankings could be misleading if based on the probability of being the best. Clinicians should always be interested in the effect sizes rather than the naive rankings.

Effects of chemopreventive agents on the incidence of recurrent colorectal adenomas: a systematic review with network meta-analysis of randomized controlled trials

BACKGROUND

Protective effects of several chemopreventive agents (CPAs) against colorectal adenomas have been well documented in randomized controlled trials (RCTs); however, there is uncertainty regarding which agents are the most effective.

METHODS

We searched for RCTs published up until September 2016. Retrieved trials were evaluated using risk of bias. We performed both pairwise analysis and network meta-analysis (NMA) of RCTs to compare the effects of CPAs on the recurrence of colorectal adenomas (primary outcome). Using NMA, we ranked CPAs based on efficacy.

RESULTS

We identified 20 eligible RCTs enrolling 12,625 participants with a history of colorectal cancer or adenomas who were randomly assigned to receive either a placebo or one of 12 interventions. NMA using all trials demonstrated that celecoxib 800 mg/day (relative risk [RR] 0.61, 95% confidence interval [CI] 0.45-0.83), celecoxib 400 mg/day (RR 0.70, 95% CI 0.55-0.87), low-dose aspirin (RR 0.75, 95% CI 0.59-0.96) and calcium (RR 0.81, 95% CI 0.69-0.96) were significantly associated with a reduction in the recurrence of any adenomas. NMA results were consistent with those from pairwise meta-analysis. The evidence indicated a high (celecoxib), moderate (low-dose aspirin) and low (calcium) Grading of Recommendations, Assessment, Development and Evaluation (GRADE) quality. NMA ranking showed that celecoxib 800 mg/day and celecoxib 400 mg/day were the best CPAs, followed by low-dose aspirin and calcium. Considering advanced adenoma recurrence, only celecoxib 800 mg/day and celecoxib 400 mg/day were demonstrated to have a protective effect (RR 0.37, 95% CI 0.27-0.52 vs RR 0.48, 95% CI 0.38-0.60, respectively).

CONCLUSION

The available evidence from NMA suggests that celecoxib is more effective in reducing the risk of recurrence of colorectal adenomas, followed by low-dose aspirin and calcium. Since cyclooxygenase-2 (COX-2) inhibitors (eg, celecoxib) are associated with important cardiovascular events and gastrointestinal harms, more attention is warranted toward CPAs with a favorable benefit-to-risk ratio, such as low-dose aspirin and calcium.

Additional considerations are required when preparing a protocol for a systematic review with multiple interventions

OBJECTIVES

The number of systematic reviews that aim to compare multiple interventions using network meta-analysis is increasing. In this study, we highlight aspects of a standard systematic review protocol that may need modification when multiple interventions are to be compared.

STUDY DESIGN AND SETTING

We take the protocol format suggested by Cochrane for a standard systematic review as our reference and compare the considerations for a pairwise review with those required for a valid comparison of multiple interventions. We suggest new sections for protocols of systematic reviews including network meta-analyses with a focus on how to evaluate their assumptions. We provide example text from published protocols to exemplify the considerations.

CONCLUSION

Standard systematic review protocols for pairwise meta-analyses need extensions to accommodate the increased complexity of network meta-analysis. Our suggested modifications are widely applicable to both Cochrane and non-Cochrane systematic reviews involving network meta-analyses.

The Impact of Excluding Trials from Network Meta-Analyses - An Empirical Study

Network meta-analysis (NMA) expands the scope of a conventional pairwise meta-analysis to simultaneously compare multiple treatments, which has an inherent appeal for clinicians, patients, and policy decision makers. Two recent reports have shown that the impact of excluding a treatment on NMAs can be substantial. However, no one has assessed the impact of excluding a trial from NMAs, which is important because many NMAs selectively include trials in the analysis. This article empirically examines the impact of trial exclusion using both the arm-based (AB) and contrast-based (CB) approaches, by reanalyzing 20 published NMAs involving 725 randomized controlled trials and 449,325 patients. For the population-averaged absolute risk estimates using the AB approach, the average fold changes across all networks ranged from 1.004 (with standard deviation 0.004) to 1.072 (with standard deviation 0.184); while the maximal fold changes ranged from 1.032 to 2.349. In 12 out of 20 NMAs, a 1.20-fold or larger change is observed in at least one of the population-averaged absolute risk estimates. In addition, while excluding a trial can substantially change the estimated relative effects (e.g., log odds ratios), there is no systematic difference in terms of changes between the two approaches. Changes in treatment rankings are observed in 7 networks and changes in inconsistency are observed in 3 networks. We do not observe correlations between changes in treatment effects, treatment rankings and inconsistency. Finally, we recommend rigorous inclusion and exclusion criteria, logical study selection process, and reasonable network geometry to ensure robustness and generalizability of the results of NMAs.

Assumptions of Mixed Treatment Comparisons in Health Technology Assessments - Challenges and Possible Steps for Practical Application

The validity of mixed treatment comparisons (MTCs), also called network meta-analysis, relies on whether it is reasonable to accept the underlying assumptions on similarity, homogeneity, and consistency. The aim of this paper is to propose a practicable approach to addressing the underlying assumptions of MTCs. Using data from clinical studies of antidepressants included in a health technology assessment (HTA), we present a stepwise approach to dealing with challenges related to checking the above assumptions and to judging the robustness of the results of an MTC. At each step, studies that were dissimilar or contributed to substantial heterogeneity or inconsistency were excluded from the primary analysis. In a comparison of the MTC estimates from the consistent network with the MTC estimates from the homogeneous network including inconsistencies, few were affected by notable changes; that is, a change in effect size (factor 2), direction of effect or statistical significance. Considering the small proportion of studies excluded from the network due to inconsistency, as well as the number of notable changes, the MTC results were deemed sufficiently robust. In the absence of standard methods, our approach to checking assumptions in MTCs may inform other researchers in need of practical options, particularly in HTA.

Hypoglycaemia when adding sulphonylurea to metformin: a systematic review and network meta-analysis

AIMS

The risk of hypoglycaemia may differ among sulphonylureas (SUs), but evidence from head-to-head comparisons is sparse. Performing a network meta-analysis to use indirect evidence from randomized controlled trials (RCTs), we compared the relative risk of hypoglycaemia with newer generation SUs when added to metformin.

METHODS

A systematic review identified RCTs lasting 12-52 weeks and evaluating SUs added to inadequate metformin monotherapy (≥1000 mg/day) in type 2 diabetes. Adding RCTs investigating the active comparators from the identified SU trials, we established a coherent network. Hypoglycaemia of any severity was the primary end point.

RESULTS

Thirteen trials of SUs and 14 of oral non-SU antihyperglycaemic agents (16 260 patients) were included. All reported hypoglycaemia only as adverse events. Producing comparable reductions in HbA_1C of -0.66 to -0.84% (-7 to -9 mmol/mol), the risk of hypoglycaemia was lowest with gliclazide compared to glipizide (OR 0.22, CrI: 0.05 to 0.96), glimepiride (OR 0.40, CrI: 0.13 to 1.27), and glibenclamide (OR 0.21, CrI: 0.03 to 1.48). A major limitation is varying definitions of hypoglycaemia across studies.

CONCLUSIONS

When added to metformin, gliclazide was associated with the lowest risk of hypoglycaemia between the newer generation SUs. Clinicians should consider the risk of hypoglycaemia agent-specific when selecting an SU agent.

Sensitivity to Excluding Treatments in Network Meta-analysis

Network meta-analysis of randomized controlled trials is increasingly used to combine both direct evidence comparing treatments within trials and indirect evidence comparing treatments across different trials. When the outcome is binary, the commonly used contrast-based network meta-analysis methods focus on relative treatment effects such as odds ratios comparing two treatments. As shown in a recent report, when using contrast-based network meta-analysis, the impact of excluding a treatment in the network can be substantial, suggesting a methodological limitation. In addition, relative treatment effects are sometimes not sufficient for patients to make decisions. For example, it can be challenging for patients to trade off efficacy and safety for two drugs if they only know the relative effects, not the absolute effects. A recently proposed arm-based network meta-analysis, based on a missing-data framework, provides an alternative approach. It focuses on estimating population-averaged treatment-specific absolute effects. This article examines the influence of treatment exclusion empirically using 14 published network meta-analyses, for both arm- and contrast-based approaches. The difference between these two approaches is substantial, and it is almost entirely due to single-arm trials. When a treatment is removed from a contrast-based network meta-analysis, it is necessary to exclude other treatments in two-arm studies that investigated the excluded treatment; such exclusions are not necessary in arm-based network meta-analysis, leading to substantial gain in performance.

Wasted research when systematic reviews fail to provide a complete and up-to-date evidence synthesis: the example of lung cancer

BACKGROUND

Multiple treatments are frequently available for a given condition, and clinicians and patients need a comprehensive, up-to-date synthesis of evidence for all competing treatments. We aimed to quantify the waste of research related to the failure of systematic reviews to provide a complete and up-to-date evidence synthesis over time.

METHODS

We performed a series of systematic overviews and networks of randomized trials assessing the gap between evidence covered by systematic reviews and available trials of second-line treatments for advanced non-small cell lung cancer. We searched the Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, MEDLINE, EMBASE, and other resources sequentially by year from 2009 to March 2, 2015. We sequentially compared the amount of evidence missing from systematic reviews to the randomized evidence available for inclusion each year. We constructed cumulative networks of randomized evidence over time and evaluated the proportion of trials, patients, treatments, and treatment comparisons not covered by systematic reviews on December 31 each year from 2009 to 2015.

RESULTS

We identified 77 trials (28,636 patients) assessing 47 treatments with 54 comparisons and 29 systematic reviews (13 published after 2013). From 2009 to 2015, the evidence covered by existing systematic reviews was consistently incomplete: 45 % to 70 % of trials; 30 % to 58 % of patients; 40 % to 66 % of treatments; and 38 % to 71 % of comparisons were missing. In the cumulative networks of randomized evidence, 10 % to 17 % of treatment comparisons were partially covered by systematic reviews and 55 % to 85 % were partially or not covered.

CONCLUSIONS

We illustrate how systematic reviews of a given condition provide a fragmented, out-of-date panorama of the evidence for all treatments. This waste of research might be reduced by the development of live cumulative network meta-analyses.

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.

Questionable assumptions hampered interpretation of a network meta-analysis of primary care depression treatments

OBJECTIVES

We aimed to evaluate the underlying assumptions of a network meta-analysis investigating which depression treatment works best in primary care and to highlight challenges and pitfalls of interpretation under consideration of these assumptions.

STUDY DESIGN AND SETTING

We reviewed 100 randomized trials investigating pharmacologic and psychological treatments for primary care patients with depression. Network meta-analysis was carried out within a frequentist framework using response to treatment as outcome measure. Transitivity was assessed by epidemiologic judgment based on theoretical and empirical investigation of the distribution of trial characteristics across comparisons. Homogeneity and consistency were investigated by decomposing the Q statistic.

RESULTS

There were important clinical and statistically significant differences between "pure" drug trials comparing pharmacologic substances with each other or placebo (63 trials) and trials including a psychological treatment arm (37 trials). Overall network meta-analysis produced results well comparable with separate meta-analyses of drug trials and psychological trials. Although the homogeneity and consistency assumptions were mostly met, we considered the transitivity assumption unjustifiable.

CONCLUSION

An exchange of experience between reviewers and, if possible, some guidance on how reviewers addressing important clinical questions can proceed in situations where important assumptions for valid network meta-analysis are not met would be desirable.

Ranking treatments in frequentist network meta-analysis works without resampling methods

Background

Network meta-analysis is used to compare three or more treatments for the same condition. Within a Bayesian framework, for each treatment the probability of being best, or, more general, the probability that it has a certain rank can be derived from the posterior distributions of all treatments. The treatments can then be ranked by the surface under the cumulative ranking curve (SUCRA). For comparing treatments in a network meta-analysis, we propose a frequentist analogue to SUCRA which we call P-score that works without resampling.

Methods

P-scores are based solely on the point estimates and standard errors of the frequentist network meta-analysis estimates under normality assumption and can easily be calculated as means of one-sided p-values. They measure the mean extent of certainty that a treatment is better than the competing treatments.

Results

Using case studies of network meta-analysis in diabetes and depression, we demonstrate that the numerical values of SUCRA and P-Score are nearly identical.

Conclusions

Ranking treatments in frequentist network meta-analysis works without resampling. Like the SUCRA values, P-scores induce a ranking of all treatments that mostly follows that of the point estimates, but takes precision into account. However, neither SUCRA nor P-score offer a major advantage compared to looking at credible or confidence intervals.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-015-0060-8) contains supplementary material, which is available to authorized users.

Are current standards of reporting quality for clinical trials sufficient in addressing important sources of bias?

Determining the quality of a randomized clinical trial (RCT) is necessary for decision-makers to determine the believability and applicability of the trial findings. Issues that are likely to affect the utility of RCT evidence include issues of bias, random error and applicability. In this article we focus primarily on issues of bias and examine the evidence for whether reporting methodological items, including allocation concealment, sequence generation, and blinding of participants can be relied upon as evidence of bias. We present the findings of a systematic review of meta-epidemiological studies and a simulation study demonstrating that commonly examined sources of bias likely play little role in treatment exaggeration. We discuss other issues that may additionally influence trial outcomes including sample size, publication bias, and expertise of trialists. We conclude by discussing strategies to moderate the effect of known biases in assessing overall estimates of treatment effects.

Extending Treatment Networks in Health Technology Assessment: How Far Should We Go?

BACKGROUND

Network meta-analysis may require substantially more resources than does a standard systematic review. One frequently asked question is "how far should I extend the network and which treatments should I include?"

OBJECTIVE

To explore the increase in precision from including additional evidence.

METHODS

We assessed the benefit of extending treatment networks in terms of precision of effect estimates and examined how this depends on network structure and relative strength of additional evidence. We introduced a "star"-shaped network. Network complexity is increased by adding more evidence connecting treatments under five evidence scenarios. We also examined the impact of heterogeneity and absence of evidence facilitating a "first-order" indirect comparison.

RESULTS

In all scenarios, extending the network increased the precision of the A versus B treatment effect. Under a fixed-effect model, the increase in precision was modest when the existing direct A versus B evidence was already strong and was substantial when the direct evidence was weak. Under a random-effects model, the gain in precision was lower when heterogeneity was high. When evidence is available for all "first-order" indirect comparisons, including second-order evidence has limited benefit for the precision of the A versus B estimate. This is interpreted as a "ceiling effect."

CONCLUSIONS

Including additional evidence increases the precision of a "focal" treatment comparison of interest. Once the comparison of interest is connected to all others via "first-order" indirect evidence, there is no additional benefit in including higher order comparisons. This conclusion is generalizable to any number of treatment comparisons, which would then all be considered "focal." The increase in precision is modest when direct evidence is already strong, or there is a high degree of heterogeneity.

The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations

The PRISMA statement is a reporting guideline designed to improve the completeness of reporting of systematic reviews and meta-analyses. Authors have used this guideline worldwide to prepare their reviews for publication. In the past, these reports typically compared 2 treatment alternatives. With the evolution of systematic reviews that compare multiple treatments, some of them only indirectly, authors face novel challenges for conducting and reporting their reviews. This extension of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) statement was developed specifically to improve the reporting of systematic reviews incorporating network meta-analyses. A group of experts participated in a systematic review, Delphi survey, and face-to-face discussion and consensus meeting to establish new checklist items for this extension statement. Current PRISMA items were also clarified. A modified, 32-item PRISMA extension checklist was developed to address what the group considered to be immediately relevant to the reporting of network meta-analyses. This document presents the extension and provides examples of good reporting, as well as elaborations regarding the rationale for new checklist items and the modification of previously existing items from the PRISMA statement. It also highlights educational information related to key considerations in the practice of network meta-analysis. The target audience includes authors and readers of network meta-analyses, as well as journal editors and peer reviewers.

Comparative efficacy and safety of antidiabetic drug regimens added to metformin monotherapy in patients with type 2 diabetes: a network meta-analysis

Introduction

When first line therapy with metformin is insufficient for patients with type 2 diabetes (T2D), the optimal adjunctive therapy is unclear. We assessed the efficacy and safety of adjunctive antidiabetic agents in patients with inadequately controlled T2D on metformin alone.

Materials and Methods

A search of MEDLINE and CENTRAL, clinicaltrials.gov, regulatory websites was performed. We included randomized controlled trials of 3–12 months duration, evaluating Food and Drug Administration or European Union approved agents (noninsulin and long acting, once daily basal insulins) in patients experiencing inadequate glycemic control with metformin monotherapy (≥1500 mg daily or maximally tolerated dose for ≥4 weeks). Random-effects network meta-analyses were used to compare the weighted mean difference for changes from baseline in HbA1c, body weight (BW) and systolic blood pressure (SBP), and the risk of developing hypoglycemia, urinary (UTI) and genital tract infection (GTI).

Results

Sixty-two trials evaluating 25 agents were included. All agents significantly reduced HbA1c vs. placebo; albeit not to the same extent (range, 0.43% for miglitol to 1.29% for glibenclamide). Glargine, sulfonylureas (SUs) and nateglinide were associated with increased hypoglycemia risk vs. placebo (range, 4.00–11.67). Sodium glucose cotransporter-2 (SGLT2) inhibitors, glucagon-like peptide-1 analogs, miglitol and empagliflozin/linagliptin significantly reduced BW (range, 1.15–2.26kg) whereas SUs, thiazolindinediones, glargine and alogliptin/pioglitazone caused weight gain (range, 1.19–2.44kg). SGLT2 inhibitors, empagliflozin/linagliptin, liraglutide and sitagliptin decreased SBP (range, 1.88–5.43mmHg). No therapy increased UTI risk vs. placebo; however, SGLT2 inhibitors were associated with an increased risk of GTI (range, 2.16–8.03).

Conclusions

Adding different AHAs to metformin was associated with varying effects on HbA1c, BW, SBP, hypoglycemia, UTI and GTI which should impact clinician choice when selecting adjunctive therapy.

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.