Georgia Salanti

Comparative efficacy and acceptability of 12 new-generation antidepressants: a multiple-treatments meta-analysis

BACKGROUND Conventional meta-analyses have shown inconsistent results for efficacy of second-generation antidepressants. We therefore did a multiple-treatments meta-analysis, which accounts for both direct and indirect comparisons, to assess the effects of 12 new-generation antidepressants on major depression. METHODS We systematically reviewed 117 randomised controlled trials (25 928 participants) from 1991 up to Nov 30, 2007, which compared any of the following antidepressants at therapeutic dose range for the acute treatment of unipolar major depression in adults: bupropion, citalopram, duloxetine, escitalopram, fluoxetine, fluvoxamine, milnacipran, mirtazapine, paroxetine, reboxetine, sertraline, and venlafaxine. The main outcomes were the proportion of patients who responded to or dropped out of the allocated treatment. Analysis was done on an intention-to-treat basis. FINDINGS Mirtazapine, escitalopram, venlafaxine, and sertraline were significantly more efficacious than duloxetine (odds ratios [OR] 1.39, 1.33, 1.30 and 1.27, respectively), fluoxetine (1.37, 1.32, 1.28, and 1.25, respectively), fluvoxamine (1.41, 1.35, 1.30, and 1.27, respectively), paroxetine (1.35, 1.30, 1.27, and 1.22, respectively), and reboxetine (2.03, 1.95, 1.89, and 1.85, respectively). Reboxetine was significantly less efficacious than all the other antidepressants tested. Escitalopram and sertraline showed the best profile of acceptability, leading to significantly fewer discontinuations than did duloxetine, fluvoxamine, paroxetine, reboxetine, and venlafaxine. INTERPRETATION Clinically important differences exist between commonly prescribed antidepressants for both efficacy and acceptability in favour of escitalopram and sertraline. Sertraline might be the best choice when starting treatment for moderate to severe major depression in adults because it has the most favourable balance between benefits, acceptability, and acquisition cost.

Comparative efficacy and tolerability of 15 antipsychotic drugs in schizophrenia: a multiple-treatments meta-analysis

BACKGROUND The question of which antipsychotic drug should be preferred for the treatment of schizophrenia is controversial, and conventional pairwise meta-analyses cannot provide a hierarchy based on the randomised evidence. We aimed to integrate the available evidence to create hierarchies of the comparative efficacy, risk of all-cause discontinuation, and major side-effects of antipsychotic drugs. METHODS We did a Bayesian-framework, multiple-treatments meta-analysis (which uses both direct and indirect comparisons) of randomised controlled trials to compare 15 antipsychotic drugs and placebo in the acute treatment of schizophrenia. We searched the Cochrane Schizophrenia Groups specialised register, Medline, Embase, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov for reports published up to Sept 1, 2012. Search results were supplemented by reports from the US Food and Drug Administration website and by data requested from pharmaceutical companies. Blinded, randomised controlled trials of patients with schizophrenia or related disorders were eligible. We excluded trials done in patients with predominant negative symptoms, concomitant medical illness, or treatment resistance, and those done in stable patients. Data for seven outcomes were independently extracted by two reviewers. The primary outcome was efficacy, as measured by mean overall change in symptoms. We also examined all-cause discontinuation, weight gain, extrapyramidal side-effects, prolactin increase, QTc prolongation, and sedation. FINDINGS We identified 212 suitable trials, with data for 43 049 participants. All drugs were significantly more effective than placebo. The standardised mean differences with 95% credible intervals were: clozapine 0·88, 0·73-1·03; amisulpride 0·66, 0·53-0·78; olanzapine 0·59, 0·53-0·65; risperidone 0·56, 0·50-0·63; paliperidone 0·50, 0·39-0·60; zotepine 0·49, 0·31-0·66; haloperidol 0·45, 0·39-0·51; quetiapine 0·44, 0·35-0·52; aripiprazole 0·43, 0·34-0·52; sertindole 0·39, 0·26-0·52; ziprasidone 0·39, 0·30-0·49; chlorpromazine 0·38, 0·23-0·54; asenapine 0·38, 0·25-0·51; lurasidone 0·33, 0·21-0·45; and iloperidone 0·33, 0·22-0·43. Odds ratios compared with placebo for all-cause discontinuation ranged from 0·43 for the best drug (amisulpride) to 0·80 for the worst drug (haloperidol); for extrapyramidal side-effects 0·30 (clozapine) to 4·76 (haloperidol); and for sedation 1·42 (amisulpride) to 8·82 (clozapine). Standardised mean differences compared with placebo for weight gain varied from -0·09 for the best drug (haloperidol) to -0·74 for the worst drug (olanzapine), for prolactin increase 0·22 (aripiprazole) to -1·30 (paliperidone), and for QTc prolongation 0·10 (lurasidone) to -0·90 (sertindole). Efficacy outcomes did not change substantially after removal of placebo or haloperidol groups, or when dose, percentage of withdrawals, extent of blinding, pharmaceutical industry sponsorship, study duration, chronicity, and year of publication were accounted for in meta-regressions and sensitivity analyses. INTERPRETATION Antipsychotics differed substantially in side-effects, and small but robust differences were seen in efficacy. Our findings challenge the straightforward classification of antipsychotics into first-generation and second-generation groupings. Rather, hierarchies in the different domains should help clinicians to adapt the choice of antipsychotic drug to the needs of individual patients. These findings should be considered by mental health policy makers and in the revision of clinical practice guidelines. FUNDING None.

Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial

OBJECTIVE To present some simple graphical and quantitative ways to assist interpretation and improve presentation of results from multiple-treatment meta-analysis (MTM). STUDY DESIGN AND SETTING We reanalyze a published network of trials comparing various antiplatelet interventions regarding the incidence of serious vascular events using Bayesian approaches for random effects MTM, and we explore the advantages and drawbacks of various traditional and new forms of quantitative displays and graphical presentations of results. RESULTS We present the results under various forms, conventionally based on the mean of the distribution of the effect sizes; based on predictions; based on ranking probabilities; and finally, based on probabilities to be within an acceptable range from a reference. We show how to obtain and present results on ranking of all treatments and how to appraise the overall ranks. CONCLUSIONS Bayesian methodology offers a multitude of ways to present results from MTM models, as it enables a natural and easy estimation of all measures based on probabilities, ranks, or predictions.

Evaluation of networks of randomized trials

Randomized trials may be designed and interpreted as single experiments or they may be seen in the context of other similar or relevant evidence. The amount and complexity of available randomized evidence vary for different topics. Systematic reviews may be useful in identifying gaps in the existing randomized evidence, pointing to discrepancies between trials, and planning future trials. A new, promising, but also very much debated extension of systematic reviews, mixed treatment comparison (MTC) meta-analysis, has become increasingly popular recently. MTC meta-analysis may have value in interpreting the available randomized evidence from networks of trials and can rank many different treatments, going beyond focusing on simple pairwise-comparisons. Nevertheless, the evaluation of networks also presents special challenges and caveats. In this article, we review the statistical methodology for MTC meta-analysis. We discuss the concept of inconsistency and methods that have been proposed to evaluate it as well as the methodological gaps that remain. We introduce the concepts of network geometry and asymmetry, and propose metrics for the evaluation of the asymmetry. Finally, we discuss the implications of inconsistency, network geometry and asymmetry in informing the planning of future trials.

Graphical Tools for Network Meta-Analysis in STATA

Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results.

Indirect and mixed‐treatment comparison, network, or multiple‐treatments meta‐analysis: many names, many benefits, many concerns for the next generation evidence synthesis tool

The ever increasing number of alternative treatment options and the plethora of clinical trials have put systematic reviews and meta-analysis under a new perspective by emphasizing the need to make inferences about competing treatments for the same condition. The statistical component in reviews that compare multiple interventions, network meta-analysis, is the next generation evidence synthesis toolkit which, when properly applied, can serve decision-making better than the established pairwise meta-analysis. The criticism and enthusiasm for network meta-analysis echo those that greeted the advent of simple meta-analysis. The main criticism is associated with the difficulty in evaluating the assumption underlying the statistical synthesis of direct and indirect evidence. In the present article, the assumption of the network meta-analysis are presented using various formulations, the statistical and nonstatistical methodological considerations are elucidated, and the progress achieved in this field is summarized. Throughout, focus is put on highlighting the analogy between the concerns and difficulties that the scientific community had some time ago when advancing from individual trials to their quantitative synthesis via meta-analysis and those currently expressed about the transition from head-to-head meta-analyses to network meta-analysis. Copyright

Antipsychotic drugs versus placebo for relapse prevention in schizophrenia: a systematic review and meta-analysis

BACKGROUND Relapse prevention with antipsychotic drugs compared with placebo in patients with schizophrenia has not been sufficiently addressed by previous systematic reviews. We aimed to assess the association between such drugs and various outcomes in patients with schizophrenia to resolve controversial issues. METHODS We searched the Cochrane Schizophrenia Groups specialised register for reports published before Nov 11, 2008; and PubMed, Embase, and ClinicalTrials.gov for those before June 8, 2011. We also contacted pharmaceutical companies and searched the reference lists of included studies and previous reviews. Randomised trials of patients with schizophrenia continued on or withdrawn from any antipsychotic drug regimen after stabilisation were eligible. Our primary outcome was relapse between 7 and 12 months. We also examined safety and various functional outcomes. We used the random effects model and verified results for the primary outcome with a fixed effects model. Heterogeneity was investigated with subgroup and meta-regression analyses. FINDINGS We identified 116 suitable reports from 65 trials, with data for 6493 patients. Antipsychotic drugs significantly reduced relapse rates at 1 year (drugs 27%vs placebo 64%; risk ratio [RR] 0·40, 95% CI 0·33-0·49; number needed to treat to benefit [NNTB] 3, 95% CI 2-3). Fewer patients given antipsychotic drugs than placebo were readmitted (10%vs 26%; RR 0·38, 95% CI 0·27-0·55; NNTB 5, 4-9), but less than a third of relapsed patients had to be admitted. Limited evidence suggested better quality of life (standardised mean difference -0·62, 95% CI -1·15 to -0·09) and fewer aggressive acts (2%vs 12%; RR 0·27, 95% CI 0·15-0·52; NNTB 11, 6-100) with antipsychotic drugs than with placebo. Employment data were scarce and too few deaths were reported to allow significant differences to be identified. More patients given antipsychotic drugs than placebo gained weight (10%vs 6%; RR 2·07, 95% CI 2·31-3·25), had movement disorders (16%vs 9%; 1·55, 1·25-1·93), and experienced sedation (13%vs 9%; 1·50, 1·22-1·84). Substantial heterogeneity in size of effect was recorded. In subgroup analyses, number of episodes, whether patients were in remission, abrupt or gradual withdrawal of treatment, length of stability before trial entry, first-generation or second-generation drugs, and allocation concealment method did not significantly affect relapse risk. Depot preparations reduced relapse (RR 0·31, 95% CI 0·21-0·41) more than did oral drugs (0·46, 0·37-0·57; p=0·03); depot haloperidol (RR 0·14, 95% CI 0·04-0·55) and fluphenazine (0·23, 0·14-0·39) had the greatest effects. The effects of antipsychotic drugs were greater in two unblinded trials (0·26, 0·17-0·39) than in most blinded studies (0·42, 0·35-0·51; p= 0·03). In a meta-regression, the difference between drug and placebo decreased with study length. INTERPRETATION Maintenance treatment with antipsychotic drugs benefits patients with schizophrenia. The advantages of these drugs must be weighed against their side-effects. Future studies should focus on outcomes of social participation and clarify the long-term morbidity and mortality of these drugs. FUNDING German Ministry of Education and Research.

Comparative efficacy and acceptability of antimanic drugs in acute mania: a multiple-treatments meta-analysis

BACKGROUND Conventional meta-analyses have shown inconsistent results for efficacy of pharmacological treatments for acute mania. We did a multiple-treatments meta-analysis, which accounted for both direct and indirect comparisons, to assess the effects of all antimanic drugs. METHODS We systematically reviewed 68 randomised controlled trials (16,073 participants) from Jan 1, 1980, to Nov 25, 2010, which compared any of the following pharmacological drugs at therapeutic dose range for the treatment of acute mania in adults: aripiprazole, asenapine, carbamazepine, valproate, gabapentin, haloperidol, lamotrigine, lithium, olanzapine, quetiapine, risperidone, topiramate, and ziprasidone. The main outcomes were the mean change on mania rating scales and the number of patients who dropped out of the allocated treatment at 3 weeks. Analysis was done by intention to treat. FINDINGS Haloperidol (standardised mean difference [SMD] -0·56 [95% CI -0·69 to -0·43]), risperidone (-0·50 [-0·63 to -0·38), olanzapine (-0·43 [-0·54 to -0·32], lithium (-0·37 [-0·63 to -0·11]), quetiapine (-0·37 [-0·51 to -0·23]), aripiprazole (-0·37 [-0·51 to -0·23]), carbamazepine (-0·36 [-0·60 to -0·11], asenapine (-0·30 [-0·53 to -0·07]), valproate (-0·20 [-0·37 to -0·04]), and ziprasidone (-0·20 [-0·37 to -0·03]) were significantly more effective than placebo, whereas gabapentin, lamotrigine, and topiramate were not. Haloperidol had the highest number of significant differences and was significantly more effective than lithium (SMD -0·19 [95% CI -0·36 to -0·01]), quetiapine (-0·19 [-0·37 to 0·01]), aripiprazole (-0·19 [-0·36 to -0·02]), carbamazepine (-0·20 [-0·36 to -0·01]), asenapine (-0·26 [-0·52 to 0·01]), valproate (-0·36 [-0·56 to -0·15]), ziprasidone -0·36 [-0·56 to -0·15]), lamotrigine (-0·48 [-0·77 to -0·19]), topiramate (-0·63 [-0·84 to -0·43]), and gabapentin (-0·88 [-1·40 to -0·36]). Risperidone and olanzapine had a very similar profile of comparative efficacy, being more effective than valproate, ziprasidone, lamotrigine, topiramate, and gabapentin. Olanzapine, risperidone, and quetiapine led to significantly fewer discontinuations than did lithium, lamotrigine, placebo, topiramate, and gabapentin. INTERPRETATION Overall, antipsychotic drugs were significantly more effective than mood stabilisers. Risperidone, olanzapine, and haloperidol should be considered as among the best of the available options for the treatment of manic episodes. These results should be considered in the development of clinical practice guidelines. FUNDING None.

Conceptual and Technical Challenges in Network Meta-analysis

The increase in treatment options creates an urgent need for comparative effectiveness research. Randomized, controlled trials comparing several treatments are usually not feasible, so other methodological approaches are needed. Meta-analyses provide summary estimates of treatment effects by combining data from many studies. However, an important drawback is that standard meta-analyses can compare only 2 interventions at a time. A new meta-analytic technique, called network meta-analysis (or multiple treatments meta-analysis or mixed-treatment comparison), allows assessment of the relative effectiveness of several interventions, synthesizing evidence across a network of randomized trials. Despite the growing prevalence and influence of network meta-analysis in many fields of medicine, several issues need to be addressed when constructing one to avoid conclusions that are inaccurate, invalid, or not clearly justified. This article explores the scope and limitations of network meta-analysis and offers advice on dealing with heterogeneity, inconsistency, and potential sources of bias in the available evidence to increase awareness among physicians about some of the challenges in interpretation.

Hardy–Weinberg equilibrium in genetic association studies: an empirical evaluation of reporting, deviations, and power

We evaluated the testing and reporting of Hardy–Weinberg equilibrium (HWE) in recent genetic association studies, detected how frequently HWE was violated and estimated the power for HWE testing in this literature. Genetic association studies published in 2002 in Nature Genetics, American Journal of Human Genetics, and American Journal of Medical Genetics were assessed. Data were analyzed on 239 biallelic associations using 154 distinct genotype distribution data sets where HWE could be tested. Any information on HWE was given only for 150 (62.8%) associations (92 (59.7%) data sets). Reanalysis of the data showed significant deviation from HWE in the disease-free controls of 20 associations (13 data sets), but only four of them (two data sets) were admitted in the published articles. Another four deviations (in two data sets) were observed in the combined sample of cases and controls of studies where both cases and controls were diseased, and none were reported in the papers. In all six tested multiallelic associations (six data sets), there was violation of HWE, but this was not admitted in the published articles. Power calculations showed that most studies conforming to HWE simply were largely underpowered to detect HWE deviation; for example, power to detect an inbreeding of magnitude F=0.10 exceeded 80% in only 11 (7%) of the data sets being tested. This empirical evidence suggests that, even in high profile genetics journals, testing and reporting for HWE is often neglected and deviations are rarely admitted in the published reports. Moreover, power is limited for HWE testing in most current genetic association studies.