Dimitris Mavridis

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.

OBJECTIVE: Antipsychotic drug efficacy may have decreased over recent decades. The authors present a meta-analysis of all placebo-controlled trials in patients with acute exacerbations of schizophrenia, and they investigate which trial characteristics have changed over the years and which are moderators of drug-placebo efficacy differences. METHOD: The search included multiple electronic databases. The outcomes were overall efficacy (primary outcome); responder and dropout rates; positive, negative, and depressive symptoms; quality of life; functioning; and major side effects. Potential moderators of efficacy were analyzed by meta-regression. RESULTS: The analysis included 167 double-blind randomized controlled trials with 28,102 mainly chronic participants. The standardized mean difference (SMD) for overall efficacy was 0.47 (95% credible interval 0.42, 0.51), but accounting for small-trial effects and publication bias reduced the SMD to 0.38. At least a "minimal" response occurred in 51% of the antipsychotic group versus 30% in the placebo group, and 23% versus 14% had a "good" response. Positive symptoms (SMD 0.45) improved more than negative symptoms (SMD 0.35) and depression (SMD 0.27). Quality of life (SMD 0.35) and functioning (SMD 0.34) improved even in the short term. Antipsychotics differed substantially in side effects. Of the response predictors analyzed, 16 trial characteristics changed over the decades. However, in a multivariable meta-regression, only industry sponsorship and increasing placebo response were significant moderators of effect sizes. Drug response remained stable over time. CONCLUSIONS: Approximately twice as many patients improved with antipsychotics as with placebo, but only a minority experienced a good response. Effect sizes were reduced by industry sponsorship and increasing placebo response, not decreasing drug response. Drug development may benefit from smaller samples but better-selected patients.

IMPORTANCE: Numerous glucose-lowering drugs are used to treat type 2 diabetes. OBJECTIVE: To estimate the relative efficacy and safety associated with glucose-lowering drugs including insulin. DATA SOURCES: Cochrane Library Central Register of Controlled Trials, MEDLINE, and EMBASE databases through March 21, 2016. STUDY SELECTION: Randomized clinical trials of 24 weeks' or longer duration. DATA EXTRACTION AND SYNTHESIS: Random-effects network meta-analysis. MAIN OUTCOMES AND MEASURES: The primary outcome was cardiovascular mortality. Secondary outcomes included all-cause mortality, serious adverse events, myocardial infarction, stroke, hemoglobin A1c (HbA1C) level, treatment failure (rescue treatment or lack of efficacy), hypoglycemia, and body weight. RESULTS: A total of 301 clinical trials (1,417,367 patient-months) were included; 177 trials (56,598 patients) of drugs given as monotherapy; 109 trials (53,030 patients) of drugs added to metformin (dual therapy); and 29 trials (10,598 patients) of drugs added to metformin and sulfonylurea (triple therapy). There were no significant differences in associations between any drug class as monotherapy, dual therapy, or triple therapy with odds of cardiovascular or all-cause mortality. Compared with metformin, sulfonylurea (standardized mean difference [SMD], 0.18 [95% CI, 0.01 to 0.34]), thiazolidinedione (SMD, 0.16 [95% CI, 0.00 to 0.31]), DPP-4 inhibitor (SMD, 0.33 [95% CI, 0.13 to 0.52]), and α-glucosidase inhibitor (SMD, 0.35 [95% CI, 0.12 to 0.58]) monotherapy were associated with higher HbA1C levels. Sulfonylurea (odds ratio [OR], 3.13 [95% CI, 2.39 to 4.12]; risk difference [RD], 10% [95% CI, 7% to 13%]) and basal insulin (OR, 17.9 [95% CI, 1.97 to 162]; RD, 10% [95% CI, 0.08% to 20%]) were associated with greatest odds of hypoglycemia. When added to metformin, drugs were associated with similar HbA1C levels, while SGLT-2 inhibitors offered the lowest odds of hypoglycemia (OR, 0.12 [95% CI, 0.08 to 0.18]; RD, -22% [-27% to -18%]). When added to metformin and sulfonylurea, GLP-1 receptor agonists were associated with the lowest odds of hypoglycemia (OR, 0.60 [95% CI, 0.39 to 0.94]; RD, -10% [95% CI, -18% to -2%]). CONCLUSIONS AND RELEVANCE: Among adults with type 2 diabetes, there were no significant differences in the associations between any of 9 available classes of glucose-lowering drugs (alone or in combination) and the risk of cardiovascular or all-cause mortality. Metformin was associated with lower or no significant difference in HbA1C levels compared with any other drug classes. All drugs were estimated to be effective when added to metformin. These findings are consistent with American Diabetes Association recommendations for using metformin monotherapy as initial treatment for patients with type 2 diabetes and selection of additional therapies based on patient-specific considerations.