• All women should be able to access advice on how they can optimise their menopause transition and the years beyond.

As more complex meta-analytical techniques such as network and multivariate meta-analyses become increasingly common, further pressures are placed on reviewers to extract data in a systematic and consistent manner. Failing to do this appropriately wastes time, resources and jeopardises accuracy. This guide (data extraction for complex meta-analysis (DECiMAL)) suggests a number of points to consider when collecting data, primarily aimed at systematic reviewers preparing data for meta-analysis. Network meta-analysis (NMA), multiple outcomes analysis and analysis combining different types of data are considered in a manner that can be useful across a range of data collection programmes. The guide has been shown to be both easy to learn and useful in a small pilot study.Electronic supplementary materialThe online version of this article (doi:10.1186/s13643-016-0368-4) contains supplementary material, which is available to authorized users.

Which treatment best relieves menopause flushes? Results from the #NICE guideline network meta-analysis.

Background Model‐based meta‐analysis (MBMA) is increasingly used to inform drug‐development decisions by synthesising results from multiple studies to estimate treatment, dose‐response, and time‐course characteristics. Network meta‐analysis (NMA) is used in Health Technology Appraisals for simultaneously comparing effects of multiple treatments, to inform reimbursement decisions. Recently, a framework for dose‐response model‐based network meta‐analysis (MBNMA) has been proposed that combines, often nonlinear, MBMA modelling with the statistically robust properties of NMA. Here, we aim to extend this framework to time‐course models. Methods We propose a Bayesian time‐course MBNMA modelling framework for continuous summary outcomes that allows for nonlinear modelling of multiparameter time‐course functions, accounts for residual correlation between observations, preserves randomisation by modelling relative effects, and allows for testing of inconsistency between direct and indirect evidence on the time‐course parameters. We demonstrate our modelling framework using an illustrative dataset of 23 trials investigating treatments for pain in osteoarthritis. Results Of the time‐course functions that we explored, the Emax model gave the best fit to the data and has biological plausibility. Some simplifying assumptions were needed to identify the ET50, due to few observations at early follow‐up times. Treatment estimates were robust to the inclusion of correlations in the likelihood. Conclusions Time‐course MBNMA provides a statistically robust framework for synthesising evidence on multiple treatments at multiple time points. The use of placebo‐controlled studies in drug‐development means there is limited potential for inconsistency. The methods can inform drug‐development decisions and provide the rigour needed in the reimbursement decision‐making process.

L acunar strokes are small subcortical strokes caused by occlusion of single penetrating arteries. Although thromboembolism is a common cause of large artery stroke, the lacunar hypothesis, 1 much debated, 2,3 proposes that key mechanisms in lacunar pathology are microatheroma and lipohyalinosis, and that thromboembolic lacunar stroke is uncommon. 4 Microatheroma are lipid-containing plaques, which are thought to accumulate in the parent main intracranial artery, such as the middle cerebral artery, and affect the origin of penetrating arteries, or develop in the proximal-penetrating arterioles themselves. Lipohyalinosis is a small-vessel pathology characterized by abnormal endothelial architecture and fibrosis, leading to thickening of the vessel wall and irregular luminal diameter. 5 Despite associations with inflammatory endothelial dysfunction and blood-brain barrier disruption, 3,6,7 the causes of these small-vessel changes are poorly understood.Around 25% of all ischemic strokes are lacunar, 8 and although they have an apparently good functional prognosis compared with cortical ischemic stroke, similar proportions of patients have poststroke cognitive impairment and long-term studies suggest that they identify cerebral small vessel disease (SVD), which puts patients at high risk of recurrent ischemic strokes 9 and of cognitive decline. 10,11However, there is incomplete understanding of the precise mechanisms that lead to the pathology described above, and current therapeutic strategies are limited. This occurs against a background of translational failure, where many interventions reported to improve outcome in animal models of ischemic stroke more generally are not effective in human clinical trial. 12 It may be that animal models do not model human disease with sufficient validity to guide drug development; or that they do have this external validity but their conduct and reporting make them a poor guide, in practice, to support clinical drug development and trial design. For several animal models of neurological disease, systematic review and meta-analysis Background and Purpose-A total of 25% of strokes are lacunar, and these are pathophysiologically different from large artery strokes. Despite emerging evidence of a substantial impact on physical disability and dementia, little attention has been paid to the development of specific treatments. The optimal use of the animal models of lacunar stroke used to test candidate interventions is not known. Methods-We conducted a systematic review and meta-analysis of studies testing candidate interventions in animal models of lacunar stroke. We used random-effects meta-analysis to assess the impact of study characteristics and trim and fill to seek evidence of publication bias. Results-The efficacy of 43 distinct interventions was described in 57 publications. The median number of quality checklist items scored was 3 of 8 (interquartile range, 2-4). Many models reflected mechanisms of limited relevance to lacunar stroke. Meta-analysis of results from 27 s...

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