Systematic reviews as a tool for planning and interpreting trials

Background Systematic reviews followed by ameta-analysis are carried out in medical research to combine the results of two or more related studies. Stroke trials have struggled to show beneficial effects and meta-analysis should be used more widely throughout the research process to either speed up the development of useful interventions, or halt more quickly research with hazardous or ineffective interventions. Summary of review. This review summarises the clinical research process and illustrates how and when systematic reviews may be used throughout the development programme. Meta-analyses should be performed after observational studies, preclinical studies in experimental stroke, and after phase I, II, and III clinical trials and phase IV clinical surveillance studies. Although meta-analyses most commonly work with summary data, they may be performed to assess relationships between variables (meta-regression) and, ideally, should utilise individual patient data. Meta-analysis techniques may alsoworkwith ordered categorical outcome data (ordinal meta-analysis) and be used to perform indirect comparisons where original trial data do not exist. Conclusion Systematic review/meta-analyses are powerful tools in medical research and should be used throughout the development of all stroke and other interventions

Development of a cargo screening process simulator: a first approach

The efficiency of current cargo screening processes at sea and air ports is largely unknown as few benchmarks exists against which they could be measured. Some manufacturers provide benchmarks for individual sensors but we found no benchmarks that take a holistic view of the overall screening procedures and no benchmarks that take operator variability into account. Just adding up resources and manpower used is not an effective way for assessing systems where human decision-making and operator compliance to rules play a vital role. Our aim is to develop a decision support tool (cargo-screening system simulator) that will map the right technology and manpower to the right commodity-threat combination in order to maximise detection rates. In this paper we present our ideas for developing such a system and highlight the research challenges we have identified. Then we introduce our first case study and report on the progress we have made so far.