Practical guide to sample size calculations: superiority trials

A sample size justification is a vital part of any investigation. However, estimating the number of participants required to give meaningful results is not always straightforward. A number of components are required to facilitate a suitable sample size calculation. In this paper, the steps for conducting sample size calculations for superiority trials are summarised. Practical advice and examples are provided illustrating how to carry out the calculations by hand and using the app SampSize

Baseline geochemical characteristics of urban areas : a record of environmental change in the English Midlands

Systematic baseline sampling of soils in urban and rural areas has been undertaken by the British Geological Survey’s (BGS) Geochemical Baseline Survey of the Environment (G-BASE). Using these urban and rural data in conjunction with each other provides a more powerful, and useful, interpretation of urban soil quality data to be made

Completion plan for the Geochemical Baseline Survey of the Environment (G-BASE)

In response to NERC national capability (NC) prioritisation which seeks to end systematic regional geochemical mapping, this report contains options and recommendations for the completion of a national geochemical baseline by the G-BASE project by 31st March 2016. The plan delivers samples and analyses from southern England, an area estimated to be 35,500 km2, approximately 7,000 km2 of which is underlain by Chalk (and so would be unsuitable for drainage sampling). A number of options for completing a national geochemical baseline are presented based on the current G-BASE strategy but with an overall reduced sampling density. The Panalytical arrangement for XRFS analysis until January 2016 substantially reduces the analytical budget required, and is therefore a most important criterion of the completion plan. However, the Panalytical deal should not be the sole factor that drives the strategy for finishing off G-BASE. In order to maximise the science and opportunities for collaborative research secondary options are proposed for the collection of a variety of sample media from areas of greatest environmental interest. These secondary options will require additional funding to complete the non-XRFS analyses of samples which could include contributions from external organisations. The proposed work plan is primarily concerned with the “observe and monitor” part of NERC national capability. It excludes any proposal for the data interpretation, modelling and knowledge exchange, and adding value to current geochemical baseline tasks (e.g. London Earth and Clyde Basin) or anything beyond the data gathering phase of completing the geochemical mapping of southern England. It is important that the completion plan does not drive the BGS geochemistry activity into just a sample and data gathering exercise. We must continue to deliver science and information outcomes alongside completing the G-BASE baseline or we will lose the capacity to deliver any science in the future

Practical guide to sample size calculations: non-inferiority and equivalence trials

A sample size justification is a vital part of any trial design. However, estimating the number of participants required to give a meaningful result is not always straightforward. A number of components are required to facilitate a suitable sample size calculation. In this paper, the steps for conducting sample size calculations for non-inferiority and equivalence trials are summarised. Practical advice and examples are provided that illustrate how to carry out the calculations by hand and using the app SampSize

How can health economics be used in the design and analysis of adaptive clinical trials? A qualitative analysis

Introduction Adaptive designs offer a flexible approach, allowing changes to a trial based on examinations of the data as it progresses. Adaptive clinical trials are becoming a popular choice, as the prudent use of finite research budgets and accurate decision-making are priorities for healthcare providers around the world. The methods of health economics, which aim to maximise the health gained for money spent, could be incorporated into the design and analysis of adaptive clinical trials to make them more efficient. We aimed to understand the perspectives of stakeholders in health technology assessments to inform recommendations for the use of health economics in adaptive clinical trials. Methods A qualitative study explored the attitudes of key stakeholders—including researchers, decision-makers and members of the public—towards the use of health economics in the design and analysis of adaptive clinical trials. Data were collected using interviews and focus groups (29 participants). A framework analysis was used to identify themes in the transcripts. Results It was considered that answering the clinical research question should be the priority in a clinical trial, notwithstanding the importance of cost-effectiveness for decision-making. Concerns raised by participants included handling the volatile nature of cost data at interim analyses; implementing this approach in global trials; resourcing adaptive trials which are designed and adapted based on health economic outcomes; and training stakeholders in these methods so that they can be implemented and appropriately interpreted. Conclusion The use of health economics in the design and analysis of adaptive clinical trials has the potential to increase the efficiency of health technology assessments worldwide. Recommendations are made concerning the development of methods allowing the use of health economics in adaptive clinical trials, and suggestions are given to facilitate their implementation in practice

Can emergency medicine research benefit from adaptive design clinical trials?

Background: Adaptive design clinical trials use preplanned interim analyses to determine whether studies should be stopped or modified before recruitment is complete. Emergency medicine trials are well suited to these designs as many have a short time to primary outcome relative to the length of recruitment. We hypothesised that the majority of published emergency medicine trials have the potential to use a simple adaptive trial design. Methods: We reviewed clinical trials published in three emergency medicine journals between January 2003 and December 2013. We determined the proportion that used an adaptive design as well as the proportion that could have used a simple adaptive design based on the time to primary outcome and length of recruitment. Results: Only 19 of 188 trials included in the review were considered to have used an adaptive trial design. A total of 154/165 trials that were fixed in design had the potential to use an adaptive design. Conclusions: Currently, there seems to be limited uptake in the use of adaptive trial designs in emergency medicine despite their potential benefits to save time and resources. Failing to take advantage of adaptive designs could be costly to patients and research. It is recommended that where practical and logistical considerations allow, adaptive designs should be used for all emergency medicine clinical trials

Metformin in polycystic ovary syndrome: systematic review and meta-analysis

The original publication may be found at www.bmj.comObjective To assess the effectiveness of metformin in improving clinical and biochemical features of polycystic ovary syndrome. Design Systematic review and meta-analysis. Data sources Randomised controlled trials that investigated the effect of metformin compared with either placebo or no treatment, or compared with an ovulation induction agent. Selection of studies 13 trials were included for analysis, including 543 women with polycystic ovary syndrome that was defined by using biochemical or ultrasound evidence. Main outcome measure Pregnancy and ovulation rates. Secondary outcomes of clinical and biochemical features of polycystic ovary syndrome. Results Meta-analysis showed that metformin is effective in achieving ovulation in women with polycystic ovary syndrome, with odds ratios of 3.88 (95% confidence interval 2.25 to 6.69) for metformin compared with placebo and 4.41 (2.37 to 8.22) for metformin and clomifene compared with clomifene alone. An analysis of pregnancy rates shows a significant treatment effect for metformin and clomifene (odds ratio 4.40, 1.96 to 9.85). Metformin has an effect in reducing fasting insulin concentrations, blood pressure, and low density lipoprotein cholesterol. We found no evidence of any effect on body mass index or waist:hip ratio. Metformin was associated with a higher incidence of nausea, vomiting, and other gastrointestinal disturbance. Conclusions Metformin is an effective treatment for anovulation in women with polycystic ovary syndrome. Its choice as a first line agent seems justified, and there is some evidence of benefit on variables of the metabolic syndrome. No data are available regarding the safety of metformin in long term use in young women and only limited data on its safety in early pregnancy. It should be used as an adjuvant to general lifestyle improvements and not as a replacement for increased exercise and improved diet.Jonathan M Lord, Ingrid H K Flight, Robert J Norma

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