Sample sizes for the SF-6D preference based measure of health from the SF-36: a practical guide

Background Health Related Quality of Life (HRQoL) measures are becoming more frequently used in clinical trials and health services research, both as primary and secondary endpoints. Investigators are now asking statisticians for advice on how to plan and analyse studies using HRQoL measures, which includes questions on sample size. Sample size requirements are critically dependent on the aims of the study, the outcome measure and its summary measure, the effect size and the method of calculating the test statistic. The SF-6D is a new single summary preference-based measure of health derived from the SF-36 suitable for use clinical trials and in the economic evaluation of health technologies. Objectives To describe and compare two methods of calculating sample sizes when using the SF-6D in comparative clinical trials and to give pragmatic guidance to researchers on what method to use. Methods We describe two main methods of sample size estimation. The parametric (t-test) method assumes the SF-6D data is continuous and normally distributed and that the effect size is the difference between two means. The non-parametric (Mann-Whitney MW) method assumes the data are continuous and not normally distributed and the effect size is defined in terms of the probability that an observation drawn at random from population Y would exceed an observation drawn at random from population X. We used bootstrap computer simulation to compare the power of the two methods for detecting a shift in location. Results This paper describes the SF-6D and retrospectively calculated parametric and nonparametric effect sizes for the SF-6D from a variety of studies that had previously used the SF-36. Computer simulation suggested that if the distribution of the SF-6D is reasonably symmetric then the t-test appears to be more powerful than the MW test at detecting differences in means. Therefore if the distribution of the SF-6D is symmetric or expected to be reasonably symmetric then parametric methods should be used for sample size calculations and analysis. If the distribution of the SF-6D is skewed then the MW test appears to be more powerful at detecting a location shift (difference in means) than the t-test. However, the differences in power (between the t and MW tests) are small and decrease as the sample size increases. Conclusions We have provided a clear description of the distribution of the SF-6D and believe that the mean is an appropriate summary measure for the SF-6D when it is to be used in clinical trials and the economic evaluation of new health technologies. Therefore pragmatically we would recommend that parametric methods be used for sample size calculation and analysis when using the SF-6D.sample size; health-related quality of life; SF-36; preference-based measures of health; bootstrap simulation

Sample sizes for the SF-6D preference based measure of health from the SF-36: a practical guide

Background Health Related Quality of Life (HRQoL) measures are becoming more frequently used in clinical trials and health services research, both as primary and secondary endpoints. Investigators are now asking statisticians for advice on how to plan and analyse studies using HRQoL measures, which includes questions on sample size. Sample size requirements are critically dependent on the aims of the study, the outcome measure and its summary measure, the effect size and the method of calculating the test statistic. The SF-6D is a new single summary preference-based measure of health derived from the SF-36 suitable for use clinical trials and in the economic evaluation of health technologies. Objectives To describe and compare two methods of calculating sample sizes when using the SF-6D in comparative clinical trials and to give pragmatic guidance to researchers on what method to use. Methods We describe two main methods of sample size estimation. The parametric (t-test) method assumes the SF-6D data is continuous and normally distributed and that the effect size is the difference between two means. The non-parametric (Mann-Whitney MW) method assumes the data are continuous and not normally distributed and the effect size is defined in terms of the probability that an observation drawn at random from population Y would exceed an observation drawn at random from population X. We used bootstrap computer simulation to compare the power of the two methods for detecting a shift in location. Results This paper describes the SF-6D and retrospectively calculated parametric and nonparametric effect sizes for the SF-6D from a variety of studies that had previously used the SF-36. Computer simulation suggested that if the distribution of the SF-6D is reasonably symmetric then the t-test appears to be more powerful than the MW test at detecting differences in means. Therefore if the distribution of the SF-6D is symmetric or expected to be reasonably symmetric then parametric methods should be used for sample size calculations and analysis. If the distribution of the SF-6D is skewed then the MW test appears to be more powerful at detecting a location shift (difference in means) than the t-test. However, the differences in power (between the t and MW tests) are small and decrease as the sample size increases. Conclusions We have provided a clear description of the distribution of the SF-6D and believe that the mean is an appropriate summary measure for the SF-6D when it is to be used in clinical trials and the economic evaluation of new health technologies. Therefore pragmatically we would recommend that parametric methods be used for sample size calculation and analysis when using the SF-6D

Using MCDA to generate and interpret evidence to inform local government investment in public health

Smoking is the single biggest cause of preventable death in the Uited Kingdom (UK) and is a major cause of coronary heart disease, some cancers, and respiratory disease, including chronic obstructive pulmonary disease. At the time of initiating the project, smoking prevalence had not changed across four local government areas in South Yorkshire for some years. Most spending had been focussed on helping people quit, an intervention where there was clear evidence of effectiveness. A number of changes occurred in public health structures and targets, requiring a reappraisal of the range of interventions offered. This was challenging due to a lack of clear evidence for some of the areas’ alternative interventions. The aim of this paper is to describe the use of a multi-criteria decision analysis (MCDA) approach to support the health priority setting in local authorities to reduce smoking prevalence. There were three phases to this process: (1) problem structuring; (2) the multiple criteria decision analysis; (3) and using the MCDA results to influence decision making at the local government level. The MCDA approach was used to collate information in a consistent and transparent manner, using expert, stakeholder and public opinion to fill known gaps in evidence. Fifteen interventions (such as stop smoking support services, smoke-free spaces, communication and marketing exercises, and increased investment in enforcement) were ranked across eight criteria (relating to reductions in prevalence across relevant groups, as well as aspects relating to equity and feasibility), allowing a range of relevant concerns to be incorporated. Subsequent steps were taken to translate the results of this stage into workable policy options. The results differed significantly from current practice. Sensitivity analysis showed that the findings were robust to changes in preference weights. These results informed subsequent changes to the interventions offered across the four boroughs. The ability of MCDA techniques to incorporate data and both qualitative and quantitative judgements in a formal manner mean that they are well suited to support public health decision making, where evidence is often only partially available and many policies are value driven. MCDA methods, if used, should be chosen carefully based on their resource/time constraints, scientific validity, and the significance and broader context of the decision problem.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s40070-016-0059-

EQ-5D in skin conditions: an assessment of validity and responsiveness

Aims and objectives This systematic literature review aims to assess the reliability, validity and responsiveness of three widely used generic preference-based measures of health-related quality of life (HRQL), i.e., EQ-5D, Health Utility Index 3 (HUI3) and SF-6D in patients with skin conditions. Methods A systematic search was conducted to identify studies reporting health state utility values obtained using EQ-5D, SF-6D, or HUI3 alongside other HRQL measures or clinical indices for patients with skin conditions. Data on test-retest analysis for reliability, known group differences or correlation and regression analyses for validity, and change over time or responsiveness indices analysis were extracted and reviewed. Results A total of 16 papers reporting EQ-5D utilities in people with skin conditions were included in the final review. No papers for SF-6D and HUI3 were found. Evidence of reliability was not found for any of these measures. The majority of studies included in the review (12 out of 16) examined patients with plaque psoriasis or psoriatic arthritis and the remaining four studies examined patients with either acne, hidradenitis suppurativa, hand eczema, or venous leg ulcers. The findings were generally positive in terms of performance of EQ-5D. Six studies showed that EQ-5D was able to reflect differences between severity groups and only one reported differences that were not statistically significant. Four studies found that EQ-5D detected differences between patients and the general population, and differences were statistically different for three of them. Further, moderate-to-strong correlation coefficients were found between EQ-5D and other skin-specific HRQL measures in four studies. Eight studies showed that EQ-5D was able to detect change in HRQL appropriately over time and the changes were statistically significant in seven studies. Conclusions Overall, the validity and responsiveness of the EQ-5D was found to be good in people with skin diseases, especially plaque psoriasis or psoriatic arthritis. No evidence on SF-6D and HUI3 was available to enable any judgments to be made on their performance

Effects of acute fatigue on the volitional and magnetically-evoked electromechanical delay of the knee flexors in males and females

Neuromuscular performance capabilities, including those measured by evoked responses, may be adversely affected by fatigue; however, the capability of the neuromuscular system to initiate muscle force rapidly under these circumstances is yet to be established. Sex-differences in the acute responses of neuromuscular performance to exercise stress may be linked to evidence that females are much more vulnerable to ACL injury than males. Optimal functioning of the knee flexors is paramount to the dynamic stabilisation of the knee joint, therefore the aim of this investigation was to examine the effects of acute maximal intensity fatiguing exercise on the voluntary and magnetically-evoked electromechanical delay in the knee flexors of males and females. Knee flexor volitional and magnetically-evoked neuromuscular performance was assessed in seven male and nine females prior to and immediately after: (i) an intervention condition comprising a fatigue trial of 30-seconds maximal static exercise of the knee flexors, (ii) a control condition consisting of no exercise. The results showed that the fatigue intervention was associated with a substantive reduction in volitional peak force (PFV) that was greater in males compared to females (15.0%, 10.2%, respectively, p < 0.01) and impairment to volitional electromechanical delay (EMDV) in females exclusively (19.3%, p < 0.05). Similar improvements in magnetically-evoked electromechanical delay in males and females following fatigue (21%, p < 0.001), however, may suggest a vital facilitatory mechanism to overcome the effects of impaired voluntary capabilities, and a faster neuromuscular response that can be deployed during critical times to protect the joint system

Astrobiological Complexity with Probabilistic Cellular Automata

Search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous input parameters' space. We perform a simple clustering analysis of typical astrobiological histories and discuss the relevant boundary conditions of practical importance for planning and guiding actual empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.Comment: 37 pages, 11 figures, 2 tables; added journal reference belo

Progression criteria in trials with an internal pilot : an audit of publicly funded randomised controlled trials

Background With millions of pounds spent annually on medical research in the UK, it is important that studies are spending funds wisely. Internal pilots offer the chance to stop a trial early if it becomes apparent that the study will not be able to recruit enough patients to show whether an intervention is clinically effective. This study aims to assess the use of internal pilots in individually randomised controlled trials funded by the Health Technology Assessment (HTA) programme and to summarise the progression criteria chosen in these trials. Methods Studies were identified from reports of the HTA committees’ funding decisions from 2012 to 2016. In total, 242 trials were identified of which 134 were eligible to be included in the audit. Protocols for the eligible studies were located on the NIHR Journals website, and if protocols were not available online then study managers were contacted to provide information. Results Over two-thirds (72.4%) of studies said in their protocol that they would include an internal pilot phase for their study and 37.8% of studies without an internal pilot had done an external pilot study to assess the feasibility of the full study. A typical study with an internal pilot has a target sample size of 510 over 24 months and aims to recruit one-fifth of their total target sample size within the first one-third of their recruitment time. There has been an increase in studies adopting a three-tiered structure for their progression rules in recent years, with 61.5% (16/26) of studies using the system in 2016 compared to just 11.8% (2/17) in 2015. There was also a rise in the number of studies giving a target recruitment rate in their progression criteria: 42.3% (11/26) in 2016 compared to 35.3% (6/17) in 2015. Conclusions Progression criteria for an internal pilot are usually well specified but targets vary widely. For the actual criteria, red/amber/green systems have increased in popularity in recent years. Trials should justify the targets they have set, especially where targets are low