Comparison of Bayesian and frequentist group-sequential clinical trial designs

Background: There is a growing interest in the use of Bayesian adaptive designs in late-phase clinical trials. This includes the use of stopping rules based on Bayesian analyses in which the frequentist type I error rate is controlled as in frequentist group-sequential designs. Methods: This paper presents a practical comparison of Bayesian and frequentist group-sequential tests. Focussing on the setting in which data can be summarised by normally distributed test statistics, we evaluate and compare boundary values and operating characteristics. Results: Although Bayesian and frequentist group-sequential approaches are based on fundamentally different paradigms, in a single arm trial or two-arm comparative trial with a prior distribution specified for the treatment difference, Bayesian and frequentist group-sequential tests can have identical stopping rules if particular critical values with which the posterior probability is compared or particular spending function values are chosen. If the Bayesian critical values at different looks are restricted to be equal, O’Brien and Fleming’s design corresponds to a Bayesian design with an exceptionally informative negative prior, Pocock’s design to a Bayesian design with a non-informative prior and frequentist designs with a linear alpha spending function are very similar to Bayesian designs with slightly informative priors. This contrasts with the setting of a comparative trial with independent prior distributions specified for treatment effects in different groups. In this case Bayesian and frequentist group-sequential tests cannot have the same stopping rule as the Bayesian stopping rule depends on the observed means in the two groups and not just on their difference. In this setting the Bayesian test can only be guaranteed to control the type I error for a specified range of values of the control group treatment effect. Conclusions: Comparison of frequentist and Bayesian designs can encourage careful thought about design parameters and help to ensure appropriate design choices are made

Uniformly minimum variance conditionally unbiased estimation in multi-arm multi-stage clinical trials

Multi-arm multi-stage clinical trials compare several experimental treatments with a control treatment, with poorly performing treatments dropped at interim analyses. This leads to inferential challenges, including the construction of unbiased treatment effect estimators. A number of estimators unbiased conditional on treatment selection have been proposed, but are specific to certain selection rules, may ignore the comparison to the control and are not all minimum variance. We obtain estimators for treatment effects compared to the control that are uniformly minimum variance unbiased conditional on selection with any specified rule or stopping for futility

Emergency nurse practitioners and doctors consulting with patients in an emergency department : a comparison of communication skills and satisfaction

Background: Emergency nurse practitioners (ENPs) play an increasingly important role in UK emergency departments (EDs), but there is limited evidence about how this affects patient care and outcome. A study was undertaken to compare the content of, and satisfaction with, consultations made with patients presenting with problems of low acuity to an ED. Methods: Patients presenting with "primary care" problems were allocated to senior house officers (SHOs, n = 10), specialist registrars/staff grades (n = 7), sessionally-employed general practitioners (GPs, n = 12) or ENPs (n = 6) randomly rostered to work in a consulting room that had a wall-mounted video camera. At the end of each consultation the doctor/ENP and the patient were asked to complete the Physician/Patient Satisfaction Questionnaire. A stratified sample of videotaped consultations (n = 296) was analysed in depth using the Roter Interaction Analysis System. The main outcome measures were length of consultation; numbers of utterances of doctor/ENP and patient talk related to building a relationship, data gathering, activating/partnering, and patient education/counselling; doctor/ENP and patient consultation satisfaction scores. Results: ENPs and GPs focused more on patient education and counselling about the medical condition or therapeutic regimen than did ED doctors. There were no significant differences in consultation length. ENPs had higher levels of overall self-satisfaction with their consultations than ED doctors. Patient satisfaction with how actively they participated in the consultation was significantly associated with the amount of talk relating to building a relationship and activating and partnering, and patient satisfaction with information giving in the consultation was significantly associated with the amount of talk relating to building a relationship. Conclusion: These findings suggest differences between ENP and ED doctor consultations which are associated with some aspects of patient satisfaction. In contrast to previous reports, consultation length was not greater for ENPs than for doctors. There is a need for further research to test the generalisability of these findings and their impact on clinical outcome

A comparison of methods for treatment selection in seamless phase II/III clinical trials incorporating information on short-term endpoints

In an adaptive seamless phase II/III clinical trial interim analysis data are used for treatment selection, enabling resources to be focussed on comparison of more effective treatment(s) with a control. In this paper we compare two methods recently proposed to enable use of short-term endpoint data for decision-making at the interim analysis. The comparison focusses on the power and the probability of correctly identifying the most promising treatment. We show that the choice of method depends on how well short-term data predict the best treatment, which may be measured by the correlation between treatment effects on short-term and long-term endpoints

Spatial analysis of risk factors for childhood morbidity in Nigeria

Recent Demographic and Health Surveys (DHS) from Sub-Saharan Africa (SSA) indicate a decline in childhood vaccination coverage but a high prevalence of childhood diarrhea, cough, and fever. We used Nigerian DHS data to investigate the impact of geographical factors and other important risk factors on diarrhea, cough, and fever using geoadditive Bayesian semiparametric models. A higher prevalence of childhood diarrhea, cough, and fever is observed in the northern and eastern states, while lower disease prevalence is observed in the western and southern states. In addition, children from mothers with higher levels of education and those from poor households had a significantly lower association with diarrhea; children delivered in hospitals, living in urban areas, or from mothers having received prenatal visits had a significantly lower association with fever. Our maps are a novel and relevant tool to help local governments to improve health-care interventions and achieve Millennium Development Goals (MDG4)

Morbidity from diarrhoea, cough and fever among young children in Nigeria

Diarrhoea, cough and fever are the leading causes of childhood morbidity and mortality in sub-Saharan Africa. Despite it being a determinant of mortality in many developing countries, geographical location has seldom been considered as an explanatory factor for the large regional variations seen in the childhood morbidity attributed to these causes in this area. The relevant data collected in two Nigerian Demographic and Health Surveys, one in 1999 and the other in 2003, have now therefore been analysed and compared. The aim was to reveal and explore inequalities in the health of Nigerian children by mapping the spatial distribution of childhood morbidity associated with recent diarrhoea, cough and fever and accounting for important risk factors, using a Bayesian geo-additive model based on Markov-chain–Monte-Carlo techniques. Although the overall prevalences of recent diarrhoea, cough and fever recorded in 1999 (among children aged ,3 years) were similar to those seen in 2003 (among children aged ,5 years), the mapping of residual spatial effects indicated that, in each survey, the morbidity attributable to each of these causes varied, differently, at state level. Place of birth (hospital v. other), type of feeding (breastfed only v. other), parental education, maternal visits to antenatal clinics, household economic status, marital status of mother and place of residence were each significantly associated with the childhood morbidity investigated. In both surveys, children from urban areas were found to have a significantly lower risk of fever than their rural counterparts. Most other factors affecting diarrhoea, cough and fever differed in the two surveys. The risk of developing each of these three conditions increased in the first 6–8 months after birth but then gradually declined. The analysis explained a significant share of the pronounced residual spatial effects. Maps showing the prevalences of diarrhoea, cough and fever in young children across Nigeria were generated during this study. Such maps should facilitate the development of policies to fulfil the Millennium Development Goals in Nigeria and throughout sub-Saharan Africa

Directions for new developments on statistical design and analysis of small population group trials

Most statistical design and analysis methods for clinical trials have been developed and evaluated where at least several hundreds of patients could be recruited. These methods may not be suitable to evaluate therapies if the sample size is unavoidably small, which is usually termed by small populations. The specific sample size cut off, where the standard methods fail, needs to be investigated. In this paper, the authors present their view on new developments for design and analysis of clinical trials in small population groups, where conventional statistical methods may be inappropriate, e.g., because of lack of power or poor adherence to asymptotic approximations due to sample size restrictions

Estimation after subpopulation selection in adaptive seamless trials

During the development of new therapies, it is not uncommon to test whether a new treatment works better than the existing treatment for all patients who suffer from a condition (full population) or for a subset of the full population (subpopulation). One approach that may be used for this objective is to have two separate trials, where in the first trial, data are collected to determine if the new treatment benefits the full population or the subpopulation. The second trial is a confirmatory trial to test the new treatment in the population selected in the first trial. In this paper, we consider the more efficient two-stage adaptive seamless designs (ASDs), where in stage 1, data are collected to select the population to test in stage 2. In stage 2, additional data are collected to perform confirmatory analysis for the selected population. Unlike the approach that uses two separate trials, for ASDs, stage 1 data are also used in the confirmatory analysis. Although ASDs are efficient, using stage 1 data both for selection and confirmatory analysis introduces selection bias and consequently statistical challenges in making inference. We will focus on point estimation for such trials. In this paper, we describe the extent of bias for estimators that ignore multiple hypotheses and selecting the population that is most likely to give positive trial results based on observed stage 1 data. We then derive conditionally unbiased estimators and examine their mean squared errors for different scenarios

A statistical evaluation of the effects of gender differences in assessment of acute inhalation toxicity

Acute inhalation toxicity of chemicals has conventionally been assessed by the median lethal concentration (LC50) test (organisation for economic co-operation and development (OECD) TG 403). Two new methods, the recently adopted acute toxic class method (ATC; OECD TG 436) and a proposed fixed concentration procedure (FCP), have recently been considered, but statistical evaluations of these methods did not investigate the influence of differential sensitivity between male and female rats on the outcomes. This paper presents an analysis of data from the assessment of acute inhalation toxicity for 56 substances. Statistically significant differences between the LC50 for males and females were found for 16 substances, with greater than 10-fold differences in the LC50 for two substances. The paper also reports a statistical evaluation of the three test methods in the presence of unanticipated gender differences. With TG 403, a gender difference leads to a slightly greater chance of under-classification. This is also the case for the ATC method, but more pronounced than for TG 403, with misclassification of nearly all substances from Globally Harmonised System (GHS) class 3 into class 4. As the FCP uses females only, if females are more sensitive, the classification is unchanged. If males are more sensitive, the procedure may lead to under-classification. Additional research on modification of the FCP is thus proposed