The value of information and optimal clinical trial design.

Traditional sample size calculations for randomized clinical trials depend on somewhat arbitrarily chosen factors, such as type I and II errors. Type I error, the probability of rejecting the null hypothesis of no difference when it is true, is most often set to 0.05, regardless of the cost of such an error. In addition, the traditional use of 0.2 for the type II error means that the money and effort spent on the trial will be wasted 20 per cent of the time, even when the true treatment difference is equal to the smallest clinically important one and, again, will not reflect the cost of making such an error. An effectiveness trial (otherwise known as a pragmatic trial or management trial) is essentially an effort to inform decision-making, i.e. should treatment be adopted over standard? As such, a decision theoretic approach will lead to an optimal sample size determination. Using incremental net benefit and the theory of the expected value of information, and taking a societal perspective, it is shown how to determine the sample size that maximizes the difference between the cost of doing the trial and the value of the information gained from the results. The methods are illustrated using examples from oncology and obstetrics.

Cost-effectiveness analysis for multinational clinical trials.

Clinical trials of cost-effectiveness are often conducted in more than one country. The two most common ways of dealing with the multinational nature of the data are either to calculate a pooled estimate or to stratify results by country. Since the between-country heterogeneity in costs is potentially substantial, pooled estimates may be difficult to interpret for any one country. Policy decisions are often made at a national level, and so country-specific results are important. However, country-specific analyses will be based on fewer patients and will often fail to provide adequate precision for statistical analyses. Shrinkage estimation is a compromise between these two methods and has been used successfully in other fields. These estimates are country-specific yet less variable than those derived through a subgroup approach. Univariate and multivariate shrinkage estimators for costs and effects are proposed, then compared with one another and to the traditional methods in a simulation study. The methods are illustrated using data from a multinational trial evaluating the cost-effectiveness of three thrombolytic drug regimens in patients with acute myocardial infarction.

Country specific cost comparisons from multinational clinical trials using empirical Bayesian shrinkage estimation: the Canadian ASSENT-3 economic analysis.

The growing number of multinational clinical trials in which patient-level health care resource data are collected have raised the issue of which is the best approach for making inference for individual countries with respect to the between-treatment difference in mean cost. We describe and discuss the relative merits of three approaches. The first uses the random effects pooled estimate from all countries to estimate the difference for any particular country. The second approach estimates the difference using only the data from the specific country in question. Using empirical Bayes estimation a third approach estimates the country-specific difference using a variance-weighted linear sum of the estimates provided by the other two approaches. The approaches are illustrated and compared using the data from the ASSENT-3 trial.

Neutrophil counts, monocyte counts and cardiovascular disease in the elderly.

BACKGROUND: Previous studies have reported on the association between white blood cell counts, in particular monocytes, and cardiovascular disease, but have predominantly been conducted on middle-aged men. We examined whether this association is sustained in an elderly population-based sample. METHODS: Two samples of individuals aged 65 years and older living in Cambridge and Nottingham were recruited from the Medical Research Council Cognitive Function and Ageing Study (MRC CFAS). Venepuncture was undertaken in 1046 individuals, excluding only those who had probable dementia or were physically frail. Monocyte, neutrophil, lymphocyte, eosinophil and basophil counts were analysed for possible associations with history of cardiovascular disease. RESULTS: We found that monocyte and neutrophil counts were both significantly associated with history of cardiovascular disease, with respective odds ratios of 1.48 (95% CI 1.22-1.79) and of 1.44 (95% CI 1.19-1.75) per count tertile. These relationships remained significant on adjusting for age, sex, smoking and body mass index. We found no evidence of association between lymphocyte, eosinophil or basophil counts and history of cardiovascular disease. CONCLUSIONS: Monocyte and neutrophil counts are both associated with cardiovascular disease in a relatively healthy elderly population.

Survival in a population sample is predicted by proportions of lymphocyte subsets.

Comparisons of lymphocyte subsets show that the ratio of CD4 to CD8 is usually greater than one. Inversion of this ratio was found to predict survival in a Swedish octogenarian sample (n=27 deaths), although individual lymphocyte subsets did not predict survival. We have examined these relationships in a larger sample (n=153 deaths). Inversion of the CD4 to CD8 ratio was present in 16% of the sample and predicted survival when adjusted for age but not when adjusted for sex. For individual lymphocyte subsets, higher CD4 and CD19 percentages were associated with better survival, but only the CD19 percentage remained significant when adjusted for age and sex.