PubMed · 15207138
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V Piñol, M Pagès, F Rodríguez-Moranta, A Castells. [Virtual colonoscopy].. https://doi.org/10.1016/s0210-5705(03)70479-8
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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.
The systematic review community has become increasingly aware of the importance of addressing the issues of heterogeneity and publication bias in meta-analyses. A potentially bigger threat to the validity of a meta-analysis appears relatively unnoticed. The within-study selective reporting of outcomes, defined as the selection of a subset of the original variables recorded for inclusion in publication of trials, can theoretically have a substantial impact on the results. A cohort of meta-analyses on the Cochrane Library was reviewed to examine how often this form of within-study publication bias was suspected and explained some of the evident funnel plot asymmetry. In cases where the level of suspicion was high, sensitivity analysis was undertaken to assess the robustness of the conclusion to this bias. Although within-study selection was evident or suspected in several trials, the impact on the conclusions of the meta-analyses was minimal. This paper deals with the identification of, sensitivity analysis for, and impact of within-study selective reporting in meta-analysis.
A clinical trial is considered in which two treatments with binary responses are to be compared. A popular sequential stopping rule, the triangular test, is studied when various response-adaptive treatment allocation rules are applied, such as the recently proposed drop-the-loser rule, an urn randomization scheme. The paper extends previous work by Coad and Rosenberger, who combined the triangular test with the randomized play-the-winner rule. The purpose of the paper is to investigate to what extent the variability of an adaptive design affects the overall performance of the triangular test. The adaptive rules under consideration are described and some of their asymptotic properties are summarized. Simulation is then used to assess the performance of the triangular test when combined with the various adaptive rules. The main finding is that the drop-the-loser rule is the most promising of the adaptive rules considered in terms of a less variable allocation proportion and a smaller number of treatment failures. The use of this rule with the triangular test is beneficial compared with the triangular test with equal allocation, since it yields fewer treatment failures on average while providing comparable power with similar expected sample size. The results of an AIDS trial are used to illustrate the performance of the triangular test when combined with the drop-the-loser rule.