Stopping rules and estimation problems in clinical trials
ABSTRACT Stopping rules in clinical trials can lead to bias in point estimation of the magnitude of treatment difference. A simulation exercise, based on estimation of the risk ratio in a typical post-myocardial infarction trial, examines the nature of this exaggeration of treatment effect under various group sequential plans and also under continuous naive monitoring for statistical significance. For a fixed treatment effect the median bias in group sequential design is small, but it is greatest for effects that the trial has reasonable power to detect. Bias is evidently greater in trials that stop early and is dramatic under naive monitoring for significance. Group sequential plans lead to a multimodal sampling distribution of treatment effect, which poses problems for incorporating their estimates into meta-analyses. By simulating a population of trials with treatment effects modelled by an underlying distribution of true risk ratios, a Bayesian method is proposed for assessing the plausible range of true treatment effect for any trial based on interim results. This approach is particularly useful for producing shrinkage of the unexpectedly large and imprecise observed treatment effects that arise in clinical trials that stop early. Its implications for trial design are discussed.
Article: Recursive Cumulative Meta-analysis[Show abstract] [Hide abstract]
ABSTRACT: Meta-analyses of randomized evidence may include published, unpublished, and updated data in an ongoing estimation process that continuously accommodates more data. Synthesis may be performed either with group data or with meta-analysis of individual patient data (MIPD). Although MIPD with updated data is considered the gold standard of evidence, there is a need for a careful study of the impact different sources of data have on a meta-analysis and of the change in the treatment effect estimates over sequential information steps. Unpublished data and late-appearing data may be different from early-appearing data. Updated information after the end of the main study follow-up may be affected by cross-overs, missing information, and unblinding. The estimated treatment effect may thus depend on the completeness and updating of the available evidence. To address these issues, we present recursive cumulative meta-analysis (RCM) as an extension of cumulative meta-analysis. Recursive cumulative meta-analysis is based on the principle of recalculating the results of a cumulative meta-analysis with each new or updated piece of information and focuses on the evolution of the treatment effect as a more complete and updated picture of the evidence becomes available. An examination of the perturbations of the cumulative treatment effect over sequential information steps may signal the presence of bias or heterogeneity in a meta-analysis. Recursive cumulative meta-analysis may suggest whether there is a true underlying treatment effect to which the meta-analysis is converging and how treatment effects are sequentially altered by new or modified evidence. The method is illustrated with an example from the conduct of an MIPD on acyclovir in human immunodeficiency virus infection. The relative strengths and limitations of both meta-analysis of group data and MIPD are discussed through the RCM perspective.Journal of Clinical Epidemiology 04/1999; 52(4):281-291. DOI:10.1016/S0895-4356(98)00159-0 · 5.48 Impact Factor
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ABSTRACT: Li3V2(PO4)3/C cathode material is synthesized by a carbon-thermal reduction method using polyvinyl alcohol as carbon source at 700°C. The Li3V2(PO4)3/C electrode presents a high initial discharge capacity of 84.3, 111.1, 128.7, 129.2 and 132.1mAhg−1 at −20, 0, 25, 40 and 65°C between 3.0 and 4.3V, and 118.9, 132.1, 187.6, 180.3 and 172.2mAhg−1 between 3.0 and 4.8V at 0.1C, respectively. However, the electrode only delivers small discharge capacities at −20°C at 10C rate. The capacity fade at low temperatures is mainly attributed to the reduced ionic and electronic conductivity of the electrolyte, the increased impendence of solid electrolyte interface (SEI) and charge-transfer resistance on the electrolyte–electrode interfaces. At higher temperatures, the capacity increases with increasing temperature between 3.0 and 4.3V, but decreases between 3.0 and 4.8V. In the potential range of 3.0–4.8V, the larger crystal structural distortion and non-uniformity of SEI layer at high temperatures may be the main reasons for the capacity loss.Journal of Power Sources 02/2012; 199. DOI:10.1016/j.jpowsour.2011.10.054 · 5.21 Impact Factor
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ABSTRACT: Group sequential tests have been widely used to control the type I error rate at a prespecified level in comparative clinical trials. It is well known that due to the optional sampling effect, conventional maximum likelihood estimates will exaggerate the treatment difference, and hence a bias is introduced. We consider a group sequentially monitored Brownian motion process. An analytical expression of the bias of the maximum likelihood estimate for the Brownian motion drift is derived based on the alpha spending method of Lan and DeMets (1983). Through this formula, the bias can be evaluated exactly by numerical integration. We study how the Brownian motion drift and various alpha spending functions and interim analysis patterns affect the bias. A bias adjusted estimator is described and its properties are investigated. The behavior of this estimator is studied for differing situations.Statistica Sinica 01/1999; 9(4). · 1.23 Impact Factor