PubMed · 12073695
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John Hampton. 2002. Statins for all?. https://pubmed.ncbi.nlm.nih.gov/12073695/
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An increase in the uptake of long-chain Omega-3 fatty acids from fish with the diet or as ethyl esters resulted in a decreased risk for cardiac death. As mechanism for this rapidly occurring benefit (within 90 days of treatment significantly different to placebo) antiarrhythmic effects at cardiac myocytes and plaques stabilization can be discussed. The results of the GISSI Prevenzione Trial show that 175 patients have to be treated for one year to avoid one death. Regarding other available data for secondary prevention this efficacy is superior to pravastatin and at the same level as simvastatin or aspirin. Only beta-blocking agents are superior, but it is of interest that long-chain Omega-3 fatty acids from fish display their beneficial effects even in patients already treated with beta-blockers. As the intake of 0.85 g of long-chain Omega-3 fatty acids from fish per day can be regarded as save and the positive effect on total mortality occurs already after 90 days their regular use is a promising additional measure for secondary prevention.
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Evaluation of the performance of a new diagnostic procedure with respect to a standard procedure arises frequently in practice. The response of interest, often in a dichotomous form, is measured twice, once with each procedure. The two procedures are administered to either two matched individuals, or when practical, to the same individual. A large sample test for matched-pair data is the McNemar test. The main assumption of this test is independent paired responses; however, when more than one outcome from an individual is measured by each procedure, the data are clustered. Examples of such cases can be seen in dental and ophthalmology studies. Variance adjustment methods for the analysis of clustered matched-pair data have been proposed; however, because of unequal cluster sizes, variability of correlation structures within a cluster (within paired responses in a cluster as well as between paired responses in a cluster), and unequal success probabilities among the clusters, the performances of some available methods are not consistent. This research proposes a simple adjustment to the McNemar test for the analysis of clustered matched-pair data. Method of moments is used to calculate a consistent variance estimator. Using Monte Carlo simulation, the size and power of the proposed test are compared to those of two currently available methods. To illustrate practical application, clustered matched-pair data from two clinical studies are analysed.