<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
AbstractClinical trials of new drugs in the treatment of angina pectoris frequently make use of exercise tests to evaluate efficacy. The crossover design is often employed. The methods commonly used to analyse the various exercise times, for example, ‘time to pain’, are insensitive and potentially biased by the manner in which they deal with the censored nature of the data. Survival analysis can be adapted for use in crossover trials, both in a relatively simple way, and also through the full power of the Cox model. This is considerably more sensitive and not subject to the same bias. This methodology leads to the use of median survival times to illustrate treatment effects and this provides a practical interpretation of clinical relevance. The estimation of median survival times in crossover trials poses some special problems. The methodology is illustrated throughout by means of a specific two‐period example in which atenolol was compared with the combination of atenolol and nifedipine. The three‐period design is also briefly discussed.
Analysis of Variance, Clinical Trials as Topic, Time Factors, Nifedipine, Sensitivity and Specificity, Survival Analysis, Angina Pectoris, Electrocardiography, Atenolol, Bias, Research Design, Data Interpretation, Statistical, Confidence Intervals, Exercise Test, Humans, Drug Therapy, Combination, Mathematical Computing, Monitoring, Physiologic, Proportional Hazards Models
Analysis of Variance, Clinical Trials as Topic, Time Factors, Nifedipine, Sensitivity and Specificity, Survival Analysis, Angina Pectoris, Electrocardiography, Atenolol, Bias, Research Design, Data Interpretation, Statistical, Confidence Intervals, Exercise Test, Humans, Drug Therapy, Combination, Mathematical Computing, Monitoring, Physiologic, Proportional Hazards Models
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 38 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |