Biostatistics for the interventionist

Summary

This chapter will address some of the fundamental statistical issues that arise in the analysis of cardiovascular clinical trials. Examples from recently published cardiovascular clinical trials are presented throughout to illustrate the statistical issues covered.

Most clinical trials are interested in assessing the efficacy of a new treatment versus some standard treatment or placebo. Three key questions arise: (i) is the new treatment more effective than the comparator? (ii) if yes, how much more effective? and (iii) how confident can we be in our estimate of effectiveness? These three questions correspond to the subjects of significance testing, effect estimation and confidence intervals, respectively. In this chapter we will cover the interpretation of p-values and their link to confidence intervals, and consider both relative (e.g., risk ratio) and absolute (e.g., difference in risk) measures of treatment effect.

The appropriate statistical test or method of analysis to be used is principally determined by the design, in particular the nature of the outcome of interest. Three types of trial outcome are covered in this chapter: binary (e.g., dead or alive at one-year); time-to-event (e.g., time to hospitalisation) and quantitative (e.g., in-stent stenosis [mm]).

We also cover statistical issues relating to the analysis...