Clinical trials analysis

Time is a critical measure for clinical trial analysis. Time is captured in clinical trial databases in a study day variable. Study day can be defined as the number of days from therapeutic intervention to any given time point or event. By defining study day, you create a common metric for measuring time across a population of patients in a clinical trial. There can be a study day calculation for any time point of interest. Adverse event start, study termination, and clinical endpoint event date all make good choices for study day calculations. The study day calculation is performed with one of the two following approaches. 

Common clinical trial graphics are the focus of this chapter. First, we discuss the types of graphs that are most often encountered in clinical trial analysis and reporting. Then we examine the various tools that SAS provides to help produce these graphs. Sample graph programs are provided to show how many of these graphs can be produced. 

There are several types of graphs that are common to clinical trial analysis and reporting. What follows are some brief descriptions of these graphs. 

Comparison of Kaplan-Meier survival estimates is often called for in clinical trial analysis. With survival analysis, you are trying to determine which treatment group displays a better time-to-event distribution than another. Part of this analysis is the production of Kaplan-Meier estimates plots that show the probability of a given event over time for each treatment group. In the following example you see that New Drug displays better survival estimates over time than either Old Drug or Placebo. ... 

SAS has always had and will maintain a central role in the data management, analysis, and reporting of clinical trial data. Because of the strong suite of SAS statistical procedures and the power of Base SAS programming, SAS remains a favorite of statisticians for the analysis of clinical trial data. Several companies have built their clinical trial data management and statistical analysis systems entirely with SAS software. More recently, SAS has offered SAS Drug Development as an industry solution that provides a comprehensive clinical trial analysis and reporting environment compliant with 21 CRF-Part 11. 

Chapter 10 Confirmatory clinical trials Analysis of categorical efficacy data... 

Prison L, Pocock SJ (1992) Repeated measures in clinical trials analysis using mean summary statistics and its implications for design [see comments]. Statistics in Medicine 11 1685-1704. 

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