Statistics drug trials

This chapter introduces basic concepts in statistical analysis that are of relevance to describing and analyzing the data that are collected in clinical trials, the hallmark of new drug development. (Statistical analysis in nonclinical studies was addressed earlier in Chapter 4.) This chapter therefore sets the scene for more detailed discussion of the determination of statistical significance via the process of hypothesis testing in Chapter 7, evaluation of clinical significance via the calculation of confidence intervals in Chapter 8, and discussions of adaptive designs and of noninferiority/equivalence trials in Chapter 11. 

For a superiority trial the null hypothesis is that the treatment effect is zero. Sponsors of drug trials would like to generate sufficient evidence, in the form of the test statistic, to reject the null hypothesis in favor of the alternate hypothesis, thereby providing compelling evidence that the treatment effect is not zero. The null hypothesis may be rejected if the treatment effect favors the test drug, and also if it favors the placebo (as discussed, we have to acknowledge this possibility). 

Darken PF, Ho S-Y (2004) A note on sample size savings with the use of a single well-controlled clinical trial to support the efficacy of a new drug. Pharmaceutical Statistics 3 61-63. 

Senn SJ (2002) Ethical considerations concerning treatment allocation in drug development trials. Statistical Methods in Medical Research 11 403 11. 

O Neill RT (1993) Some FDA perspectives on data monitoring in clinical trials in drug development. Statistics in Medicine 12 601-608. 

Elston RC, Idury RM, Cardon LR, Lichter JB (1999) The study of candidate genes in drug trials Sample size considerations. Statistics in Medicine 18 741-751. 

From this model one can specify a set of decision rules to draw some conclusions based on the empirical results of the experiment. The result of such a statistical test procedure does not establish with certainty the true state of nature, but rather it expresses a degree of confidence that one of the two states is not likely to occur. The randomized clinical trial and associated NHST are the mainstays of certain safety and efficacy approaches, such as the FDA drug trials described later, but they have certain potential limitations in their application to the safety of ingredients new to infant formulas. 

A key element in planning and conducting clinical trials is to ensure that they have scientific validity and objectivity. This is particularly relevant with respect to Phase II and III studies, where it is desired to demonstrate a positive benefit to risk outcome. Responses to a drug among a patient population are rarely homogeneous and clear-cut. Thus, sound statistical principles must be applied in order to be able to distinguish significant effects from random events. 

A very common analysis in clinical trials involves the analysis of two binomial variables to see if there is a statistically significant association between them. A binomial variable is one that can have only one of two values. For example, let s assume that we have a variable called treatment whose value is either a 1 to indicate active drug therapy or a 0 to indicate placebo. We also have a variable called headache whose value is a 1 if the patient experiences headache after therapy and a 0 if not. What we want to know is whether a change in the level of therapy is significantly associated with a change in the level of headache. The 2x2 table looks like this ... 

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