Therapeutic Confirmatory Clinical Trials

Human pharmacology and therapeutic exploratory studies define the most likely safe and effective dosage regimens for use in subsequent therapeutic confirmatory studies. These therapeutic confirmatory studies are typically run as double-blind, randomized, concurrently controlled clinical trials. 

The technique of randomization was pioneered in the field of agriculture (plants too show considerable individual variation) by Sir Ronald Fisher, a visionary statistician. It is generally acknowledged that the first randomized clinical trial, conducted in the 1940s, was a study evaluating the use of streptomycin in treating tuberculosis conducted by the (British) Medical Research Council Streptomycin in Tuberculosis Trials Committee. The results were published in the British Medical Journal in 1948. 

Matthews (1999) made the following observation concerning randomized trials  

Over the last two to three decades randomized concurrently controlled clinical trials have become established as the method which investigators must use to assess new treatments if their claims are to find widespread acceptance. The methodology underpinning these trials is firmly based in statistical theory, and the success of randomized trials perhaps constitutes the greatest achievement of statistics in the second half of the twentieth century (Preface). 

The discipline of Statistics is employed in clinical trials to investigate a new drug s safety and efficacy. This investigation may provide compelling evidence that the drug is safe and will induce a biological response that improves patients well-being. 

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While the nature of the analyses of data from therapeutic confirmatory clinical trials is relatively straightforward compared with those undertaken in earlier stages of clinical development, supreme care should again be taken in all aspects of design, methodology, and analysis, since only then can optimum quality data be used to provide optimum answers to well-constructed research questions. Chapter 10 noted that safety data are typically presented descriptively at this time but that this may change in due course. By the time that therapeutic confirmatory trials are conducted, there should be a small number of precisely asked research questions that address the efficacy of the drug. 

This book, therefore, is a self-contained introduction to the discipline of Statistics and its use in therapeutic confirmatory clinical trials. The first part of the book provides introductory comments about the discipline of Statistics and lays the foundations for our later discussions in the context of pharmaceutical trials. Chapter 2 presents an overview of the process of new drug development and the role of clinical trials in this process. The categories of different types of clinical trials are identified and discussed so that you will understand thetypes of data collectedin them. 

At this point it is worth considering the length of time it takes to run a therapeutic confirmatory clinical trial. Such trials are often conducted as multicenter trials. Although the total numbers of individuals who participate in trials vary, we noted earlier that a typical number for a therapeutic confirmatory trial is 3000-5000 individuals. Each of these individuals needs to have the... 

Therapeutic confirmatory (Phase III) Demonstrate/confirm efficacy Establish safety profile Provide an adequate basis for assessing the benefit/risk relationship to support licensing Establish dose-response relationship Adequate and well controlled studies to establish efficacy Randomized parallel dose-response studies Clinical safety studies Studies of mortality/morbidity outcomes Large simple trials Comparative studies... 

By the time a therapeutic confirmatory trial is appropriate, it should be possible to state a single primary objective (or perhaps two if the sponsor really feels that this is appropriate) that is clinically relevant and biologically plausible. One primary objective also means that sample-size estimation can be based on that objective and the associated estimated treatment effect of interest (recall the discussions in Chapter 9). 

The requirement to show statistical significance in therapeutic confirmatory trials places a certain importance on a priori hypothesis testing. However, as we have seen, there is much more to clinical research than p-values. Piantadosi (2005) commented on this issue as follows ... 

The null hypothesis is the crux of hypothesis testing. (It is important to note that the form of the null hypothesis varies in different statistical approaches. As the main type of clinical trial discussed in this book is the therapeutic confirmatory trial, we talk about this first. We then talk briefly about the forms of the null hypothesis that are used in other types of trials in Section 3.10.) As noted earlier, therapeutic confirmatory trials are comparative in nature. We want to evaluate the efficacy of the investi-... 

Safety monitoring in clinical studies can be both data and labor intensive. In the context of later-stage therapeutic exploratory and therapeutic confirmatory trials, the collection of laboratory data is no exception. Typically, participants in clinical trials provide blood or urine samples at every clinic visit. There is an expansive range of clinical chemistry tests that can be conducted using these samples. 

The term "responders analysis" was first introduced in Chapter 9 with regard to clinical laboratory data. A responders analysis approach can be used in the context of efficacy data, as well. Consider a double-blind, placebo-controlled, therapeutic confirmatory trial of an investigational antihypertensive ("test drug"). Based on earlier experience, a period of 12 weeks is considered sufficient to observe a clinically meaningful treatment effect that can be sustained for many months. In this study, a participant whose SBP is reduced by at least 1 0 mmHg after 1 2 weeks... 

The previous chapters have provided you with an introduction to statistical methods and analyses that are commonly used in pharmaceutical clinical trials, with an emphasis on therapeutic confirmatory trials. Although we certainly have not covered all of the analyses that can be conducted in these trials, those that we have discussed have given you a solid foundation that will also enable you to understand the basics of other analyses. 

It is also appropriate to note that not all clinical trials utilize formal sample size estimation methods. In many instances (for example, FTIH studies) the sample size is determined on the basis of logistical constraints and the size of the study thought to be necessary to gather sufficient evidence (for example, pharmacokinetic profiles) to rule out unwanted effects. However, when the objective of the clinical trial (for example, a superiority trial) is to claim that a true treatment effect exists while at the same time limiting the probability of committing type I or II errors (a and P), there are computational methods used to estimate the required sample size. The use of formal sample size estimation is required in therapeutic confirmatory trials, this book s major focus, and strongly suggested in therapeutic exploratory trials. 

Turner (2007) noted that, in a very real sense, all the clinical studies that are conducted before a therapeutic confirmatory trial is undertaken have one purpose To allow the primary objective in the therapeutic confirmatory trial to be stated as simply as possible. An objective that can be stated simply can be tested simply, that is, in a straightforward and unambiguous manner. This is a highly desirable attribute in a primary objective. 

Therapeutic exploratory (Phase lb/II) Explore use for the targeted indication Estimate dosage for subsequent studies Provide basis for confirmatory study design, endpoints, methodologies Earliest trials of relatively short duration in well-defined narrow patient populations, using surrogate or pharmacological endpoints or clinical measures Dose-response exploration studies... 

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