Published online by Cambridge University Press: 05 November 2015
Introduction
It is the responsibility of clinicians to provide the best possible care for their patients. However, this simple statement masks a much more complex issue. How does one know precisely what the best care is for a particular patient? In particular, how does one balance the likely benefits and risks for a particular course of treatment? A new drug may appear promising, but can one really be sure that it represents a real improvement on current practice? Generally speaking, unless the action of a particular treatment is both immediate and breathtaking (such as insulin for diabetic coma), we cannot be absolutely certain which treatment is best for which people. Historical comparisons, or other database-dependent methods, can prove misleading. What is required is a method that will provide reliable, convincing evidence that can be used to inform future practice.
Fortunately, there is such a tool: the randomised controlled trial (RCT). At its heart are two principles. First, through randomisation, any differences between patients receiving one treatment and those receiving another are purely down to chance; therefore, if a sufficiently large difference is detected, then it must be due to the only factor that is systematically different between the two groups, namely the treatment. Second, with large numbers of patients, it becomes easier to detect smaller treatment effects and to conclude that any differences are not the result of chance. This, the statistical aspect of RCTs, is effectively a formalisation of common sense. If one tosses a coin 10 times and gets 6 heads and 4 tails, it is not out of the ordinary; but if one saw 6000 heads and 4000 tails from 10,000 tosses, then one would be concerned that the coin may be biased. The proportion of heads is the same, but larger numbers give stronger evidence of an unfair coin.
This chapter will concentrate on obtaining reliable evidence on the efficacy (whether the treatment works under ideal conditions, usually in a highly selected population) and effectiveness (whether a treatment will be beneficial in a real-life setting) of treatments for cancer. In particular, it will look at the factors that constitute a successful clinical trial, how the ideas can be extended to look at the weight of evidence provided by a number of clinical trials (meta-analysis) and how additional laboratory studies can help assess more modern targeted therapies.
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