Drug trials statistics placebo effect

But do the clinical-trial data submitted to the FDA even establish proof of principle Recall that the rather small differences found between drug and placebo in the trials submitted to the FDA could have been due to the breaking of blind on the basis of perceived side effects. It may simply be evidence of an enhanced placebo effect, rather than a true drug effect. As I noted in Chapter i, once side effects are taken into account, the difference between SSRI and placebo is not even statistically significant.30... 

The objective of clinical trials is to demonstrate the safety and effectiveness of the drug compared to placebo or control. The statistical method normally used is known as hypothesis testing. 

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). 

As we have seen, several summary measures of central tendency can be used for continuous outcomes. The most common of these measures is the mean. In clinical trials we calculate sample statistics, and these serve to estimate the unknown population means. When developing a new drug, the estimated treatment effect is measured by the difference in sample means for the test treatment and the placebo. If we can infer (conclude) that the corresponding population means differ by an amount that is considered clinically important (that is, in the positive direction and of a certain magnitude) the test treatment will be considered efficacious. 

Placebo-controlled trial of a new active medicinal product, if positive, means that the trial was capable of detecting a difference, and that the test treatment is, at least, more efficacious than placebo. This achieves two outcomes provision of an internal validity check of the trial methods, and provision to regulatory authorities of a basis on which to judge the difference between a statistically significant but clinically inadequate effect that would probably lead to the drug not being licensed. 

The meta-analysis of all studies comparing clomipramine or SRIs with placebo for the treatment of OCD found that the active drug produced a better result in every trial. We then calculated the effect size and the statistical significance for clomipramine alone and fluvoxamine alone. Their results showed a highly significant effect for both drugs (Table 13-10 and Table 13-11). There were also several studies with sertraline, fluoxetine, and paroxetine that demonstrated similar results (219, 220, 221, 222. 223,. 224, 225 and 226). 

In the present example, an effect size of 3.00 mmHg was observed. That is, the difference between the drug treatment group mean change score and the placebo treatment group mean change score was 3.00 mmHg. This effect size has been precisely calculated on the basis of the data obtained in the clinical trial. Recall, however, that in a randomized clinical trial the subjects used are a random sample of all the people in the disease population of interest. Our interest actually lies with the effect size in that population. The population effect size is not known, and a question of interest is How well does the effect size calculated in our sample reflect the unknown effect size in the population This question is at the heart of inferential statistics. 

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