## Variabilitythe Source Of Uncertainty

Virtually no drug has an identical response in all patients. For example, an effective antibiotic will, almost certainly, be ineffective in some patients, possibly because such patients are infected with a resistant strain or have a deficient immune response. Variability in response introduces uncertainty in establishing cause and effect. The fact that administering a drug to a given subject has not resulted with the desired therapeutic effect does not necessarily imply that the drug in ineffective. Causality, in the strict sense discussed in the previous section, can no longer be established when outcome of an experiment is subject to variability. However, one can still talk about causality in a probabilistic sense by modifying the requirement that 'whenever A is present B must be present, too' necessary for the establishment of causality, to 'the probability that B will occur is greater in the presence of A than when A is not present'.

Another issue is that when the measurement of efficacy is variable, it is impossible to determine what part of the measured outcome is due to the effect of the drug and what part is due to variability unrelated to the drug effect. The size of a drug effect is called the 'signal' while the variability associated with it is called the 'noise'. Clearly, the larger the 'signal-to-noise ratio', the easiest it is to establish a causal relationship. Thus, in a clinical drug trial, it is equally important to measure both noise and signal. How are these measured? The nature of variability is that it is random. When we measure the blood pressure of an individual subject repeatedly, the measurements will be dispersed around some central value in a random fashion; some will be larger and some smaller. The effect, on the other hand, is systematic. If, for example, we measure the blood pressure of an individual repeatedly before and just after administering an antihy-pertensive drug, the pre- and post-treatment measurements will be dispersed around different central values, the post-treatment lower than the pretreatment value. The magnitude of the effect

(signal) is usually calculated as the mean of the individual effects in a population of subjects. The variability (noise) is usually calculated as the standard deviation.

0 0