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Dictionary of Evidence-based Medicine.pdf

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<strong>Dictionary</strong> <strong>of</strong> <strong>Evidence</strong>-<strong>based</strong> <strong>Medicine</strong> 59<br />

Excess risk<br />

In a comparative study <strong>of</strong> risks associated with exposure to two therapies<br />

or environments, the difference in risk can be expressed in absolute or<br />

relative terms (see Risk difference, Relative risk and Risk ratio). The ratio<br />

<strong>of</strong> the risk associated with one exposure divided by the risk associated<br />

with the other is the relative risk. Suppose that the risk <strong>of</strong> developing<br />

diarrhoea after receiving a course <strong>of</strong> antibiotic A is 5 in 100 and 2 in 100 for<br />

antibiotic B, then the relative risk <strong>of</strong> developing this side-effect when<br />

receiving A instead <strong>of</strong> B is 2.5 (i.e. 0.05/0.02). The excess risk is the difference<br />

in risk expressed as a percentage or 150% in this case (i.e. 100 x (5-2)/2). A<br />

common mistake in the literature is to interpret a risk ratio or relative risk<br />

<strong>of</strong> 2.5 as a 250% or two and a half-fold increase in risk (Lam TH (1997)<br />

Relative risks are inflated in published literature. BMJ. 315: 880).<br />

Explanatory trial analysis (see under Intention to treat analysis)<br />

Exponential survival model<br />

The exponential survival model is characterized by the following survival<br />

function, where T is a random variable representing failure time:<br />

S(t) = P(T ^ t) = exp(-to)<br />

The corresponding probability density function is given by/(y) = A exp(-Af).<br />

The mean (j, <strong>of</strong> the exponential distribution is given by I/A and its variance<br />

a 2 by I/A, 2 . The shape <strong>of</strong> the survival curve is <strong>of</strong> the type shown in<br />

Figure 8.<br />

Expressed preference method (see under Willingness to pay)<br />

External validity<br />

External validity refers to how applicable the results <strong>of</strong> a study are to the<br />

target population. For example, a frequently expressed concern is whether<br />

conclusions drawn from the results <strong>of</strong> clinical trials using patients adhering<br />

to strict inclusion criteria are applicable to the population <strong>of</strong> patients<br />

visiting primary care physicians. In other words, critics question the external<br />

validity or generalizability <strong>of</strong> such clinical trial data to the average<br />

primary care patient.

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