Dictionary of Evidence-based Medicine.pdf
Dictionary of Evidence-based Medicine.pdf
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.