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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> 151<br />

adverse outcome; (v) only small apparent differences between the different<br />

options (Kassirer }P (1994) Incorporating patients' preferences into medical<br />

decisions. New England Journal <strong>of</strong> <strong>Medicine</strong>. 330:1895-6).<br />

Surrogate outcome measure<br />

A surrogate outcome measure is an end point used in lieu <strong>of</strong> another which<br />

is usually clinically more meaningful, but practically more difficult, to<br />

measure. For example, bone mineral density is <strong>of</strong>ten used as a surrogate<br />

outcome measure for bone fracture in clinical trials <strong>of</strong> prophylatic<br />

treatments, such as <strong>of</strong> hormone replacement therapy.<br />

Survival analysis<br />

Survival analysis refers to the study <strong>of</strong> time to events (e.g. time to death or<br />

recovery, time to failure <strong>of</strong> light bulbs, time to breakdown <strong>of</strong> a machinery<br />

component, etc.). The methodology overcomes problems associated with<br />

single time point estimations <strong>of</strong> failure (e.g. deaths, breakdowns and disease<br />

relapse) because the complete survival or failure curve is considered<br />

including censoring or loss to follow-up and end <strong>of</strong> study before 100%<br />

failure (see Cox model, Censoring). (Parmar MKB, Machin D (1995) Survival<br />

analysis. John Wiley, Chichester. Kalbfleisch JD, Prentice DL (1980) The<br />

statistical analysis <strong>of</strong> failure time data. John Wiley, New York).<br />

Survival function<br />

The survival function, usually written as S(t), is the probability that the<br />

individual concerned survives longer than time t and hence is alive (or free<br />

from event) at time t. This can be calculated as follows:<br />

Symmetric distribution<br />

A symmetric distribution is one in which values are symmetrically distributed<br />

around the mean. The population mean and median are then the<br />

same and the interval between the 25th percentile and the mean is equal to

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