Pre- and post-test probability: Difference between revisions

Revision as of 22:01, 7 April 2024

Latest revision as of 16:19, 8 May 2025

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The post-test probability of disease given a negative result is calculated as:

Negative posttest probability = 1 - (FalseTrue negatives / (False negatives + True negatives))

The validity of the equations above also depend on that the sample from the population does not have substantial [[sampling bias]] that make the groups of those who have the condition and those who do not substantially disproportionate from corresponding prevalence and "non-prevalence" in the population. In effect, the equations above are not valid with merely a [[case-control study]] that separately collects one group with the condition and one group without it.

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The [[prevalence]] in the population sample is calculated to be:

*Prevalence = (2 + 1) / 203 = 0.0148 or 1.48%

The individual's pre-test probability was more than twice the onethat of the population sample, although the individual's post-test probability was less than twice the onethat of the population sample (which is estimated by the positive predictive value of the test of 10%), opposite to what would result by a less accurate method of simply multiplying relative risks.

====Specific sources of inaccuracy====