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{{Use dmy dates|date=August 2013}}
'''Pre-test probability''' and '''post-test probability''' (alternatively spelled pretest and posttest probability) are the [[Subjectivity|subjective]] [[probabilities]] of the presence of a condition (such as a [[disease]]) before and after a [[diagnostic test]], respectively. ''Post-test probability'', in turn, can be ''positive'' or ''negative'', depending on whether the test falls out as a [[positive test]] or a [[negative medical test|negative test]], respectively. In some cases, it is used for the probability of developing the condition of interest in the future.
The subjectivity of the probabilities is based on the fact that, in reality, an individual either has the condition or not (with the probability always being 100%), so pre- and post-test probabilities for individuals can rather be regarded as psychological phenomena in the minds of those involved in the [[diagnostics]] at hand.
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==Estimation of post-test probability==
In clinical practice, post-test probabilities are often just roughly estimated or even guessed. This is usually acceptable in the finding of a ''[[pathognomonic]]'' sign or symptom, in which case it is almost certain that the target condition is present; or in the absence of finding a ''[[sine qua non]]'' sign or symptom, in which case it is almost certain that the target condition is absent.
In reality, however, the subjective probability of the presence of a condition is never exactly 0 or 100%. Yet, there are several systematic methods to estimate that probability. Such methods are usually based on previously having performed the test on a [[reference group]] in which the presence or absence on the condition is known (or at least estimated by another test that is considered highly accurate, such as by "[[Gold standard (test)|Gold standard]]"), in order to establish data of test performance. These data are subsequently used to interpret the test result of any individual tested by the method. An alternative or complement to ''reference group''-based methods is comparing a test result to a previous test on the same individual, which is more common in tests for [[monitoring (medicine)|monitoring]].
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! Method !! Establishment of performance data !! Method of individual interpretation !! Ability to accurately interpret subsequent tests !! Additional advantages !! Additional disadvantages
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! By [[predictive value]]s
| Direct quotients from reference group ||<span style="color:DarkGreen;">Most straightforward: Predictive value equals probability ||<span style="color:DarkRed;"> Usually low: Separate reference group required for every subsequent pre-test state ||<span style="color:DarkGreen;"> Available both for [[binary classification|binary]] and [[Continuity (mathematics)|continuous]] values ||
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! By [[Likelihood-ratio test|likelihood ratio]]
| Derived from [[sensitivity and specificity]] || Post-test odds given by multiplying pretest odds with the ratio ||<span style="color:DarkGreen;"> Theoretically limitless ||<span style="color:DarkGreen;"> Pre-test state (and thus the pre-test probability) does not have to be same as in reference group ||<span style="color:DarkRed;">
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! By [[relative risk]]
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| style="background: #ddffdd;" |'''''Positive'''''
| style="background: #ddffdd;" |'''''Negative'''''
|-
| rowspan="2" style="background: #ffdddd;"| '''Test<br>outcome'''
| style="background: #ffdddd;"|'''''Positive'''''
| style="background: #eeeeff;"| <span style="color:#007700;"> '''True Positive'''
| <span style="color:#770000;"> '''False Positive'''<BR>([[Type I and type II errors#False positive rate|Type I error]])
| <span style="color:#770077;"> → [[Positive predictive value]]
|-
| style="background: #ffdddd;"|'''''Negative'''''
| style="background: #eeeeff;"|<span style="color:#770000;"> '''False Negative'''<BR>([[Type I and type II errors#False negative rate|Type II error]])
| <span style="color:#007700;"> '''True Negative'''
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In these cases, the ''prevalence'' in the reference group is not completely accurate in representing the ''pre-test probability'' of the individual, and, consequently, the ''predictive value'' (whether ''positive'' or ''negative'') is not completely accurate in representing the ''post-test probability'' of the individual of having the target condition.
In these cases, a posttest probability can be estimated more accurately by using a [[Likelihood-ratio test|likelihood ratio]] for the test. ''Likelihood ratio'' is calculated from [[sensitivity and specificity]] of the test, and thereby it does not depend on prevalence in the reference group,<ref name=cebm/> and, likewise, it does not change with changed ''pre-test probability'', in contrast to positive or negative predictive values (which would change). Also, in effect, the validity of ''post-test probability'' determined from likelihood ratio is not vulnerable to [[sampling bias]] in regard to those with and without the condition in the population sample, and can be done as a [[case-control study]] that separately gathers those with and without the condition.
Estimation of post-test probability from pre-test probability and likelihood ratio goes as follows:<ref name=cebm>[http://www.cebm.net/index.aspx?o=1043 Likelihood Ratios], from CEBM (Centre for Evidence-Based Medicine). Page last edited: 1 February 2009. When used in examples, the general formulas are taken from reference, while example numbers are different</ref>
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|-
| rowspan="2" style="background: #ffdddd;"| '''Fecal<br>occult<br>blood<br>screen<br>test<br>outcome''' sexo
| style="background: #ffdddd;"|'''''Positive'''''
| style="background: #eeeeff;"| <span style="color:#007700;"> '''TP = 2'''
| <span style="color:#770000;"> '''FP = 18'''
| → Positive predictive value<BR>= TP / (TP + FP)<BR>= 2 / (2 + 18)<BR>= 2 / 20<BR>'''= 10%'''
|-
| style="background: #ffdddd;"|'''''Negative'''''
| style="background: #eeeeff;"|<span style="color:#770000;"> '''FN = 1'''
| <span style="color:#007700;"> '''TN = 182'''
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*Positive posttest probability = 0.229 / (0.229 + 1) = 0.186 or 18.6%
Thus, that individual has a post-test probability (or "post-test risk") of 18.6% of having bowel cancer.
The [[prevalence]] in the population sample is calculated to be:
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===By diagnostic criteria and clinical prediction rules===
Most major diseases have established [[diagnostic criteria]] and/or [[clinical prediction rule]]s. The establishment of diagnostic criteria or clinical prediction rules consists of a comprehensive evaluation of many tests that are considered important in estimating the probability of a condition of interest, sometimes also including how to divide it into subgroups, and when and how to treat the condition. Such establishment can include usage of predictive values, likelihood ratios as well as relative risks.
For example, the [[Systemic lupus erythematosus#Diagnostic criteria|ACR criteria for systemic lupus erythematosus]] defines the diagnosis as presence of at least 4 out of 11 findings, each of which can be regarded as a target value of a test with its own sensitivity and specificity. In this case, there has been evaluation of the tests for these target parameters when used in combination in regard to, for example, interference between them and overlap of target parameters, thereby striving to avoid inaccuracies that could otherwise arise if attempting to calculate the probability of the disease using likelihood ratios of the individual tests. Therefore, if diagnostic criteria have been established for a condition, it is generally most appropriate to interpret any post-test probability for that condition in the context of these criteria.
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==References==
{{reflist|30em}}
{{Medical research studies}}
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