Sensitivity and specificity
Updates to Article Attributes
Sensitivity and specificity are fundamental characteristics of diagnostic imaging tests.
The two characteristics derive from a 2x2 box of basic, mutually exclusive outcomes from a diagnostic test:
- true positive (TP): an imaging test is positive and the patient has the disease/condition
- false positive (FP): an imaging test is positive and the patient does not have the disease/condition
- true negative (TN): an imaging test is negative and the patient does not have the disease/condition
- false negative (FN): an imaging test is negative and the patient has the disease/condition
On a first pass, we don't assume some relationship between the test and the disease/condition, but we hope there will be some relationship between the test and the disease/condition, because otherwise the test would be worthless.
Sensitivity
For a given test and disease/condition, its sensitivity is how well it can be positive among all those with the condition. Therefore:
- sensitivity = TP / (TP + FN)
- true positives / (all those with the disease)
Specificity
For a given test and disease/condition, its specificity is how well it can distinguish those with disease from those without. The test must not just fail to pick up a segment of the population (that might be poor sensitivity), it must distinguish those without the disease... the true negatives (TNs). Therefore:
- specificity = TN / (TN + FP)
- true negatives / (all those without the disease)
SpPin and SnNout rule
SnNout: if a diagnostic test, characterized by high sensitivity (Sn), returns the negative value (N), then it excludes the diagnosis (out) 2-3.
SpPin: if a diagnostic test, characterized by high specificity (Sp), returns the positive value (P), then it admits the diagnosis (in) 2-3.
See also
- ROC curve: graphically displays a diagnostic system's trade-off between sensitivity and specificity
- sensitivity and specificity of multiple tests
-</li></ul><h6>SpPin and SnNout rule</h6><p><strong>SnNout</strong>: if a diagnostic test, characterized by high sensitivity (Sn), returns the negative value (N), then it excludes the diagnosis (out)<sup> 2</sup>.</p><p><strong>SpPin</strong>: if a diagnostic test, characterized by high specificity (Sp), returns the positive value (P), then it admits the diagnosis (in)<sup> 2</sup>.</p><h4>See also</h4><ul>- +</li></ul><h6>SpPin and SnNout rule</h6><p><strong>SnNout</strong>: if a diagnostic test, characterized by high sensitivity (Sn), returns the negative value (N), then it excludes the diagnosis (out)<sup> 2-3</sup>.</p><p><strong>SpPin</strong>: if a diagnostic test, characterized by high specificity (Sp), returns the positive value (P), then it admits the diagnosis (in)<sup> 2-3</sup>.</p><h4>See also</h4><ul>
References changed:
- 3. Baeyens JP, Serrien B, Goossens M, Clijsen R. Questioning the "SPIN and SNOUT" rule in clinical testing. (2019) Archives of physiotherapy. 9: 4. <a href="https://doi.org/10.1186/s40945-019-0056-5">doi:10.1186/s40945-019-0056-5</a> - <a href="https://www.ncbi.nlm.nih.gov/pubmed/30891312">Pubmed</a> <span class="ref_v4"></span>
Unable to process the form. Check for errors and try again.