Sensitivity vs. Specificity in Diagnostic Testing
Sensitivity measures how well a test identifies patients WITH disease (true positive rate), while specificity measures how well a test identifies patients WITHOUT disease (true negative rate)—these are inversely related characteristics that define a test's diagnostic accuracy. 1
Core Definitions
Sensitivity is the percentage of individuals with disease who will have abnormal (positive) test results 1. It answers: "If the patient has the disease, what is the probability the test will be positive?" 1
Specificity is the percentage of individuals without disease who will have normal (negative) test results 1. It answers: "If the patient does not have the disease, what is the probability the test will be negative?" 1
Mathematical Framework
Sensitivity calculation: Number of true positives divided by all patients with disease (true positives + false negatives) 1
Specificity calculation: Number of true negatives divided by all patients without disease (true negatives + false positives) 1
For FISH probes specifically, sensitivity of at least 95% and specificity of at least 98% are recommended for clinical testing 1
The Inverse Relationship
Sensitivity and specificity are inversely related—when one increases, the other decreases 1, 2. This tradeoff occurs because:
- Lowering the diagnostic threshold increases sensitivity (catches more disease) but decreases specificity (more false positives) 1
- Raising the diagnostic threshold increases specificity (fewer false positives) but decreases sensitivity (misses more disease) 1
- All tests have a range of inversely related sensitivities and specificities that can be selected by specifying a diagnostic cut point 1
Clinical Context and Interpretation
Disease prevalence significantly affects how these measures perform in practice 3. Higher disease prevalence is associated with higher estimated sensitivity but lower estimated specificity 3. This means:
- Sensitivity is influenced by disease severity, effort level, and anti-ischemic drugs 1
- Specificity may be affected by drugs (e.g., digoxin), baseline ECG patterns, and left ventricular hypertrophy 1
- If the population is skewed toward individuals with greater disease severity, the test will have higher sensitivity 1
Critical Distinction from Predictive Values
Sensitivity and specificity are characteristics of the test itself and theoretically remain constant regardless of disease prevalence, while predictive values change with prevalence 1, 4.
- Positive predictive value (PPV) and sensitivity change in opposite directions 2
- Negative predictive value (NPV) and specificity change in opposite directions 2
- Predictive values are more useful clinically but cannot be applied across populations with different disease prevalence 4
- Sensitivity and specificity cannot be used to estimate probability of disease in individual patients 4
Common Pitfalls
Selection bias in case and control groups can artificially inflate or deflate these measures 1. Avoid:
- Using healthy controls instead of disease mimics (inflates specificity) 1
- Selecting cases based on prior positive test results (inflates sensitivity) 1
- Applying sensitivity/specificity from referral centers to general populations 1
The reference standard (gold standard) must be accurate 1. When the reference test is imperfect, estimates of sensitivity and specificity become untrustworthy and require statistical adjustments 1.