• See Also
  1. Screening Test
  2. Contingency Grid or Cross Tab (includes Statistics Example)
  3. Bayes Theorem (Bayesian Statistics)
  4. Fagan Nomogram
  5. Experimental Error (Experimental Bias)
  6. Lead-Time Bias
  7. Length Bias
  8. Selection Bias (Screening Bias)
  9. Likelihood Ratio (Positive Likelihood Ratio, Negative Likelihood Ratio)
  10. Number Needed to Screen (Number Needed to Treat, Absolute Risk Reduction, Relative Risk Reduction)
  11. Negative Predictive Value
  12. Positive Predictive Value
  13. Pre-Test Odds or Post-Test Odds
  14. Receiver Operating Characteristic
  15. Test Specificity (False Positive Rate)
  16. U.S. Preventive Services Task Force Recommendations
  • Definitions
  1. Test Sensitivity
    1. Screening Test's ability to identify true disease
    2. A Test with high sensitivity has few False Negatives
    3. Independent of disease Prevalence in the community
    4. Sensitive Tests allow user to RULE OUT a condition (mnemonic "SNout")
  2. Recall
    1. Identical to the Test Sensitivity, but Recall term is used more in data science
    2. Reflects what percentage of relevant items are positive (not missed as False Negatives)
    3. See Test Precision (Positive Predictive Value)
  • Calculation
  1. Test Sensitivity
    1. True positive tests per total affected patients tested
    2. Test Sensitivity = P(positive test | disease)
      1. Where P (A | B) = Probability of A given B
    3. Expressed as a percentage
  2. False Negative Rate
    1. True cases missed by the Screening Test (test negative despite presence of condition)
    2. False Negative Rate = 1 - Test Sensitivity
  1. Patients with known Crohn's Disease tested: 45
  2. Patients with known Crohn's Disease who have a positive test: 36
  3. Sensitivity = 36/45 or 80%
  • References
  1. Hennekens (1987) Epidemiology Medicine, p.327-47
  2. Gates (2001) Am Fam Physician 63(3):513-22 [PubMed]
  3. MacLean (1996) Med Clin North Am 80(1):1-14 [PubMed]
  4. Nielsen (1999) Med Clin North Am 83(6):1323-37 [PubMed]