Positive Predictive Value

1. See Also
   1. Screening Test
   2. Contingency Grid (includes Statistics Example)
   3. Test Sensitivity
   4. Test Specificity
   5. Negative Predictive Value
   6. Likelihood Ratio
   7. Number Needed to Screen
   8. Length Bias
   9. Leadtime Bias
   10. Selection Bias
2. Definition
   1. Percent of patients with positive test having disease
   2. Assesses reliability of positive test
3. Indications
   1. Puts Test Specificity in context of disease Prevalence
   2. Lower disease Prevalence results in lower PPV
      1. Test Specificity effect is magnified
      2. False positives increase substantially
      3. Results in less reliable positive test
4. Calculation
   1. PPV = (True positive) / (True + False positives)
5. Example 1: High Prevalence Disease
   1. Major DepressionPrevalence is 10 per 100
   2. New Screening Test efficacy
      1. Test Sensitivity: 100%
      2. Test Specificity: 99% (1 false positive in 100)
   3. Screen 1000 patients
      1. True positives: 100 per 1000 (10% Prevalence)
      2. False positives: 10 per 1000 (99% Test Specificity)
      3. PPV: 100 true positives / 110 total positives = 91%
6. Example 2: Low Prevalence Disease
   1. SclerodermaPrevalence is 1 per 1000
   2. New Screening Test efficacy
      1. Test Sensitivity: 100%
      2. Test Specificity: 99% (1 false positive in 100)
   3. Screen 1000 patients
      1. True positives: 1 per 1000 (0.1% Prevalence)
      2. False positives: 10 per 1000 (99% Test Specificity)
      3. PPV: 1 true positive / 11 total positives = 9%
         1. Contrast with PPV 91% for high Prevalence disease