C. 0.33 – Explanation
A contingency table can be constructed from the above data, as shown below:
| Down’s | Not Down’s | |
| Test Positive | 15 | 30 |
| Test Negative | 5 | 50 |
Positive predictive value = TP / (TP + FP) = 15 / (15 + 30) = 0.33
Screening test statistics
It would be unusual for a medical exam not to feature a question based around screening test
statistics. The
available data should be used to construct a contingency table as below:
TP = true positive; FP = false positive; TN = true negative; FN = false negative
| Disease present | Disease absent | |
| Test positive | TP | FP |
| Test negative | FN | TN |
The table below lists the main statistical terms used in relation to screening tests
| Sensitivity | TP / (TP + FN) | Proportion of patients with the condition who have a positive test result |
| Specificity | TN / (TN + FP) | Proportion of patients without the condition who have a negative test result |
| Positive Predictive Value | TP / (TP + FP) | The chance that the patient has the condition if the diagnostic test is positive |
| Negative Predictive Value | TN / (TN + FN) | The chance that the patient does not have the condition if the diagnostic test is negative |
| Likelihood Ratio for a Positive Test Result | Sensitivity / (1 – Specificity) | How much the odds of the disease increase when a test is positive |
| Likelihood Ratio for a Negative Test Result | (1 – Sensitivity) / Specificity | How much the odds of the disease decrease when a test is negative |
Positive and negative predictive values are prevalence dependent. Likelihood ratios are not
prevalence dependent
