B. 0.66 – Explanation
The new test was negative in 20 of the patients later shown to have myocardial ischemia (false
negative) and negative in 40 patients confirmed not to have myocardial ischemia (true negative)
Negative predictive value = TN / (TN + FN)
= 40 / (40 + 20) = 0.66
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
