Applying epidemiologic and biostatistical reasoning to patient management decisions as tested on USMLE Step 3.
35 cards · basic cards · AI-written, checked twice. Edit anything.
- As disease prevalence decreases in a population, what happens to a screening test's positive predictive value (PPV), assuming sensitivity and specificity stay constant?
- PPV decreases.
- As disease prevalence decreases in a population, what happens to a screening test's negative predictive value (NPV), assuming sensitivity and specificity stay constant?
- NPV increases.
- Do a test's sensitivity and specificity change as disease prevalence in the tested population changes?
- No, sensitivity and specificity are intrinsic properties of the test itself and do not change with prevalence.
- A highly sensitive test is best used for what clinical purpose?
- Ruling out disease, since a negative result argues strongly against having the disease.
- A highly specific test is best used for what clinical purpose?
- Ruling in disease, since a positive result argues strongly for having the disease.
- How is sensitivity calculated?
- True positives divided by (true positives plus false negatives).
- How is specificity calculated?
- True negatives divided by (true negatives plus false positives).
- How is positive predictive value (PPV) calculated?
- True positives divided by (true positives plus false positives).
- How is negative predictive value (NPV) calculated?
- True negatives divided by (true negatives plus false negatives).
- What does a positive likelihood ratio (LR+) greater than 10 indicate about a positive test result?
- It substantially raises the probability that the patient has the disease.
- What does a negative likelihood ratio (LR-) close to 0 indicate about a negative test result?
- It substantially lowers the probability that the patient has the disease.
- How is the positive likelihood ratio (LR+) calculated?
- Sensitivity divided by (1 minus specificity).
- In Bayesian clinical reasoning, ____ combined with a test's likelihood ratio determines the posttest probability of disease.
- pretest probability
- What does number needed to treat (NNT) represent?
- The number of patients who must be treated to prevent one additional bad outcome.
- How is number needed to treat (NNT) calculated?
- 1 divided by the absolute risk reduction.