Synopsis
Move from clinical data to calibrated diagnostic probabilities, choose tests by decision value, and revise conclusions when results, trajectories or competing explanations disagree.
- Define the decision before ordering a test: rule out a dangerous possibility, confirm a treatable diagnosis, stage disease, select treatment or monitor change.
- Estimate pre-test probability from the patient's pattern and relevant population; predictive values cannot be transported unchanged when prevalence differs.
- Convert probability to odds, multiply by the likelihood ratio, then convert post-test odds back to probability when a quantitative update is needed.
Reasoning priorities
Anchor interpretation to the patient and setting before the result is known.
Use a validated clinical model when applicable or state a reasoned range; retrospective estimates after seeing the result are vulnerable to hindsight.
Worked reasoning
Inputs: pre-test probability 30%; a negative result from a test with sensitivity 90% and specificity 80%; decide whether the result crosses a 5% action threshold.
- Convert pre-test probability to odds: 0.30 divided by 0.70 equals 0.4286.
- Calculate LR−: one minus sensitivity, 0.10, divided by specificity, 0.80, equals 0.125.
- Multiply: post-test odds equal 0.4286 times 0.125, which is 0.0536.
- Convert back: 0.0536 divided by 1.0536 equals 0.0509, or about 5.1%; the result sits just above rather than below the stated 5% threshold.
- Conclude that the negative test narrowly fails the predefined threshold, so further evidence or observation is needed rather than calling disease excluded.
- Verify with 1,000 people at 30% prevalence: 300 have disease, giving 270 true positives and 30 false negatives at 90% sensitivity; 700 do not have disease, giving 560 true negatives and 140 false positives at 80% specificity. Of the 590 negative results, 30 have disease: 30/590 = 5.08%, agreeing with the odds calculation and remaining just above the hypothetical 5% action threshold.
A stable patient has an intermediate probability of a condition and several possible tests.