1. What is Post-Test Probability?

Definition: Post-test probability is the updated probability of a condition after considering the results of a diagnostic test.

Purpose: It helps clinicians and researchers understand how test results modify the likelihood of a disease or condition.

2. How Does the Calculator Work?

The calculator uses the formula:

Where:

• \( P_{post} \) — Post-test probability (0-1)
• \( P_{pre} \) — Pre-test probability (0-1)
• \( Se \) — Test sensitivity (0-1)
• \( Sp \) — Test specificity (0-1)

Explanation: The formula combines pre-test probability with test characteristics to give an updated probability estimate.

3. Importance of Post-Test Probability

Details: Understanding post-test probability helps in clinical decision making, determining whether to proceed with treatment or further testing.

4. Using the Calculator

Tips: Enter values between 0 and 1 for all parameters. Pre-test probability is often based on prevalence or clinical judgment.

5. Frequently Asked Questions (FAQ)

Q1: What's the difference between pre-test and post-test probability?
A: Pre-test probability is the estimated likelihood before testing, while post-test probability incorporates test results.

Q2: How do I determine pre-test probability?
A: Use disease prevalence in the population or clinical prediction rules based on patient characteristics.

Q3: What if my test result is negative?
A: For negative results, use the formula: \( P_{post} = \frac{P_{pre} \times (1 - Se)}{P_{pre} \times (1 - Se) + (1 - P_{pre}) \times Sp} \)

Q4: What are typical sensitivity and specificity values?
A: Good tests typically have Se and Sp > 0.8, but this varies by test. Always check test specifications.

Q5: Can I use percentages instead of decimals?
A: Yes, just divide percentages by 100 before entering (e.g., 20% = 0.20).