1. What is PSA Test Sensitivity?

Sensitivity measures how well a PSA test correctly identifies individuals with prostate cancer. It's the proportion of true positives (people with cancer who test positive) among all people who actually have the disease (true positives + false negatives).

2. How Does the Calculator Work?

The calculator uses the sensitivity formula:

Where:

• \( TP \) — True Positives (people with cancer who test positive)
• \( FN \) — False Negatives (people with cancer who test negative)

Explanation: Sensitivity ranges from 0 to 1 (or 0% to 100%). Higher values indicate better test performance at detecting disease.

3. Importance of Sensitivity Calculation

Details: Understanding PSA test sensitivity helps clinicians interpret test results and assess the likelihood of missing prostate cancer cases. It's crucial for evaluating screening programs and diagnostic tests.

4. Using the Calculator

Tips: Enter the number of true positive and false negative cases from a study or clinical data. Both values must be non-negative integers, and their sum must be greater than zero.

5. Frequently Asked Questions (FAQ)

Q1: What is a good sensitivity value for PSA tests?
A: Typical PSA test sensitivity ranges from 70-90% at common thresholds (e.g., 4.0 ng/mL), but depends on the cutoff used and population characteristics.

Q2: How does sensitivity relate to specificity?
A: Sensitivity and specificity are inversely related. Lowering the PSA threshold increases sensitivity but decreases specificity.

Q3: Why might PSA sensitivity vary?
A: Sensitivity depends on factors like cancer stage, patient age, prostate volume, and the specific PSA threshold used.

Q4: What's the difference between sensitivity and PPV?
A: Sensitivity measures detection rate in diseased individuals, while positive predictive value (PPV) measures the probability of disease given a positive test.

Q5: How can sensitivity be improved?
A: Using lower PSA thresholds, incorporating PSA velocity/density, or adding new biomarkers can improve sensitivity but may increase false positives.