Sensitivity
Calculate diagnostic test sensitivity (true positive rate) from TP and FN values. Free online sensitivity calculator with charts, breakdown tables, and formula reference.
About This Calculator
The Sensitivity Calculator helps you compute the true positive rate (recall) of a diagnostic test or classification model using the standard formula: Sensitivity = TP / (TP + FN). Sensitivity, also known as the true positive rate, measures the proportion of actual positive cases that a test correctly identifies. It is one of the most important metrics in diagnostic test evaluation, medical screening, and machine learning classification.
The calculation uses your input of true positives (TP) — people with the condition who tested positive — and false negatives (FN) — people with the condition who tested negative. The sensitivity is expressed as a percentage, where a higher value indicates the test is better at detecting the condition. A highly sensitive test rarely produces false negatives, making it ideal for screening where missing a case could have serious consequences.
Regional Notes
India: The Indian Council of Medical Research (ICMR) evaluates diagnostic tests for diseases like tuberculosis, COVID-19, and dengue using sensitivity analysis. The National Health Mission uses sensitivity thresholds for screening programmes across states.
United States: The FDA requires diagnostic test manufacturers to report sensitivity in 510(k) and PMA submissions. Clinical laboratories follow CLIA guidelines for test validation. The CDC uses sensitivity analysis for infectious disease surveillance and screening recommendations.
United Kingdom: The UK National Screening Committee evaluates screening programmes using sensitivity as a key performance indicator. NICE guidelines reference sensitivity in diagnostic technology appraisals, and NHS laboratories validate tests against sensitivity benchmarks.
Frequently Asked Questions
What is sensitivity in diagnostic testing?
Sensitivity, also called the true positive rate or recall, measures the proportion of actual positive cases that are correctly identified by a diagnostic test. It answers the question: 'Of all people who have the condition, how many did the test correctly identify as positive?'
What is the formula for sensitivity?
The sensitivity formula is: Sensitivity = TP / (TP + FN), where TP is the number of true positives (correctly identified cases) and FN is the number of false negatives (missed cases). The result is typically expressed as a percentage.
What is the difference between sensitivity and specificity?
Sensitivity measures how well a test identifies true positive cases (TP / (TP + FN)), while specificity measures how well it identifies true negative cases (TN / (TN + FP)). A highly sensitive test rarely misses positive cases, while a highly specific test rarely mislabels negative cases as positive.
What is a good sensitivity value for a diagnostic test?
A good sensitivity depends on the clinical context. For screening tests, sensitivity above 90% is preferred to avoid missing cases. For confirmatory tests, high specificity is often more important. In the US, the FDA evaluates test sensitivity in premarket submissions. The UK National Screening Committee recommends sensitivity above 80% for population screening programmes.
How does sensitivity relate to false negatives?
Sensitivity and false negative rate (FNR) are complementary: FNR = 1 − Sensitivity. A test with 95% sensitivity has a 5% false negative rate, meaning 5 out of every 100 people with the condition will receive a negative test result. Minimizing false negatives is critical for diseases where early detection is important.
What is the difference between sensitivity and positive predictive value?
Sensitivity (TP / (TP + FN)) measures the test's ability to detect the condition among those who have it. Positive Predictive Value or PPV (TP / (TP + FP)) measures the probability that a positive test result truly indicates the condition. PPV depends on disease prevalence, while sensitivity is a property of the test itself.
Can sensitivity be 100%?
Yes, a test can have 100% sensitivity if it identifies all positive cases correctly (FN = 0). However, such tests often have lower specificity because the threshold is set very low. A test with 100% sensitivity but low specificity may produce many false positives, making it useful for screening but requiring confirmatory testing.