Testing Notes

NOTES NOTES TESTING SENSITIVITY (SN) & SPECIFICITY (SF) osms.it/sensitivity-specificity ▪ Validity measure; concerned with how close test’s result is to truth (i.e. did test/ instrument measure what it is intended to measure?) ▫ No perfect test → some miscalculation degree inevitable (i.e. healthy individual tests positive for disease → false positive; sick individual tests negative → false negative) ▫ Sn, Sp: complementary test characteristic measures must be used together SENSITIVITY ▪ Population proportion who test positive for disease, have disease ▪ AKA true positive rate ▪ Highly sensitive test with positive result identifies people who are truly diseased (true positives), some healthy people (false positives) ▪ Sensitivity: proportion containing all truly positive, false positives ▪ Can assume two things ▫ Test with high sensitivity is negative, individual must be healthy → rule out disease ▫ Test with high sensitivity is positive, individual may/may not have disease (ensure lack of false positive; further testing required) ▫ High sensitivity negative test → useful for ruling-out disease SPECIFICITY ▪ Population proportion tests negative for disease, free of disease ▫ AKA true negative rate ▪ Highly specific test with negative result ▪ Identifies all people who are truly free of disease (true negatives), some sick people (false negatives) ▪ Specificity: proportion containing all truly negative, false negatives; two things assumed ▫ Test with high specificity positive → confirm disease ▫ Test with high specificity negative → individual may/may not have disease (ensure not false negative; further testing required) ▪ Positive test with high specificity → useful disease confirmation CUTOFF POINT ▪ For continuous variables: sensitivity, specificity may overlap → midpoint usually sought (avoids misclassification) ▪ Cutoff point needed to distinguish between normal/healthy, abnormal/unhealthy results High cutoff point ▪ Highly specific: low false positives ▫ Everyone categorized as abnormal has disease ▪ Poorly sensible: high false negatives ▫ Not everyone categorized as normal is free of disease OSMOSIS.ORG 79

▪ I.e. previous hypertension definition stated 140/90mmHg as cutoff point ▫ Highly specific: everyone categorized as abnormal has disease ▫ Poorly sensitive: not everyone categorized as normal is free of disease Low cutoff point ▪ Poorly specific: high false positives ▫ Not everyone categorized as abnormal has disease ▪ Highly sensitive: low false negatives ▫ Everyone categorized as normal is free of disease ▪ I.e. new hypertension definition states 120/80mmHg as cutoff point ▫ Poorly specific: not everyone categorized as abnormal has diseases ▫ Highly sensitive: everyone categorized as normal is free of disease Cutoff point determined by test’s purpose ▪ Screening test ▫ Needs to detect all possible diseased → low cutoff point → highly sensitive → low false negatives ▪ Confirmatory test ▫ Need to be sure of disease presence → high cutoff point → highly specific → low false positives ▫ First test sensitivity x second test sensitivity ▪ Net specificity: proportion of healthy people that test negative on either first, second test ▫ (First test specificity + second test specificity) - (first test specificity * second test specificity) Simultaneous testing ▪ Two tests with different characteristics performed at same time → more sensitive results ▫ Simultaneous testing: three groups of people ▫ People detected only by Test A ▫ People detected only by Test B ▫ People detected by both Test A and Test B ▫ Pools all possibly relevant information → more sensitive results ▪ Sensitivity, specificity calculations must include both tests’ characteristics ▪ Net sensitivity: proportion of true cases that test positive on either test A or B ▫ (Test A sensitivity + Test B sensitivity) (Test A sensitivity x Test B sensitivity) ▪ Net specificity: proportion of healthy people that test negative on both tests A and B ▫ Test A specificity x Test B specificity SEQUENTIAL & SIMULTANEOUS TESTING Sequential testing ▪ AKA two-stage testing ▪ Consecutive tests performed with different characteristics → obtain more specific results ▫ Perform first test → positive → perform second test → positive → disease likely present ▫ Perform first test → negative → disease not likely present ▪ Similar to “double checking” results ▪ First test often easier/cheaper/less invasive than second test ▪ Sensitivity, specificity calculations must include both tests’ characteristics ▪ Net sensitivity: proportion of true cases that test positive on both first, second test 80 OSMOSIS.ORG Figure 13.1 Illustration showing how sensitivity and specificity are affected by moving the cut-off point.

Chapter 13 Biostatistics & Epidemiology: Testing POSITIVE & NEGATIVE PREDICTIVE VALUE osms.it/positive-negative-predictive-value ▪ PPV: probability that if test is positive, person has disease ▫ Divide true positives, total positive test number ▪ NPV: probability that if test is negative, person is free of disease ▫ Divide true negatives, total negative test number ▪ Both measures directly influenced by prevalence, test specificity ▫ High prevalence: more likely that person has disease → ↑ PPV ▫ Low prevalence: less likely that person has disease → ↑ NPV ▫ Low prevalence: need a good test in confirming disease (high specificity) → ↑ PPV OSMOSIS.ORG 81

TEST PRECISION & ACCURACY osms.it/test-precision-accuracy ▪ Both concerned with how likely test to be reproduced → return results close to truth ▫ Neither measuring devices nor people perfect → affects test precision, accuracy ▪ Test precision: how repeatable test results are over time, regardless of result accuracy ▫ High precision test: consistently deliver similar results, regardless of whether true/not ▪ Test accuracy: how true test results are, regardless of test repeatability ▫ High accuracy test: gives correct results; cannot always be reproduced 82 OSMOSIS.ORG ▪ Comparing test precision, accuracy ▫ Oximeter consistently (precisely) reports true pO2 (accurately) ▫ Oximeter consistently (precisely) reports pO2 20% lower than truth (not accurate) ▫ Oximeter inconsistently (not precise) reports true pO2 (accurate) ▫ Oximeter inconsistently (not precise) reports pO2 20% lower than truth (not accurate)