Evidence based medicine Diagnostic tests Ross Lawrenson

Diagnostic tests When looking at a paper about a diagnostic test we ask ourselves three questions.

Diagnostic tests Is this test useful?

Diagnostic tests Is this test useful? Is it reliable?

Diagnostic tests Is this test useful? Is it reliable? Is it valid?

Is this test useful? The test should have been researched in a study population relevant to the individual or population in whom it is to be used.

Reliability Reliability refers to the repeatability or reproducibility of a test. It can be assessed by repeating the test using the same or different observers.

Validity Relates to whether the test measures what it purports to measure. Is the result true?

Validity For example if you measure blood pressure in an obese patient and use a cuff that is too small you are likely to get a falsely high reading. The reading maybe reliable (you get the same blood pressure if you do it again) but it lacks validity.

Sensitivity and specificity

DiseaseHealthyTotal Test + a b a+b Test - c d c+d Total a+c b+d Sensitivity and specificity

Sensitivity The probability that the test will be positive if the disease is present = a/a+c

Sensitivity The probability that the test will be positive if the disease is present = a/a+c A sensitive test is likely to also record a number of false positive tests

Sensitivity If the cut off point of this test is set low then it will be sensitive (all patients with disease will test positive) but there will also be a number of false positives DiseasedHealthy

Specificity Theprobability that the test will be negative if the disease is truly absent. d/b+d

Specificity Theprobability that the test will be negative if the disease is truly absent. d/b+d In this situation there is a high likelihood of false negatives.

Accuracy of the test (a+d)/(a+b+c+d)

Example 5000 women underwent a test for blood glucose at 24 weeks following a glucose load. 243 women were found to have a blood glucose greater than 6.8 mmol/L and were referred for an OGTT. 186 were found to have gestational diabetes. Four women who initially had tested negative were diagnosed as having diabetes later in their pregnancy.

Example Prevalence Sensitivity Specificity Positive predictive value Negative predictive value Likelihood ratio + test Likelihood ratio - test Accuracy

DiabetesNo diabetesTotal Positive Negative Total

Example Prevalence190/5000 Sensitivity186/190 Specificity4753/4810 Positive predictive value186/243 Negative predictive value4753/4757 Likelihood ratio + test(186/190)/(57/4810) Likelihood ratio - test(4/190)/(4753/4810) Accuracy /5000

Gold standard..

The gold standard is the test or battery of tests that will most accurately diagnose a particular disease or condition. Thus traditionally the OGTT has been seen as the gold standard when testing for diabetes. Other diagnostic tests may have a gold standard that is too expensive or invasive for routine use e.g. fluoroscein angiography for diabetic retinopathy. Sometimes the gold standard is a battery of tests or symptoms e.g. the Jones criteria for rheumatic fever

Percent agreement AbnormalSuspectNormal AbnormalABC SuspectDEF NormalGHI Percent agreement = (A+E+I) / Total X100

Percent agreement MelanomaIndeterminateBenign Melanoma101 Indeterminate000 Benign0016 Percent agreement = ( )/37 X100 = 70 %

KAPPA SecondExam NormalRetinopathyTotal FirstNormal ExamRetinopathy Total Observed agreement = /100 = 78%

KAPPA SecondExam NormalRetinopathyTotal FirstNormal58%x5642%x5656 ExamRetinopathy58%x4442%x4444 Total

KAPPA SecondExam NormalRetinopathyTotal FirstNormal ExamRetinopathy Total Agreement expected by chance = /100 =51%