Diagnostic Test Characteristics Flashcards
Indicated by fever, headache, fatigue, and a characteristic skin rash (erythema migrans)
Lyme disease
Caused by the bacterium Borrelia Burgdorferi
-transmitted through the bite of infected blacklegged ticks
Lyme disease
A serological test for lyme disease has a:
- ) Sensitivity of
- ) Specificity of
- ) 95%
2. ) 90%
A form of testing based on test results that predicts the disease status
Diagnostic testing
To develop a diagnostic test, you want to compare it to a current
Gold standard
To develop a diagnostic test, you want to define the test results, meaning what is the
Accuracy, and what is a misclassification
What two aspects make up conditional probability?
- ) Sensitivity
2. ) Specificity
The probability of testing positive, given that a patient has a disease
Sensitivity
The probability of testing negative, given that a patient does not have the disease
Specificity
Diagnostic testing requires which three things?
Sensitivity, specificity, and prevalence
The proportion of a group of people possessing a clinical condition or outcome at a given point in time
Prevalence
Can be thought of as the probability of disease before the test result is known
Prevalence
What are two other names for prevalence
Prior probability and pretest probability
The probability of having a disease given a positive test result
Positive Predictive value (“Predictive value positive)
The probability of not having a disease, given a negative test result
Negative Predictive value of a test (“predictive value negative”)
A diagnostic test’s accuracy is determined by comparing it to a
Gold Standard
Comes from the pretest probability and likelihood ratio and is used to derive the posttest probability
Nomogram
Summarize both sensitivity and specificity into one number
Likelihood ratio
How do we find the positive likelihood ratio (LR+)?
LR+ = sensitivity / (1-specificity)
How do we find the negative likelihood ratio (LR-)?
LR- = (1-sensitivity) / Specificity
Defined as the probability of that test result in people with the disease divided by the probability of the result in people without the disease
Likelihood ratio
Express how many times more (or less) likely a test result is to be found in diseased, compared with non-diseased, people
Likelihood ratios
To simplify likelihood ratios: values between 0 and 1
Decrease the probability of disease
To simplify likelihood ratios: values greater than 1
Increase the probability of disease
The probability of disease is not affected if the likelihood ratio is
1
How do we use the likelihood ratio to calculate the post test odds?
Posttest odds = Pretest odds (prevalence) x LR
What are odds?
Odds = probability of event / (1- probability of event)
What is probability?
Probability = Odds / (1 + odds)
What are the factors on predictive values?
Prevalence, specificity, sensitivity
The probability of disease, given the results of a test is called the
Predictive value
The more sensitive a test is, the better will be it’s
Negative Predictive Value
The more specific the test is, the better will be its
PPV
Assesses how confident the clinician can be that a negative test rules out the disease being sought
NPV
Assesses how confident the clinician can be that a positive test confirms the diagnosis
PPV
Positive results, even for a very specific test, when applied to patients with a low likelihood of having the disease will largely be
False positives
The ratio of the proportion of diseased people with a positive test result to the proportion of nondiseased people with a positive result
LR+
The ratio of the proportion of diseased people with a negative test result divided by the proportion of non-diseased people with a negative test result
LR-
Will rarely miss people with the disease
Sensitive tests
Will rarely misclassify people as having the disease when they do not
Specific tests
A highly sensitive test is most helpful to the clinician when the test result is
Negative
Most useful to confirm a diagnosis
-rarely gives false positives
Specific test
