Updated: 2/9/2022

# Testing and Screening

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 Overview Diagnostic testing performance is measured in a variety of ways Sensitivity and specificity describe the frequency of test results by disease status Positive and negative predictive value describe the frequency of disease status by test result Precision and accuracy describe different types of variation in test results Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value These 4 measures describe how well diagnostic tests capture the true presence or absence of disease  Predictive value changes with disease prevalence, sensitivity and specificity do not A 2x2 contingency table can help with calculations  sensitivity (SN)   % with disease who test positive = a/(a+c) = TP/(TP+FN)  highly sensitive tests are good at ruling out disease (rule out SnOut) tests with high sensitivity are good for screening purposes  e.g., COVID-19 testing would benefit from high sensitivity so all potential cases can be isolated quickly, even if that means briefly isolating those who do not have the disease until follow-up test results return false negative rate = 1-sensitivity specificity (SP)  % without disease who test negative = d/(b+d) = TN/(FP+TN) highly specific tests are good at ruling in disease (rule in SpIn) tests with high specificity are good confirmatory tests e.g., after a patient screens positive for HIV on a rapid test, the confirmatory test should be highly specific to ensure that the person is not given a false positive diagnosis of a serious illness false positive rate = 1-specificity positive predictive value (PPV)        % positive test results that are true positives = a/(a+b) = TP/(TP+FP)  ↑ prevalence causes ↑ PPV negative predictive value (NPV)   % negative test results that are true negatives = d/(c+d) = TN/(FN+TN)  ↑ prevalence causes ↓ NPV  Cut-off point for positivity may be adjusted to optimize sensitivity and specificity for different purposes, which are inversely related (cut-off point with decreased sensitivity is associated with increased specificity and vice-versa)   Receiver operating characteristic (ROC) curves are a graphical depiction of a test's overall diagnostic performance Y axis sensitivity X axis 1-specificity the closer the curve fills out the top left corner, the better the test is performance is quantified by the area under the curve (AUC) an AUC of 0.5 states that the test performs no better than chance (bad test!) an AUC of 0.9 suggests a better-performing test Likelihood Ratios (LRs) Also used to assess diagnostic test performance in isolation or in sequence Does not change with disease prevalence Represents the probability of a patient with a disease having a positive or negative test result in comparison to the probability of a patient without the disease having a positive or negative test result Positive LR "How many times more likely is a positive test result observed in cases versus non-cases?" suggests how well disease is ruled in = probability of positive test in cases/probability of positive test in non-cases = true positive/false positive = sensitivity/1-specificity = [a/(a+c)]/[1-(d/(b+d))] or [a/(a+c)]/[b/(b+d)] positive LR > 1 suggests that patients with the disease are more likely to have a positive result compared to those without the disease Negative LR "How many times more likely is a negative test result observed in cases versus non-cases?" suggests how well disease is ruled out = probability of negative test in cases/probability of negative test in non-cases = false negative/true negative = 1-sensitivity/specificity = [1-a/(a+c)]/[d/(b+d)] or [c/(a+c)]/[d/(b+d)] negative LR < 1 suggests that patients with the disease are less likely to have a negative result compared to those without the disease
 Precision and Accuracy Precision    also known as reliability   consistent  reproducible no random variation Accuracy  reflects true value no systematic variation

Average 3.7 of 20 Ratings

Questions (19)
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(M1.ST.14.10) A new real time-PCR test for the hepatitis C virus is approved for medical use. The manufacturer sets the threshold number of DNA copies required to achieve a positive result such that the sensitivity is 98% and the specificity is 80%. The tested population has a hepatitis C prevalence of 0.7%. Which of the following changes in the prevalence, incidence, or threshold concentration will increase the positive predictive value of the test, if the other two values are held constant?

QID: 103972
1

An increase in incidence

10%

(7/72)

2

An increase in prevalence

57%

(41/72)

3

A decrease in incidence

7%

(5/72)

4

A decrease in prevalence

0%

(0/72)

5

Lowering the threshold concentration required for a positive test.

15%

(11/72)

M 1 E

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(M1.ST.14.25) An at-home recreational drug screening test kit is currently being developed. They consult you for assistance with determining an ideal cut-off point for the level of the serum marker in the test kit. This cut-off point will determine what level of serum marker is associated with a positive or negative test, with serum marker levels greater than the cut-off point indicative of a positive test and vice-versa. The cut-off level is initially set at 4 mg/uL, which is associated with a sensitivity of 92% and a specificity of 97%. How will the sensitivity and specificity of the test change if the cut-off level is raised to 6 mg/uL?

QID: 105635
1

Sensitivity decreases, specificity decreases

1%

(1/84)

2

Sensitivity increases, specificity decreases

20%

(17/84)

3

Sensitivity decreases, specificity increases

54%

(45/84)

4

Sensitivity increases, specificity increases

10%

(8/84)

5

Sensitivity decreases, specificity may increase or decrease

7%

(6/84)

M 1 D

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(M1.ST.14.6) A 16-year-old female is seen at her outpatient primary medical doctor's office complaining of a sore throat. Further history reveals that she has no cough and physical exam is notable for tonsillar exudates. Vitals in the office reveal HR 88, RR 16, and T 102.1. Using the Centor criteria for determining likelihood of Group A beta-hemolytic strep pharyngitis, the patient has a score of 3. A review of the primary literature yields the findings in Image A. What is the specificity of the Centor criteria using a score of 3 as a cutoff value?

QID: 103968
FIGURES:
1

9/54 = 17%

4%

(2/54)

2

41/50 = 82%

57%

(31/54)

3

41/46 = 89%

15%

(8/54)

4

45/50 = 90%

2%

(1/54)

5

Not enough information has been provided

4%

(2/54)

M 1 E

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(M1.ST.13.4) Health officials are considering a change be made to the interpretation of the tuberculin skin test that will change the cut-off for a positive purified protein derivative (PPD) from 10 mm to 5 mm for healthcare workers. Which of the following is a true statement regarding this potential change?

QID: 103966
1

This change will decrease the positive predictive value of the test

38%

(20/52)

2

This change will decrease the negative predictive value of the test

19%

(10/52)

3

This change will not change the negative predictive value of the test

12%

(6/52)

4

This change will not change the sensitivity of the test

4%

(2/52)

5

This change will increase the specificity of the test

17%

(9/52)

M 1 D

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(M1.ST.12.1) As a public health practitioner, you are charged with choosing which blood test to use for the screening of a new infectious disease. You want to ensure that as many cases of this disease as possible are picked up by this initial screening test. Which of the following is the highest priority characteristic of this new test?

QID: 103963
1

Highly sensitive test

77%

(58/75)

2

Highly specific test

8%

(6/75)

3

Low false positive rate

0%

(0/75)

4

High true positive rate

4%

(3/75)

5

Low negative predictive value

3%

(2/75)

M 1 D

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Evidence (16)
VIDEOS & PODCASTS (3)