Question

1. The percentage of tested patients with disease who actually tested positive is called:

a. Specificity
b. Negative predictive value
c. Sensitivity
d. Positive predictive value

2.

The percentage of patients with a negative test who actually do NOT have the disease is called:

a. Negative predictive value
b. Sensitivity
c. Specificity
d. Positive predictive value

3. The percentage of tested patients without disease who actually tested negative is called:

a. Negative predictive value
b. Specificity
c. Sensitivity
d. Positive predictive value

4. In simultaneous testing, there is a:

a. a net gain in sensitivity and a net gain in specificity.
b. net gain in sensitivity and a net loss in specificity.
c. a net loss in sensitivity and a net loss in specificity.
d. a net loss in sensitivity and a net gain in specificity.

5. The percentage of patients with a positive test who actually have the disease is called:

a. Specificity
b. Negative predictive value
c. Positive predictive value
d. Sensitivity

6. Which of the following can impact a predictive value?

a. Sensitivity if the disease is rare
b. Incidence
c. Whether the disease is treatable
d. Prevalence

7. The ability of a test to determine who does and who does not have disease is measured by

a. Positive predictive value
b. Sensitivity and specificity
c. Predictive values
d, Sensitivity

8. In sequential testing, there is a:

a. net gain in sensitivity and a net loss in specificity.
b. net gain in sensitivity and a net gain in specificity.
c. net loss in sensitivity and a net gain in specificity.
d. net loss in sensitivity and a net loss in specificity.

9. In sequential testing, a person with a negative test is given a second test.

a. True
b. False

10. A Kappa statistic of 0.55 indicates
a. High Intrasubject variability (low agreement)
b. High interobserver variability (low agreement)
c. Medium interobserver variability (medium agreement)
d. Low intraobserver variability (high agreement)

Answer 1

1.The percentage of tested patients with disease who actually tested positive is called:

a. Specificity
b. Negative predictive value
c. Sensitivity
d. Positive predictive value

answer:c sensitivity

explanation of the correct answer option:

Sensitivity is defined as the proportionate/ percentage of the sick people who are correctly identified as having the illness by the test.

sensitivity percentage=diseased people with positive test/all diseased people*100

sensitivity percentage= [true positives / false negative+true positives]  * 100

Since the above statement corresponds to the definition of sensitivity,hence this is the answer option.

the reason why the other options are not be correct answer:

Specificity is the percentage or proportion of the healthy people without the illness correctly identified by the test as not having the illness.Positive predictive value of a test is the probability that the persons with a positive test actually have the disease. Negative predictive value of a test is the probability that the persons with a negative test will actually not have the disease. Since the above statement does not correspond to the definitions of specificity, positive predictive value and negative predictive value, these options are not the correct answer options.

2.The percentage of patients with a negative test who actually do NOT have the disease is called:

a. Negative predictive value
b. Sensitivity
c. Specificity
d. Positive predictive value

answer: a. Negative predictive value

explanation of the correct answer option :

NPV equal to the probability that a patient is not having the disease when the test is negative.

Negative predictive value percentage =[true negatives / true negative + false negative] * 100

Negative predictive value of a test is the probability that the persons with a negative test will actually not have the disease. Since the above statement corresponds to the definition of negative predictive value,hence this is  the correct answer option.

the reason why the other options are not be correct answer:

Sensitivity is defined as the proportionate/ percentage of the sick people who are correctly identified as having the illnessSpecificity is the percentage or proportion of the healthy people without the illness correctly identified by the test as not having the illness..Positive predictive value of a test is the probability that the persons with a positive test actually have the disease. Negative predictive value of a test is the probability that the persons with a negative test will actually not have the disease. Since the above statement does not correspond to the definitions of specificity ,sensitivity, positive predictive value and corresponds to the definition of negative predictive value, these other 3 options are not the answer options

3. The percentage of tested patients without disease who actually tested negative is called:

a. Negative predictive value
b. Specificity
c. Sensitivity
d. Positive predictive value

answer b. Specificity

explanation of the correct answer option :

Specificity is the percentage or proportion of the healthy people without the illness correctly identified by the test as not having the illness.

specificity percentage=[nondiseased with negative test/total nondiseased]*100

specificity percentage =[true negative/true negative+false positive ]* 100

Since the above statement corresponds to the definition of specificity,hence this is the answer option.

the reason why the other options are not the correct answer:

Sensitivity is defined as the proportionate/ percentage of the sick people who are correctly identified as having the illness.Specificity is the percentage or proportion of the healthy people without the illness correctly identified by the test as not having the illness..Positive predictive value of a test is the probability that the persons with a positive test actually have the disease.. Negative predictive value of a test is the probability that the persons with a negative test will actually not have the disease.Since the rest three options do not correspond to the definitions of specificity as in the statement given, these are not the answer options.

4. In simultaneous testing, there is a:

a. a net gain in sensitivity and a net gain in specificity.
b. net gain in sensitivity and a net loss in specificity.
c. a net loss in sensitivity and a net loss in specificity.
d. a net loss in sensitivity and a net gain in specificity.

answer:optionb. net gain in sensitivity and a net loss in specificity.

explanation of the correct answer option :

In simultaneous testing, there is a net increase in the sensitivity as each of the two tests individually identify the diseased people thereby increasing the sensitivity of the test. So there is a net gain in the sensitivity. In simultaneous testing as there is an overlap in the percentage of the people without the illness as correctly identified by the test in not having the illness,this net specificity percentage decreases. ,hence this is the answer option.

the reason why the other options are not the correct answer:

In sequential testing ,two tests are applied serially for detecting the disease. There is a net loss in the sensitivity in  the sequential testing as the number of people correctly labelled positive decreases but overall gain in the specificity as the number of people correctly labelled negative increases. Hence in sequential testing, there is a overall loss in the net sensitivity and gain in the net specificity.Since the other three options do not  correspond to the results obtained in a simultaneous testing, they are not the correct answer options.

8. In sequential testing, there is a:

a. net gain in sensitivity and a net loss in specificity.
b. net gain in sensitivity and a net gain in specificity.
c. net loss in sensitivity and a net gain in specificity.
d. net loss in sensitivity and a net loss in specificity.

answer c. net loss in sensitivity and a net gain in specificity.

explanation of the correct answer option :

In sequential testing, two tests are applied serially for detecting the disease. There is a net loss in the sensitivity of the sequential testing as the number of people correctly labelled positive decreases but overall gain in the specificity as the number of people correctly labelled negative increases. Hence in sequential testing. there is a overall loss in the net sensitivity and gain in the next specificity(option )c.So this is the correct answer.

the reason why the other options are not the correct answer:

In simultaneous testing, there is a net increase in the sensitivity as each of the two tests individually identify the diseased people thereby increasing the sensitivity of the test. So there is a net gain in the sensitivity. In simultaneous testing as there is an overlap in the percentage of the people without the illness as correctly identified by the test in not having the illnesses, this net specificity percentage decreases. Since the other three statements do not correspond to the results obtained in a sequential  testing, they are not the correct answer options.