QuestionSBA
QuestionChoice
Sensitivity of a test is the ability of a test to correctly identify those with a disease.

Sensitivity = true positives / (true positives + false negatives)

So in this case 80/(80+15) = 84.2%
32543
a
84.2%
QuestionChoice
This is the number of true negatives expressed as a percentage, not the sensitivity
32544
b
92.0%
QuestionChoice
This is the number of true positives expressed as a percentage, not the sensitivity
32545
c
80.0%
QuestionChoice
This is the specificity of the test, not the sensitivity. Specificity of a test is the ability of the test to correctly identify those without a disease.

Specificity = true negatives / (true negatives + false positives).
In this case = 920/(920+3) = 99.7%
32546
d
99.7%
QuestionChoice
This is the number of true negatives expressed as a percentage, not the sensitivity
32547
e
90.2%
Concept
Chapter
# Overview 

Several key parameters can be calculated to help describe how effective a certain test is at diagnosing a condition.

|                    | Patients with colon cancer | No cancer |
| ------------------ | :------------------------: | --------: |
| Biomarker positive |             a              |         b |
| Biomarker negative |             c              |         d |

# Sensitivity

Sensitivity is the proportion of people with the condition who will have a positive result. If, for example, the sensitivity of a test is 80%, out of a hundred people with the condition, only 80 will have a positive test result.

Sensitivity = a/(a+c)

# Specificity

Specificity describes the proportion of people without the disease who will have a negative test. A specificity of 90% can be interpreted as, out of 100 people without the disease, 90 will have a negative test result.

Specificity = d/(b+d)

# Positive Predictive Value

Positive predictive value (PPV) is the proportion of people with a positive test who actually have the disease. PPV varies with prevalence of disease in a population. The lower the prevalence, the lower the positive predictive value. A PPV of 78% will mean that if 100 people tested positive, 78 people will have the disease.

PPV = a/(a+b)

# Negative Predictive Value

Negative predictive value (NPV) is the proportion of people with a negative test who truly do not have the disease.

NPV varies with prevalence of disease in a population. The lower the prevalence, the higher the negative predictive value. An NPV of 97% will mean that if 100 people tested negative, 97 people will not have the disease.

NPV = d/(c+d)

# False positive rate

The false positive rate is the proportion of those without the condition who will test positive.

False positive rate = 1 - specificity

False negative rate = 1 - d/(b+d)

# False negative rate

The false negative rate is the proportion of those with the condition who will test negative.

False negative rate = 1 - sensitivity

False negative rate = 1 - a/(a+c)

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Evaluation of a diagnostic test
Topic
51
Medical Statistics
6509
Sensitivity measures a test's ability to correctly identify individuals with a disease, calculated as true positives divided by the sum of true positives and false negatives.
A company develops a new coronavirus test. They trial it on 1000 people and have 83 positive tests, of which 80 were later confirmed to be positive through alternative means of testing. Of those who tested negative, 15 were later confirmed positive through alternative testing.

What is the sensitivity of the new test?
a