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# Sensitivity and Specificity

Sensitivity and Specificity

Characteristics of Screening

In order for screening to take place, it must be feasible. In other words, it must be economical, highly reliable and valid, free of risk, available to a large number of individuals, and ethical to screen.

For this Application Assignment please download the Sensitivity/Specificity Problem Set and submit your responses.

Sensitivity and Specificity

Sensitivity/Specificity Problem Set

For Week 11’s Application Assignment complete this Sensitivity and Specificity problem set. Make sure to check the Calculation Application Rubric prior to submitting your responses.

Clearly mark your responses for each question.

When you are completed, submit to the Week 11: Application Dropbox using the correct naming convention on the file. See Week 11’s Application page for directions.

1. Sensitivity is:
2. The probability that a test correctly classifies as positive those who have preclinical disease.
3. The probability that a test correctly classifies individuals without preclinical disease as negative
4. The probability that those who test positive have the preclinical disease
5. The probability that those who test negative do not have the preclinical disease
• Specificity is:
• The probability that a test correctly classifies as positive those who have preclinical disease.
• The probability that a test correctly classifies individuals without preclinical disease as negative
• The probability that those who test positive have the preclinical disease
• The probability that those who test negative do not have the preclinical disease

A screening examination was performed on 250 persons for Factor X, which is found in disease Y. A definitive diagnosis for disease Y among the 250 persons had been obtained previously. The results are charted below:

• The sensitivity of this test is expressed as:
• 40%
• 70%
• 29%
• 80%
• The specificity of this test is expressed as:
• 40%
• 70%
• 7%
• 80%
• The positive predictive value of this test is:
• 40%
• 70%
• 7%
• 80%
• The negative predictive value of this test is:
• 40%
• 70%
• 93%
• 80%
• If the same screening test is conducted in two populations, one with a high prevalence of the disease and one with a low prevalence of the disease, assuming the sensitivity and specificity of the screening test are the same, which of the following statements about positive predictive value (PPV) applies:
1. PPV is higher in the screened population with higher prevalence
2. PPV is lower in the screened population with higher prevalence
3. PPV is the same in both populations
4. It cannot be determined
• Lead time bias can be described as:
• An apparently lower survival rate among persons screened compared to an unscreened group.
• A bias that occurs because screening tends to identify cases with less aggressive forms of the disease
• A similar survival time for persons identified during a screening program relative to persons who are diagnosed by clinical symptoms.
• An apparently longer survival time among those identified during a screening program because they were identified at an earlier stage of their disease
• Length-Bias can be described as:
• An apparently lower survival rate among persons screened compared to an unscreened group.
• A bias that occurs because screening tends to identify cases with less aggressive forms of the disease
• A similar survival time for persons identified during a screening program relative to persons who are diagnosed by clinical symptoms.
• An apparently longer survival time among those identified during a screening program because they were identified at an earlier stage of their disease

A new screening test for a disease is developed for use in the general population. The sensitivity and specificity of the new test are 60% and 70%, respectively. Four hundred (400) people are screened at a clinic during the first year the new test is implemented. (Assume the true prevalence of the disease among clinic attendees is 10%.)

Calculate the following values:

1. The predictive value of a positive test is:
2. 13.3%
3. 18.2%
4. 24%
5. 22.2%
1. The number of false positives is:
2. 108
3. 132
4. 24
5. 252
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