16. A new test was developed for screening of breast cancer. This new test was applied on 750 women known early cases of breast cancer and 900 women free from cervical cancer on the gold standard test. The new test was positive for 600 women with breast cancer and 60 women without breast cancer.
a. Construct a two-by-two table showing the above screening test results and disease status
b. Calculate Sensitivity
c. Calculate Specificity
d. Calculate Positive predictive value
e. Calculate Negative predictive value
f. Calculate yield
Yeah I agree it is C
To answer these questions, we need to construct a two-by-two table showing the screening test results and disease status. The table will look like this:
Disease Present (+) Disease Absent (-)
Test Positive 600 60
Test Negative 150 840
Now, let's calculate the values for each question:
a. Construct a two-by-two table showing the above screening test results and disease status:
This has already been constructed in the table above.
b. Calculate Sensitivity:
Sensitivity measures the proportion of true positive results among all individuals with the disease. It is calculated using the formula:
Sensitivity = (True Positives) / (True Positives + False Negatives)
In this case, the true positives are 600 (women with breast cancer who tested positive) and the false negatives are 150 (women with breast cancer who tested negative).
So, Sensitivity = 600 / (600 + 150) = 0.8
c. Calculate Specificity:
Specificity measures the proportion of true negative results among all individuals without the disease. It is calculated using the formula:
Specificity = (True Negatives) / (True Negatives + False Positives)
In this case, the true negatives are 840 (women without breast cancer who tested negative) and the false positives are 60 (women without breast cancer who tested positive).
So, Specificity = 840 / (840 + 60) = 0.9333
d. Calculate Positive predictive value:
Positive predictive value (PPV) measures the proportion of true positive results among all individuals who tested positive. It is calculated using the formula:
PPV = (True Positives) / (True Positives + False Positives)
In this case, the true positives are 600 (women with breast cancer who tested positive) and the false positives are 60 (women without breast cancer who tested positive).
So, PPV = 600 / (600 + 60) = 0.9091
e. Calculate Negative predictive value:
Negative predictive value (NPV) measures the proportion of true negative results among all individuals who tested negative. It is calculated using the formula:
NPV = (True Negatives) / (True Negatives + False Negatives)
In this case, the true negatives are 840 (women without breast cancer who tested negative) and the false negatives are 150 (women with breast cancer who tested negative).
So, NPV = 840 / (840 + 150) = 0.8485
f. Calculate Yield:
Yield measures the proportion of individuals who tested positive among all individuals who were screened. It is calculated using the formula:
Yield = (True Positives) / (True Positives + False Positives + False Negatives)
In this case, the true positives are 600 (women with breast cancer who tested positive), the false positives are 60 (women without breast cancer who tested positive), and the false negatives are 150 (women with breast cancer who tested negative).
So, Yield = 600 / (600 + 60 + 150) = 0.7353