Question

The Table below presents data related to a screening test for breast cancer. Questions 5 – 8 refer to the data in the Table.

Screening Test for Breast Cancer Cancer

	Cancer Confirmed	Cancer not Confirmed	Total
Positive	132	983	1115
Negative	45	63650	63695
Total	177	64633	64810

5. Using the data in the above table, present the formula and calculate the sensitivity of the screening test.

6. What is the specificity of the screening test (show the formula along with your calculation)?

7. What is the PV+ (include the formula with your answer)?

8. What is the PV_ (include the formula with your answer)?

Answer 1

1. To calculate sensitivity, the formula is:

$Sensitivity=\frac{TruePositives}{TruePositives+FalseNegatives)}$

True positives are 132, false negatives are 45 so;

$Sensitivity=\frac{132}{132+45}$

$Sensitivity=\frac{132}{177}$

$Sensitivity=0.75$

2. To calculate specificity, the formula is:

$Specificity=\frac{TrueNegatives}{TrueNegatives+FalsePositives}$

Where true negatives are 63,650 and false positives are 983. So;

$Specificity=\frac{63650}{63650+983}$

$Specificity=\frac{63650}{64633}$

$Specificity=0.99$

3. To find Positive Predictive value, the formula is:

$Predictive Value+=\frac{TruePositives}{TruePositives+FalsePositives}$

$Predictive Value+=\frac{132}{132+983}$

$Predictive Value+=\frac{132}{1115}$

$Predictive Value+=0.12$

4. To find Negaitive Predictive value, the formula is:

$Predictive Value-=\frac{TrueNegatives}{TrueNegatives+FalseNegatives}$

$Predictive Value-=\frac{63650}{63650+45}$

$Predictive Value-=\frac{63650}{63695}$

$Predictive Value-=0.999 \approx 1.00$