Case of Screening

Screening is defined as the search for unrecognized disease or defect by means of rapidly applied tests, examinations or other procedures in apparently healthy individuals.

The intention of screening is to identify disease in a community early, thus enabling earlier intervention and management in the hope to reduce mortality and suffering from a disease.

Case Scenario 1:

A mammography screening test for breast cancer was performed on 500 females. Screening test was positive in 100 individuals out of which only 35 females were positive for disease by Fine needle aspiration cytology.  250 females were true negative.

1. Construct  2 x 2 table for the above information
2. Label a, b, c & d cells.
3. Calculate validity of the screening test & interpret your results in words.

Case Scenario 2:

A screening test was applied on smokers and nonsmokers to diagnose lung cancer in 1000 individuals. Out of 1000 individuals, 100 were smokers, out of whom 75 were diagnosed with lung cancer on Lung Biopsy. 900 were non-smokers out of whom 125 were diagnosed with lung cancer.

1. Construct a 2 * 2 table by the above information
2. Label a, b, c and d.
3. Calculate Yield of the screening test & interpret your results in words.

Case Scenario 3:

1. Calculate prevalence of the disease
2. Calculate Accuracy & validity of the screening test & interpret your result in words.

Case Scenario 4:

In Village XYZ of Rawalpindi whose population is 1000, diabetes prevalence is 2 %.  A screening test was applied on all population. Screening test was applied with sensitivity of 90 % and specificity of 95 %.

1. Construct a 2 X 2 table with the above information.
2. Calculate positive predictive value and negative predictive value & interpret your results in words.

Learning Objectives:-

1. Iceberg Phenomenon of disease.
2. Time lag, lead time and screening time concepts.
3. Screening aims and objectives
4. Uses and types of Screening
5. Screening test principles and its criteria (Wilson’s criteria)
6. Shall be able to construct a 2 X 2 Table and be able to evaluate a screening test by finding out its
   • Validity = Sensitivity & specificity,
   • Yield = Positive predictive value and negative predictive values.
   • Accuracy and Prevalence of the disease
   • Shall be able to interpret the results in words.

Case scenario 1:

a) Construct  2X2 table & label a,b,c,d cells

	Disease	No Disease	Total
Test +ve	35 (True +ve)	65 (False +ve)	100
Test -ve	150 (False –ve)	250 (True –ve)	400
Total	185	315	500

b)Calculate validity of the test & interpret your results

Sensitivity = a/(a+c) x 100

= 35/185 x 100

= 18.91%

Specificity= d/(b+d) x 100

= 250/315 x 100

= 79.36%

Accuracy= (a+d)/(a+b+c+d) x 100

= (35+250)/500 x 100

= 85%

• The ability to detect true +ve is 18.91%
• The ability to detect true -ve is 79.36%
• Accuracy of the screening test is 85%

Case scenario 2:

a) Construct  2X2 table & label a,b,c,d cells

	Disease	No Disease	Total
Test +ve	75 (True +ve)	25 (False +ve)	100
Test -ve	125 (False –ve)	775 (True –ve)	900
Total	200	800	1000

b) Calculate yield of screening test & interpret your results

Positive Predictive Value = a/(a+b) x 100

= 75/100 x 100

= 75%

Negative Predictive Value = d/(d+b) x 100

= 775/900 x 100

= 86.11%

• The test is able to predict that 75% of persons with a +ve test will have this disease
• The test is able to predict that 86.11% of persons with a -ve test will not have this disease

Case scenario 3:

a) Calculate prevalence of the disease

Prevalence=Total diseased persons

=45+98

=143

b) Calculate accuracy & validity of the test & interpret your results

Sensitivity = 45/143 x 100

= 31.46%

Specificity= 737/757 x 100

= 97.35%

Accuracy= 45+737/900 x 100

= 86.88%

• The ability to detect true +ve is 31.46%
• The ability to detect true -ve is 97.35%
• Accuracy of the screening test is 86.88%

Case scenario 4:

a) Construct  2X2 table

	Disease	No Disease	Total
Test +ve	18	49	67
Test -ve	2	931	933
Total	20	980	1000

b) Calculate yield of screening test & interpret your results

PPV = 18/67 x 100

= 26%

NPV= 931/933 x 100

= 99.78%

• The test is able to predict that 26% of persons with a +ve test will have this disease
• The test is able to predict that 99.78% of persons with a -ve test will not have this disease

Read more about screening

Screening for Disease