LibGuides: Public Health: Screening

What Makes a Good Screening Test?

Screening is the identification if disease or a risk factor in asymptomatic individuals.

Fundamentals of Screening

The disease must have a great enough burden of suffering to make going through the screening worth it.
A screening test must be able to find disease earlier than you would without the screening test.
There must a therapy or treatment that will lead to the patient having a better outcome.

Disorders show should have a low prevalence and be relatively rare.
Must screen a large number of people.
Most screening test are going to have a good number of false positives.
Screening risks should be rare but apply to everyone.
Only a few will benefit from screening.

Sensitivity & Specificity

Sensitivity and specificity describe how accurate a test is.

Sensitivity is a measure of how reliable a test is in identifying the presence of a condition. It measures how often a test will detect the presence of a disease in people who have the disease (true positives).

Specificity is a measure of how often a test will detect the absence of a disease in those who do not have the disease (true negatives).

True Positive, False Positive, True Negative, and False Negative results are used to calculate sensitivity, specificity, and predictive values of diagnostic tests.

True Positive (TP) = positive test result for a person who has the condition

False Positive (FP) = positive test result for a person who does not have the condition

True Negative (TN) = negative test result for a person who does not have the condition

False Negative (FN) = negative test result for a person who has the condition

Calculating Sensitivity by Dr. Shaneyfelt

How to calculate Specificity by Dr. Shaneyfelt

Positive & Negative Predictive Value

Predictive value describes the likelihood that a person has or does not have the condition based on the results of the test. The more prevalent the disease, the higher the PPV and the lower the NPV.

Positive Predictive Value (PPV) is the likelihood that a person with a positive test result truly has the disease.

Negative Predictive Value (NPV) is the likelihood that a person with a negative test result truly does not have the disease.

How to calculate Positive Predictive Value by Dr. Shaneyfelt

How to calculate Negative Predictive Vale by Dr. Shaneyfelt

References

Evans, I. (Ed.). (2011). Testing treatments: Better research for better healthcare (2. ed). Pinter & Martin. http://www.testingtreatments.org/wp-content/uploads/2012/09/TT_2ndEd_English_17oct2011.pdf