What does screening mean?Screening refers to the application of a medical procedure or test to people who as yet have no symptoms of a particular disease, for the purpose of determining their likelihood of having the disease. The screening procedure itself does not diagnose the illness. Those who have a positive result from the screening test will need further evaluation with subsequent diagnostic tests or procedures. Show Why do we do screening?The goal of screening is to reduce morbidity or mortality from the disease by detecting diseases in their earliest stages, when treatment is usually more successful. Examples of Screening Tests:Pap smear, mammogram, clinical breast exam, blood pressure determination, cholesterol level, eye examination/vision test, and urinalysis. What are sensitivity and specificity?Sensitivity and specificity are measures of a test's ability to correctly classify a person as having a disease or not having a disease. Sensitivity refers to a test's ability to designate an individual with disease as positive. A highly sensitive test means that there are few false negative results, and thus fewer cases of disease are missed. The specificity of a test is its ability to designate an individual who does not have a disease as negative. A highly specific test means that there are few false positive results. It may not be feasible to use a test with low specificity for screening, since many people without the disease will screen positive, and potentially receive unnecessary diagnostic procedures. It is desirable to have a test that is both highly sensitive and highly specific. This is frequently not possible. Typically there is a trade-off. For many clinical tests, there are some people who are clearly normal, some clearly abnormal, and some that fall into the gray area between the two. Choices must be made in establishing the test criteria for positive and negative results. What is predictive value?The probability of having the disease, given the results of a test, is called the predictive value of the test. Positive predictive value is the probability that a patient with a positive (abnormal) test result actually has the disease. Negative predictive value is the probability that a person with a negative (normal) test result is truly free of disease. Predictive value is an answer to the question: If my patient's test result is positive, what are the chances that my patient does have the disease? Predictive value is determined by the sensitivity and specificity of the test and the prevalence of disease in the population being tested. (Prevalence is defined as the proportion of persons in a defined population at a given point in time with the condition in question.) The more sensitive a test, the less likely an individual with a negative test will have the disease and thus the greater the negative predictive value. The more specific the test, the less likely an individual with a positive test will be free from disease and the greater the positive predictive value. When the prevalence of preclinical disease is low, the positive predictive value will also be low, even using a test with high sensitivity and specificity. For such rare diseases, a large proportion of those with positive screening tests will inevitably be found not to have the disease upon further diagnostic testing. To increase the positive predictive value of a screening test, a program could target the screening test to those at high risk of developing the disease, based on considerations such as demographic factors, medical history or occupation. For example, mammograms are recommended for women over the age of forty, because that is a population with a higher prevalence of breast cancer. What criteria should be considered for an effective screening program?
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