Screening
“...the identification of unrecognized disease or defect by the application of tests, examinations or other procedures...” “...sort out apparently well persons who probably have disease from those who probably do not.” “...not intended to be diagnostic...”
Types of screening Mass screening, no selection of population (e.g., checking all infants for hearing problems) Selective screening (e.g., by age and sex: mammograms for women aged over 40) Multiphasic screening (a series of tests, as family doctors do at annual health exams)
When should we screen? Screen when: It is an important health problem (think about how to define ‘important’?) There is an accepted and effective treatment Disease has a recognizable latent or early symptomatic stage There are adequate facilities for diagnosis and treatment There is an accurate screening test There is agreement as whom to consider as cases
Characteristics of a good screening test Valid (e.g., sensitive and specific) Reliable (gives consistent results; no random errors) Cost – benefit (compare costs avoided due to early detection of the disease against cost of the screening. Does the test merely uncover more disease that is expensive to treat without appreciable advantage?) Acceptable (discomfort, invasiveness, cost of obtaining test) Follow-up services (plan needed to deal with positive results)
Validity – get the correct result Sensitivity Specificity Predictive values Reliable – get same result each time How good is the test?
What is used as a “gold standard” 1. Most definitive diagnostic procedure e.g. microscopic examination of a tissue specimen 2. Best available laboratory test e.g. polymerase chain reaction (PCR) for HIV virus 3. Comprehensive clinical evaluation e.g. clinical assessment of arthritis
8 Sensitivity and specificity Assess correct classification of: Sensitivity means probability of having a positive test results among those with disease Specificity means probability of having a negative test results among those without the disease (specificity)
True positive True negative False positive False negative Sensitivity = True positives All cases a + c b + d = a a + c Specificity = True negatives All non-cases = d b + d a + b c + d True Disease Status Cases Non-cases Positive Negative Screening Test Results a d b c X 100
10 True Disease Status Cases Non-cases Positive Negative Screening Test Results a d 1,000 b c 60 Sensitivity = True positives All cases ,000 = Specificity = True negatives All non-cases = 19,000 20,000 1,140 19, ,000 = = 70% 95%
Uses of sensitive test: 1. In emergency department. 2. In screening. 3. In diseases with low frequency. 4. In highly serious communicable disease. * Best use of sensitive test when test result is –v. Uses of specific test: 1. Chronic cases as in wards and clinic. 2. To confirm the diagnosis. 3. When the treatment is harmful as cytotoxic drugs. 4. When cost of treatment is very high. * Best use of specific test when test result is +v.
12 Interpreting test results: predictive value Probability (proportion) of those tested who are correctly classified Having disease / all positive tests Not having disease / all negative tests
13 True positive True negative False positive False negative PPV = True positives All positives a + c b + d = a a + b NPV = True negatives All negatives = d c + d a + b c + d True Disease Status CasesNon-cases Positive Negative Screening Test Results a d b c X 100
True Disease Status Cases Non-cases Positive Negative Screening Test Results a d 1,000 b c 60 PPV = True positives All positives ,000 = 140 1,140 NPV = True negatives All negatives = 19,000 19,060 1,140 19, ,000 = = 12.3% 99.7%
15 Positive predictive value, Sensitivity, specificity, and prevalence Se (%) Sp (%) Prevalence (%) PV+ (%)
Cut off point: the point at which a test results is considered to change from +v to –v. so by moving the cut off point will change every parameter in the test. Lower cut-point: increases sensitivity, reduces specificity Higher cut-point: reduces sensitivity, increases specificity
17 Considerations in selection of cut-point Implications of false positive results burden on follow-up services labelling effect Implications of false negative results Failure to intervene
Ethics in screening Informed consent obtained? Implications of positive result? Number and implications of false positives? Labeling and stigmatization