Screening
Dr. N. Birkett,School of Epidemiology, Public Health and Preventive Medicine,
University of Ottawa
SUMMER COURSE:INTRODUCTION TO
EPIDEMIOLOGY
AUGUST 27, 1330-1500
Session Overview• Review key features of tests for detecting disease.• Screening programmes
• Overview• Criteria for utility
Scenario (1)A 54 year old female teacher visited her family physician for an annual checkup. She reported no illnesses in the previous year, felt well and had no complaints. Hot flashes related to menopause had resolved. A detailed physical examination, including breast palpation, was unremarkable. A screening mammogram was recommended as per current guidelines.
Scenario (2)The mammogram results were ‘not normal’ and a follow-up breast biopsy was recommended. The surgeon confirmed the negative clinical exam. Based on the abnormal mammogram, a fine-needle aspiration biopsy of the abnormal breast under radiological guidance was recommended. Pathological review of the biopsy revealed the presence of a malignant breast tumor. Further surgery was scheduled to pursue this abnormal finding.
Test Properties (1)• Most common situation (for teaching at least) assumes:
• Dichotomous outcome (ill/not ill)• Dichotomous test results (positive/negative)
• Represented as a 2x2 table (yet another variant!).• Advanced methods can consider tests with multiple
outcomes• advanced;• moderate; • minimal; • no disease
Diseased Not diseased
Test +ve 90 5 95
Test -ve 10 95 105
100 100 200
Test Properties (2)
True Positives
False Negatives
False Positives
True Negatives
Diseased Not diseased
Test +ve 90 5 95
Test -ve 10 95 105
100 100 200
Test Properties (3)
Sensitivity=0.90 Specificity=0.95
Diseased Not diseased
Test +ve a b a+b
Test -ve c d c+d
a+c b+d a+b+c+d
Test Properties (4)
Sensitivity Specificity
Test Properties (5)Sensitivity = Pr(test positive in a person with disease)Specificity = Pr(test negative in a person without
disease)• Range: 0 to 1
• > 0.9: Excellent• 0.8-0.9: Not bad• 0.7-0.8: So-so• < 0.7: Poor
Test Properties (6)• Generally, high sensitivity associated with low specificity
and vice-versa (more later).• Do you want a test with high sensitivity or specificity?
• Depends on cost of ‘false positive’ and ‘false negative’ cases.• PKU – one false negative is a disaster.• Ottawa Ankle Rules
Test Properties (7)• Patients don’t ask:
• if I’ve got the disease how likely is it that the test will be positive?• They ask:
• My test is positive? Does that mean I have the disease?
Predictive values.
Diseased Not diseased
Test +ve 90 5 95
Test -ve 10 95 105
100 100 200
Test Properties (8)
PPV=0.95
NPV=0.90
Diseased Not diseased
Test +ve a b a+b
Test -ve c d c+d
a+c b+d a+b+c+d
Test Properties (9)
PPV
NPV
Test Properties (10)PPV = Pr(subject has disease given that their test
was positive)NPV = Pr(subject doesn’t have disease given that
their test was negative)• Range: 0 to 1
• > 0.9: Excellent• 0.8-0.9: Not bad• 0.7-0.8: So-so• < 0.7: Poor
Test Properties (11)Effect of disease prevalence• Common diseases are easier to find than rare diseases.• Sensitivity & specificity are not affected by prevalence.• PPV is affected by the prevalence of the disease in the
target population.
Let’s do an example. Assume we have:• sens = 0.85; spec = 0.9
Diseased Not diseased
Test +ve 425 50 475
Test -ve 75 450 525
500 500 1,000
Test Properties (12)
PPV=0.89
Tertiary care: research study. Prevalence = 0.5
Diseased Not diseased
Test +ve
Test -ve
Test Properties (13)
PPV=0.08
Primary care: Prevalence = 0.01Diseased Not diseased
Test +ve
Test -ve
10,000
Diseased Not diseased
Test +ve
Test -ve
0.01*10,000 10,000
Diseased Not diseased
Test +ve
Test -ve
100 9,900 10,000
Diseased Not diseased
Test +ve 0.85*100
Test -ve
100 9,900 10,000
Diseased Not diseased
Test +ve 85
Test -ve 15
100 9,900 10,000
Diseased Not diseased
Test +ve 85
Test -ve 15 0.90*9,900
100 9,900 10,000
Diseased Not diseased
Test +ve 85 990
Test -ve 15 8,910
100 9,900 10,000
Diseased Not diseased
Test +ve 85 990 1,075
Test -ve 15 8,910 8,925
100 9,900 10,000
Test Properties (14)• Most tests give continuous readings
• Serum hemoglobin• PSA• X-rays
• How to determine ‘cut-point’ for normal vs. diseased (negative vs. positive)?
• ↑ sensitivity ↓specificity• Receiver Operating Characteristic (ROC) curves
False -ve False +ve
PositiveNegative
False -ve False +ve
PositiveNegative
AUCArea Under Curve
Screening (1)• Screening
• The presumptive identification of an unrecognized disease or defect by the application of tests, examinations or other procedures
• Can be applied to an unselected population or to a high risk group.
• Examples• Pap smears (cervical cancer)• Mammography (breast cancer)• Early childhood development• PKU
Screening (2)• Levels of prevention:
• Primary prevention• Secondary prevention• Tertiary prevention
• Boundaries between levels are fuzzy• Interventions can impact on multiple outcomes or stages
of disease progression• Antihypertensive drugs
• secondary prevention for ‘high blood pressure’• primary prevention for ‘stroke’
Screening (3)
Screening (4)DPCP§
§ Detectable Pre-Clinical Phase
Screening (5)
Screening (6)Criteria to determine if a screening programme should be implemented• Disease Factors
• Severity• Presence of a lengthy DPCP• Evidence that earlier treatment improves prognosis
Screening (6)• Test Factors
• Valid - sensitive and specific with respect to DPCP• Reliable and reproducible (omitted from most lists, but shouldn’t
be)• Acceptable - cf. sigmoidoscopy• Easy• Cheap• Safe
Screening (7)• Test Factors (cont.)
• Test must reach high-risk groups - cf Pap smears• Sequential vs. parallel tests
• Sequential higher specificity• Parallel higher sensitivity
• System Factors• Follow-up provided and available to all• Treatment resources adequate
Screening (8)• Biases in interpreting evaluations of screening
programmes.• Lead-time Bias
• Detecting disease early gives more years of ‘illness' but doesn’t prolong life
• Length Bias• Slowly progressive cases are more likely to be detected than
rapidly progressive cases
Screening (9)
Screening (10)
Screening (11)
Screening (12)
Screened Detected
Slow: 5/5
Fast: 2/5
Better survival than non-screened subjects even if screening is useless
Summary• Diagnostic tests can be evaluated by considering their
error rates• sensitivity & specificity are the key parameters used
• Screening tests have similar properties• Screening should not be used unless early detection of
diseases changes natural history• Screening tests generally need high sensitivity