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