Screening and Early Detection

Epidemiological Basis for Disease Control – Fall 2001

Joel L. Weissfeld, M.D. M.P.H.

Objectives

1. Theoretical justification for disease control through early detection of disease.

2. Concepts and quantitative methods used to evaluate a screening test.

Definitions

1. Screening program -- comprehensive disease control activity based on the identification and treatment of persons with either unrecognized disease or unrecognized risk factors for disease.

2. Screening test -- specific technology (survey questionnaire, physical observation or measurement, laboratory test, radiological procedure, etc.) used to help identify persons with unrecognized disease or unrecognized risk factors for disease.

Definitions

3. Primary prevention -- disease control approach based on the elimination or reduction of risk factors for disease. Primary prevention aims to prevent the occurrence of disease. Primary prevention may use screening tests to identify persons with risk factors.

Definitions

4. Secondary prevention -- disease control approach based on the active identification and treatment of persons with unrecognized disease. Secondary prevention aims to prevent the occurrence of adverse outcomes from disease (such as fatal outcomes), without necessarily reducing the occurrence of disease. Secondary prevention must screen to identify persons with unrecognized disease.

Generalities

1. Screening often implies a public health related activity involving asymptomatic or healthy subjects coming from the general population.

2. Case-finding refers to special clinical efforts to recognize disease among persons who consult a health professional.

Two essential attributes of successful secondary prevention

1. Screening must accomplish early detection of disease. The screening program must detect disease in asymptomatic persons or in sympto-matic persons not recognized to have disease. Relative to background conditions, screening must identify affected persons at an earlier time point in the natural history of disease.

2. The act of early detection increases the effectiveness of treatments for the disease.

Evaluation framework used by US Preventive Services Task Force

1. Assess burden of suffering.

2. Assess properties of the screening test.

3. Determine the efficacy, effectiveness, and cost-effectiveness of early detection.

Important properties of a screening test

1. Screening is simple, inexpensive, and easily diffused through the population.

2. The act of screening is safe and acceptable.

3. The screening test is reliable.

4. The screening test is accurate.

Reliability

1. Kappa -- an appropriate reliability measure (or measure of agreement) for a screening test which gives a categor-ical result.

2. Intraclass correlation coefficient -- an appropriate reliability measure for a screening test, which gives a quantitative result.

Cohen’s Kappa

Po = a + d = proportion observed agreement

Pe = P1∙P2 + Q1∙Q2 = proportion expected agreement

kappa = (Po - Pe)/(1 - Pe)

2nd obspos neg

1st obs pos a b P1

neg c d Q1

P2 Q2 1.00

Subject X1 X2 0.5*d^2 X1 X21 213 189 288,0 Mean 205 2022 185 194 40,5 SD 56 543 193 155 722,0 CV 0,27 0,274 162 191 420,55 256 277 220,56 174 178 8,0 SD(Err) 15,77 165 203 722,0 CV(Err) 0,0778 198 185 84,59 228 213 112,5

10 164 134 450,0 Tot var 3001,011 217 229 72,0 ICC 0,91812 195 195 0,013 240 217 264,514 191 153 722,015 250 203 1104,516 220 214 18,017 118 146 392,018 165 178 84,519 314 303 60,520 189 202 84,521 299 293 18,022 186 206 200,023 88 83 12,524 174 179 12,525 330 324 18,0

Sum 5114 5044 6132,0

Calculating the intraclass correlation coefficient (ICC)

Click for larger picture

Origin of the term1. Screening implies a simple process, which classifies

persons into one of two groups.2. Members of the group with a positive (or abnormal)

screening test result have disease with a probability high enough to justify diagnostic testing (for confirmation of disease presence) and/or medical therapies (for prevention of adverse outcomes from disease).

3. Members of the group with a negative (or normal) screening test result have disease with a probability too low to justify diagnostic testing (for confirmation of disease presence) and/or medical therapies (for prevention of adverse outcomes from disease).

Comparison of screening test results against gold standard

1. A screening test may produce only a categorical (positive or negative) result. Important concepts include disease prevalence, test sensitivity, test specificity, positive predictive value, negative predictive value, proportion test positive, proportion test negative, and disease yield.

Classification of screening test results against gold standard

Screening test resultsPositive Negative

Gold standard Positive TP FNNegative FP TN

TP true positiveTN true negativeFP false positiveFN false negative

Classification of screening test results against gold standard

Screening test resultsPositive Negative Total

Gold standard Positive a b a + bNegative c d c + dTotal a + c b + d 1.00

a + b Disease prevalencea + c Proportion test positive

a Yielda/(a+b) Sensitivityd/(c+d) Specificitya/(a+c) Positive predictive value (PPV)d/(b+d) Negative predictive value (NPV)

Comparison of screening test results against gold standard

2. Sensitivity and specificity are said to be properties of the screening test. That is, sensitivity and specificity of a screening test may be relatively independent of the population being screened.

Comparison of screening test results against gold standard

3. For rare conditions, specificity has a major impact on positive prediction (Bayes Theorem). Despite a direct effect on yield, sensitivity has quantitatively less impact on positive prediction.

Deriving Bayes theorem

Step 1: Specify the prevalence (P) of disease

Screening test resultsPositive Negative Total

Gold standard Positive PNegative 1 - PTotal 1.00

Deriving Bayes theorem

Step 2: Use sensitivity (Se) to distribute test results among the diseased

Screening test resultsPositive Negative Total

Gold standard Positive SeP (1-Se)P P

Negative 1 - PTotal 1.00

Deriving Bayes theorem

Step 3: Use specificity (Sp) to distribute test results among the non-diseased

Screening test resultsPositive Negative Total

Gold standard Positive SeP (1-Se)P P

Negative (1-Sp)(1-P) Sp(1-P) 1 - P

Total 1.00

Deriving Bayes theorem

Step 4: Determine the proportion testing positive and the proportion testing negative

Screening test resultsPositive Negative Total

Gold standard Positive SeP (1-Se)P P

Negative (1-Sp)(1-P) Sp(1-P) 1 - P

Total SeP + (1-Sp)(1-P) (1-Se)P + Sp(1-P) 1.00

Deriving Bayes theorem

Step 5: Equate PPV and NPV with appro-priate expressions from Step 5

PPV = SeP/[SeP + (1-Sp)(1-P)]

NPV = Sp(1-P)/[(1-Se)P + Sp(1-P)]

Comparison of screening test results against gold standard

4. A screening test may produce quantitative values. However, for decision-making purposes, a screening program must convert quantitative test results into two (or more) discrete categories. The screening program has a choice of different cutpoint(s), which may be used to categorize test results. In general, the choice of cutpoint(s) will affect values for sensitivity and specificity. Analysis of receiver operating characteristic (ROC) curves provides a graphical method for studying the effects of different cutpoints on the performance (sensitivity and specificity) of a screening test. ROC curve analysis also provides a method for comparing competing screening tests.

Net effects from screening

1. True negatives are exposed to the costs, inconvenience, and hazards of screening. True negatives may be reassured by knowledge of a negative screening test result.

2. False positives are exposed to the costs, inconvenience, and hazards of screening and follow-up diagnostic evaluations. The falsely positive screening test result may cause psychological and emotional distress.

Net effects from screening

3. False negatives are exposed to the costs, inconvenience, and hazards of screening. False negatives may be falsely reassured by knowledge of a negative screening test result. False negatives represent lost opportunities to prevent adverse outcomes from disease.

4. True positives are exposed to the costs, inconvenience, and hazards of screening, follow-up diagnostic evaluations, and therapeutic interventions. Only true positives have an opportunity to benefit from medical therapy.

Disease pre- Test accuracy Complication? TreatmentPopulation valence (P) (Se & Sp) Screen Diag outcome?

True positive No No GoodSe No Yes Good

Yes No GoodYes Yes GoodNo No Poor

Diseased No Yes PoorP Yes No Poor

Yes Yes Poor

False negative NoScreen (1 - Se) Yes

False positive No No(1 - Sp) No Yes

Yes NoHealthy Yes Yes(1 - P)

True negative NoSp Yes

Generalities

1. Specificity is often the major determinant of the costs and feasibility of a screening program.

2. Sensitivity establishes the maximum extent (upper bound) to which a screening program is capable of producing health benefit.