Screening in Disease Detection. Natural history of disease Onset of symptoms Usual time of diagnosis Exposure Pathologic changes Stage of susceptibility.

Screening in Disease Detection

Natural history of disease

Onset ofsymptoms

Usual time ofdiagnosis

Exposure

Pathologicchanges

Stage ofsusceptibility

Stage ofsubclinical

disease

Stage ofclinicaldisease

Stage ofrecovery,

disability ordeath

PRIMARYPREVENTION

SECONDARYPREVENTION

TERTIARYPREVENTION

“Screening is the application of a test to

people who are asymptomatic for the

purpose of classifying a person with respect

to their likelihood of having a particular

disease”

A Key Assumption of Screening Programs:

Early detection will lead to more favorable prognosis

Screening, in and of itself, does not diagnose disease.

• Persons who test positive are referred to physicians for more detailed

assessment

• Physicians determine the presence or absence of disease.

Screening is one of the most practical applications of epidemiology. It’s goal is to promote health and prevent disease.

When is it appropriate to initiate screening programs?

1. When the disease is serious

2. When the prevalence of pre-clinical disease is high

3. When medical care is available and health interventions are known to be effective

4. When failure to screen could be considered unethical

World Health Organization Criterion for Screening

Is it a health problem?

Is there treatment?

Are there facilities in place?

Is it detectable pre-clinically?

Is there a suitable screening test?

Is the screening test acceptable to people?

Is the natural history of disease understood?

Are the costs acceptable?

Wilson JMG, Junger G. (1967) The principles and practice of screening for Disease. Public Health Paper 34: Geneva, Switzerland: World Health Organization

Screening involves:

• Organizing a deployment of public health resources, policies, and procedures

• Defining the target population

• Setting priorities among diseases and conditions

• Choosing effective screening tests

It also involves:

• Assessing the effectiveness of screening procedures and programs

• Adopting practice guidelines to local needs

• Dealing with controversial and conflicting guidelines

• Translating guidelines into programs through public health departments, managed-care organizations, community based coalitions, and workplace coalitions.

Community

Media

Managed care

Health Departments

Universities

SchoolsWorkplaces

Community Based

Organizations(e.g. Churches)

Clinic- Patient- Provider- Community Liaison

Places ofRecreation

Conceptual framework relating screening at the individual, settings, and community levels

When examining a screening test we tend to look most

closely at its

Validity

Reproducibility

Efficacy

How do we judge the validity of a screening test?

We compare the screening test against some “gold standard”

Disease “gold standard”

Test Result Present Absent

Positive true positive false positive

Negative false negative true negative

As a measure of the validity of the test we calculate:

Sensitivity

= Probability that a person having the disease is detected by the test

= P (test positive | they have the disease)

Specificity

= Probability that a person who does not have the disease is classified that way by the test

= P(test negative | they don’t have the disease)

Disease “gold standard”

Test Result Present Absent Total

Positive TP FP all who test +

Negative FN TN all who test -

Total All with All without

Disease Disease

Sensitivity = TP Specificity = TN

TP + FN FP + TN

How do we examine the reproducibility?

We do the tests repeatedly in the same individuals

and calculate measures of:

Intrasubject Variation (Table 4-7 in Gordis)

Interobserver Variation (Figure 4-12 in Gordis)

Overall Percent Agreement

Kappa Statistic

For a measure of the efficacy of the test we use . . .

Positive Predictive Value

= Probability that someone who tests positive for the disease will actually have the disease

= P (have disease | positive test result)

Negative Predictive Value

= Probability that someone who tests positive for the disease will actually

have the disease

= P (don’t have disease | negative test result)

Disease “gold standard”

Test Result Present Absent Total

Positive TP FP all who test +

Negative FN TN all who test -

Total All with All without

Disease Disease

Positive predictive value = TP / TP + FP

Negative predictive value = TN / TN + FN

One of the reasons Positive Predictive Value is used as a measure of efficacy is because it depends on the prevalence of the disease

For a given screening test with sensitivity fixed at X% and specificity fixed at Y%,

if the prevalence then PPV

or

if the prevalence then PPV

For example, for a screening test with sens=99% and spec=95% (Gordis, 1996)

Disease

Prev Test Present Absent Total PPV

1% + 99 495 594 17%

- 1 9,405 9,406 =99/594

Totals 100 9,900 10,000

5% + 495 475 970 51%

- 5 9,025 9,030 =495/970

Totals 500 9,500 10,000

What if we want to screen for a quantitative risk factor?

Blood cholesterol levels Heart Disease

Plasma Glucose levelsDiabetes

Cognitive function Dementia

Body Mass Index Obesity

Blood pressure Hypertension

For quantitative tests, we have to think about screening a little differently

Truly

Diseased

Not

DiseasedTrue Negatives

False Negatives

False Positives

True Positives

“Disease Cutpoint” for screening

Risk factor level

Risk factor level

So what would happen if we lowered the cut off?

Truly

Diseased

Not

DiseasedTrue Negatives

False Negatives

False Positives

True Positives

“Disease Cutpoint”

Some notable features of sensitivity and specificity for a quantitative

test:

Lowering the cutpoint for the screening test will

true positives sensitivity

true negatives specificity

And of course, increasing the cutpoint will have the exact opposite effect.

Given that there will be trade-offs between sensitivity and specificity, how do we decide

which “errors” are more costly?

1. Failing to detect some true cases because of lower sensitivity

or

2. Misclassifying some people as diseased because of lower specificity

It depends . . .

On the prevalence of the disease

On the severity of the disease

On the potential fatality of the disease

On how good the test is

On the acceptability of the test to people

Sensitivity and Specificity for Fibrinogen Levels

00.20.40.60.8

1

1 2 3 4 5 6 7 8 9 10 11

Fibrinogen

Sen

Spec

What’s the most appropriate cutpoint? (What if it’s a marker for a lethal disease?

What its just a health indicator?)

What are other strategies for dealing with this tradeoff?

Use parallel tests

- here a positive result on any one test defines the person as a

probable case

Use serial tests

- here a positive result on a first test are re- evaluated on a second test

- individuals must test positive on both tests to be considered a probable case.

Biases when evaluating a screening program

There are three possible sources of bias when evaluating a screening program that may result in a false picture of its efficacy:

– 1. Volunteer bias

– 2. Lead time bias

– 3. Length time bias

Biases when evaluating a screening program

1. Compliance (volunteer) bias: Volunteers for screening are generally more health conscious/concerned than the general population, apt to assume greater responsibility for their own care, hence, more likely to comply with therapy.

Biases when evaluating a screening program

2. Lead time bias

Lead time is the amount of time by which the diagnosis was advanced due to screening. Lead time bias means that survival may erroneously appear to be increased among screen-detected cases simply because the diagnosis was made earlier in the course of the disease.

Fig. 1.—Natural history of disease. Diagram illustrates that preclinical phase begins at onset and ends when signs or symptoms develop. Clinical phase then starts, ending with death. Detectable preclinical phase (DPCP) begins when disease is detectable by a test. Detection (X) during DPCP advances time of diagnosis by duration of lead time.

Fig. 2.—Lead-time bias. Diagram shows that, with screening, time of diagnosis is advanced by lead time provided by positive test result. If earlier diagnosis has no effect on time of death from disease, then survival with testing is equal to survival without testing plus lead time.

Biases when evaluating a screening program

3. Length time bias

Less aggressive forms of a disease are more likely to be picked up in a screening program because they have a longer detectable pre-clinical phase. Less aggressive forms of disease usually have better survival.

Fig. 3.—Diagram shows how probability of detection is related to rate of disease progression. Length of each arrow represents length of detectable preclinical phase, from initial detectability to clinical diagnosis (Dx). Testing at a single moment detects four slowly progressive cases but only two rapidly progressive cases. Cases not detected by test (thin arrows) are diagnosed clinically either before or after time of testing. Thick arrows indicate detected cases.

Prostate Cancer Example

Prostate cancer

It is the second most common form of cancer among men in the United States.

It is also the second leading cause of cancer deaths.

American Cancer Society estimates that 179,300 new cases of prostate cancer were diagnosed in 1999 and 37,000 men died in 1999.

This cancer is most common among men 65 years and older.

http://www.cdc.gov/cancer/prostate/prostate.htm

Prostate cancer

At all ages, African American men

• have the highest incidence of PCA in the world

• diagnosed with the disease at later stages

• die of prostate cancers at higher rates

http://www.cdc.gov/cancer/prostate/prostate.htm

Incidence of Prostate Cancer

Recently, we’ve been better able to detect prostate cancer and hence our estimates of its incidence have increased

http://www.cdc.gov/cancer/prostate/prostate.htm

Death rates for Prostate Cancer

Death rates for African American men is twice what it is for White men.

http://www.cdc.gov/cancer/prostate/prostate.htm

Age-dependent Incidence and Death Rates

Incidence of PCA appears to level off above 70 yrs

but the death rate becomes exponentially worse at that age.

http://www.cdc.gov/cancer/prostate/prostate.htm

Early Detection

The benefits of early detection of prostate cancer

are thought to be the same as for any cancer.

However,

• Little is know about how to prevent the disease

• Scientific evidence is lacking about whether screening reduces deaths

• Evidence is lacking about whether current treatments really prolong men’s

lives.

Two commonly used methods for detecting prostate cancer

1. Digital rectal examination (DRE)

This has been used for years. . . But its ability to detect PCA is limited

• It can’t detect some small tumors

• It can’t distinguish between benign tumors and cancer

2. Prostate-specific antigen (PSA) test

PSA is an enzyme that increases with age and because of prostate abnormalities

• Its now used widely but medical consensus hasn’t been reached on its utility

• It also cannot distinguish between benign and cancerous tumors.

What are the treatment alternatives?

Radical prostatectomy

Radiation therapy

Watchful waiting

Criterion Prostate Cancer

Is it a health problem? Yes

Is there treatment? Probably

Are there facilities in place? Yes

Is it detectable pre-clinically? Yes

Is there a suitable screening test? Yes

Is the screening test acceptable? Yes

Is the disease understood?Partially

Are the costs acceptable?Possibly

Is continuous screening set up?PrematureMeyer F, Fradet Y. Clinical basics:Prostate Cancer:4. Screening. Can Med Assoc J; 1998 159(8):968-972

Data from American Cancer Society’s National Prostate Cancer Detection Project and the European Randomized Study of Screening for Prostate Cancer

Prostate Cancer

Test result Present AbsentTotal

Positive 197 1169 1366

Negative 29 5828 5857

Total 226 6997 7223

Positive test result = a PSA level >4ng/ml and DRE evidence

False negatives detected by biopsy after transurethal ultrasonography yielded abnormal findings.

Meyer F, Fradet Y. Clinical basics:Prostate Cancer:4. Screening. Can Med Assoc J; 1998 159(8):968-972

Data from Canadian National Breast Screening Study

Breast Cancer

Test result Present AbsentTotal

Positive 142 3,2303,372

Negative 15 16,324 16,339

Total 226 19,5554 19,711

Positive test result = a suspicious finding by mammogram and/or physical exam

False negatives are those in whom breast cancer was discovered in 1st yr follow-up

Meyer F, Fradet Y. Clinical basics:Prostate Cancer:4. Screening. Can Med Assoc J; 1998 159(8):968-972

Comparison of Breast and Prostate Cancer

Prostate BreastCancer Cancer

Sensitivity,% 87.2 90.4Specificity, % 83.3 83.5Positive test, % 18.9 17.1Prevalence, % 3.1 0.8Positive predictive 14.4 4.2value, %

Meyer F, Fradet Y. Clinical basics:Prostate Cancer:4. Screening. Can Med Assoc J; 1998

159(8):968-972

Other issues related to Screening Programs:

• Evaluating the effectiveness of the program

• Defining High Risk subgroups

- Those subgroups for whom the prevalence of asymptomatic disease is expected to be

higher

• Ethical considerations

- Who should be offered the test?

- Who should have access to the results?

Selected Examples of Prevention Effectiveness

Annual US % of personsPrevention Undesired Incidence without Prevention Economic at Risk CoveredType* Outcome Intervention Method % Effectiveness Analysis by Method

Primary Measles 4,000,000 Vaccination 95-98 $16.85 per By age 2, 50-80%;

case prevented by age 6, 98%

Secondary Breast cancer 50,000 Mammography 20-70 $45K to $165K per 15-38 deaths screening year of life saved

Tertiary Blindness from 24,000 Retinal screening, 50 $100 per year of 60-80 Diabetes treatment vision saved

* Primary prevention = directed at susceptible persons before they develop a particular disease (risk factor reduction); Secondary prevention = directed at persons who are symptomatic but who have developed biologic changes (early detection and treatment); Tertiary prevention = directed at preventing disability in persons who have symptomatic disease (prevent complications and rehabilitation).

SOURCE: Thacker et. Al. (1994)

Group Health Cooperative of Puget Sound’s Breast Cancer Risk Algorithm and Screening Protocol

Mammography Risk Relative PercentageFrequency Level Risk-Level Criteria Risk WomenAnnual

Every 2 Years

Every 3 Years

Not Recommended

1

2

3

4

Previous breast cancer or atypia on biopsy results; at least 2 first-degree relatives with breast cancer

One first-degree relative with breast cancer; >50 years of age and >2 MRF’s

>50 years of age and >1 MRF; or >50 years of age and > MRF

<50 years of age and no MRF

4-14

1.9-3.5

1.2-1.9

1.0

Source: Taplin et al. (1990)

1

15

66

17

Conditions for Which Screening Is Recommended, USPSTF 1996

Health Outcome Test(s) Populations(s) Age Group (years)

HIV

HbgSS/PKU/

Hypothyroidism

Anemia

Lead poisoning

Rubella

Tuberculosis

Hearing

Vision

Lab

Hgb/Phenylalanine

T4&TSH

Hgb/Hct

Blood lead

Lab

PPD

--

--

HR2/HR3

General/General

general

HR1/HR/P (female)HR7

General (female)

HR1/HR3/HR6/HR7

General

General

0-10/11+

Birth/Birth

Birth

0-10/11+

0-10

11-24, 25-64

65+/0-24/25-64

65+

0-10, 65+

Source: U.S. Preventive Services task Force [USPSTF] (1996)

More Conditions for Which Screening Is Recommended

Health Outcome Test(s) Populations(s) Age Group (years) Obesity

CVD/HBP

CVD

Injury/Liver disease

Colorectal cancer

Breast cancer

Cervical cancer

Chlamydia

Gonorrhea

Syphilis

Height/Weight

Blood pressure

Cholesterol

Alcohol overuse

Fecal Occult Blood TestSigmoidoscopy

Mammography/Clinical Breast Exam

Pap Smear

Lab

Lab

Lab

General

General

General/HR6

General

General

General

General

General/HR4

HR2

HR1/HR9

All

All

25-64/65+

11+

25+

50+ (female)

11+ (female)

11-24/11-64

11-24, 25-64

11-64/65+

Source: U.S. Preventive Services task Force [USPSTF] (1996)