Diagnosis, screening and prevention

Puzzle• Virus present randomly in 1 in 1000

population

• Test for virus 99% reliable – i.e. misses 1% of infected individuals and

falsely labels 1% of non infected individuals

• Select 1 individual at random.

• If the test result is positive, what is the probability that that individual is infected?

1000

1

999

~ 1

~ 0

10

989

Probability that that individual is infected= 1 / 10+1 = 9% (= PPV)

TP

FP

FN

TN

Diagnostic testsObjectives

Student should be able to:

• describe how tests are evaluated

• define and calculate se\sp\pv and describe their inter-relationships

• demonstrate the ability to correctly interpret test results

• utilise prior probability in the judicious selection of diagnostic tests

Objectives contd.

• describe how prior probablilities are derived

• sources of health information in Ireland / other countries

Key points1. Purpose of testing

– to move probability of disease towards 0% or 100%

2. Tests vary in performance (validity)– sensitivity and specificity

3. +ve test result person has disease– PPV, NPV

4. Same test performs differently in different situation– Diagnostic vs screening contexts

1. Purpose of testing

• To move probability of disease towards 0% or 100%

Pre-test probabilityPopulation prevalence

Demographic characteristics

Risk factors

Probability of disease

0% 50% 100%

Definitive Test (s) Definitive

test test

Post-test probability

2. Test validity

• Validity measured by se and sp.• Sensitivity is the probability of a positive

test result in the presence of disease.• Specificity is the probability of a negative

test result given the absence of disease.• Sensitivity and specificity are inversely

related.

Test validity"TRUTH"

Testresult

DISEASE NO DISEASE

POSITIVE True positivea

False positiveb

NEGATIVE False negativec

True negatived

Se = a / a + c Sp = d / d + b

Test validity

• Sensitivity – probability of a positive test result in the

presence of disease

= a / a + c

• Specificity – probability of a negative test result given

the absence of disease

= d / d + b

Se = 99% Sp = 99%

"TRUTH"

Test result Disease No disease

Positive

1 (.99)

a

10

b

Negative

c

0 (.01)

d

989

Total 1 999

Puzzle: Pre-test probability (prevalence) = 1/1000Test for virus 99% reliable i.e. misses 1% of infected individuals,and falsely labels 1% of non infected individuals

Comparison of fine needle aspiration test results with findings from surgical

excisional biopsies in women without and with palpable breast masses

(from C Smith et al. Surgery 1988 103:178))

Comparison of fine needle aspiration test results with findings from surgical excisional biopsies in

women without and with palpable breast masses (from C Smith et al. Surgery 1988 103:178))

With palpable masses

"TRUTH"

Test result Disease present Disease absent

Positive

113

a

15

b

Negative

c

8

d

181

Se = 113/113 + 8 Sp = 181/181+15 = 93% = 92%

With palpable masses

"TRUTH"

Test result Disease present Disease absent

Positive

113

a

15

b

Negative

c

8

d

181

3. Positive test result person has disease

• PPV: probability of disease, given positive test result = a /a + b

• NPV: prob. of no disease, given negative test result = d / d + c

• PPV rises: • as specificity increases• as prior probability/ prevalence increases

PPV

NPV

"TRUTH"

Test result Disease No disease

Positive

~1

a

10

b

Negative

c

~ 0

d

989

Total 1 999

Se = 99% Sp = 99%

Puzzle: Virus present randomly in 1 in 1000 population.Test 99% reliable Select 1 individual at random: If the test result is positive, what is the probability that that individual is infected?

PPV = a/a+b 1/11 = 9.1%

NPV = d/d+c = 989/989 100.0%

"TRUTH"

Test result Disease No disease

Positive

1

a

10

b

Negative

c

0

d

989

Total 1 999

(

Se = 99% Sp = 99%Puzzle: Virus present randomly in 1 in 1000 population.Test 99% reliable Select 1 individual at random: If the test result is positive, what is the probability that that individual is infected?

Comparison of fine needle aspiration test results with findings from surgical excisional biopsies in

women without and with palpable breast masses (from C Smith et al. Surgery 1988 103:178))

With palpable masses

"TRUTH"

Test result Disease present Disease absent

Positive

113

a

15

b

Negative

c

8

d

181

With palpable

masses

"TRUTH"

Test result Disease

present

Disease

absent

Positive

113

a

15

b

PPV = 88%

Negative

c

8

d

181 NPV = 96%

Se = 93% Sp = 92% Prevalence =

38%

Comparison of fine needle aspiration test results with findings from surgical excisional biopsies in

women without and with palpable breast masses (from C Smith et al. Surgery 1988 103:178))

Without palpable masses

"TRUTH"

Test result Disease present Disease absent

Positive

14

a

8

b

Negative

c

1

d

91

Without palpable

masses

"TRUTH"

Test result Disease

present

Disease

absent

Positive

14

a

8

b

PPV = 64%

Negative

c

1

d

91 NPV = 99%

Se = 93% Sp = 92% Prevalence =

13%

Positive predictive values (PPV) are highly dependent on PREVALENCE

For a screening test with:95% sensitivity and 95% specificity:

• if prevalence is 20%• if prevalence is 10%• if prevalence is 1%• if prevalence is 0.1%

• PPV is 83%• PPV is 68%• PPV is 16%• PPV is 2%

Positive predictive values (PPV) also vary greatly with SPECIFICITY

For a disorder with prevalence (pre-test probability) of 1%,

& a test with 60% sensitivity:

• if specificity is 60%• if specificity is 80%• if specificity is 90%• if specificity is 95%• if specificity is 99%

• PPV is 1.5%• PPV is 2.9%• PPV is 5.7%• PPV is 10.8%• PPV is 37.7%

4. Same test performs differently in different situations

• Usefulness varies according to pretest probability (prevalence) of disease.

• Implications of link between prior probability and PPV:– Clinical

• if prior probability is very low - or very high - test contributes little information

– Screening • PPV is usually very low, especially for disease

of low frequency

CASS: % with coronary artery disease according to symptom history

(DA Weiner et al. NEJM 301:230-5,1979)

Definite angina ?

Probable angina ?

Non-ischaemic ?

CASS: % with coronary artery disease according to symptom history

(DA Weiner et al. NEJM 301:230-5,1979)

Men Women

Definite angina 89 62

Probable angina 70 40

Non-ischaemic 22 5

Prevention and screening Objectives

Student should be able to: • describe the levels of prevention

• list and apply the criteria for screening

• describe the impact of prevalence on predictive values

• explain why there are difficulties with screening

• PRIMARY PREVENTION– Prevention of disease by controlling risk

factors, removing causes• e.g. non-smoking promotion

• SECONDARY PREVENTION– Reduction in consequences of disease by

early diagnosis and treatment • e.g. cervical cancer screening

• TERTIARY PREVENTION– Reduction of complications of disease

• e.g. MV crashes and ICU

Levels of prevention

Screening:process of identifying unrecognised

diseases/defects using tests that can be applied rapidly on a large scale

• Tests sort apparently healthy from those with (subclinical) disease

• Not diagnostic – investigative follow-up and treatment

required

• Safety paramount– initiative from health service, not client

1. Purpose of testing

• To move probability of disease towards 0% or 100%

NATURAL HISTORY OF DISEASE

Biologiconsetof disease

Diseasedetectableby screening

Detection byscreening test

Disease detectableby routine methods

Onset of symptoms

Death

Screening Criteria

• Important health problem – high prevalence \ radical consequences

• Natural history known– long pre-clinical phase

• Tests: valid, acceptable, ‘cheap’

• Effective treatment– adequate facilities for dx & Rx

• Economically justifiable

We screen for many different types of disease :

• metabolic disorders

• genetic disorders

• congenital defects

• developmental problems

• infectious diseases

• cancers and other chronic diseases

Types of screening

• Mass screening

• Opportunistic screening (case finding)

• Targeted screening

• Multiphasic screening

SCREENING BIASES• Lead time bias:

– date of diagnosis automatically advanced for those cancers detected by screening

• Length bias:– tendency of screening to detect cancers

which spend longer in the asymptomatic state (slower growing)

• Selection bias:– tendency for non-acceptors of screening to

be at higher (or lower) risk of developing and/or dying from this disease than the general population

NATURAL HISTORY OF DISEASE

Biologiconsetof disease

Diseasedetectableby screening

Detection byscreening test

Disease detectableby routine methods

Onset of symptoms

Death

NATURAL HISTORY OF DISEASE

Biologiconsetof disease

Diseasedetectableby screening

Detection byscreening test

Disease detectableby routine methods

Onset of symptoms

Death

SCREENING BIASES• Lead time bias:

– date of diagnosis automatically advanced for those cancers detected by screening

• Length bias:– tendency of screening to detect cancers

which spend longer in the asymptomatic state (slower growing)

• Selection bias:– tendency for non-acceptors of screening to

be at higher (or lower) risk of developing and/or dying from this disease than the general population.

Evaluation of screening programmes

• RCT

• Apparent ‘benefit’ of screeningenhanced if:– ‘poor’ quality RCT– Non RCT e.g. case control studies

Target groups for screening:

• NEONATES

• "FOETUSES”

• PREGNANT WOMEN/PARENTS-TO-BE

• ADULTS

• ELDERLY

• PKU/CHT/GAL/HCU/MSUD, CDH, NTD, Down syndrome, thalassaemia

• UTI, STD, AIDS, rubella, blood sugar, Rhesus factor

• Rubella, AIDS, sickle cell anaemia, thalassaemia, Tay Sachs

• cancers (breast, cervix, rectal), hypertension, cholesterol

• glaucoma, cataract, hearing, mobility.

The treatment aims of screening differ

Target group

• Neonates• "Foetuses"• Pregnant women

• Parents-to-be• Children

• Adults

• Elderly

Treatment• Prevention of serious morbidity• Termination• Prevention of foetal damage (also

maternal welfare)• Prevention of conception• Alleviation / prevention of

morbidity• Reduction in morbidity or mortality

/ prevention of disease onset • Alleviation

Key points 1 - 2

• 1. Purpose of testing– to move probability of disease towards 0% or

100%.

• 2. Tests vary in performance (validity)– Sensitivity

• probability of pos. test result when disease present

– Specificity • probability of neg. test result when disease absent

– Trade off between sensitivity and specificity

Key points 3 - 4

• 3. +ve test result person has disease– PPV: probability of disease, given a pos. test result– NPV: prob. of no disease, given neg.test result– PPV rises:

• as specificity increases• as prior probability/ prev. increases

• 4. Implications of link between prior prob. and PPV:– Same test performs differently in different situations– Clinical context

• if prior probability is very low - or very high - test contributes little information

– Screening for disease of low frequency• PPV is very low

Task force on sudden death in sport(Nov 2005)

• Clinical screening for sudden death in all teenagers and adults who play sport– PPV = 1/1000

Better to use family history i.e.targeted screening

*Screening test: blood spot trypsinogen

Nutritional benefits of neonatal screeningP. Farrell et al. NEJM 1997; 337:963-9

Cystic fibrosis

"TRUTH"

Test

result*

Present Absent

Positive

69TP

447FP

PPV = 13.4%

Negative

FN

5

TN

324,650 NPV = 99.9%

Totals 74 325,097 325,171

Se =

93.2%

Sp =

99.9%

Prevalence =

2.3/10,000

Intervention Cost per QALY* in US dollarsOpportunistic screening for type 2 diabetes $56,600

Intensive glycaemic control in type 2 diabetes $16,000

Plus tight blood pressure control additional $700

Detection of mild thyroid disease in women aged > 35 years,

during a health check $9,000

Breast cancer screening with mammography in women aged 50 - 65 years $150,000

Colon cancer screening using FOBT in patients

aged 50 – 75 years $16,000

Cervical cancer screening using pap smears every 4 years

for women aged 20 – 75 years $16,000

* Quality adjusted life years

Cochrane review of breast cancer screening

Relative risk of death from breast cancer in screened vs control groups

Gotzsche & Olsen, Lancet 2000; 355: 129-34

• Total mortality - no difference

• Breast cancer mortality - marginal difference

Relative risk of death from breast cancer in screened vs control groups

Gotzsche & Olsen, Lancet 2000; 355: 129-34

No. randomised No. breast cadeaths

Screening Controls Scr Cntrls RR (95%CI)

Randomisation adequate (Malmo, Canada)

Total 66,013 66,105 183 177 1.04(0.84-1.27)

Randomisation not adequate (6 trials*)

Total 182,179 142,052 654 725 0.75(0.67-0.83)

*Goteborg, Stockholm, Kopparberg, Ostergotland, New York, Edinburgh

Trials with adequate randomisation Breast ca

deaths Alive Total

Screened group

183 65830 66013

Control (not screened)

177 65920 66105

RR = 183 / 66013 = 1.04 177 / 66105 OR = 183 * 65928 = 1.04 177 * 65830 RD = 183 / 66013 - 177 / 66105

= 2.77 / 1000 - 2.68 / 1000 = 0.09 / 1000 = 9 / 100,000

NNT = ??