Diagnosis, screening and prevention

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Diagnosis, screening and prevention

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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. - PowerPoint PPT Presentation

Transcript of Diagnosis, screening and prevention

Page 1: Diagnosis, screening and prevention

Diagnosis, screening and prevention

Page 2: 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?

Page 3: Diagnosis, screening and prevention

1000

1

999

~ 1

~ 0

10

989

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

TP

FP

FN

TN

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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

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Objectives contd.

• describe how prior probablilities are derived

• sources of health information in Ireland / other countries

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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

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1. Purpose of testing

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

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Pre-test probabilityPopulation prevalence

Demographic characteristics

Risk factors

Probability of disease

0% 50% 100%

Definitive Test (s) Definitive

test test

Post-test probability

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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.

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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

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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

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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

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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))

Page 14: Diagnosis, screening and prevention

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

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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

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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

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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?

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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?

Page 19: Diagnosis, screening and prevention

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

Page 20: Diagnosis, screening and prevention

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%

Page 21: Diagnosis, screening and prevention

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

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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%

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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%

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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%

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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

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CASS: % with coronary artery disease according to symptom history

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

Definite angina ?

Probable angina ?

Non-ischaemic ?

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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

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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

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• 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

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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

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1. Purpose of testing

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

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NATURAL HISTORY OF DISEASE

Biologiconsetof disease

Diseasedetectableby screening

Detection byscreening test

Disease detectableby routine methods

Onset of symptoms

Death

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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

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We screen for many different types of disease :

• metabolic disorders

• genetic disorders

• congenital defects

• developmental problems

• infectious diseases

• cancers and other chronic diseases

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Types of screening

• Mass screening

• Opportunistic screening (case finding)

• Targeted screening

• Multiphasic screening

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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

Page 37: Diagnosis, screening and prevention

NATURAL HISTORY OF DISEASE

Biologiconsetof disease

Diseasedetectableby screening

Detection byscreening test

Disease detectableby routine methods

Onset of symptoms

Death

Page 38: Diagnosis, screening and prevention

NATURAL HISTORY OF DISEASE

Biologiconsetof disease

Diseasedetectableby screening

Detection byscreening test

Disease detectableby routine methods

Onset of symptoms

Death

Page 39: Diagnosis, screening and prevention

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.

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Evaluation of screening programmes

• RCT

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

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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.

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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

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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

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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

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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

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*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

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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

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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

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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

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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 = ??