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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
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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.
• 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 = ??