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Transcript of EK-5 20Jahghn Dr.cita_DX_200111 (Sri-Laptop's Conflicted Copy 2014-01-28) (Rachmi-MacBook-Air's...
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How to Appraise a Diagnostic Test?
Dr. Cita Rosita Sigit Prakoeswa, dr, SpKK(K)Department of Dermato Venereology Dr Soetomo Hospital
Faculty of Medicine, Airlangga University, SurabayaTropical Disease Center, Airlangga University, Surabaya
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What is diagnosis ?
Increase certainty aboutpresence/absence ofdisease
Disease severity Monitor clinical course
Assess prognosisrisk/stage within diagnosis
Plan treatment Screening
Epidemiology
Knottnerus, BMJ 2002
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By the end of this session,
you should be able to.
describe and illustrate key measures of
diagnostic test performance
represent diagnostic test performance in 2
different ways
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EBM Process
Patient
Encounter
Formulating the
Clinical Question
Searching the
Evidence
Appraising the
Evidence
Diagnosis
Therapy
Prognosis
Etiology
Patient
Intervention
Comparison
Outcome
Hierarchy of evidence
Pre appraised resources
Drawing conclusion
That impact on practice
DOES
POEM
(Lang, 2000) 4
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What should I do
about this condition
or problem?
What causethe problem?
Does this person
have the condition
or problem?
Who will get
the condition
or problem?
How common
is the problem?
What are the
type of problem?
INTERVENTION
PROGNOSIS/RISK FACTORS
DIAGNOSIS
PROGNOSIS FACTORS
FREQUENCY & RATE
PHENOMENA / THOUGHTS
CLINICALQUESTION
5
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ACQ Diagnosis (PICO)
Patient /
Problem /
Population
Intervention
(Index)Comparison Outcome
In an otherwise
healthy 7-year-
old boy with
sore throat
how does the
clinical exam
compare to
throat culture
in diagnosing
GAS infection?
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ResearcherInvolvement
Longitudinal
Cross-sectional
ResearchGoal
ResearchApproach
Controlled?Randomized?
ResearchFocus Clinical Manifestation / Diagnosis / Prognosis / Therapy / Review
13 2 4
7
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Hierarchy of study designs
8
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Basic Principles (1)
Ideal diagnostic testsright answers:
(+) results in everyone with the disease and
( - ) results in everyone else
Usual clinical practice:
The test be studied in the same way it would
be used in the clinical setting
Observational study, and consists of: Predictor variable (test result)
Outcome variable (presence / absence of the
disease)
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Basic Principles (2)
Sensitivity, specificity
Prevalence, prior probability, predictive values
Likelihood ratios Dichotomous scale, cutoff points (continuous
scale)
Positive (true and false), negative (true & false) ROC (receiver operator characteristic) curve
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What is the reason that there aremany parameters in diagnostic test?
PrevalenceSensitivity (%)Specificity (%)LR+
LR-PPV (%)NPV (%)Pre-test OddsPost-test OddsPre-test Probability (%)Post-test Probability (%)
Disease
(+)
Disease
(-)Total
Test
(+)
True pos
a
False
pos
b
a+b
Test
(-)
False
neg
c
True neg
dc+d
Total a+c b+d
a+b+
c+d
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METHOD 1:
NATURAL FREQUENCIES TREE
Population
1.000
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IN EVERY 1.000 PEOPLE, 200 WILL HAVE THE DISEASE
Disease +
200
Disease -
800
Population
1.000
If these 1000 people are representative of the population atrisk, the assessed rate of those with the disease (20%)
represents the PREVALENCEof the diseaseit can also beconsidered the PRE-TEST PROBABILITY of having the disease
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Sensitivity
The proportion of people who truly
have a designated disorder who are
so identified by the test. Sensitive tests have few false
negatives.
When a test with a high Sensitivity isNegative, it effectively rules out the
diagnosis of disease. SnNout
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Disease +200
Disease -800
Test +190
Test -10
Population
1.000
In other words, thesensitivity is
190/200=95%
Test Alergi dengan Uji KulitSensitivitas 95 %, artinya:
SnNout: bila hasil uji kulitnya (-): 95% out (dia bukan penderita alergi )
Sensitivity
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The proportion of people who are
truly free of a designated disorder
who are so identified by the test.
Specific tests have few false positives
When a test is highly specific, a
positive result can rule inthe
diagnosis. SpPin
Specificity
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Disease +
200
Disease -
800
Test +
190
Test -
10
Population1000
Test Alergi dengan Uji KulitSpesifitas 96 % artinya:
SpPin: bila hasil uji kulitnya (+): 96% in (dia penderita alergi)
Test +
32
Test -
768
In other words, thespecificity is 768/800
= 96%
Specificity
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CASESNON-CASES
Sensitivity & Specificity
Negative Positive
Degree of positivity on test
%o
fGroup
DISEASED
NON-DISEASED
Test cut-offFALSE
NEGATIVES
FALSEPOSITIVES
Numeric? (complex)
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Sensitivity & Specificity
Sensitivity and Specificity are usuallyconsidered properties of the test ratherthan the setting, and are thereforeusually considered to remain constant.
However, sensitivity and specificity are
likely to be influenced by complexity ofdifferential diagnosesand a multitude ofother factors(cf spectrum bias).
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Sensitivity & Specificity
Positive & Negative Predictive Value
For sensitivity and specificity, thereference variable (denominator) is theDISEASE
For predictive value, the reference
variable (denominator)is the TEST
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POSITIVEPREDICTIVE
VALUE = 190/222=86 %
Disease +
200
Disease -
800
Test +
32
Test -
768
Test +
190
Test -
10
Population
1000
This is also the POST-
TEST PROBABILITY ofhaving the disease
Positive Predictive Value
Test Alergi dengan Uji KulitPPV 86 % artinya bila hasil uji kulitnya (+): kemungkinan dia
menderita alergi adalah 86%
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Disease +
200
Disease -
800
Test +
32
Test -
768
Test +
190
Test -
10
Population
1000
Negative Predictive Value
NEGATIVEPREDICTIVEVALUE = 768/778=99%
Test Alergi dengan Uji KulitNPV 99 % artinya bila hasil uji kulitnya (-): kemungkinan dia
tidak menderita alergi adalah 99 %
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Positive & Negative
Predictive Value
The Positive Predictive Value of a testwill vary (according to the prevalenceof the condition in the chosen setting)
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Predictive value & changing prevalence
Disease +
200
Disease -
9.800
Population
10.000
Prevalence reduced by an orderof magnitude from 20% to 2%
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Disease +
200
Disease -
9.800
Test +
392
Test -
9.408
Test +
190
Test -
10
Population
10.000Sensitivity and
Specificityunchanged
Predictive value & changing prevalence
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POSITIVE
PREDICTIVEVALUE = 33%
Positive predictive value
at low prevalence
Disease +
200
Disease -
9.800
Test +392
Test -
9.408
Test +190
Test -
10
Population
10.000Previously, PPV
was 86%
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NEGATIVEPREDICTIVE
VALUE >99%
Disease +
200
Disease -
9.800
Test +
392
Test -
9.408
Test +
190
Test -
10
Population
10.000Previously, NPV
was 99%
Negative predictive value
at low prevalence
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Prediction of low prevalence events
Even highly specific tests, when applied
to low prevalence events, yield a high
number of false positive results
Because of this, under such
circumstances, the Positive Predictive
Value of a test is low
However, this has much less influence
on the Negative Predictive Value
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Likelihood Ratio
Relative likelihood that a given test would be
expected in a patient with (as opposed to one
without) a disorder of interest.
probability (%) of the test resu ltin patients without disease
LR=probability (%) of a test resu ltin patients with disease
http://eta.cche.net/usersguides/hg/calculators/c1C-2.asp?A=50&B=50&C=50&D=50&H=ONhttp://eta.cche.net/usersguides/hg/calculators/c1C-2.asp?A=50&B=50&C=50&D=50&H=ON -
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Likelihood
The likelihood thatsomeone with thedisease will have apositive testis
190/200 or 95%This is the same asthe sensitivity
Disease +
200
Test +
190
Test -
10
Population
1000
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The likelihood thatsomeonewithoutthe disease willhave a positive testis 32/800 or 4%This is the same asthe (1-specificity)
Disease -
800
Test +
32
Test -
768
Population
1000
Likelihood
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LIKELIHOOD OF POSITIVE TESTIN THE ABSENCE OF THE DISEASE
SENSITIVITY
1- SPECIFICITY= = 23.8
LIKELIHOOD OF POSITIVE TEST
GIVEN THE DISEASE=LIKELIHOODRATIO (LR)
A Likelihood Ratio (LR) of 1.0
indicates an uninformative test (occurs when sensitivity and specificityare both 50%)
The higher the Likelihood Ratiothe better the test (other factors being equal)
0.95
0.04=
Test Alergi dengan Uji KulitLR+=23,8, artinya bila hasil uji kulitnya (+): hasil (+) ini dapat terjadi 23,8kali lebih besar terjadi pada penderita alergi dibandingkan dengan yang
bukan penderita alergi
Likelihood Ratio
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0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 0.2 0.4 0.6 0.8 1
PRE-TEST PROBABILITY
POST-TE
A (90%)
B (70%)
C (50%)
A : Sensitivity =Specificity = 0.9LR+ = 9.0
B : Sensitivity =Specificity = 0.7LR+ = 3.0
C : Sensitivity =
Specificity = 0.5LR+ = 1.0
P
OST-TESTPROBA
BILITY
Sensitivity & Specificity; PositivePredictive Value; Prevalence & LR
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DISEASE
Yes No Total
3 7Yesa b
10a+b
c dNo 1 89 90 c+d
4 96 100
TEST
Total a+c b+d a+b+c+d
METHOD 2:
TRADITIONAL 2x2 TABLES
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DISEASE
Yes No Total
3 7Yesa b
10a+b
c dNo 1 89 90 c+d
4 96 100TEST
Totala+c b+d a+b+c+d
SENSITIVITY
SENSITIVITY
The proportion of people with the diagnosis(N=4) who are correctly identified (N=3)
Sensitivity = a/(a+c) = 3/4 = 75%
FALSENEGATIVES
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DISEASE
Yes No Total
3 7Yesa b
10a+b
c dNo 1 89 90 c+d
4 96 100TEST
Totala+c b+d a+b+c+d
SPECIFICITY
SPECIFICITY
The proportion of people without the diagnosis(N=96) who are correctly identified (N=89)
Specificity = d/(b+d) = 89/96 = 93%
FALSEPOSITIVES
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DISEASE
Yes No Total
3 7Yes a b
10 a
+b
c dNo 1 89 90 c+d
4 96 100TEST
Totala+c b+d a+b+c+d
PRE-TEST ODDS
In the sample as a whole, the odds of having thedisease are 4 to 96 or 4% (the PRE-TEST ODDS)
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DISEASE
Yes No Total
3 7Yesa b
10a+b
c dNo 1 89 90 c+d
4 96 100TEST
Totala+c b+d a+b+c+d
POST-TEST ODDS
In those who score positive on the test, the odds of havingthe disease are 3 to 7 or 43% (the POST-TEST ODDS)
In the sample as a whole, the odds of having the diseaseare 4 to 96 or 4% (the PRE-TEST ODDS)
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DISEASEYes No Total
3 7Yesa b
10a+b
c d
No 1 89 90 c+d
4 96 100TES
T
Totala+c b+d a+b+c+d
POST-TEST ODDS
In those who score positive on the test, the odds of havingthe disease are 3 to 7 or 43% (the POST-TEST ODDS)
In the sample as a whole, the odds of having the disease
are 4 to 96 or 4% (the PRE-TEST ODDS)
In those who score negative on the test, the odds of having
the disease are 1 to 89 or approximately 1%
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BAYES THEOREM
POST-TEST ODDS =
LIKELIHOOD RATIO x PRE-TEST ODDS
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LIKELIHOOD RATIO AND PRE-
AND POST-TEST PROBABILITIES
For a given test with a givenlikelihood ratio, the post-
test probability will dependon the pre-test probability(that is, the prevalence ofthe condition in the sample
being assessed)
SENSITIVITY ANALYSIS OF
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SENSITIVITY ANALYSIS OF
A DIAGNOSTIC TEST
Value 95% CI
Pre-testprobability
35% 26% to 44%
SENSITIVITY ANALYSIS OF
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Applying the 95% confidence
intervals above to the nomogram,the post-test probability is likely to
lie in the range 55-85%
Value 95% CI
Pre-testprobability
35% 26% to 44%
Likelihoodratio
5.0 3.0 to 8.5
SENSITIVITY ANALYSIS OF
A DIAGNOSTIC TEST
The diagonal line (representing Sensitivity=0.5
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RECEIVER OPERATING CHARACTERISTIC CURVE
Overall shape ispredicted by thereciprocal relationshipbetween sensitivity andspecificity
The closer the curve getsto Sensitivity=1 andSpecificity=1, the betterthe overall performanceof the test
g ( p g yand Specificity=0.5) represents performance nobetter than chance
Hence the area under thecurve gives a measure ofthe tests performance
FALSE POSITIVE RATE (1-Specificity)
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0
100
1-Specificity
Sensitivit
y
AREA UNDER ROC CURVES
0
100
1-Specificity
S
ensitivity
Sensitivity and specificity both100% - TEST PERFECT
Sensitivity and specificity both50% - TEST USELESS
AREA=1.0
AREA=0.5The area under a ROCcurve will be between0.5 and 1.0
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0
100
1-Specificity
Sensitivity
Area = 0.7 (between0.5 and 1.0)
Consider (hypothetically) two patients drawn
randomly from the DISEASE+ and DISEASE- groupsrespectively
If the test is used to guess which patient is from theDISEASE+ group, it will be right 70% of the time
AREA UNDER ROC CURVES
APPLYING A DIAGNOSTIC TEST
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APPLYING A DIAGNOSTIC TEST
IN DIFFERENT SETTINGS
The Positive Predictive Value of a test will vary
(according to the prevalence of the condition in
the chosen setting)
Sensitivity and Specificity are usually consideredproperties of the testrather than the sett ing, and
are therefore usually considered to remain
constant
However, sensitivity and specificity are likely to
be influenced by complexity of differential
diagnoses and a multitude of other factors (cf
spectrum bias)
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Diagnosis test & clinical setting
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Diagnosis test & clinical setting
Diagnosis test & clinical setting
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Diagnosis test & clinical setting
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Interpreting Diagnostic Studies
VIA - RaMMbo
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Validity
Selection? VALIDITYQUESTION
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Participants
Index group (IG) &Gold standard
Comparison Group (CG)
Outcome
IG
C
G
+- DC
+ -BA
Representative?
VALIDITY
Reproducible
Maintain?
Measurementsblind subjective? OR
objective?
QUESTION:
Di ti A St d
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Diagnostic Accuracy Study:Basic Design
Series of patients
Index test
Reference standard
Blinded cross-classification
Recruitment:
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Recruitment:Was diagnostic test evaluated is representative
spectrum of patient?
Series of patients
Index test
Reference standard
Blinded cross-classification
Maintenance:
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Maintenance:Was the endpoint of the reference standard
obtained for all subjects?
Series of patients
Index test
Reference standard
Blinded cross-classification
Measurement:
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Measurement:Were the assesors kept blind to the results of eachtest and/or were the reference standard endpoint
objective
Series of patients
Index test
Reference standard
Blinded cross-classification
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Selected Patients
Index test
Reference standard
Blinded cross-classification
Spectrum Bias
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Series of patients
Index test
Reference standard
Blinded cross-classification
Verification Bias
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Series of patients
Index test
Blinded cross-classification
Ref. Std A Ref. Std. B
Differential Reference Bias
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Series of patients
Index test
Reference standard
Unblinded cross-classification
Observer Bias
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Importance
What should I do
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INTERVENTION
ETIOLOGY/RISK FACTORS
DIAGNOSIS
PROGNOSIS & PREDICTION
FREQUENCY & RATE
PHENOMENA / THOUGHTS
I
M
P
O
RT
A
NC
E
about this condition
or problem?
What causethe problem?
Does this person
have the condition
or problem?
Who will get
the condition
or problem?
How commonis the problem?
What are the
type of problem?66
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CLINICAL TRIAL
PROGNOSIS
DIAGNOSTIC
RRR, ARR, NNT
p & CI
Survival curve
RR / ORp & CI
Sn,Sp,LH,PPV,NPV
p & CI
I
M
P
O
RT
A
NC
E 67
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Applicability
PICO & Applicability
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PICO & Applicability
Your question
(PICO)
Study What do theResult mean?
How well was
study done?
Validity
Importance
Applicability
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Diagnostic tests
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Diagnostic tests
Is not about finding absolute truth, butabout limiting uncertainty
establishes both the necessity and the
logical base for introducing probabilities,pragmatic test-treatment thresholds ..
Start thinking about
what youre going to do with the results of thediagnostic test, and
whether doing the test will help your patients
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CRITICALAPPRAISALDIAGNOSTICTEST
Critical appraisal diagnostic test
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Critical appraisal diagnostic test
Use worksheet (VIA; RAMMbo)
STARD
Use supporting softwares CAT Maker
http://localhost/var/www/apps/Local%20Settings/Temp/catmaker/CATMAKER.EXEhttp://localhost/var/www/apps/Local%20Settings/Temp/catmaker/CATMAKER.EXE -
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Validity (1)
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y ( )Apakah penelitian uji diagnostik dilakukan secara tersamar dengan baku
emas yang benar ?
Validity (2)Apakah uji diagnostik dilakukan terhadap pasien dengan spektrum
penyakit atau kelainan yang memadai sehingga dapat diterapkan dalampraktek sehari-hari?
Validity (3)Apakah pemeriksaan dengan baku emas dilakukan tanpa memandanghasil pemeriksaan dengan uji diagnostik ?
Important
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pBerapa Sn, Sp, LR+, LR-, PPV, NPV, Pre-test probability, Post-test
probability, Pre-test Odds, Post-test Odds ?
Applicable (1)
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Applicable (1)Apakah uji diagnostik tersebut tersedia, terjangkau dan akurat?
Applicable (2)Apakah kita bisa memperkirakan pre-test probability (prevalens)penyakit pada pasien kita ?
Applicable (3)Apakah post-test probability yang dihitung akan mengubah tatalaksana
pasien kita?
Applicable (4)Apakah secara keseluruhan uji diagnostik tersebut bermanfaat bagi
pasien ?
STARD initiative (25 items)
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Section and and
topic
Title, abstract, and
keywords
Introduction
Methods
Participants
Test methods
Statistical methods
Results Participants
Test results
Estimates
Discussions
STARD initiative (25 items)Standards for Reporting of Diagnostic Accuracy
Bossuyt PM, Reitsma JB, Bruns, DE, Gatsonis CA, Glasziou PP et al. BMJ 2003,326:41-6
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1stcomponent of STARD
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2nd component of STARD
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Does early diagnosis really lead to improvedsurvival, or quality of life, or both?
Are the early diagnosed patients willing partners inthe treatment strategy?
Is the time and energy it will take us to confirm thediagnosis and provide (lifelong) care well spent?
Do the frequency and severity of the target disorderwarrant this degree of effort and expenditure?
Guides for deciding whether a screening or
early diagnostic maneuver does more goodthan harm: