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Kelas MKO KMPK
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Casecontrol:
Case Ca paru R
on ro e as a paruIntervention Control
penyakitnya
em an ng an proporspaparan (merokok vs tidakmerokok)
u come u come
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Seluruh populasi, Cohort study
paparannya. Population
Yangdibandingkan:Non Random Allocation
Angka kejadian
en akitn aGroup A Group B
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Lebih mudah menemukan kasus diRS
Akses ke rekam medis yanglengkap
as en cen erung e mu a a a e er asama(karena penelitian ini tentang penyakit yang
Mudah mendapatkan kontrol
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Akta kematian,laboratorium patologi klinik,
data
, ,
kerja
Tetangga,teman,pasien laindari dokter yang
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Kemungkinan besar berasal dari lingkungan
ekonomi,
tempat tinggal,
akses ke layanan,
Rekam medis standard
Mudah bekerjasama
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dirawat karena penyakit lainyangjuga
disebabkan oleh merokok
Sehingga,kebiasaan merokok pada kontrolakan lebih tin i dari ada o ulasi normal
hubungan antara merokok dan Ca Paruakan ?
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Cases Controls
Cigare e smoker 1,350 1,296
Non-smoker 7 61
T a ,357 ,357
Proporsi perokok pada kasus: 1.350/1.357=99.5%
Proporsi perokok pada kontrol: 1.296/1.357=95.5%
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Oddsmerokok pada pasien Ca Paru (kasus):
Odds = probability / (1 - probability) = proportion / (1 - proportion)
Odds of smoking, cases:= = . :
Odds = #yes / #no = #wins / #losses = #exposed / #unexposed
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12 1 1 1 =12 1 =21.2 : 1
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Ra io of odds = (a/c) (b d) =(1350 7) (1296 61) =192.9 21.2 =9.1
C oss- oduc a io =(a d b c) =(1350 61) (12 6 7) = .
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Jumlah rokok #kasus #Kontrol
114
rokok/hari 565 706
=
7/61
1-14 ciga e es, OR =(565 61) / (706 7) = 7.0
15-24 ciga e es, OR = 445 61 408 7 = 9.525+ cigarettes, OR = (340 x 61) / (182 x 7 ) =16.3
All smokers, OR = (1350 x 61) / (1296 x 7) = 9.1
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Selectionbias
In ormation ias
Confounding Investigatorerror
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Daily Rate
number of Deaths Person- Mortality rate differencecigarettes from lung years per 1000 Rate per 1000smo ed cancer a ris erson- ears Ratio erson- ears
0 3 42,800 0.07 referent referent
1-14 22 38,600 0.57 8.1 0.50
15-24 54 38,900 1.39 19.8 1.32
25+ 57 25,100 2.27 32.4 2.20
All smokers 133 102,600 1.30 18.6 1.23
Total 136 145,400 0.94
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The twomajortypesofbias:
Measurement bias
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characteristicsof
people
selected for
astudy
and
those notselected
If it occurs: we see a relation between risk factor and disease
that is different in those in the study compared
not participate
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Whyisitimportant?
resultsto
THE
WHOLE
POPULATION
eg Letstryandfindoutwhatproportionofpost
menopausalwomen
in
Australia
use
HRT?
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Remember..
Wheneverwedoastud weselecta rou of
people,
do
the
study,
get
the
result...
Wethenusetheresulttogeneralizetothewhole
population
eg isthisthetrueprevalenceofwomenonHRTin
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Prevalenceofpostmenopausalwomenin
Australia
usin
HRT?
AskALL
women
GotoGP
Recruitfromgyms
Randomtelephonecontact
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have effected the type of subjects you have in yourstudy
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=
Advertisein
the
newspapers
=?
health
conscious
women
GotoGP=?morelikelytobeonHRT Recruitfromshoppingcentres=?healthconsciouswomen Recruitfromgyms=?healthconsciouswomen =
home
Randomtelephonecontact=?lesshealthconsciouswomen
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Selectionbiasincasecontrolstudies
an e a ma or pro em
Controlsshouldbeselectedsothattheyrepresent
drawn.
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Selectionbiasincasecontrolstudies
Eg Case control study of childhood brain tumor. Cases
.
How do we find controls? How might you do this?
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Hospitalbasedcontrols Oftenused
Couldtherebeaproblem?
Best=matched
to
post
code.
Why?
E Casecontrolstud oflun cancerattheAlfredHospital.Canyoucollectcontrolsfromthe
orthopoedic unit?
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Less problem because exposure is identified,
group selected
eg potential problem if general population is used
healthy worker effect
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Thosethat
drop
out
of
the
study
NOT
the
same
as
thosethatsta inastud
Mayintroducebias
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Occurswhen
the
measurement
or
classification
of
diseaseorriskfactorare notaccurate
supposedtomeasure
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:
server o server as
Studyparticipant
(responder
bias)
Theinstruments e.g.questionnaireorsphygmomanometer)usedtomakethe
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