Tutorial Tambahan Tiara 3 Nov 2011

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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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