PENELITIAN ANALITIKDr. Ernawaty Tamba, MKM

Desain Penelitian Berdasarkan tujuanBerdasarkan bingkai waktuBerdasarkan ada tidaknya perlakuanBerdasarkan penelusuran sebab-akibatBerdasarkan pengambilan informasi faktor sebab & akibat

1. Berdasarkan tujuanStudi Deskriptif : mendeskripsikan suatu kejadian ( outcome).Menjelaskan distribusi masalah kesehatan (Describe the disease by Time, Place and Person)Laporan kasusSeri kasusStudi kros-seksionalStudi ekologi

Studi Analitik : Studi mengenai determinant dari masalah kesehatan. Mendeskripsikan asosiasi antara exposure dengan outcome Kasus kontrolKohortStudi intervensi

2. Berdasarkan bingkai waktuProspective study ( cohort study )Retrospective study ( case control study )Retrospective cohort study

Berdasarkan bingkai waktu (outcome dgn mulainya penelitian)

Case control studyDiseaseControlsExposure??

timeExposureDiseaseoccurrenceProspective cohort study

Retrospective cohort studiesExposuretimeDiseaseoccurrenceCase study Salmonella in Belfast

Main Observational Study DesignsFUTUREPRESENTPASTCross-sectional studyCase-control studyProspective cohortRetrospective cohortFUTUREPRESENTPASTCrosssectional studyCase-control studyProspective cohortRetrospective cohortAssess exposure and outcomeKnown outcomeAssess exposureAssess exposureKnown exposureAssess outcomeAssess outcomeKnown exposureAssess outcomeTime

3. Berdasarkan ada tidaknya perlakuan

a. Penelitian observasional:1. Penelitian diskriptif2. Kasus-kontrol3. Studi kohort

b. Penelitian intervensi:1. Trial/eksperimental 2. Penelitian kuasi eksperimental

4. Berdasarkan penelusuran sebab-akibat

a. Tak ada penelusuran sebab - akibat:- Penelitian diskriptif

b. Ada penelusuran sebab - akibat:- Kasus kontrol - Kohort prospektif - Kohort retrospektif - Studi intervensi

5. Berdasarkan pengambilan informasi faktor sebab & akibat

1. Informasi status sebab & akibat pada saat yang sama: Studi kros-seksional

2. Informasi status sebab & akibat pada saat yang berbeda (sebab yg terjadi waktu yg lalu atau sedang berjalan):Studi longitudinal:a. Studi kasus-kontrolb. Studi kohortc. Studi intervensi

Studi Cross-sectional Tujuan:Mempelajari angka kejadian suatu penyakit/masalah kesehatanMempelajari hubungan antara suatu faktor risiko dengan angka kejadian suatu penyakitFaktor risiko/exposure dan status penyakit/masalah kesehatan diukur pada saat yang sama.

Studi Cross-sectionalDisebut juga studi prevalensiPengukuran variabel independet (exposure) dan variabel dependent (outcome) dilakukan secara simultanTemporal relationship tidak jelas Tidak dapat terlihat sekuens mana yang terjadi lebih dulu, variabel independent atau variabel dependent, atau sebaliknya. Tidak dapat melihat hubungan sebab-akibat (exposure harus mendahului outcome )Unit pengamatan dan unit analisisnya adalah individu

Cross-sectional DesigntimeStudy only exists at this point in timeStudypopulationNo DiseaseDiseasefactor presentfactor absentfactor presentfactor absent

ANALISIS YANG DILAKUKAN 1. DESKRIPTIF : Distribusi frekwensi kejadian penyakit/ masalah kesehatan berdasarkan orang - tempat - waktu Distribusi frekwensi variabel exposure dan outcome (angka prevalens) 2. ANALITIK : melihat korelasi/hubungan antara variabel- variabel yang diteliti

Kros-Seksional (Studi prevalens, Prevalens survei)Jumlah?Umur?Sex?Pendidikan?Pekerjaan?Status penyakit X?Status variabel Y?

Study DesignExposure(Risk Factor) Disease (Outcome) ++__

Prevalence ratio of disease in exposed and unexposedDiseaseYesNoExposureYesNoabcda + b c + dcaPR =So a/a+b and c/c+d = probabilities of diseaseand PR is ratio of two probabilities

Prevalence ratio of exposure in disease and nondisease DiseaseYesNoExposureYesNoabcda + c b + dbaPR =So a/a+c and b/b+d = probabilities of exposureand PR is ratio of two probabilities

Cohort studiesCohort study is undertaken to support the existence of association between suspected cause and diseaseKey point: presence or absence of risk factor is determined before outcome occurs

Cohort studiesFaktor risiko diidentifikasi, kemudiansubyek diikuti sampai periode tertentu untuk melihat terjadinya efek.Subyek diikuti secara alamiah sampai terjadinya kasus ( penyakit )Sebagai pembanding adalah kelompok yang tidak terpajan sama sekali, dan diikuti sampai periode tertentu, untuk melihat terjadinya efek

Analisis yang dilakukanIdentify group of exposed, unexposedFollow up for disease occurrenceMeasure incidence of diseaseCompare incidence between exposed and unexposedRelative Risk : Ie / Iue

Case control studyIn Case control studies, comparison are made between a group of people who have the disease being studied ( cases ) and group of people who do not ( control )It compares the exposure distribution between the group of patient with and without the diseaseProceeds from effects to cause

Analisis yang dilakukanAnalisis hasil studi kasus kontrol yaitu penentuan Odds ratio Odds ratio in case control study :The Ratio of odds that the cases were exposed to the odds that the control were exposedThe ratio off odds of exposure among the Cases to the odds of exposure among the Control

OR : estimates the strength or magnitude of the association between an exposure and a disease Odds adalah perbandingan antara peluang terjadinya efek dibagi peluang tidak terjadinya efekOR : odds pada kelompok kasus dibanding odds pada kelompok kontrolOR = 1; pajanan bukan faktor risikoOR < 1 ; pajanan merupakan faktor protektifOR > 1 ; pajanan merupakan faktor risiko

Probability and OddsOdds another way to express probability of an eventOdds = # events # non-eventsProbability = # events # events + # non-events = # events # subjects

Probability and OddsProbability = # events # subjects Odds = # events # subjects = probability # non-events (1 probability) # subjectsOdds = p / (1 - p) [ratio of two probabilities]

Probability and OddsIf event occurs 1 of 5 times, probability = 0.2.

Out of the 5 times, 1 time will be the event and 4 times will be the non-event, odds = 0.25

To calculate probability given the odds: probability = odds / 1+ odds

Odds ratioAs odds are just an alternative way of expressing the probability of an outcome, odds ratio (OR), is an alternative to the ratio of two probabilities (prevalence or risk ratios)

Odds ratio = ratio of two odds

Odds ratio of disease in exposed and unexposedDiseaseYesNoExposureYesNoabcda + b c + dcaOR =aa + b1 -cc + d1 - Formula of p / 1-p in exposed / p / 1-p in unexposed

Odds ratio of disease in exposed and unexposeda + b c + dcaOR =aa + b1 -cc + d1 - = aa + b ba + b cc + d dc + d a b c d

==adbc

Odds ratio of exposure in diseased and not diseasedDiseaseYesNoExposureYesNoabcda + c b + dbaOR =aa + c1 -bb + d1 -

OR for disease = OR for exposurea + c b + dbaORexp =aa + c1 -bb + d1 - = aa + c ca + c bb + d db + d a c b d

==adbcImportant characteristic of odds ratio

Experimental studies

Always prospectiveInvolving human participantsControlsDrugs, procedures, preventive measure

Experimental studies uuStudi yang paling baik dalam memperlihatkan hubungan sebab akibatUji klinis acak terkontrol ( randomized controlled trial = RCT ) adalah Baku emas uji klinisKelompok pasien yang diobati harus sama dalam hal: perjalanan penyakit, perlakuan selama penelitian, kriteria dan pengukuran kesembuhan

Experimental studiesSalah satu aspek yang sangat penting dalam uji klinis adalah randomisasiRandomisasi : proses penentuan subyek penelitian yang mendapat perlakuan dan kelompok yang merupakan kontrolJenis randomisasi : simple randomization,block randomization, stratified randomizationHal lain yang juga sangat penting dalam menghindarkan bias dalam uji klinis adalah membuat ketersamaran ( masking/blinding), salah satunya dengan penggunaan plasebo pada kelompok kontrol

Clinical TrialPhase 1: mendapatkan informasi tentang aspek keamanan, dan aspek farmakologi obatPhase 2: menilai dosis terapi yang paling efektifPhase 3: evaluasi obat secara keseluruhan, dibandingkan dengan terapi standarPhase 4: post marketing trial, mengevaluasi obat yang telah dipakai di masyarakat

Key element of RCT :ControlRandomizationBlinding

THANK YOU AND HAVE A NICE DAY

**********************The proportion with prevalent disease among those exposed is the probability of prevalent disease among the exposed, and similarly for the unexposed. We are making this point to distinguish a ratio based on probabilities from a ratio based on odds, to be explained shortly.**********Odds is an alternative way to express the probability of an event. Odds are most simply calculated as the number of events divided by the number of non-events. Probability is the number of events divided by the total of the number of events plus the number of non-events, which is the same as the number of events divided by the number of subjects.*The formal way to describe the odds is as the probability of the event divided by the probability of the non-event. So odds are the ratio of two fractions: the number of events divided by the number of subjects (the probability of the event) and that fraction divided by the number of non-events divided by the number of subjects (the probability of the non-event). So the formula for odds is p / (1 p). Since both fractions have the number of subjects in the denominator, they reduce to our first presentation of odds as the number of events divided by the number of non-events.*To apply some numbers to the formulas, if the probability is 1/5 = 0.2, then the odds will be are 1/5 / 4/5 = = 0.25. Calculating the odds without the number of subjects by the ratio of the number of events (1) by the number of non-events (4), odds = = 0.25.

To go in the other direction from odds to probability divide the odds by 1 + odds. In this example, / 1+1/4 = / 5/4 = 1/5, the probability.

For those interested in why odds are used in gambling: odds give the ratio of the event to the non event, and the ratio of the event to the non-event tells you what the pay out has to be for a fair bet. For example, if you wager 1 dollar that the toss of one die will be the number 3, the probability is 1/6 since the die has 6 sides with 1 through 6 on the sides. Since the probability is 1/6, the odds are 1/6 / 5/6 = 1/5. The expectation is that 6 rolls of the die will result in a 3 one time and other numbers 5 times (on average!). So for the payout and the amount bet to be fair, i.e., balanced, you would need to receive 5 dollars when the number 3 comes up one time out of six to equal the 5 dollars you will lose one at a time on the other 5 tosses. So the odds are 1/5 usually written as 1:5 or 5:1 and spoken as five to one. Of course, in gambling calculating the odds are usually used to insure that the payout is not according to fair odds but odds that favor the casino.

*To repeat, the odds ratio is less intuitive than a prevalence ratio or a risk ratio, but it is no less valid and expresses the probability of an outcome in a mathematically rigorous way. *We switch from numbers and return to our algebraic schematic of the 2x2 table to illustrate some important characteristics of the odds ratio. This just expresses probability and (1 - probability) for the exposed and for the unexposed groups using the a, b, c, and d of the schematic.*Doing a little algebra to show how these four fractions reduce down to what is called the cross-product of the 2x2 table, the ratio of the products of the two diagonals. Notice that this result would not be affected by whether we arrange disease across the top of the table and exposure down the side or the other way around (as in STATA).*So now we are calculating the probabilities of exposure and non-exposure in those with disease and similarly for those without disease and then forming an odds ratio. So the probabilities, with our arrangement of disease across the top, are calculated within the columns rather than within the rows. In a cross-sectional study, we would normally not be interested in looking at exposure by disease status because we are always interested in how exposure leads to disease, i.e., how disease is distributed among the exposed. We are looking at this way in order to show that the odds ratio for exposure equals the odds ratio for disease.*Again some algebra demonstrates that we get the same term as before. This is an important property of the odds ratio and its use in case-control studies.

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