study design magister.pptx

8/10/2019 Study Design Magister.pptx

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Study Designs

in Clinical Research:An Overview

Kuntjoro Harimurti

Department of Internal MedicineCenter for Clinical Epidemiology and EBM (CE-EBM)

Cipto Mangunkusumo Hospital / Faculty of Medicine UI, Jakarta

[email protected]


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...a poor design cannot be salvaged by a

good statistics


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Research Design

A specific plan or protocol for conducting the

study, which allows the investigator to

translate the conceptual hypothesis into anoperational one

All procedures for selecting and recruiting

individuals in the study sample


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Clinical Study Types

Observational Studies

Case report

Case series

Cross-sectional

Case-control

Cohort

Experimental Studies Uncontrolled

Controlled


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Observational Studies

A study in which the investigator

monitors, but does not influence, theexposure status of individual subjects and

their subsequent disease status


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Case-report and case series

Not considered to be true investigation

Only describe clinical / laboratory

characteristics

No hypothesis, no statistical analysis, no

sample size estimation

Involve new disease, rare disease, or rare

manifestations of common diseases

Sometimes useful to identify research

problem and generating hypothesis


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Cross-sectional study

A study in which determinant (risk factors)

and outcome (disease) are collected at the

same point in time for each participant

Characteristics of cross-sectional study:

Observational = non-experimental

No time-axis

Individual observed only once

Could be descriptive or analytic


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Use of cross-sectional studies

Prevalence studies (descriptive): survey, census

Etiologic studies Determinant characteristics that do not change (sex,

gene expression)

Diagnostic studies Estimate probability of disease presence on basis of

diagnostic determinants

Reference range studies

Repeated cross-sectional studies Measure change / evaluate intervention


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Measures and analyses

in cross sectional studies

Categorical variables

Prevalence, percentage

Prevalence ratio

Odds ratio

Numerical variables

Mean Means difference

Correlation coefficient


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Case-control study

I would trust only six people in the world to doa proper case-control study (David L. Sackett)

A study in which outcomes (disease/cases andno-disease/controls) identified first and riskfactors accounted in and compared betweencases and controls

Characteristics of case-control study: Observational

Retrospective Analytic

Essence of case-control study: sampling!


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Analysis in case-control studies

Objective: to measure association, estimating

relative risk/risk ratio (RR)

Risk could not directly calculated from a case-

control dataalternative measure: odds Odds: probability of event / probability of no-event

(p/1-p)

Odds ratio (OR): ratio of two odds (with CI and p-

value) Interprete cautiously as RR (risk ratio or relative

risk)


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Cohort study

Cohort: the tenth division of the Roman army.

Cohort of war fighters

In research: a cohort is a group of subjects

from which data are collected

Cohort studies: disease-free subjects

selected first according to the risk factor and

further followed for the disease Prospective and restrospective cohort


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Analysis in cohort studies

Measuring incidence: Cumulative incidence (risk)

Incidence density: person-time

Measuring (strength of) association: Risk ratio/relative risk (RR) Sometimes expressed as OR

With p-value and CI

Special analysis in cohort studiessurvivalanalysis: Time to event as outcome

Calculating prob. of survival in a specific period

Measure of association: hazard ratio (HR)


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Observational Designs

Today

Participants,

Patients,

Subjects

Cases

Controls

E

(+)

E(-)

E(+)

E(-)

Retrospective

Cohort

Case-control

Cases Controls

E(+) E(-)E(+) E(-)

Exposure

NoExpo.

Case

Control

Case

Control

Prospective Cohort

Cross-sectional

Time


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Examples

In a discussion after a ward round, a medical student

noted that most of their patients in the ward having

problem of infections, including hospital-acquired infection

(nosocomial infection). After quick search, they were

informed that nosocomial infection is a common problembut the incidence and contributing factors are varies in

different settings.

The supervisor suggest them

to conduct a research regardingthis problem.


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Cross-sectional: method

The researcher come to a ward during 2012-2013

period, collecting data about risk factors and

diagnosis of nosocomial infection at one point of time

in each patient. Determine who have risk factors or

not, and who have nosocomial infection or not.

Calculate the prevalence of nosocomial infection

Compare the prevalence of nosocomial infection in

patients with and without risk factorsprevalence

ratio (PR)

Prevalence: proportion of disease among population

at risk


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Cross-sectional: result

300 patients hospitalized during 2012-2013

35 patients have diabetes and nosocomial infection

40 patients have diabetes but do not have

nosocomial infection 75 patients do not have diabetes but have

nosocomial infection

150 patients do not have either diabetes or

nosocomial infection


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Cross-sectional: analysis

Nosocomial

(+)

Nosocomial

(-)

Diabetes

(+)

35 40 75

Diabetes

(-)75 150 225

110 190 300

Prevalence of nosocomial among all hospitalized patients?

Prevalence of nosocomial among pts with diabetes?

Prevalence of nosocomial among pts without diabetes?

Prevalence ratio (PR)?


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Nosocomial

(+)

Nosocomial

(-)

Diabetes

(+)

35 40 75

Diabetes

(-)75 150 225

110 190 300

Prevalence of nosocomial among all hospitalized patients = 110/300 = 36,7%

Prevalence of nosocomial among pts with diabetes?




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Nosocomial

(+)

Nosocomial

(-)

Diabetes

(+)

35 40 75

Diabetes

(-)75 150 225

110 190 300


Prevalence of nosocomial among pts with diabetes = 35/75 = 46,7%




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Nosocomial

(+)

Nosocomial

(-)

Diabetes

(+)

35 40 75

Diabetes

(-)75 150 225

110 190 300



Prevalence of nosocomial among pts without diabetes = 75/225 = 33,3%



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Nosocomial

(+)

Nosocomial

(-)

Diabetes

(+)

35 40 75

Diabetes

(-)75 150 225

110 190 300



Prevalence of nosocomial among pts without diabetes = 75/225 = 33,3%

Prevalence ratio (PR) = 46,7% / 33,3% = 1,4


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Case-control: method

The researcher come to the ward, identify

patients with nosocomial infection (case) and

then select patients without nosocomial

infection (control). Measure risk factors incase and control.

Calculate and compare the odds of risk

factors in case and in controlodds ratio

(OR)

Odds: probability of event / probability of no-

event (p/1-p)


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Case-control: result

Among 150 patients with nosocomial infection

(case), 75 of them were hospitalised >7 days

Among 150 patients without nosocomial

infection (control), 50 of them werehospitalised >7 days


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Case-control: analysis

Nosocomial

(+)

Nosocomial

(-)

Hosp.d

>7 days

75 50

Hosp.d

7 days among nosocomial (+) pts?

The odds of hospitalised >7 days among nosocomial (-) pts?

Odds ratio (OR)?


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Nosocomial

(+)

Nosocomial

(-)

Hosp.d

>7 days

75 50

Hosp.d

7 days among nosocomial (+) pts = 75/75 = 1

The odds of hospitalised >7 days among nosocomial (-) pts?

Odds ratio (OR)?


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Nosocomial

(+)

Nosocomial

(-)

Hosp.d

>7 days

75 50

Hosp.d


The odds of hospitalised >7 days among nosocomial (-) pts = 50/100 = 0,5

Odds ratio (OR)?


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Nosocomial

(+)

Nosocomial

(-)

Hosp.d

>7 days

75 50

Hosp.d


The odds of hospitalised >7 days among nosocomial (-) pts = 50/100 = 0,5

Odds ratio (OR) = 1 / 0,5 = 2


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Cohort: method

The researcher select all new patients without nosocomial

infection and measure/ determine risk factors in all

subjects at admission. Afterward, follow-up all patients for

certain period and determine whether nosocomial

infection occurs or not during hospitalization.

Calculate incidence of nosocomial infection in all patients

Calculate and compare the incidences (risks) of

nosocomial infection in subject with and without risk

factorrelative risk/risk ratio (RR)

Incidence: new cases (outcome) among subject who were

followed-up in certain periods


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Cohort: result

Among 150 patients age >60 years without

nosocomial infection on admission, 60 of

them develop nosocomial infection during 30-

day of follow-up Among 150 patients age


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Cohort: analysis

Nosocomial

(+)

Nosocomial

(-)

Age >60

years

60 90 150

Age 60 years old pts?

Incidence of nosocomial among


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Cohort: analysis

Nosocomial

(+)

Nosocomial

(-)

Age >60

years

60 90 150

Age 60 years old pts?



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Cohort: analysis

Nosocomial

(+)

Nosocomial

(-)

Age >60

years

60 90 150

Age 60 years old pts = 60/150 = 40%



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Cohort: analysis

Nosocomial

(+)

Nosocomial

(-)

Age >60

years

60 90 150




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Cohort: analysis

Nosocomial

(+)

Nosocomial

(-)

Age >60

years

60 90 150




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Experimental Study

A study in which the investigator

influences the exposure status of

individual subjects and then monitors the

subjects outcome


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Types of experimental studies (trials)

Blinded Not blinded

Randomised Not randomised

Controlled Not controlled

Trial

A randomized double-blind controlled clinical trial (RCT)


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Clinical Trial

A randomized double-blind controlled clinical

trial (RCT)

Gold standard of research design which

provide the most convincing evidence ofrelationship between exposure (intervention)

and outcome

Use human subject Always prospective

Comparing two or more intervention

strategies


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Clinical Trial: Parallel Group Design

Participantsscreened for

entry criteria

Co

ntrol

Trea

tment

Experimental

Treatment

W

ithout

Outcome

With

Outcome

Without

Outcome

With

Outcome

Time

Screening Baseline Treatment

R

Outcome

measurement


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Nosocomial infection example: RCT

Research question

Is simvastatin effectively reduce the risk of

nosocomial infection in hospitalized elderly patients?

Hypothesis

Simvastatin can reduce the risk of nosocomial

infection in hospitalized elderly patients


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RCT: method

Investigator randomly allocated a number of eligible

patients on admission into two groups: intervention

and placebo

Intervention drug and placebo were given in blinding

fashion

After certain of time (eg. 30-days), determine (with

objective criteria or in blinding fashion) how many

patients develop nosocomial infection in each group


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RCT: results

200 patients were randomly allocated into

simvastatin group (100 patients) and placebo

group (100 patients)

Among 12 patients in simvastatin group andamong 18 patients in placebo group

developed nosocomial infection during 30

days of follow-up


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RCT: analysis

Nosocomial

(+)

Nosocomial

(-)

Simvastatin 12 88 100

Placebo 18 82 10030 170 200

Event rate in experimental (simvastatin) group (EER)?

Event rate in control (plasebo) group (CER)?

Relative risk reduction (RRR)?

Absolute risk reduction (ARR)?

Number needed to treat (NNT)?


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RCT: analysis

Nosocomial

(+)

Nosocomial

(-)


Placebo 18 82 10030 170 200

Event rate in experimental (simvastatin) group (EER) = 12/100 = 12%

Event rate in control (plasebo) group (CER)?





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RCT: analysis

Nosocomial

(+)

Nosocomial

(-)


Placebo 18 82 10030 170 200

Event rate in experimental (simvastatin) group (EER) = 12/100 = 12%

Event rate in control (plasebo) group (CER) = 18/100 = 18%





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RCT: analysis

Nosocomial

(+)

Nosocomial

(-)


Placebo 18 82 10030 170 200

Event rate in experimental (simvastatin) group (EER) =12/100 = 12%

Event rate in control (plasebo) group (CER) =18/100 = 18%

Relative risk reduction (RRR) =[CEREER] / CER = [18%12%] / 18% = 33,3%




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RCT: analysis

Nosocomial

(+)

Nosocomial

(-)


Placebo 18 82 10030 170 200

Event rate in experimental (simvastatin) group (EER) =12/100 = 12%Event rate in control (plasebo) group (CER) =18/100 = 18%

Relative risk reduction (RRR) =[CEREER] / CER = [18%12%] / 18% = 33,3%

Absolute risk reduction (ARR) =CEREER = 18% - 12% = 6%



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Meta-Analysis

Quantitative method of combining the results of

independent research (primary) studies and

synthesizing conclusions to evaluate the

effectiveness of treatments or procedures

Begins with systematic finding, evaluating, andpresenting the results of primary studies

Systematic Review

No collecting data directly from the study subjects

secondary research

Considered as true investigation and has highest

rank in level-of-evidence


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Advantages of Meta-analysis

Quantitatively summarize estimate from

previous studiesresolve controversies

Using protocol to choose the individual

studiesavoid bias Increase power for statistical test and

increase precision for confidence intervals

Conclusions often reflect broad spectrum ofpatient and characteristicsresults are

more generalizable


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Study I 1992Study II 1994Study III 1995Study IV 1995Study V 1996Study VI 1997Study VII1 1999Study VIII 2000

Combined

0.1 10OR = 1

Favor drug Favor placebo

Meta-analysis of RCTs

with nominal outcome


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Study I 1992Study II 1994Study III 1995Study IV 1995Study V 1996Study VI 1997Study VII1 1999Study VIII 2000

Combined

-1.0 +1.0Mean difference (X1-X2) = 0

Favor drug Favor placebo

Meta-analysis of RCTs

with numerical outcome


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Choosing study design:

Depends on: research questions

research goals

researcher beliefs and values

researcher skills time and funds

It is also related to: status of existing knowledge

occurrence of disease

duration of latent period

nature and availability of information

available resources


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Thank you...

study design magister.pptx

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