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8/2/2019 Applied PharEpi

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Pharmacoepidemiology:Pharmacoepidemiology:Application IApplication I

Teerapon Dhippayom

PharmD, MClinPharm, PhD

Basic Pharmacoepidemiology: Semester 2/2554


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Application of pharmacoepidemiology

Validity of research finding

Scope

Bias and confounding

Issues to be considered in

pharmacoepidemiological study


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Application of Pharmacoepidemiology

To promote the rational use of medicine

To investigate the safety of medicine

To investigate the effectiveness of

medicine


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Internal validity

The study measured what it set out to

External validity

The ability to generalize from the studyto the readers patient


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Internal validity

Systematic error Random error

Bias Confounding


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Bias

Bias in research process

Literature review and variable selection

Sample selection

Intervention or treatment

Exposure and outcome measurement

Data analysis Results interpretation

Paper publication


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Bias

Selection bias

The relation between exposure and outcome

is different for those who participate and

Information bias

A distortion in measuring exposure oroutcome data that results in different quality

or frequency of information between

comparison groups


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Bias

Bias

Selection bias

Sampling bias

Attrition biasRecall bias

Measurement bias

Response bias

Information bias


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Confounding

Confounding

A situation in which a measure of the effect

of the exposure with other factor(s) that

influence the outcome under study


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Confounding

GI bleedingAspirin

NSAIDs


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Confounding control

Confounding control

Study design

Restriction

Matching

Data analysis

Stratification

Multivariate

analysis


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Issues to be considered

What to look for in observational studies

Is selection bias present?

Is information bias present?

Is confounding present?

If none of the above is presented, could

they be the results of chance

If all errors are excluded, the results might

be real and worthy of note


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Cohort study

Bias and confounding

Measurement and outcome

Follow-up time period


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Case-control study

Selection bias

Control selection

Sources of control group



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Case selection

Well defined (inclusion criteria)

Represent population at risk

Incident case

Control selection

Risk of developing outcome case

Chance of exposing to risk factor case


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Sources of control group

Reduce referral bias

Community based

High cost and low compliance

Ideal, generalization

Hospital based

Convenience and low cost

May not represent the population at risk


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Recall bias

Case and control group must be assessed

for exposure in the same way


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Application: an example


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Abstract


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Background

Several studies suggested the beneficialeffects of selected CHF drugs

in HF trials

Older patients may not received appropriate

HF drugs like younger patients


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Objectives

Compare outpatient CHF drug utilisationand hospital re-admission patterns in

patients 75+yrs with those age


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Methods

Nested case-control

Design

A French teaching hospital

Setting

12-month period (in 2000)

Study period


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Methods

All adults admitted to eight departments

Di n HF i h r

Study population

Standardised form? Claims for reimbursement under French

health insurance system

Data sources


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Methods

CHF drug utilisation patterns

Medication prescribed at discharged

Outcome measured

Medication prescribed during follow-up

Hospital re-admission patterns

Re-admission rate

Number of re-admission

Cumulative duration of hospitalisation


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Results

Patientcharacteristics


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Results


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Exercise

Odds ratio: calculation

Cases Noncases

OR =AD

BC

Exposed A B

Not exposed C D


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Disease conditions

Sample

Exposure torisk factor

Yes

Exercise

Population

at risk

w

disease(cases)

Samplewithout

disease

(controls)

No

Yes

No

Time

Research


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What is case

HF patients age 75+ years

Exercise

What is control

HF patients age 75 years or younger

What is exposing factors

HF medications


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Exercise

Calculate OR for prescribing of ACE inhibitors

> 75 years < 75 years

OR = = 0.5148 x 68

63 x 102

ACE inhibitors 48 63

No ACE inhibitors 102 68


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Results


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Results


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Internal validity

The study implication

Systematic error Random error

Bias Confounding


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Issues considered

Study design: Nested case control

Begin with a record of factors interested

-

Identify case and control from a cohort

Look back for the expose of risk factors in

each group


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Issues considered

Selection bias

A French teaching hospital

L rin ll w-

Only 50% have their EF measured

Any different among group?

Number and type of concomitantmedication

Appropriate dose among group were not

measured


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Issues considered

Information bias

Appropriateness of diagnosis

Data from 8 different departments

Criteria for discharge diagnosis wasunknown

The completeness of the information

recorded It is not cleared if the re-hospitalisation

was for HF related


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Issues considered

Confounding bias

Confounding variables were adjusted

h r n i l n n r w r n

addressed Post-MI

Stroke

Cardiac surgery

etc


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Issues considered

Other issues

Hospitalisation among younger

patients appeared not different

The difference between two agegroup not prescribed HF drugs were

obvious, but yet not statistically sig.

Other factors may contribute to thelonger duration in older patient not

prescribed the drug


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Conclusion

The descriptive results on utilisationpattern in this study maybe useful

e mp ca on on ana y ca par s

questionable

It is crucial to evaluate the method

used before utilising the outcomes ofa study


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Questions

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