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General Stud Desi n Considerations

Yu-Xiao Yan MD MSCE FACPCenter for Clinical Epidemiology and Biostatistics

University of Pennsylvania

School of Medicine

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Back round and Definitions

Study Designs in Pharmacoepidemiology

Observational studies

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A desire to takeA desire to takemedications is, perhaps, themedications is, perhaps, thegreatest feature whichgreatest feature which

s ngu s es man roms ngu s es man romother animals.other animals.,,

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Pharmacologystudy of the effects ofdru s

Clinical Pharmacologystudy of the effectsof drugs in humans

Pharmacokineticsbody effect on the drug Pharmacodynamicsdrug effect on the body

Epidemiologystudy of the distribution

and determinants of diseases in

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Focus of inquiry is clinical

epidemiology

Epidemiology

Population:

Pharmacoepidemiology

Population:

Taco eaters

Exposure:

Green peppers

HTN patients

Exposure:

ACE inhibitors

Outcome:

Infection

Outcome:

Cough

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the study of the use and effects ofmedications in populations

the a lication of the methods of

clinical epidemiology to address thesubject matter of clinicalp armaco ogy

the science underlying the publichealth practice of drug safetysurveillance

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Analytic Studies

Experimental Study Prospective Cohort Study

Retrospective Cohort Study

Case-Control Study

Descri tive Studies

Analyses of Secular Trends

Case Reports

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Analytic Studies

Experimental Study Prospective Cohort Study

Retrospective Cohort Study

Case-Control Study Descri tive Studies

Analyses of Secular Trends

Case Reports

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Pharmacoepidemiology Formal studies

RCTs rare Ethical concerns

Time and funding constraints

e aana ys s o sObservational studies most common

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Background: Uncertain risk/benefit of HRT in women despiteobservational data

This trial found that, compared with placebo, womenrece v ng es rogen p us proges n exper ence

increased risk of myocardial infarction

increased risk of stroke ,

increased risk of breast cancer

decreased risk of colorectal cancer

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therapy may reduce the protective effect of clopidogrel againstcoronary artery disease

The Co ent Trial

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CCEB The Cogent Trial

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Say what?Say what?

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Metaanalysis of 42 trials

In the rosiglitazone group, as compared with thecon ro group,

OR for myocardial infarction 1.43 (95% CI 1.03to 1.98)

CCEB OR for CV death 1.64 (95% CI, 0.98 to 2.74)

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Observational Studies

Large number of diverse real-life

Made possible by electronic databases

nexpens ve Useful for hypothesis-generation, -

Generation of preliminary data

May be the only feasible design insome instances

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Observational Studies

Key steps

Good study question

Forming a research team

Choice of data source

e n ng s u y co or

Choice of study design

Defining outcomes

Obtain funding (optional) Data collection

Data analysis

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Principal Investigator sua y a c n ca p armac s or p ys c an

A Ph.D. level biostatistician

A programmer familiar with databasemana ement

Generally requires funding

Trainees in medicine, harmacolo , orepidemiology

Free!

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Often dictated by the data source Should be relevant for the study

question

Exposure Outcome

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Case-control vs. cohort

study CaseCase--Control StudyControl Study

DiseaseDisease

PresentPresent AbsentAbsent

A Bdyee

PresentPresent

h

ortSt

E

xposu

E

xposu

C sentsent

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Cohort Studyperson-time

14

Exposed

26

26-

randomprocess Unexpose

d

22

24

20

26

Observation PeriodStud

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More intuitive design the case-control Analogous to RCT

Calculation of incidence ossible

Simultaneous assessment of multiple

Viewed more favorably by some

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Is cohort study always better than CC study?

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Relevant questions Incidence data desired?

Multiple exposures or levels of exposure ofn eres

Multiple outcomes of interest?

arrower con ence nterva es re

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CC design is a more commonly useds u y es gn p armacoep em o ogystudies why?

c ency, e c ency an e c ency

Dose

urat on

Recency (e.g., current vs. past use)

Different formulations

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The sophisticated use

and understanding of-

methodologic

development of modernep em o ogy.

Kenneth J. Rothman

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because it need not be

extremely expensive nor time-

consuming to conduct a case-

,

-

investigators who lack even a

rudimentary appreciation for

ep em o og c pr nc p es.

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Case-control stud : The observational

epidemiologic study of persons with the

group of persons without the disease.The relationship of an attribute [risk

comparing the diseased and non-

diseased with regard to how frequently

.John M. Last, Dictionary of Epidemiology

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-Control Studies

Efficient to study multiple exposuresor a s ng e ou come

Often less expensive than cohort study

Disease is rare Exposure data are expensive to collect

There is a long latency or induction period

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ase-con ro u y

SourceSource

PopulationPopulation Ex osureEx osure

Outcome AOutcome Awith Awith A

StudyStudysamplesample

Analysis ofAnalysis ofex osureex osure

ObservedObserved

outcomeoutcome

WithoutWithout

with andwith and

without Awithout A

n erpren erpre

RiskRisk

Outcome AOutcome A

Ex osureEx osure

Odds RatioOdds Ratio

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If a case-control study iscon uc e w n an enumera e

minimizes the possibility of

selection bias), it can be thought

study.

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Source CohortSource Cohort

The "source cohort" behind a caseThe "source cohort" behind a case--control study iscontrol study isthe population (cohort) that gave rise to the casesthe population (cohort) that gave rise to the cases

..

xamp e:xamp e:

CasesCases: lun cancer cases listed in the cancer re istr: lun cancer cases listed in the cancer re istr

of the State of Pennsylvaniaof the State of PennsylvaniaSource cohortSource cohort: ?: ?

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S l ti f C

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Selection of Cases

Ideally include all the cases in the defined

(and not necessary to draw valid conclusion).

Most studies use sample of patients selectedfrom some convenient source: often from

.

Better to use incident rather than prevalentcases.

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Selection of Controls

Controls are people who do not have the diseasebut are otherwise com arable to the cases.

Need to pick subjects who would have become

i.e. they are representative of the underlyingo ulation.

Must be selected independent of exposure status.

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s

The ratio of the probability of an occurrence

Any ratio of two natural numbers can be

Total: 50 Exposed: 20

Unexposed: 30

Odds of exposure: 20/50 divided by 30/50; or 20/30

Exposure oddsExposure odds

Ratio of those exposed to those who are notRatio of those exposed to those who are not

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Exposure Odds Ratio (OR)

DDDD TotalTotalcc

aa

c)c)c/(ac/(a

cca aa aOddsOdds

11 ==++

++==

aa

EE a + ba + bddbb

ddd bd bd)d)b/(bb/(bOddsOdds

00 ==++

==

ddccEE c + dc + d

bcbcb/db/d====

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OR also sometimes called the crossOR also sometimes called the cross--products ratioproducts ratio

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--

Most familiar type of caseMost familiar type of case--control designcontrol design

Controls can be thought of as a sampleControls can be thought of as a sample

freefree at the end of followat the end of follow--upup (i.e.,(i.e.,survivorssurvivors

authorsauthors

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Exposure Odds Ratio for the Source Cohort?Exposure Odds Ratio for the Source Cohort?

Odds of EXPOSURE in diseasedOdds of EXPOSURE in diseased

Odds of EXPOSURE in nonOdds of EXPOSURE in non--diseaseddiseased

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Sam le ofSam le of

Source CohortSource CohortEntire Source CohortEntire Source Cohort

DISEASEDISEASE--

FREEFREEDISEASEDISEASE--

FREEFREE

UNEXPOSEDUNEXPOSEDUNEXPOSEDUNEXPOSED C D UNEXPOSED c d

11 001 00

If cases are representative of diseased inIf cases are representative of diseased in

source o ulation then a/c ex osure oddssource o ulation then a/c ex osure oddsestimates A/Cestimates A/C

--

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source population at the end of followsource population at the end of follow--up, then b/dup, then b/d(exposure odds) estimates B/D(exposure odds) estimates B/D

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Exposure Odds Ratio inExposure Odds Ratio in

a Casea Case--Control StudyControl Study

CASESCASESininoddsoddsEXPOSUREEXPOSURE CONTROLSCONTROLSininoddsoddsEXPOSUREEXPOSURE

ddaabbaaccaa ======

cccc

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Conditions

The exposure odds ratio is an estimate of the measureThe exposure odds ratio is an estimate of the measure

of association possible from a cohort study if theof association possible from a cohort study if theo ow ng con ons are me :o ow ng con ons are me :

.. ases are represen a ve o sease n sourceases are represen a ve o sease n sourcecohort, then a/c (exposure odds) estimates A/Ccohort, then a/c (exposure odds) estimates A/C

2.2. Control are representative of diseaseControl are representative of disease--free in sourcefree in source

,,

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Assumption

If you wish to use data from a cumulativeIf you wish to use data from a cumulative

cumulative incidence ratio (CIR) or incidencecumulative incidence ratio (CIR) or incidencerate ratio (IRR), an additional condition mustrate ratio (IRR), an additional condition mustbe met for the exposure odds ratio tobe met for the exposure odds ratio toestimate CIR or IRR:estimate CIR or IRR: the disease must be rarethe disease must be rare

Why?Why?

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=

If ri k

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--

estimate RRestimate RR

--

rates among the exposed and unexposedrates among the exposed and unexposed

es su e or a s or a ency per oes su e or a s or a ency per obetween exposure and outcomebetween exposure and outcome

.g., acu e ep em c se ng.g., acu e ep em c se ng

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What if the disease outcome is notrare?

period between exposure and-

among patients?

a you wan o es ma e eincidence rates?

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I id D it D i f CI id D it D i f C

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Incidence Density Design for CaseIncidence Density Design for Case--

Control StudiesControl Studies

Best for an identifiable source cohort inBest for an identifiable source cohort in--

between persons (e.g., dynamic cohort)between persons (e.g., dynamic cohort)

--

Controls can be thought of as a randomControls can be thought of as a randomsamp e o e personsamp e o e person-- me o e sourceme o e sourcecohortcohort

a ea e r s setr s set samp ng y some aut orssamp ng y some aut ors

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Cohort Study

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Cohort Studyperson-time

14

Exposed

26

26-

random

process Unexpose

d

2224

20

26



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Un- Person-

diseased Time

Exposed 2 3+ + + + =

119

Un- 14+26+22+20+26=expose

= =e .Rate

= 3 108 = 0.0278 events/time units

= =

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Un- Person-

diseased Time

Exposed 2 3+ + + + =

119

Un- 14+26+22+20+26=expose

Rate Ratio = (2 / 119) (3 / 108); rearrangement

(2 / 3) (119 / 108) = 0.60

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odds of exposure in

underlying person-time

odds of exposure in

diseased subjects

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DiseaseDiseaseDiseaseDisease--

FreeFree TotalTotalPersonPerson--

TimeTime

ExposedExposed AA BB TT11 YY11

UnexposedUnexposed CC DD TT00 YY00

NN11 NN00 YYTT

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DiseaseDiseaseDiseaseDisease--

FreeFree TotalTotalPersonPerson--

TimeTime

ExposedExposed AA BB TT11 YY11

UnexposedUnexposed CC DD TT00 YY00

NN11 NN00 YYTTSamples of diseasedSamples of diseased

--at riskat risk

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11

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equivalent to the rate ratio (no rare diseaseassum tion needed

Incidence Rate of DISEASE in EXPOSEDIncidence Rate of DISEASE in EXPOSED

IRR=IRR= ------------------------------------------------------------------------------------------------------------------------------------Incidence Rate of DISEASE in UNEXPOSEDIncidence Rate of DISEASE in UNEXPOSED

Exposed cases / PersonExposed cases / Person--time (exposed)time (exposed)

== ------------------------------------------------------------------------------------------------------------------------------------

Unexposed cases / PersonUnexposed cases / Person--time (unexposed)time (unexposed)

Exposed cases / unexposed casesExposed cases / unexposed cases

== ------------------------------------------------------------------------------------------------------------------------------------------

PersonPerson--time (exposed)/Persontime (exposed)/Person--time (unexposed)time (unexposed)

Exposure odds in DISEASEDExposure odds in DISEASED

== ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

--

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cohort)cohort)

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Source CohortSource CohortEntire Source CohortEntire Source Cohort

DiseaseDisease

DiseaseDisease--

FreeFree TotalTotal

PersonPerson--

TimeTimeDiseaseDisease

DiseaseDisease--

FreeFree TotalTotal

PersonPerson--

TimeTimeDiseaseDisease

DiseaseDisease--

FreeFree TotalTotal

PersonPerson--

TimeTime

CASESCASES CONTROLSCONTROLSCASESCASES CONTROLSCONTROLS

ExposedExposed AA BB TT11 YY11ExposedExposed AA BB TT11 YY11ExposedExposed AA BB TT11 YY11EXPOSEDEXPOSED aa bbEXPOSEDEXPOSED aa bb

Unexposenexpose CC DD TT00 YY00

NN11 NN00 YYTT

Unexposenexpose CC DD TT00 YY00Unexposenexpose CC DD TT00 YY00

NN11 NN00 YYTT

UNEXPOSEDUNEXPOSED cc dd

nn nn

UNEXPOSEDUNEXPOSED cc dd

nn nn

If cases are representative of diseased inIf cases are representative of diseased in

source cohort then a/c ex osure oddssource cohort then a/c ex osure oddsestimates A/Cestimates A/C

--

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time in source cohort, then b/d (exposure odds)time in source cohort, then b/d (exposure odds)estimates Yestimates Y11/Y/Y00

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Sample of Total Person-Time ats n e ource opu a on

Density samplingDensity sampling: Select one or more controls from: Select one or more controls fromremaining diseaseremaining disease--free members of the sourcefree members of the source

each case occurseach case occurs

proportional to the personproportional to the person--time at risktime at risk

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Case-Control Study

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y

controls sampled

Exposed-

random

process Unexpose

d



Procedures for Incidence

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Procedures for Incidence

a e amp ng..

2.2. Identify all members of the cohort (including cases) who wereIdentify all members of the cohort (including cases) who were

diseasedisease--free on that date (called the "risk set")free on that date (called the "risk set")3.3. Randomly select one control (or more) from the risk setRandomly select one control (or more) from the risk set

4.4. Repeat steps 1Repeat steps 1--3 for 23 for 2ndnd, 3, 3rdrd,, last caselast case

1.1. Controls areControls are matchedmatched to cases on followto cases on follow--up (atup (at--risk) timerisk) time

2.2. A case is eligible to be a control for another case before it became a caseA case is eligible to be a control for another case before it became a case

3.3. Control selection for each case is done with replacement (i.e., a subject canControl selection for each case is done with replacement (i.e., a subject canbe selected as a control for multiple casesbe selected as a control for multiple cases

..

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Case-Control Study

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y

controls sampled2 3 8 6 7

2

Exposed 5

4

-

random

process Unexpose

d

67

8

9



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Random Control Selection, 3 per casease o en a con ro s amp e

controls

, , , , , , , , , ,

3 1,4,5,6,7,8,9,10 5,8,9

8 1,4,5,6,7,9,10 4,9,10

6 1,4,5,7,9,10 1,5,10

7 1,4,5,9,10 4,9,10

Ex osure odds 8/7

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Sam led

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Sam led

Diseased person-time Person-

contro s

Ex osed 2 8 119

Un-3 7 108

IRR = (2 / 119) (3 / 108) = 0.60

= (2 / 3) (119 / 108)

2 / 3 8 / 7 = 0.58Equal

exce t for

CCEBrandom

variation

Notes on Incidence Density

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Some selected controls may later be selected as cases,Some selected controls may later be selected as cases,especially if incidence is high !especially if incidence is high !

Some controls may be selected more than once !Some controls may be selected more than once !

Probability of a person being selected as a control isProbability of a person being selected as a control isproportional to that personproportional to that persons contribution to thes contribution to the

. .,. .,rate calculations in the source cohortrate calculations in the source cohort

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Density Design

No need for rare diseaseassumption if you use density

Also works if exposure statuschanges over time

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Biases in CaseBiases in Case--controlcontrol

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StudiesStudies

Selection biasSelection bias

Occurs when selection of either the casesOccurs when selection of either the casesor controls is related to the probability ofor controls is related to the probability of

Typically occurs when controls notTypically occurs when controls notselected from the source o ulationselected from the source o ulation

Differential measurement of exposureDifferential measurement of exposure

Typically occurs when measurement ofexposure takes place after disease has

CCEB

occurred

Not a concern in electronic medical

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-

Much more efficient than a cohortdesign, especially for rare outcomes

Validity depends upon whethercontrols provide a clear view ofpopulation from which cases arise

The OR from incidence densitysampling is equivalent to the rateratio (no rare disease assumption

nee e

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H brid Desi n

analysisanalysis

Nested caseNested case--controlcontrol

analysisanalysis

CCEB Laheij et al.Laheij et al. JAMA. 2004;292:1955-1960

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Prevent Femur Fracture?

CCEB

A staggering amount of work;

logistic and ethical difficulties

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Thiazides

allocation No

thiazides


CCEB = Femur fracture

population

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a e a o = ven s person- me n rea eEvents / person-time in untreated

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How could this be studiedas a cohort study?

ystem in Netherlandscontains re-existin dru &diagnosis info for 108k

CCEB

Compile exposure, outcome, &

confounder info on 108,000 subjects

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Thiazide-

Random

process

No

thiazides



population=

108,000 people

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a e a o = ven s person- me n rea eEvents / person-time in untreated

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as a case-control study?

, .1996;49:115-119)

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Get outcome info on 108,000

subjects. Get exposure &

Controlsconfounder info on 386 cases +

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Controls

sampled

confounder info on 386 cases +

386 controls.

Thiazide

-

Random

process

No

thiazides



population=

108,000 people

Data from Herings RMC,

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n p em o ; : -

femur fracture no femur fracture

totalthiazides 46 70 116

total 386 386 772Odds ratio = (46 / 340) (70 / 316)

Or, to make math easier, (46 316) / (70 340)

= 0.6 = unbiased estimate of rate ratio

The rate of femur fracture is 40% lower in

thiazide users than non-users (assuming no

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confounding).

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Thestudied

772people instead of

108,000!

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Part II

avea s an a s

Yu-Xiao Yang, MD, MSCE, FACPCenter for Clinical E idemiolo and Biostatistics

University of Pennsylvania

School of Medicine

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Bias

Confounding

How to wei h risk/benefit ratio

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Selection bias

Misclassification bias

Proto athic bias

Immortal time bias

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A distortion in the estimate ofA distortion in the estimate ofoccurrence or effect resultingoccurrence or effect resultingfrom the manner in which subjectsfrom the manner in which subjectsare selected for the studyare selected for the study

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Does therapy with 6MP increase ther s o eu open a

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Cohort study of IBD patients treated

w compare o pa en s notreated with 6MP

Setting: Health plan participants with

6MP

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Which 6MP treated patients shouldou include?

,patients are already taking 6MP

follow-up in the available data v

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De letion of Susce tible

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Subjects

Treatment with mercaptopurine (6MP)

can resu n one marrow suppress on Rapid metabolism to 6TGN

n peop e w gene c as s or very owactivity

Early severe leukopenia when treated with 6MP

Other reasons such as infection or druginteraction

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Subjects

If you include the prevalent users

ose a ng a e s ar o edata), you will have selected a cohort

Those with early leukopenia will have been

Results will be biased toward ___________

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Subjects

If you include the prevalent users

data), you will have selected a cohortof survivors Those with early leukopenia will have been

excluded

esu s w e ase owar e nu(could be away from the null in a differentscenario)

This problem is called Depletion ofsusceptibles a type of selection bias

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problem?

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By creating the study cohort

exc us ve y o new users, ep e on osusceptible subjects can be avoided.

Our example

New users of 6MP compared to non-userso

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Exposure misclassification

Outcome misclassification

. -

misclassification

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Complex exposure patterns

Episodic, continuous, remote, recent, current

Actual consumption vs. prescription

Date prescribed date exposure started

Days supplied duration of exposure

How to handle overlapping dispensing periods?

Plausible latency period between exposureand outcome

Availability of OTC exposure Example: Aspirin/NSAIDs

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Statin use may reduce the risk of

co orec a cancer

Primary definitions of statin exposurein published studies

Any prescription of statin within the pastmon

Cumulative duration of statin use >5 years

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Rule-out diagnosis vs. actual diagnosis

Prevalent vs. incident diagnosis

CCEB Lewis et al. PDS 2005;14:443Lewis et al. PDS 2005;14:443

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Validity of the diagnosis

Direct validation (paper record review,physician or patient survey, etc.)

orro ora ve proce ures rea men

Example: colon cancer, colorectal surgery, chemo

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Information / Misclassification

Bias

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Bias

Misclassification of disease or

exposure s a us

If misclassification is differential (i.e.,differs between cases and controls),

bias may be toward or away from the

CCEB

-

Misclassification Bias

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True or false

Non-differential bias should always biasthe results towards the null

.

CCEB

A Caveat about Non-differential


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Misclassification Bias The real answer is it depends

true The exposure is binary

Other conditions required if it is >2 levels

Exposure misclassification errors are

analysis E.g., one measure from a comprehensive questionnaire

sence o n erac ons w o er sources osystematic error, e.g., selection bias andconfounding

CCEB

A Caveat about Non-differential


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Misclassification Bias no er cavea

Bias towards the null does not always lead to an underestimateof the relative risk

The rules refer to expected values, ie., the averageresult ofapplying estimator to repeated samplesnot to the value

Definition of non-differential: the probably of error is the same between

those with the outcome and those w/o the outcome

estimate from a study must be an underestimate because thebias is towards the null.

estimate than above it

CCEB

Difference in life

expectancy: 79.7 vs. 75.8

years; = .

28% Reduction in riskf d h !!

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of death per year!!

CCEB

Redelmeier et al. Ann Intern Med. 2001:134:955-962

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OscarOscar

WinnersWinners

ImmortalImmortal

TimeTime

rr WinningWinning

OscarOscar

F/u timeF/u time

onon--w nnersw nners

CCEB

DeathDeath

BirthBirth

-

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ExposedExposed

ImmortalImmortal

TimeTimeF/u periodF/u period

oror

dx datedx dateStart ofStart of

InfliximabInfliximab F/u timeF/u time

F/u periodF/u period

DeathDeath1994 or CD1994 or CD

dx datedx date

CCEB

HR for mortality: 1.33 (95% CI, 0.56 to 3.00)

Fidder et al. Gut 2009;58:5018

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Treat exposure as time-dependent In Coxre ression

periodperiod

PeriodPeriod TimeTime

F/u periodF/u periodImmortalImmortal

TimeTime

EnrolmentEnrolment

datedate

DrugDrugCensoringCensoring

eventevent

CCEB

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Ann Intern Med. 2006;145:361-363

CCEB

-

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ExposedExposed

ImmortalImmortal

TimeTimeF/u periodF/u period

oror

dx datedx dateStart ofStart of

InfliximabInfliximabF/u timeF/u time

F/u periodF/u period

DeathDeath1994 or CD1994 or CD

dx datedx date

CCEB

HR for mortality: 2.37 (95% CI, 1.02 to 5.33)

Lewis JD Gut 2010;59:1586-1587

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Study cohort: 483,733 VA patients

Study period: Oct 1998 to June 2004

Study design: Case-control

Exposure

Cases: Any Rx for statin prior to the dx of lung CA on ro s: ny x or s a n pr or o e en o

observation period

Results: Statin associated with 45% reduction

in lung cancer risk (adjusted OR 0.55, 95% CI:0.52-0.59).

CCEBKhurana et al. Chest. 2007;131:12821288

Time-Window Bias inase- on ro u es

Cases had a shorter observational period than

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Cases had a shorter observational period thancontrols

Shorter observational period = less chance for

s a n exposure Over-representation of unexposed cases = spurious

CCEB

-

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How to address this bias?

Use a cohort design with time-varyingexposure

se nc ence ens y samp ng o se ec

controls Select one or more controls from remainin disease-free members of the source cohort at theinstantaneous time period in which each caseoccurs

The probability of control selection is proportional tothe person-time at risk

CCEB

-

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Statin use and lung cancer: A GPRD study

CCEBSuissa et al. Epidemiology 2011;22: 228231

PPI Thera and ColorectalPPI Thera and Colorectal

CancerCancer

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CancerCancer

PPI-induced hypochlorhydria

Secondary hypergastrinemia

investigate this

Increased cell roliferation

association?

Accelerated progression through the adenoma-

carcinoma sequence

CCEB

Increased colon cancer risk

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RCT?

Prospective Cohort?

Nested case-control?

Most feasible Design

Can use large electronic medical records (e.g.,THIN

Identify incident gastric cancer and select controlsusing incidence density sampling

PPI exposure before index date

CCEB

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Potential problem in exposure

e n on Patients with colorectal cancer may have

-dx

for empirical treatment of such symptoms

PPI use close to cancer dx date index

date) might appear to cause colorectalcancer

CCEB

yy

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Duration ofDuration ofCases N (%)Cases N (%)

Controls NControls N Crude ORCrude OR (95%(95% Adjusted ORAdjusted OR

NonNon--usersusers 3,663 (82.7)3,663 (82.7) 39,159 (88.4)39,159 (88.4) ReferenceReference ReferenceReference

< 1 year< 1 year

RecentRecent

PastPast

400 (9.0)400 (9.0)

211 (4.8)211 (4.8)

1,663 (3.8)1,663 (3.8)

2,017 (4.6)2,017 (4.6)

2.6 (2.32.6 (2.3--2.9)2.9)

1.1 (1.01.1 (1.0--1.3)1.3)

2.6 (2.32.6 (2.3--2.9)2.9)

1.1 (0.91.1 (0.9--1.3)1.3)-- .. .. . .. . -- .. . .. . -- ..

22--3 years3 years 34 (0.8)34 (0.8) 385 (0.9)385 (0.9) 1.0 (0.71.0 (0.7--1.4)1.4) 0.9 (0.60.9 (0.6--1.3)1.3)

33--4 years4 years 24 (0.5)24 (0.5) 211 (0.5)211 (0.5) 1.2 (0.81.2 (0.8--1.9)1.9) 1.1 (0.71.1 (0.7--1.7)1.7)Proto athic bias?44--5 years5 years 17 (0.4)17 (0.4) 140 (0.3)140 (0.3) 1.3 (0.81.3 (0.8--2.2)2.2) 1.1 (0.71.1 (0.7--1.9)1.9)

>5 years>5 years 16 (0.4)16 (0.4) 144 (0.3)144 (0.3) 1.2 (0.71.2 (0.7--2.0)2.0) 1.1 (0.71.1 (0.7--1.9)1.9)

CCEB

Yang et al. Gastroenterology2007;133:748754

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Use of the drug to treat early signs ofUse of the drug to treat early signs of

e ou comee ou come Early symptoms of CRC leading to PPI useEarly symptoms of CRC leading to PPI use

Different from confounding byDifferent from confounding by

indicationindication Why? Because the indication here is theWhy? Because the indication here is the

outcome!outcome!

CCEB

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How to address it?

Lag-time approach: a specific time periodbefore the date of diagnosis with the

from the exposure assessment

But what is the o timal la -time? 6months? 12 months? Should it bedependent on the outcome?

CCEB

-

u

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u -

time (generally in monthly increments).

tep 2: Use segmenta regress on ana ys s to est mate opt malag-time

y = a + bx + cx2

if x < x0

x= lag time; x0 = change point

y=ln(OR)

CCEB Tamim et al. PDS 2007; 16: 250258


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p gy

Confounding by indication

Examples

Measures to address confounding byn ca on

Channeling

CCEB

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Confounding may be considered to beConfounding may be considered to be

a m x ure o e ec s. pec ca y, ea m x ure o e ec s. pec ca y, eestimate of the effect of the exposureestimate of the effect of the exposure

mixed with the effect of an extraneousmixed with the effect of an extraneous

CCEB

Confoundin of anConfoundin of anConfoundin of anConfoundin of an

AssociationAssociationAssociationAssociation

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ConfounderConfounder

CCEB

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CCEB

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Factors in the causal pathway are not

con oun ers more on s a er

Medication OutcomeCausal

CCEB

PPI Thera & FracturesPPI Thera & Fractures

Possible mechanismsPossible mechanisms

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Osteoclastic PP inhibition may decrease boneOsteoclastic PP inhibition may decrease boneresorptionresorption

Acid suppression may decrease Ca absorptionAcid suppression may decrease Ca absorption

Gastrin may induce parathyroid hyperplasiaGastrin may induce parathyroid hyperplasia

PPIPPI--induced B12induced B12--insufficiencyinsufficiency

Low B12 is associated with decreased bone formationLow B12 is associated with decreased bone formation

Homocysteinemia can weaken collagen crossHomocysteinemia can weaken collagen cross--linking*linking*

Increased fall risk*Increased fall risk*

*

CCEB

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Is PPI therapy a risk factor for hipIs PPI therapy a risk factor for hip

rac uresrac ures

Ways to do the studyWays to do the study

RCTRCT May be unethical to randomizeMay be unethical to randomize

Cohort studyCohort study -- OKOK

CaseCase--control studycontrol study -- OKOK

CCEB

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CCEB

et o s Design

Nested case-control study

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Nested case control study

General Practice Research Database (GPRD)

Electronic medical records system 1987-2003 (n=9,371,083)

, ,

>50 years of age at enrollment and >1 year of follow-up

Incident hip fracture cases

Incidence density sampling

Matched on sex, index date, year of birth, date of the

CCEB

beginning of UTS follow-up and duration of UTS follow-upbefore index date

ORORus eus e

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OROR

95%CI95%CI(95% CI)(95% CI)

No acid suppressiveNo acid suppressivetherapytherapy

referencereference referencereference

> 1 yr> 1 yrOBSERVEDOBSERVEDPPIPPI

TherapyTherapy

1.81.8

(1.7(1.7--2.0)2.0)

1.41.4

(1.3(1.3--1.6)1.6)

CCEB

. -

Cumulative PPI Ad usted Oddstherapy durations Ratio

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therapy durations Ratio

(95% CI)

-1 year

2 years

1.22 (1.15-1.30)

1.41 (1.28-1.56)3 years

4 years1.54 (1.37-1.73)1.59 (1.39-1.80)

CCEBYang et al. JAMA 2006;296:2947-2953

>1 yr H2RA>1 yr H2RA >1 yr PPI>1 yr PPI

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>1 yr H2RA>1 yr H2RAAverage Daily doseAverage Daily dose

>1 yr PPI>1 yr PPI

Average Daily doseAverage Daily dose

QDQD BIDBID QDQD BIDBID

AdjustedAdjustedOROR 1.21.2 1.31.3 1.41.4 2.72.7

(95% CI)(95% CI)(1.1(1.1--1.4)1.4) (1.2(1.2--1.5)1.5) (1.3(1.3--1.5)1.5) (1.8(1.8--3.9)3.9)

Hi h

Acid Suppression

CCEBYang et al. JAMA 2006;296:2947-2953

PPI Therapy and Fracture RiskPPI Therapy and Fracture Risk

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Targownik et al.

2008;179(4):319-26

CCEB

Is this a real biolo icalIs this a real biolo ical

effect?effect? on oun ngon oun ng

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Doctors may be more likely to prescribeDoctors may be more likely to prescribe

, ,, ,demented or with poor nutritional statusdemented or with poor nutritional statusthan healthier atientsthan healthier atients

These comorbid conditions are associatedThese comorbid conditions are associated

with increased facture riskwith increased facture risk How will we know whether the increasedHow will we know whether the increased

risk of hip fracture among PPI users wasrisk of hip fracture among PPI users was

PPI therapy?PPI therapy?

CCEB

Options for ControllingOptions for Controlling

StudiesStudies

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Design stageDesign stage

MatchingMatching RestrictionRestriction

Analysis stageAnalysis stage

Stratified anal sesStratified anal ses

Mathematical modelingMathematical modeling

CCEB

PPI Thera and Risk ofPPI Thera and Risk ofFracturesFractures

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ObjectiveObjective: to estimate the PPI fracture: to estimate the PPI fracture

assoc a on n pa en s w ou ma or assoc a on n pa en s w ou ma or risk factors for fracturerisk factors for fracture

CaseCase--control study #1control study #1: to identify: to identify

major risk factors for hip fracturemajor risk factors for hip fracture CaseCase--control study #2control study #2: reassess the: reassess the

association among patients withoutassociation among patients without

ma or r s ac orsma or r s ac ors

CCEBJick et al. Pharmacotherapy 2008;28(8):951Jick et al. Pharmacotherapy 2008;28(8):951959959

PPI Thera and Risk ofPPI Thera and Risk ofFracturesFractures

os common s en e n aseos common s en e n ase

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Previous fracturesPrevious fractures

OsteoporosisOsteoporosis

CVACVA

Accidental FallsAccidental Falls

SeizuresSeizures FeFe--deficiency anemiadeficiency anemia

Patients with these diagnoses were excluded inPatients with these diagnoses were excluded in

CCEBJick et al. Pharmacotherapy 2008;28(8):951Jick et al. Pharmacotherapy 2008;28(8):951959959

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ConclusionConclusion

PPI therapy is not associated with hip fracture risk in patients withoutPPI therapy is not associated with hip fracture risk in patients without

major RFs for fracturesmajor RFs for fractures

CCEB Jick et al. Pharmacotherapy 2008;28(8):951Jick et al. Pharmacotherapy 2008;28(8):951959959

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CCEB

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Previously observed positive association wasPreviously observed positive association was

Effect modification according to fracture riskEffect modification according to fracture risk

GeneralizabilityGeneralizability

Restriction based on intermediate factorsRestriction based on intermediate factorsbetween PPI and fracturebetween PPI and fracture

Osteoporosis, BOsteoporosis, B--12 deficiency, previous fractures,12 deficiency, previous fractures,etc.etc.

CCEB

Use of Restriction Analysis toUse of Restriction Analysis to

on oun er on oun er PPIPPI

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Used to restrict cohortUsed to restrict cohort

IntermediateIntermediateOsteoporosis, BOsteoporosis, B--12 deficiency, etc12 deficiency, etc

Will bias towards the nullWill bias towards the null

Generally NOT used to restrict cohortGenerally NOT used to restrict cohort

CCEBp rac urep rac ure

M t l H l th dM t l H l th d

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Mantel Haenszel methodsMantel Haenszel methods

Logistic regressionLogistic regression

Linear regressionLinear regression

regressionregression

Etc.Etc.

CCEB

emograp cs er ea care n o.

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Age at enrollment Sex Excessive ETOH

Body mass index

Smoking history

Calendar year of

enrollment ura on o o ow-up

Number of prior visits

CCEB

Di Vision loss

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Diagnoses Celiac sprue

Congestive hear failure Cerebral vascular

accident

Pagets disease Osteomalasia

Dementia

Impaired mobility

Cushings disease

Inflammator bowel disease Myocardial infarction

COPD or Asthma Menopausal status

Prior history of fracture

Peripheral vasculardisease

Seizure disorder

CCEB

Rheumatoid arthritis

Axiolytics Bisphonsphonate

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y

Anti-Parkinson's Anticonvulsants

Corticosteroids Calcium supplementation

CCEB

What do the res lts of aWhat do the res lts of a

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What do the results of aWhat do the results of a

multivariable model mean?multivariable model mean?

association of each variableassociation of each variable

after adjusting for all otherafter adjusting for all other

CCEBvar a es n e mo evar a es n e mo e

Ignoring the stratified resultsIgnoring the stratified results

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Ignoring the stratified resultsIgnoring the stratified results

CoCo--linear variableslinear variables Absence of overlapAbsence of overlap

Too many variablesToo many variables

pathwaypathway

confoundersconfounders

CCEB

Assuming that modeling canAssuming that modeling can

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Assuming that modeling canAssuming that modeling can

correc pro ems w e a acorrec pro ems w e a acollectioncollection

You cant turn garbage into goldYou cant turn garbage into gold

with statisticswith statistics Residual confounding whenResidual confounding when

not capturednot captured

CCEB

Statistical methods have been developed

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Statistical methods have been developed

o com ne mu p e var a es n o asingle variable

ropens y scores

Risk scores Comorbidity indices

Charlson / Deyo Score

CCEB

Variable which describes the probability

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Variable which describes the probability

conditioned on a set of covariates

se ra ona mo e ng ec n ques ocreate propensity score

Independent variable any variable otherthan the outcome

Propensity score corresponds to theprobably of receiving the treatment

CCEB

er ma c or s ra y su ec s y epropensity score

CCEBCCEB

What is channeling?

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What is channeling?

Definition: Drugs with similar therapeutic indications are

differences

CCEB

A stud com arin atients started onCOX-2 inhibitors after their initialmarketing vs those remaining on NSAIDs

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marketing vs. those remaining on NSAIDs

in 1998-1999

CCEB

Wolfe F et al. J Rheumatol 2002;29:101522

Approach similar to whats used for

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Approach similar to what s used for

con oun ng y n ca on Propensity score matching or

adjusting

The goal is to even out the probabilityof receiving the drug

Limitations

Large sample size required Unmeasured factors cannot be accounted

CCEBfor

All drugs can cause adverse events

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d ugs ca cause ad e se e e ts

Must weigh risks vs potential benefits Risk tolerance is atient and h sician

specific

Fre uenc of event

Severity of outcome

Reversibilit

Alternative therapies

CCEB

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CCEB

Occupation Risk of Death per

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,

.

Firefighter 10.6

Taxi driver 36.1

CCEBCohen JT. Health Affairs 2007:26:636Cohen JT. Health Affairs 2007:26:636--4646

Medication Risk of Death per

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,

As irin to revent heart 10.4disease and cancer 50

year old menNatalizumab for MS 65

pain

CCEB

o en . ea a rs : :o en . ea a rs : : --

Transportation Risk of Death per

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,

.

Car 11

Additional risk fromtalking on cell phone

1.3

Motorcycle 450

CCEBCohen JT. Health Affairs 2007:26:636Cohen JT. Health Affairs 2007:26:636--4646

of Drug for Bowel Ailment

I cant believe the F.D.A. would do such a thing.

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,39, of Fredericksburg, Va. I would rather takemy chances of having a heart attack than live inI.B.S. hell.

----(March 30, 2007)

CCEB

rugs can cause a verse reac ons

Observational drug surveillance studies have

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medications

studies depends on

Appropriate choice of study design Appropriate definition of exposure and outcome

Addressing potential biases and confounding

ccep a y o r s epen s on po en a

benefits, alternative therapies, patienttolerance

CCEB

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CCEB

Documents

0304 dia 02