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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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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)
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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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u ca on
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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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.
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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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S l ti f C t l
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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
Observation PeriodStud
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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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. . .
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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
Observation PeriodStud
CCEB = Study outcomepopulation
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
Observation PeriodStud
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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
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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?
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A staggering amount of work;
logistic and ethical difficulties
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Thiazides
allocation No
thiazides
Observation PeriodStud
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
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Compile exposure, outcome, &
confounder info on 108,000 subjects
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Thiazide-
Random
process
No
thiazides
Observation PeriodStud
CCEB = Femur fracture
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
Observation PeriodStud
CCEB = Femur fracture
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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Pharmacoepidemiology
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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De letion of Susce tible
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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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De letion of Susce tible
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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
CCEB
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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Misclassification Bias
True or false
Non-differential bias should always biasthe results towards the null
.
CCEB
A Caveat about Non-differential
Misclassification Bias
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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
Misclassification Bias
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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
Pharmacoepidemiology
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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