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Divison of gastroenterology
Department of Medicine
Samsung Medical Center
Sungkyunkwan University School of Medicine
•Pancreas and biliary tract
Kwang Hyuck Lee M.D., [email protected]
SMC pancreas biliary tract
Biliary tract and pancreasManaging with specialized Endoscopy
복부 초음파 Vs 위 내시경검사
내시경 초음파를 이용 조직검사 (EUS: endoscopic ultrasound)
Endoscopic ultrasound in Pancreaticobiliary disease
ERCP (endoscopic retrograde cholangiopancreatography)
ERCP
Endoscopic Retrograde CholangioPancreaticography
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Why do medical doctors have to learn epidemiology?
Graduate school degree Investigation journal
Academic position Interested in a research
Ability to Do a case-control study Evaluate other papers properly
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Case-control study – historical synonyms
Retrospective study Trohoc study Case comparison study Case compeer study Case history study Case referent study
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Case Control Study
1 0
0 1
( )A B
OR cross product ratioA B
Disease
Yes No
Exposed Yes A1 B1
No A0 B0
Case Control
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생체 간이식 후 간수치 상승 환자에서 담도 협착의 조기 발견과 관련된 요인
오초롱오초롱 , , 이광혁이광혁 , , 이종균 이종균 , , 이규택 이규택 , , 권준혁권준혁 *,*, 조재원조재원 *, *, 조주희조주희 ****
성균관대학교 의과대학성균관대학교 의과대학 , , 삼성서울병원 소화기내과삼성서울병원 소화기내과 , , 이식외과이식외과 *, *, 암교육센터암교육센터 ****
연구목적연구목적
생체간이식 (LDLT) 후 발생하는 담도 합병증
가장 좋은 치료인 내시경적 치료 성공률 : 50% 전후
담도 합병증을 조기에 발견하여 내시경적 배액술을 시행하면 성공률이 높다 .
LDLT 후 간 기능 이상 소견을 보이는 환자 중에 담도 합병증을 예측할 수 있는 요인을 찾고자 하였다 .
대상 및 방법대상 및 방법
기간 및 대상 환자 2006 년 1 월부터 2008 년 12 월 생체간이식을 받은 환자
수술 후 회복된 간기능이 다시 악화되었던 환자
duct to duct 문합 환자만 포함 (hepaticojejunostomy 환자는 제외 )
조사한 항목 기저질환 , 증상
간기능 검사
수술기록
영상의학검사
분석 분석 groupgroup
LDLT 후 간수치가 재상승한 환자를 대상으로 group 을 나눔
( 상승 기준 : AST>80, ALT>80, ALP>250 or bilirubin>2.2)
Group AGroup A: ERCP 가 필요한 환자 Vs ERCP 필요하지 않은 환자
Group BGroup B: 문합부 담도협착 환자 Vs 거부반응 환자
Group CGroup C: CT 상 협착소견이 없었던 환자 중에ERCP 가 필요한 환자 Vs 필요하지 않은 환자
n=46
23
7
5
3
3
5
n=74
58
13
3
LDLT patients during 3years : n=213
need ERCP
stricture
leakage
stone
Patients with LFT elevation : n=120
not need ERCP
rejection
infection
HCC
viral reactivation
vessel stenosis
etc
Analysis group B
Analysis group A
Analysis group C CT(-) need ERCP : 32 CT(-) not need ERCP : 40
Case-Control Study or not?
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Brock MV, et al. N Engl J Med 2008;358:900-921
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Conducting case-control studies
Case and Control selection
Exposure measurement
Odds ratio
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Research
New Question ?? Method
Clinical study Translational study Laboratory study
Clinical study Observational studies
• Case-control study Vs Cohort study
Randomized controlled trial
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Why case-control studies?
New question of interest
Cohort study with the appropriate outcome or exposure ascertainment does NOT exist
Need to initiate a new study
Do you have the time and/or resources to establish and follow new cohort?
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Case control study ??
High cholesterol Myocardial infarction
MI (+) case MI (-) control Cholesterol level Result
• Negative • Positive
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Impetus for case-control studies : EFFICIENCY
May not have the sufficient duration of time to see the development of diseases with long latency periods.
May not have the sufficiently large cohort to observe outcomes of low incidence.
NOTE: Rare outcomes are not necessary for acase-control study, but are often the drive.
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Efficiency of case-control study
Do maternal exposures to estrogens around time of conception cause an increase in congenital heart defects?
Assume RR = 2, 2-sided α = 0.05, 90% power Cohort study: If I0 = 8/1000, I1 = 16/1000, would
need 3889 exposed and 3889 unexposed mothers Case-control study: If ~30% of women are exposed
to estrogens around time of conception, would need 188 cases and 188 controls
Schlesselman, p. 1728
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Strengths of case-control study
Efficient – typically: Shorter period of time Not as many individuals needed Cases are selected, thus particularly good for
rare diseases
Informative – may assess multiple exposures and thus hypothesized causal mechanisms
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Learning objectives
Exposure Selection of cases and controls Bias
Selection, Recall, Interviewer, Information Odds ratios Matching Nested studies Conducting a case-control study
DCR Chapter 8
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Exposure ascertainment – examples
Active methods Questionnaire (self- or interviewer-
administered) Biomarkers
Passive methods Medical records Insurance records Employment records School records
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Exposure ascertainment issues
Establish biologically relevant period Measurement occurs once at current time
Repeated exposure Previous exposure
Measure of exposure occurs after outcome has developed Possibility of information bias Possibility of reverse causation (outcome
influences the measure of exposure)
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Is it possible in case-control study? – relevant period
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Yesterday smoking and radiation Cancer risk
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Information bias: recall bias
Mothers of babies born with congenital malformations more likely to recall (accurately or “over-recall”) events during pregnancy such as illnesses, diet, etc.
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Possibility of reverse causation
High cholesterol Myocardial infarction
MI (+) case MI (-) control Cholesterol level Result ? MI Cholesterol level decrease Measure cholesterol after MI
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Case selection – basic tenets
Eligibility criteria Characteristics of the target and source population
Diagnostic criteria Definition of a case: misclassification
Feasibility
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Source populations – samples
Health providers: clinics, hospitals, insurers Occupations: work place, unions Surveillance/screening programs Laboratories, pathology records Birth records Existing cohorts Special interest groups: disease foundations or
organizations
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Incident versus prevalent cases
Incident cases: All new cases of disease cases (that become diagnosed) in a certain period
Prevalent cases: All current cases regardless of when the case was diagnosed
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Incident Vs Prevalence
Do the cases represent all incident cases in the target population?
Exposure–disease association Vs Exposure–survival association
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Prevalence cases
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Disease only A (causal factor) 1-month survival A+B (protective factor) 1-year survival A+C (protective factor) 10-year survival
Patient A: A 1 month Patient B: A+B 1 year Patient C: A+C 10 years
Prevalence cases A,B,C: Causes intervention of B or C ↓↓Survival
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Disease severity
Which stage is chosen for a case? Early stage only Progression not always Late stage only Influence of severity
Increase sample size for stratification
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Early stage only
Finding risk factors of thyroid cancer Decrease risk factors Prevent thyroid cancer Health promotion
Case: small thyroid cancer Control: normal population Determined the differences of exposure
Small thyroid cancer no progression What is the clinical meaning of this study?
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Late stage only – difficult diagnosis
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Pancreatic cancer Vs. Weight Cases: pancreatic cancer (late stage)
Low weight due to Cancer progression
Conclusion low weight pancreatic cancer
Increase sample size for stratification
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Selection bias
Selection of cases independent of exposure status
Related to severity
Related to hospitalization or visiting
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Example selection bias (1)
Hypothesis Common cold Asthma
Setting Patients in Hospital
Truth Common cold: aggravating factor not causal factor No different incidence of asthma according to
common cold Common cold (+) aggravation hospital visit Common cold (-) no symptoms no visit
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Total Common cold in society
Patients in hospital
Common cold in hospital
Asthma 1,000 10 50 10
General 200,000 2,000 1000 20 (10+ alpha)
Cause positive Cause negative
Case (asthma) 10 40
Control 1 49
Odds ratio = (1X49)/(4X1)
Example selection bias (2)
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Case and Control selection
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Same distribution of risk factors ??
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Guallar E, et al. N Engl J Med 2002;347:1747-5448
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Selection of controls – basic tenets
Same target population of cases Selection needs to be independent of exposure
Should have the same proportion of exposed to non-exposed persons as the underlying cohort (source population)
Confirmation of lack of outcome/disease Should answer yes to: If developed disease of
interest during study period, would they have been included as a case?
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Selecting controls – Same as case source
Characteristics 1. Convenient2. Most likely same target population3. Rule out outcome – avoids misclassification4. Similar factors leading to inclusion into source
population5. Sometimes impractical
Examples Breast cancer screening program
• Confirmed breast cancer – cases• No breast cancer – controls
Same hospital as case series• Similar referral pattern – examine by illness types
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Source for controls
Geographic population Roster needed Probability sampling
Neighborhood controls Random sample of the neighborhood
Friends and family members Hospital-based control
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Selection of controls: Friends or family
members Friends or family members
Ask each case for list of possible friends who meet eligibility criteria
Randomly select among list Type of matching - will be addressed later
Concerns: May inadvertently select on exposure status, that is,
friends because of engaging in similar activities or having similar characteristics/culture/tastes
“over-matching”
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Am J Epidemiol 2004;159:915-21 53
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Selection of controlsHospital or clinic-based
Strengths Ease and accessibility Avoid recall bias
Concerns Section bias: exposure related to the hospitalization A mixture of the best defensible control
Referral pattern Same Or not
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Diet pattern: Colon cancer
소화기 암 전문 병원 (GI referral center) 에서 연구를 수행함
Case : 소화기 클리닉의 대장암 (+) Control : 호흡기 클리닉의 대장암 (-)
• 소화기 클리닉 : 대기실 소화기 암 관련 음식 정보• 호흡기 클리닉
두 군 간에 차이는 질환의 차이가 아니라 클리닉의 차이를 반영할 수도 있다 .
Control : 소화기 클리닉의 위암 (+)
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Guallar E, et al. N Engl J Med 2002;347:1747-5456
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Weakness of Case-Control Studies
Time period from which the cases arose Survival factor, Reverse causation Biologically relevant period
Only one outcome measured Susceptibility to bias
Separate sampling of the cases and controls Retrospective measurement of the predictor
variables
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Issues in case-control studiesEliseo Guallar, MD, [email protected]
Juhee Cho, M.A., [email protected]
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Case and Control selection
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Same distribution of risk factors ??
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Selection of cases
Case selection in hospitals/ Control selection in general population Alcohol Hip fractures: All visit hospitals IUD abortion
1st abortion: Some visit but others not Women with IUD in general population more frequently visit clinics
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Disease No disease
Exposed
Non-exposed
Target population
Disease No disease
Exposed
Non-exposed
Study sample
aA B b
C cD d
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1st abortion: 3% rate and no relation of IUD
General population IUD(+) 1000 30 970 IUD(-) 9000 270 8730
IUD: frequent visit Hospital population
IUD (+) 90% 27 873 IUD (-) 45% 122 3930
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case control
Yes 10 10
No 90 90
100 100
case control
Yes 27 15
No 122 134
149 149
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Case control Total
Yes 27 15 42
(%) 18.1 10.1 14.1
No 122 134 256
(%) 81.9 70.0 85.9
Total 149 149 298
% 100 100 100
Pearson chi2(1) = 3.9911 Pr=0.046
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How to overcome….
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Control: general population difference due to frequent visit
Control: Hospital population theoretically same unless this control
group has higher abortion rates due to other problems
Control mixture: both
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Critics from papers
Limited casesSelection bias from control selection
To make you paper better than previous studies
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Nomura A, et al. N Engl J Med 1991;325:1132-666
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Selection bias in nested case-control study
Controls were excluded if they had had gastrectomy or history of peptic ulcer disease
Controls with a cardiovascular disease or cancer at baseline or during follow-up were excluded
Disease No disease
Exposed
Non-exposed
Target population
Disease No disease
Exposed
Non-exposed
Study sample
aA B b
C cD d
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MacMachon B, et al. N Engl J Med 1981;304:630-3 69
At GI clinic
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MacMachon B, et al. N Engl J Med 1981;304:630-3 70Exclude other diseases
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MacMachon B, et al. N Engl J Med 1981;304:630-3 71
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Selection bias in case-control study
Controls were largely patients with diseases of the gastrointestinal tract
Control patients may have reduced their coffee intake as a consequence of GI symptoms
Disease No disease
Exposed
Non-exposed
Target population
Disease No disease
Exposed
Non-exposed
Study sample
aA B b
C cD d
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Antunes CMF, et al. N Engl J Med 1979;300:9-13 74
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Antunes CMF, et al. N Engl J Med 1979;300:9-1375
Non-GY Control 6.0 GY Control 2.1
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Criticisms of prior case-control
studies
Diagnostic surveillance bias Women on estrogens are evaluated more
intensively – they are more likely to be diagnosed and to be diagnosed at earlier stages
Women with asymptomatic cancer who receive estrogens are more likely to bleed and to be diagnosed
Antunes CMF, et al. N Engl J Med 1979;300:9-13 76
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To avoid selection bias in case-control
studies Selection of cases
Types of cases selected (non-fatal, symptomatic, advanced) Response rates among cases Relation of selection to exposure – Are exposed cases more
(or less) likely to be included in the study?
Selection of controls Type of controls (general population, hospital, friends and
relatives) For hospital controls, diseases selected as control conditions Response rate among controls Relation of selection to exposure – Are exposed controls
more (or less) likely to be included in the study?
Similar response rates in cases and controls do NOT rule out selection bias 77
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Recall issues
All information in case-control studies is historic, so if relying on reporting by participants, accuracy depends on recall
Concerns: Do cases recall prior events differently from controls? Mindset of someone with disease : Is there
something that I did that may have caused the disease?
Recall Bias
(Information Bias) 79
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Recall bias – example
Mothers of babies born with congenital malformations more likely to recall (accurately or “over-recall”) events during pregnancy such as illnesses, diet, etc.
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Folic acid and neural tube defects
Figure 1: Features of neural tube development and neural tube defects. Botto et el. Neural tube defects. NEJM 1999. (28th days after fertilization)
Background and Aim
A reduced recurrent risk of neural tube defects among women receiving muti-vitamin supplements containing folic acid.
Most of NTDs are de-novo; less than 10% of NTDs are recurrent.
First occurrence of only NTDs and periconceptional folate supplements
Study population
Case NTDs
Control Other major malformations due to recall bias Subjects with oral clefts were excluded because vitamin
supplementation has been hypothesized to reduce the risk: selection bias
Pregnant women
Target
Source
Study
Overall data
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Folate (+) OR = 0.6 (0.4 – 0.8)
Recall Bias: Previous knowledge
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Recall Bias quantification
Case Control OR In this study
1000 1000 Recall rate
real 500 800 0.625 Control – 75%
all 400 600 0.667 Case – 80% 0.6
Prev known 450 600 0.750 Case – 90% 0.8
Prev unknown 375 600 0.625 Case – 75% 0.4
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Recall bias – assessment / avoidance
Check with recorded information, if possible Use objective markers or surrogates for
exposure – careful of markers that are affected by disease
Ask participant to identify which factor(s) are important for disease
Build in false risk factor to test for over-reporting
Use controls with another disease
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Study population
Case NTDs
Control Other major malformations due to recall bias Subjects with oral clefts were excluded because vitamin
supplementation has been hypothesized to reduce the risk:
selection bias
Pregnant women
Target
Source
Study
Selection bias
If oral clefts were included in control group, control with exposure (lack of vitamin supplement or folate intake) increased.
As B number increases, the probability of rejecting null hypothesis decreases.
Case Control
Exposure (+) A B
Exposrue (-) C D
Exposure: lack of folate intake
Cleft = ↓intake of vitamin
Methods
Periconceptional folic acid exposure was determined by Interview with study nurses
Demographic Health behavior factors Reproductive history Family history of birth defects Occupation Illnesses (chronic and during pregnancy) Use of alcohol, cigarettes and medications Vitamin use during the 6 months before the last LMP
through the end of pregnancy Semi-quantitative food frequency questionnaire Knowledge of vitamins and birth defects
Confounding
Exposure ↓ Folate intake
Outcome↑ NTDs
Confounding Alcohol
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Interviewer bias
Differential interviewing of cases and controls, i.e., may probe or interpret responses differently
Interviewer Bias
(Information Bias)
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Interviewer bias – avoidance / assessment
Self-administered instruments (prone to more non-response)
Standardized instruments Computerized instruments (CADI, ACASI)
Avoid open-ended questions but rather use questions with each possible response elicited
Training Masking interviewers to research question Masking interviewers to case/control status Same interviewers for cases and controls
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Odds ratio
1 0
0 1
( )A B
OR cross product ratioA B
Disease
Yes No
Exposed Yes A1 B1
No A0 B0
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Example: CHD and Diabetes
CHD
Yes No
Diabetes Yes 183 65
No 575 735
183 / 65
3.62575 / 735CHDOR
No units!
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Some properties of odds ratios
Null value: OR = 1 OR >= 0 (cannot be negative) Multiplicative scale (be careful with plots) Use logistic regression to estimate
multivariate adjusted odds ratios in case-control studies
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Odds ratios and the “rare disease assumption”
With incidence density sampling (represents underlying cohort at time of case) and sampling of cases and controls independent of exposure:
OR ≈ IR
With outcomes of very low incidence in the underlying cohort and sampling of cases and controls independent of exposure:
OR ≈ RR
Higher incidence increases the bias away from the null
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Matching
Individual matching Up to 1:5
Frequency matching Case selection confounder frequency
matching
Stratified sampling Stratification selection of case and
control
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Odds ratio – matched pairs
Case Control # pairs
A1 B1 n11
A1 B0 n10
A0 B1 n01
A0 B0 n00
N = total # pairsN pairs = N cases and N controls 2 N people
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Antunes CMF, et al. N Engl J Med 1979;300:9-13102
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Matching
Cannot examine the independent effect of matched variable on outcome
May inadvertently match On the exposure itself or its surrogate On a factor in the causal pathway On a factor that is affected by the outcome
Logistical complexity of matching Particularly useful when distribution of
confounders is very different in cases and controls
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Designing a case-control studyOverview I
What is the research question? In what target population? What source(s) will be used? How long will recruitment take? What is the definition of the cases? What confirmation is needed? Is screening/additional
testing necessary? Will prevalent cases be used? Does exposure
influence the disease prognosis? What is the underlying cohort? How many cases are seen per year in the source?
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What are the eligibility criteria for controls? What source(s) will be used to identify controls? Do they represent the same underlying cohort as the
cases? What confirmation is needed? Is screening/additional
testing necessary? Sampling methods? Will the controls be selected
throughout the study period? Can they be selected as cases if they later develop disease?
Do additional sources need to be used? For both cases and controls, does exposure status
affect: inclusion in source populations or participation?
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Designing a case-control studyOverview II
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Are there known confounders? Should matching be used? What methods will be used to recruit cases and controls? What methods will be used to obtain information about
exposures and potential confounders? Active / Passive? Are the methods of data collection objective and
independent of case/control status? What methods are in-place to avert and monitor differential
recall by case/control status if interviewing is involved? If study involves personnel-administered data collection,
are the personnel masked to case-control status?
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Designing a case-control study Overview III
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Summary
What is the study question? Appropriate Duration of recruitment
Definition of cases Prevalence case
Eligibility of controls Represent the target population
Another sources
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