1 design and analysis techniques for case- control studies instructor: 李奕慧...
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Lecture Overview
1. Case-Control Study
2. Example: ”Risk factors associated with lung cancer in Hong Kong”
3. OR for multiple exposure levels
4. Confounding factors
5. Methods of Controlling (adjusting for) confounders
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Epidemiologic Study Design
Analytical studies
Intervention studies Clinical trials
Observational studiesCohort studiesCase-control studies
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Case-control study
Study Population
Cases
Controls
Exposed
Non-exposed
Exposed
Non-exposed
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Selection of cases
Establish a strict diagnostic criteria for the disease: Examples:Type 1 diabetes in children: severe
symptoms, very high BG, marked glycosuria, and ketonuria.
Type 2 diabetes: few if any symptoms, Slightly elevated BG, diagnosis “complicated”.
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Selection of cases
Population-based cases: include all subjects or a random sample of all subjects with the disease at a single point or during a given period of time in the defined population: Danish childhood diabetes register
Hospital-based cases:
All patients in a hospital department at a given time
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Selection of ControlsPrinciples of Control Selection: Study base:
Controls can be used to characterise the distribution of exposure
Comparable-accuracy Equal reliability in the information obtained from cases
and controls no systematic misclassification
Overcome confounding Elimination of confounding through control selection
matching or stratified sampling
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Selection of Controls
General population controls:registries, households, telephone samplingcostly and time consumingrecall biaseventually high non-response rate
Hospitalised controls:Patients at the same hospital as the casesEasy to identifyLess recall biasHigher response rate
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Ascertainment of Disease and exposure status External sources:
Death certificates, disease registries, Hospital and physicians records etc.
Internal sources: Questionnaires and interviews, information
from a surrogate (spouses or mother of children), biological sampling( e.g. antibody)
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Bias in Case-Control studies
Selection biasNon-responseDetection bias
cases and controls are identified not independently of the exposure
Observation biasRecall Bias: Cases are more likely to remember
exposure than controls
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Strengths in Case-control Quick, inexpensive Well-suited to the evaluation of
diseases with long latency period Rare diseases Examine multiple etiologic factors for a
single disease
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Limitations in Case-control
Case-control study Not rare exposure Incidence rates cannot be estimated
unless the study is population based Selection Bias and recall bias
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Risk factors associated with lung cancer in Hong Kong
Lung Cancer 40 (2003) 131-14013
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Chi-Square Tests
Value dfAsymp. Sig.
(2-sided) Exact Sig. (2-sided)
Exact Sig. (1-
sided)
Pearson Chi-Square
0.257a 1 .613
Risk Estimate
Value
95% Confidence Interval
Lower Upper
Odds Ratio for Marital (other / married)
.880 .535 1.446
Multiple Exposure Levels
B1High A1
DNot exposed C
CasesExposurelevel
B2Medium A2
B3Low A3
OR1
OR2
OR3
Reference
Controls OR
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Multiple Exposure Levels
16Lung Cancer 40 (2003) 131/140Lung cancer.sav
A significant (P<0.05) increasing trend in the OR was found between nonsmokers, ex- and current smokers; and increasing amount of smokingamong the ever smokers.
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smoking * case Crosstabulationcase
Totalcase controlsmoking nonsmoker Count 52 96 148
% within case 24.5% 45.3% 34.9%exsmoker Count 68 87 155
% within case 32.1% 41.0% 36.6%current smoker Count 92 29 121
% within case 43.4% 13.7% 28.5%Total Count 212 212 424
% within case 100.0% 100.0% 100.0%
Chi-Square Tests
Value dfAsymp. Sig.
(2-sided)Pearson Chi-Square 48.212a 2 .000
Likelihood Ratio 50.088 2 .000
Linear-by-Linear Association
42.734 1 .000
N of Valid Cases 424
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 60.50.
抽煙與罹患肺癌有關，Case中抽煙者佔較高的比例 (43% vs 13.7%)
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Data > Select cases >
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只選 smoking=2, 3的資料進行分析
Risk Estimate
Value
95% Confidence Interval
Lower Upper
Odds Ratio for smoking (exsmoker / nonsmoker)
1.443 .908 2.293
For cohort case = case 1.249 .942 1.656
For cohort case = control .865 .721 1.039
N of Valid Cases 303
Exsmoker 罹患肺癌是 nonsmoker 的 1.4倍 ,95%CI (0.9, 2.3)Exsmoker 與nonsmoker罹癌機率沒有顯著差異
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Confounding factors (干擾因素）
Confounder:
Variable is associated with both the disease and the exposure variable.
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Method for control for confounders Study design:
restriction/ matching/ randomization Statistical adjustment:
1. Standardization; e.g. age standardized (where age is a confounder)
2. Stratified by confounder (Mantel-Haenszel test)
3. Incorporate the confounder into a regression analysis as a covariate. (logistic regression approach)
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Restriction
Example研究主旨：二手煙 (ETS, exposure)與罹患肺癌(disease)的關係confounder: 研究對象本身是否抽煙
為了避免干擾只分析 ETS 對 nonsmoker的影響
Stratified Analysis
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將性別當作分層 (stratum)的因子
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smoking * case * sex CrosstabulationCount
sexcase
Totalcase controlmale smoking ex- and current smoker 160 116 276
nonsmoker 52 96 148Total 212 212 424
female smoking ex- and current smoker 13 6 19
nonsmoker 106 113 219Total 119 119 238
Lung cancer2.sav
Sex-Specific OR for smoking
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Risk Estimate
sex Value
95% Confidence Interval
Lower Uppermale Odds Ratio for smoking (ex- and
current smoker / nonsmoker)2.55 1.68 3.85
N of Valid Cases 424female Odds Ratio for smoking (ex- and
current smoker / nonsmoker)2.31 0.85 6.30
N of Valid Cases 238
Lung cancer2.sav
可以將男士的 OR與女士的 OR合併嗎？怎麼併？
Thank you!
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