OUTLINE: Confounding- cont. Generalizability Reproducibility Effect modification Confounding Bias: Stratification Example 1: Association between place of residence & Chronic bronchitis Residence Chronic bronchitis Yes No Urban 194 2219 RR= 1.48 Rural 69 1208 Confounding Bias: Stratification Example 1: Stratified by Smoking: Smokers Non-smokers Bronchitis Bronchitis Residence Yes No Yes No Urban 167 1094 27 1125 Rural 53 417 16 791 RR=1.18 RR=1.17
Confounding Bias: Stratification Example 1: But 1.18 1.17 = 1.48 (crude) Smoking is a confounding variable! Confounding Bias: Stratification Example 2: Study the association between Alcohol consumption & Myocardial Infarction Alcohol MI Yes No Yes 71 52 OR=2.2 No 29 48 Confounding Bias: Stratification Example 2: Stratified by smoking: Smokers Non-smokers Alcohol MI No MI MI No MI Yes 8 16 63 36 No 22 44 7 4 OR=1 OR=1
Confounding Bias: Stratification Example 2: But 1 = 1 = 2.2 (crude) Smoking is a confounding variable! Confounding Bias: Stratification Example 3: Study the association between Treatment 1 & Treatment 2 with survival Alive Dead Total T1 40 60 100 T2 60 40 100 Total 100 100 200 RR (Crude) = 0.67 Confounding Bias: Stratification Example 3: Stratified by gender: Females Males Alive Dead Alive Dead T1 24 3 16 57 T2 58 30 2 10 RR=1.35 RR=1.32
Confounding Bias: Stratification Example 3: But 1.35 1.32 = 0.67 (crude) Gender is a confounding variable! Mantel-Haenzel: Calculating an adjusted RR i th stratum: Outcome No outcome Total E ai bi No E ci di Total Ni RR MH = ai(ci + di) /Ni ci(ai + bi) /Ni Mantel-Haenzel: Example Example: Females Males Success Failure Success Failure T1 24 3 16 57 T2 58 30 2 10 RR= 1.35 RR= 1.32 RR Adjusted = RR MH = 24(58+30)/115 + 16 (2+10)/85 58(24+3)/115 + 2 (16+57)/85 = 1.34
Concerns in Epidemiologic studies I. Internal validity: Was the study carefully designed and analyzed? II. III. External validity (Generalizability): Are the results applicable to the external population? Reproducibility of the results (precision): Are the results reproducible? External validity Also Known as generalizability. The extent to which the analytic inference derived from study sample is correct for the external population. External population Target Population Study Sample External validity External validity is dependent on internal validity. Maximize external validity by selecting study subject from a target population as similar as possible to the external population.
Concerns in Epidemiologic studies I. Internal validity: Was the study carefully designed and analyzed? II. III. External validity (Generalizability): Are the results applicable to the external population? Reproducibility of the results (precision): Are the results reproducible? Reproducibility Subjects in a study are always a sample of a population. Repetitive sampling results in a range of estimates for different samples: Sampling variation. The smaller the sample, the less reproducible will be the sample estimate. To decrease sampling error, increase sample size. Reproducibility Target Population Sample 2 Sample 1 Sample 3 Study sample
Effect Modification (Interaction) Example 1: Association between severe injury & death. Death No Death Severe injury 45 55 No Severe injury 6 94 RR = 0.45/0.06 = 7.5 Effect Modification (Interaction) Example 1: Stratified by age: <65 years > 65years Death No Death No Death Death Severe injury 15 35 30 20 No Severe injury 2 28 4 66 RR= 4.48 RR= 10.5 Effect Modification (Interaction) Example 1: 4.48 = 10.5 = 7.5 (crude) Age is an effect modifier!
Effect Modification (Interaction) When the exposure- outcome relationship is different for the different levels of a third variable, we have interaction (effect modification). The crude RR is hiding important effects. Solution: Report the RR separately for each category of the variable (for the different levels of the effect modifier). Effect Modification (Interaction) Example 2: 1.69 = 3 = 1 (crude) Gender is an effect modifier! Effect Modification (Interaction) A Confounder or Effect modifiers? Males RR=2 Hip Fracture Young Old Males Hip Fracture Males Hip Fracture RR= 0.7 RR= 3
Effect Modification (Interaction) A Confounder or Effect modifiers? Obesity RR=1.6 Breast cancer Pre-menopausal Post-menopausal Obesity Breast cancer Obesity Breast cancer RR= 1.1 RR= 2 Effect Modification (Interaction) A Confounder or Effect modifiers? Smoking RR=3 Low birth weight (LBW) Young Old Smoking LBW Smoking LBW RR= 2 RR= 4 Effect Modification (Interaction) Example 2: A cohort study was conducted to evaluate the association between air pollution and a specific lung disease. From the information below would you conclude that gender is a confounder or an effect modifier??? D No D Total E 200 1800 2000 No E 400 3600 4000 Total 600 5400 6000 3500 individuals were females 500 females were exposed 490 females had the disease 110 females had disease & were exposed 1410 males were exposed & did not have the disease 20 males were not exposed & had the disease
Biases: Review T (True) or F (False): To ensure that the study is internally valid we need to check for the 4 main biases: Selection bias, information bias, confounding and effect modification. Generalizability is the extent to which the inference derived from the study sample is correct for the target population. Biases: Review External validity depends on If you increase the sample size you increase Biases: Review T (True) or F (False): Blinding the interviewer minimizes observation bias. Recall bias is common in case control studies while loss to follow up is common in randomized clinical trials.
Biases: Review A cohort study is planned to investigate the association between maternal alcohol consumption during pregnancy and fetal alcohol Syndrome (a disease that is difficult to diagnose) in newborn children. What are the possible biases? Biases: Review In a closed cohort study, most of those who were exposed and developed the disease died before the end of the study. What will happen to the RR? What are the characteristics of a confounder? Biases: Review T (True) or F (False): The crude relative risk for smoking and myocardial infarction was 2.8. When stratified by gender, the relative risk for males was 5.6 and 1.5 for females. The study investigators concluded that results are biased by gender which is an effect modifier and hence they adjusted for gender in the analysis.
Effect Modification (Interaction) A Confounder or Effect modifiers? Having Pets RR=2.3 Asthma Children Adults Having Pets Asthma Having Pets Asthma RR= 2.1 RR= 2.4