1 A casecontrol study was performed to determine whether head injury was associated with an increased risk of brain tumors in children. 200 cases with brain cancer were identified from the state cancer registry and 200 controls were recruited from the same neighborhoods where the cases lived. The mothers of the children completed a questionnaire that asked them to describe their child's past history of head injury. The investigators found that the mothers of the children with brain tumors reported a past head injury for 70 of the cases while a past history of head injury was reported in 30 of the controls. What type of bias was likely to have influenced the findings of this study, and why? What can be done to minimize this type of bias? 1. QUESTION 2 The association between cellular telephone use and the risk of brain cancer was investigated in a case-control study. The study included 475 cases and 400 controls and the following results were seen: Cellular Phone User No Cases Controls 270 200 205 200 Total 475 400 Calculate the odds ratio based on these data. The p value for this odds ratio is 0.06. State your interpretation of this p-value. Gender was considered a potential confounder and effect measure modifier in this study. The data were stratified into males and females in order to assess these issues. Cellular Phone User Yes Yes Males Cases 242 No 100 Controls 150 Yes 50 No Females Cases Controls 28 50 105 150 Calculate the stratum-specific odds ratios. Is gender a confounder in this study? Briefly justify your answer. Is gender an effect measure modifier in this study? Briefly justify your answer. QUESTION 3 1. A study followed 900,000 US adults from 1992 to 2008. At baseline, all participants were screened and determined to be cancer free and their body mass index (BMI) was calculated. Body mass index is a measure of obesity that is calculated using a person's height and weight. Subjects were separated into the following groups according to their BMI: (a) normal weight, (b) slightly overweight, (c) moderately overweight and (d) greatly overweight. 57,145 deaths from cancer occurred in the population during the follow-up period. . The following results were seen for men and women when the heaviest members of the cohort (greatly overweight) were compared to those with normal weight: Men: Risk ratio of cancer death = 1.5, 95% confidence interval = 1.1-2.1 Women: Risk ratio of cancer death = 1.6, 95% confidence interval = 1.4-1.9 State in words your interpretation of the risk ratio given for the men. State in words your interpretation of the risk ratio given for the women. Are these results confounded by gender? The authors stated that they controlled for confounding many risk factors using a multivariate analysis. State an alternative method that the authors could have used to control for confounding in the design or analysis. In addition, name two confounding variables that you think should be controlled using this method. Solution...... (1) Recall bias. : Minimize =200x+200y (2)(I) Odd ratio =(270*200)/(200*205) =1.32 (ii)Given that the null hypothesis is true, the Chance of seeing these results, or more extreme Result, is 6% (i)Stratum-specific odd ratio =0.8 (ii)Gendar is a confounder but not an effect modifier. (iii) Gender is not an effect measure modifier but it is comfounder. (3) (i) Risk ratio =1.1/2.1 =0.5238 (ii)Risk ratio =1.4/1.9 =0.7368 (iii) Yes these results confounded by gender (iv)-Rendomizing -Matching Solution...... (1) Recall bias. : Minimize =200x+200y (2)(I) Odd ratio =(270*200)/(200*205) =1.32 (ii)Given that the null hypothesis is true, the Chance of seeing these results, or more extreme Result, is 6% (i)Stratum-specific odd ratio =0.8 (ii)Gendar is a confounder but not an effect modifier. (iii) Gender is not an effect measure modifier but it is comfounder. (3) (i) Risk ratio =1.1/2.1 =0.5238 (ii)Risk ratio =1.4/1.9 =0.7368 (iii) Yes these results confounded by gender (iv)-Rendomizing -Matching