Case-control studies are an efficient research method for investigating risk factors of a disease. The method involves the comparison of the odds of exposure in a patient group with that of the... Show moreCase-control studies are an efficient research method for investigating risk factors of a disease. The method involves the comparison of the odds of exposure in a patient group with that of the odds of exposure in a control group. As only a minority of the population is included in the study, less time can be devoted to those who remain free of the disease of interest. The design of a case-control study can be complex due to the selection of the appropriate cases and controls. Cases can be identified in a prospective and retrospective manner from various sources. Controls can be obtained via the patient, random digit dialing or in a hospital and all at different points in the time period of the study. All options have their own advantages and disadvantages. Furthermore, different forms of bias, such as recall bias and selection bias, can occur. When appropriately designed, case-control studies can provide the same information as in a cohort study, in a more rapid and efficient manner. Copyright (C) 2009 S. Karger AG, Basel Show less
In confounding, the effect of the exposure of interest is mixed with the effect of another variable. It is important to identify relevant confounders and remove the confounding effect as much as... Show moreIn confounding, the effect of the exposure of interest is mixed with the effect of another variable. It is important to identify relevant confounders and remove the confounding effect as much as possible. There are three criteria that need to be fulfilled to determine whether a variable could be considered a potential confounder. The first criterion is that the variable needs to be associated with the exposure. The second criterion is that the variable needs to be associated with the outcome or disease. The third criterion is that the variable should not be an intermediate variable in the causal pathway between exposure and outcome. Only if all the criteria are fulfilled is the variable under question a confounder. If one incorrectly adjusts for a variable that is not a confounder, one risks overadjustment or adjustment for spurious associations. Confounders can be prevented from entering the study, during the design of a study, or if this is not possible, one can try to remove it during the analysis phase. Copyright (C) 2010 S. Karger AG, Basel Show less
We discuss the analytic and practical considerations in a large case-control study that had two control groups; the first control group consisting of partners of patients and the second obtained by... Show moreWe discuss the analytic and practical considerations in a large case-control study that had two control groups; the first control group consisting of partners of patients and the second obtained by random digit dialling (RDD). As an example of the evaluation of a general lifestyle factor, we present body mass index (BMI). Both control groups had lower BMIs than the patients. The distribution in the partner controls was closer to that of the patients, likely due to similar lifestyles. A statistical approach was used to pool the results of both analyses, wherein partners were analyzed with a matched analysis, while RDDs were analyzed without matching. Even with a matched analysis, the odds ratio with partner controls remained closer to unity than with RDD controls, which is probably due to unmeasured confounders in the comparison with the random controls as well as intermediary factors. However, when studying injuries as a risk factor, the odds ratio remained higher with partner control subjects than with RRD control subjects, even after taking the matching into account. Finally we used factor V Leiden as an example of a genetic risk factor. The frequencies of factor V Leiden were identical in both control groups, indicating that for the analyses of this genetic risk factor the two control groups could be combined in a single unmatched analysis. In conclusion, the effect measures with the two control groups were in the same direction, and of the same order of magnitude. Moreover, it was not always the same control group that produced the higher or lower estimates, and a matched analysis did not remedy the differences. Our experience with the intricacies of dealing with two control groups may be useful to others when thinking about an optimal research design or the best statistical approach. Show less
Deep venous thrombosis is a common disease. Already in 1856 it was suggested that immobilization could cause venous thrombosis. However, so far little research has shown whether exercise or... Show moreDeep venous thrombosis is a common disease. Already in 1856 it was suggested that immobilization could cause venous thrombosis. However, so far little research has shown whether exercise or ambulation could decrease the risk of venous thrombosis. We performed a historical review regarding the role of venous thrombosis risk in the change of the practices regarding ambulation after delivery. We could not find well-performed studies showing that early ambulation reduced venous thrombosis risk. Furthermore we performed two studies on the relation between participating in physical activity and venous thrombosis risk. In one case-control study in the Netherlands we showed that exercise decreases the risk of venous thrombosis. However, in a cohort study in elderly people from the USA, we showed that exercise seemed to increase this risk. A possible explanation for this difference might be due to an increased risk of injuries among elderly people as we showed that injuries increase the risk of venous thrombosis 5 fold. Furthermore we showed that for the very rare thrombosis of the arm, sports activities which highly involve the arm result in an increased risk. In summary, although immobilization seems to increase venous thrombosis risk, it is unclear whether mobilization or exercise decrease this risk. Show less
