Studies of this type compare cases with a disease with controls susceptible to the disease but free of it. Using this method, the research compares the exposure rate in the cases with the exposure rate in the controls, adjusting statistically for factors that may confound the association. As with any formal epidemiology study, great care has to be taken in the design. Special attention is needed in case definition so that the cases truly represent the specific outcome of interest (e.g. Stevens-Johnson Syndrome, and not all cases of rash). It is also important to select an appropriate control group that represents the population that gave rise to the cases. Careful design can minimize the amount of bias in a study; adequate control in the analysis is also important. Case-control studies have provided a substantial body of evidence for major drug safety questions. Two notable examples are studies that demonstrated the association between aspirin and Reyes Syndrome (Hurwitz et al., 1987), and the evaluation of DES and vaginal cancer in the offspring of mothers who took DES in pregnancy (Herbst et al., 1974, 1975). Moreover, a case-control study established the protective effects of prenatal vitamin supplementation on the develop ment of neural tube defects (Werler et al., 1993) The final results of these studies present a measure of the risk of the outcome associated with the exposure under study—expressed as the Odds Ratio. Only in very special circumstances can the absolute risk be determined. Clearly, a fairly small increase in the risk of a common, serious condition (such as breast cancer) may be of far greater public health importance than a relatively large increase in a small risk (such as primary hepatic carcinoma).
Case-control studies are more efficient than cohort studies, because intensive data need only be collected on the cases and controls of interest. Case-control studies can often be nested within existing cohort or large clinical trial studies. A nested case-control study affords the ability to quantify absolute risk while taking advantage of the inherent efficiency of the case-control design.
These studies involve a large body of patients followed up for long enough to detect the outcome of interest. Cohort studies generally include an exposed and an unexposed group, but there are also single-exposure, disease, or general population follow-up studies and registries. Studies must be designed to minimize potential biases. An advantage of the cohort study is its ability to quantify both an absolute risk and a relative risk. Cohort studies can be conducted prospectively, but such studies are usually expensive and time-consuming. Retrospective cohort studies can be conducted within large existing databases, providing the advantage of the cohort study design and the efficiencies inherent in studies using existing records.
Case-control studies are particularly useful to confirm a safety signal relating to a rare event (less than 1/1000). Cohort studies are useful when the outcome has not already been identified or when multiple outcomes are of interest. Both case-control and cohort studies can be conducted within large existing databases, assuming the required information is available.
An example of a large existing database can be found in the Medicines Evaluation and Monitoring Organization (MEMO). MEMO
achieves "record-linkage" by joining together general practitioner prescription data (the exposure data) with hospital discharge summaries (the outcome data). This activity takes place in Tay-side, Scotland where (uniquely in the United Kingdom) all patients have a personal Community Health Number (CHNo) which is widely used by National Health Service facilities of all types. Advantages include completeness, freedom from study-introduced bias in data collection, and timely availability of data for analysis. MEMO is an example of the types of databases that have been established over the last 30 years that utilize data collected systemmatically for other purposes. These databases have been used to detect and quantitatively evaluate hypotheses regarding safety signals.
Data resources now exist in many countries, especially in North America and Western Europe. Some examples of these data resources and application of these databases to answer important safety questions will be described in further chapters.
Randomized Controlled Trials (RCTs)
In this method of study a group of patients is divided into two in strictly random order; one group is then exposed and the other not exposed, so that the outcomes can be compared. The method is of great importance because of its resistance to biases. It is, however, of only limited (but important) use as a pharmacoepide-miological tool because most serious ADRs are relatively uncommon; RCTs used in such contexts can, therefore, become unmanageably large and expensive. Large simple trials have become common in evaluating safety and efficacy in special circumstances, such as vaccine development.
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