Pharmacoepidemiology Overview

Pharmacoepidemiology definition

Pharmacoepidemiology is the study of the utilization and effects of drugs in large numbers of people; it provides an estimate of the probability of beneficial effects of a drug in a population and the probability of adverse effects. It can be called a bridge science spanning both clinical pharmacology and epidemiology. Pharmacoepidemiology concentrates on clinical patient outcomes from therapeutics by using methods of clinical epidemiology and applying them to understanding the determinants of beneficial and adverse drug effects, effects of genetic variation on drug effect, duration-response relationships, clinical effects of drug-drug interactions, and the effects of medication non- adherence. Pharmacovigilance is a part of pharmacoepidemiology that involves continual monitoring, in a population, for unwanted effects and other safety concerns arising in drugs that are already on the market. Pharmacoepidemiology sometimes also involves the conduct and evaluation of programmatic efforts to improve medication use on a population basis.

Pharmacoepidemiologic studies

Pharmacoepidemiology aims to complete the evaluation of drugs made before approval, by providing reliable information concerning effectiveness, safety and utilization of medicines in realistic conditions. The goal may be only descriptive or aetiological. In the latter, the conclusions from observational studies can be jeopardized by systematic errors and cannot achieve the robustness of experimental designs. According to directionality, three main types of studies can be identified: cross-sectional, prospective and retrospective. Prospective and retrospective studies can be based on a single group (descriptive studies) or include a reference group (comparative or aetiologic studies). The interest of prospective studies is reduced when the incidence of the considered event becomes low or one intends to assess the effects of various causal factors. Retrospective studies are approaching their limits when the prevalence of the exposure is low in the source-population or several events or outcomes are concerned.

Basic elements of epidemiologic studies

The basic elements of an epidemiological study can be characterized as follows:

• formulation of the study question or hypothesis

• selection of study populations and study samples

• selection of indicators of exposure

• measurement of exposure and disease

• analysis of the relationship between exposure and disease

• evaluation of the role of bias evaluation of the role of chance

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Errors in Epidemiological Studies

Many sources of error in epidemiologic studies can be considered: selective survival, selective recall, incorrect classification of subjects with regard to their disease and/or exposure status. Because of the limited opportunity for experimental controls, error, particularly "bias", is an overriding concern of epidemiologists as well as the principal basis for doubting or disputing the results of epidemiologic investigations. Types of error include random (chance) error, which is associated with precision and systematic error/bias, associated with selection.

Common sources of error are selection bias, absence or inadequacy of controls, unwarranted conclusion, ignoring the periods of exposure to risk, improper interpretation of associations, mixing of non-comparable records and error of measurement.

Random error or chance variation: Random error or chance variation is an error that generally occurs in sampling procedure. It is a divergence, due to chance alone, of an observation on a sample from the true population value, leading to lack of precision in the measurement of an association. Example: out of a sample of 100 people, 3 consecutive samples drawn randomly may contain: 0% diseased people | 10% diseased people | 70% diseased people. This is called random error where the error is due to chance. The only way to reduce it is to increase the size of sample; the elimination of error is not possible. Sources of random error are individual biological variation, sampling error and measurement error; the types of random error are type I error (alpha error) and type II error (beta error). Increasing the size of the study is a way to reduce the random error.

Systemic Error/Bias: Systemic Error/Bias is any process or attempts in any stage of the study from designing to its execution to the application of information from the study which produces results or conclusions that differ systematically from truth. Selection bias is a distortion in true study finding due to improper selection procedures or it is due to an effect of selection process. Some potential sources of selection biases are: self selection bias, selection of control group, selection of sampling frame, loss to follow up, improper diagnostic criteria, more intensive interview to desired subjects etc, while information bias is distortion in true study finding due to improper information/lack of information or misclassification. Potential sources of information bias are: invalid instrument, incorrect diagnostic criteria, misclassifications, recall laps error, Interviewing techniques, losses to follow up, attrition/experimental mortality, etc. The confounding bias is a special type of bias; the term “confounding” is the effect of extraneous variable that entirely or partially explains the apparent association between the study exposure and the disease. It is a bias that results when a study factor effect is mixed, in the data, with effects of extraneous variable or the third variables5.

Confounding Variables: A variable is a confounder if it is an independent risk factor (cause) of disease; it is unevenly distributed among the exposed and the non-exposed, and it is not on the causal pathway between exposure and the disease. Methods of controlling confounding in epidemiological study are made in two stages: (1) in designing stage (randomization, restriction and matching); (2) in analysis stage (stratification and statistical modeling (multivariate)).

Conclusion

Pharmacoepidemiologic studies are here to stay. Their primary strength is that they are the only possible way of studying a number of important research questions, but they are also cheaper and faster than randomized controlled trials. The negative side is their lower validity, and readers must carefully assess all sources of error.

References

1. Pharmacoepidemiology Research. John Hopkins Medicine. CIOMS website. http://www.hopkinsmedicine.org/gim/resea rch/content/pharmacoepi.html. Accessed 09/14/2016.

2.Bégaud B, Dangoumau J. Pharmacoepidemiology: definitions, problems, methodology. Therapie. 2000; 55(1): 113-7. http://www.ncbi.nlm.nih.gov/pubmed/1086 0010. Accessed 09/14/2016. PMDI10860010.

3. Water sanitation hygiene. WHO website. http://www.who.int/water_sanitation_healt h/dwq/iwachap7.pdf. Accessed 09/14/2016.

4. Schoenbach V. Understanding the fundamentals of epidemiology — an evolving text. Fall ed. Chapel Hill, USA. 2000: 287. http://www.epidemiolog.net/evolving/Sour cesofError.pdf. Accessed 09/14/2016.

5. Errors and Bias in Epidemiological Studies. Medchrome’s Community Medicine website. http://community.medchrome.com/search/l abel/Epidemiology. Accessed 09/14/2016.

6. Jepsen P, Johnsen S et al. Interpretation of observational studies. Heart. 2004; 90(8): 956-960. http://www.ncbi.nlm.nih.gov/pmc/articles/ PMC1768356/. Accessed 09/14/2016. PMC1768356.

7. Authoral work: Ferreira F.  (2016). What do you understand by pharmacoepidemiology? What are the common errors encountered in pharmacoepidemiology? James Lind Institute.

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