Epidemiology The Basics Only…

1. EpidemiologyThe Basics Only… Adapted with permission from a class presentation developed by Dr. Charles Lynch – University of Iowa, Iowa City

2. Epidemiology • Study of the distribution and determinants of health-related states or events in specified human populations and the application of this study to control of health problems.

3. Epidemiology Objectives • Identify etiology of disease • Determine extent of disease • Study natural history • Evaluate new modes of health care delivery and new preventive and therapeutic measures • Provide foundation for developing public policy

4. Usual Pattern of Reasoning • Develop a hypothesis • Test the hypothesis on an exposed human population and include an appropriate comparison group • Systematically collect and analyze data to determine whether a statistical association exists

5. Usual Pattern of Reasoning • Assess validity of any observed statistical association by excluding possible alternative explanations such as • Chance (random error) • Bias (systematic error) • Confounding (effects of additional variables) • Describe interaction

6. Usual Pattern of Reasoning • Judge whether the observed association represents a cause-effect relationship between exposure and disease

7. VALIDITYDefinition The degree to which a measurement or study reaches a correct conclusion

8. TYPES OF VALIDITYDefinitions • Internal: Do the results of an investigation accurately reflect the true situation of the study participants? • External (i.e., generalizability): Are the results of a study applicable to other populations?

9. Internal and External Validity • Internal validity- • must be the primary study objective because you would not want to generalize an invalid result

10. Epidemiologic Study Cycle Descriptive Studies- data aggregation and analysis Analysis of results suggests further descriptive study of hypotheses and new hypotheses Analytic Studiesto test hypotheses Form hypothesis

11. Types of Studies • Observational • Descriptive • Study of the amount and distribution of disease within a population by person, place, and time • Analytic • Study of the determinants of disease or reasons for relatively high or low frequency in specific groups

12. Descriptive • Undertaken when little is known of the epidemiology of a disease • Provides information on patterns of disease occurrence in populations by characteristics such as age, race, marital status, social class, occupation, geographic area, and time occurrence

13. Descriptive • Usually uses routinely collected data IMPORTANT DIFFERENCE • Used to generate the hypothesis NOT test the hypothesis

14. Populations Correlational Ecologic Aggregate Individuals Case report (describes single patient) Case series (describes characteristics of a number of patients) Descriptive

15. Analytic • Designed to test causal hypotheses that usually have been generated from descriptive studies • Collection of new data • More definitive conclusions about causation

16. Types of Studies for Testing Hypotheses Observational • Cross-sectional • Case-Control • Cohort (prospective, retrospective Intervention (experimental, clinical trials)

17. Experimental Versus Observational Study Design

18. Sequence of Studies in Human Populations Clinical Observations Descriptive Studies Available Data Case-Control Studies Cohort Studies Randomized Trials

19. Design of a Randomized Clinical Trial

20. Clinical Applications of Various Types of Studies Type of StudyApplication to Clinical Practice Etiologic Can risk be reduced among susceptible persons? Diagnostic Can accuracy and timeliness of diagnosis be improved? Prognostic Can prognosis be determined more definitively? Therapeutic Can treatment be improved?

21. Case Reports • Describe the experience of a single patient • Generally provide detailed documentation of a unique medical occurrence • May lead to the generation of a new hypothesis • Traditionally, a common type of study published in medical journals • Chief limitation: Sample size of 1

22. Case Series • Collections of individual case reports • Often used as an early means to identify the beginning or presence of an epidemic • May lead to the generation of a new hypothesis • Chief limitation: Lack of an appropriate comparison group

23. Descriptive Studies of Population Groups • Also called • Correlational studies • Ecologic studies • Aggregate studies • Studies in which the unit of analysis is some aggregate of individuals rather than an individual person

24. CHANCEDefinition of P-value The probability that an effect at least as extreme as that observed in a particular study could have occurred by chance alone, given that there is truly no relationship between exposure and disease.

25. CHANCEP-value • If p-value < 0.05: Since there is less than a 5% probability (1 in 20 chance) of observing a result as extreme as that observed due solely to chance, we generally consider the association between the exposure and disease to be statistically significant.

26. CHANCEP-value • If p-value > 0.05 - by convention: • We generally consider that chance cannot be excluded as a likely explanation • Findings are stated to be not statistically significant at that level

27. BIASDefinition Any systematic error in the design, conduct, or analysis of a study that results in a mistaken estimate of an exposure’s effect on the risk of disease.

28. CONFOUNDING: ANOTHER TYPE OF BIAS Definition • A variable that: • Is causally related to (or at least associated with) the disease under study (or, as often occurs in practice, serves as a proxy measure for unknown or unmeasured causes), and • Is associated with the exposure under study in the study population but is not a consequence of this exposure