Epidemiology The Basics Only…
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Transcript of Epidemiology The Basics Only…
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EpidemiologyThe Basics Only…
Adapted with permission from a class presentation developed by Dr. Charles Lynch – University of Iowa, Iowa City
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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.
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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
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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
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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
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Usual Pattern of Reasoning
• Judge whether the observed association represents a cause-effect relationship between exposure and disease
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VALIDITYDefinition
The degree to which a measurement or study
reaches a correct conclusion
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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?
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Internal and External Validity
• Internal validity- – must be the primary study objective
because you would not want to generalize an invalid result
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Epidemiologic Study Cycle
Descriptive Studies - dataaggregation and analysis
Analysis of results suggests further descriptive study of hypotheses and new hypotheses
Analytic Studies to test hypotheses
Form hypothesis
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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
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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
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Descriptive
• Usually uses routinely collected data
IMPORTANT DIFFERENCE
• Used to generate the hypothesis NOT test the hypothesis
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Descriptive
• Populations – Correlational– Ecologic– Aggregate
• Individuals– Case report (describes
single patient)– Case series (describes
characteristics of a number of patients)
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Analytic
• Designed to test causal hypotheses that usually have been generated from descriptive studies
• Collection of new data
• More definitive conclusions about causation
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Types of Studies for Testing Hypotheses
Observational– Cross-sectional– Case-Control– Cohort (prospective, retrospective
Intervention (experimental, clinical trials)
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Experimental Versus Observational Study Design
E xp erim en ta l S tu d y
G rou p A G rou p B
R an d om A lloca tion
P op u la tion
O b serva tion a l S tu d y
G rou p A G rou p B
O th er-th an -ran d omA lloca tion
(e .g . S e lf-S e lec tion )
P op u la tion
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Clinical Observations
Available Data
Case-Control Studies
Cohort Studies
Randomized Trials
DescriptiveStudies
Sequence of Studies in Human Populations
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Design of a Randomized Clinical Trial
Im p roved N ot Im p roved
N ewTrea tm en t
Im p roved N ot Im p roved
C u rren tTrea tm en t
R an d om ized
D efin ed P op u la tion
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Clinical Applications of Various Types of Studies
Type of Study Application 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?
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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
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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
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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
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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.
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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.
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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
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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.
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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