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Biostats/Epidemiology
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Terms in this set (76)
Health
State of complete physical, mental and social well-being and not merely the absence of disease or infirmity
Epidemiology
Study of health and illness on human populations, how disease is distributed and factors that influence such Tertiary prevention
Goal of Epidemiology
Identify sub-groups in a population who are at high risk for disease
Primary Prevention
Prevent development of disease in a person who is well and does not have the disease in question
Secondary Prevention
Identify people who have already developed a disease, at an early stage in the disease's natural history, through screening and early intervention
Types of Secondary Prevention
-Population based approach (Non-invasive and inexpensive)
-High-risk approach (Perhaps invasive and expensive)
Tertiary prevention
-Prevent complications in patients such as disability
-Prevent damage and pain from the disease
-Give better care to persons with the disease
-Slow down the disease: for progressive diseases such as Multiple Sclerosis
John Snow
"Father" of Modern Epidemiology that showed cholera was linked to contaminated water
Miasma Theory
Diseases such as cholera or black death were caused by pollution or a noxious form of bad air that clings low to the surface of the earth
Direct Transmission
Mode is Person-person contact e.g. Influenza, STDs
Indirect Transmission
Mode is:
1. Common vehicle (contaminated air or water or food) and may result from single exposure, multiple exposures, continuous exposure
2. Vector: e.g. mosquito
Endemic
The habitual presence of a disease within a given geographic area. It may also refer to the usual occurrence of a given disease within such an area. e.g. yellow fever
Epidemic
Defined as the occurrence in a community or region of a group of illnesses of similar nature, clearly in excess of normal expectancy, and derived from a common or from a propagated source. e.g. influenza
Pandemic
Worldwide epidemic e.g. avian flu, HIV/AIDS
Herd Immunity
Defined as the resistance of a group to an attack by a disease to which a large proportion of the members of the group are immune
Criteria for Herd Immunity
-Disease agent must be restricted to a single host species within which transmission occurs
-Transmission must be relatively direct from one member of the host species to another
Attack Rate
Number of people at risk who develop a certain illness/Total number of people at risk
Primary Attack Rate
People who acquire disease from exposure/Total number of people at risk
Secondary Attack Rate
Susceptible persons who acquires disease from infected person/Total number of people at risk
Incidence
The number of new cases that occur during a specified period of time in a population at risk for developing the disease
Cumulative incidence
No. of new cases of a disease occurring
in the population during a specified period of time divided by ALL individuals at risk in a population
Incidence Rate or Incidence Density
No. of new cases of a disease occurring in the population during a specified period of time divided by the sum (no. of times members of the population are at risk during that period of time) {often expressed as person-years}
Prevalence
-The number of affected persons present in the population at a specific time divided by the number of persons in the population at that time
Period Prevalence
Answers the question: How many people have a disease at any time during a given period, such as a calendar year?
Point Prevalence
Answers the question: What is the number of persons living with a disease at a certain point in time?
Annual mortality rate
(Total no. of deaths from all causes in 1 year divided by the # of persons in the population at mid-year) X 1,000
Case-fatality rate
# of individuals that died during a specified period of time after disease onset or diagnosis divided by the # of individuals with specified disease
Proportionate mortality
-No. of deaths from a disease divided by the total deaths
-Does not tell us that the risk of death form a disease is increasing
Years of potential life lost (YPLL)
Average life span in a population - Age of death
Disability adjusted life-years (DALYs)
-Takes into account years lost due to premature deaths as well as years lost due to disability
-Allows researchers/public health officials to compare across diseases
-Gives common units to living with a disease or deaths
Informational Bias
Results from systematic differences in the way data on exposure or outcome are obtained from various study groups (i.e. observer bias)
Recall Bias
May result in underestimate or overestimate of association
Selection bias
Results from an error in choosing the individuals or groups to take part in a scientific study
Confounding Variable
-Possibility that an observed association is due (partly, at least) to the effects of differences between study groups (other than exposure
1.The variable must be independently associated with the outcome (i.e. be a risk factor).
2.The variable must be associated with the exposure under study in the source population.
3.It should not lie on the causal pathway between exposure and disease
Case Series Study
-Certain characteristics of patients described in a report
-No statistical validity
-Useful to setup other studies
Case-Control (CC) Study
-Retrospective in nature
-Begin with outcome and try to look back for possible causes or risk factors
-Two groups: Cases (individuals affected by disease) and Controls (Individuals not affected by disease)
-Answers question: what happened?
Cross-Sectional Study
-Analyze data collected on a group of subjects at one time rather than a period of time
Answer question: what is happening right now?
-AKA prevalence studies
Cohort Studies
-Answers the question: what will happen?
-Follow subjects over a period of time
-Can be prospective or retrospective
Three ideal qualities of controls in CC study
-Comparability is more important than representativeness in the selection of controls
-The control must be at risk of getting the disease
-The control should resemble the case in all respects except for the presence of disease
Advantages of Case Control Studies
1. Only realistic study design for uncovering etiology in rare diseases
2. Important in understanding new diseases
3. Commonly used in outbreak investigation
4. Useful if induction period is long
5. Relatively inexpensive
Disadvantages of Case Control Studies
-Susceptible to bias if not carefully designed (and matched)
-Especially susceptible to exposure misclassification
-Especially susceptible to recall bias
-Restricted to single outcome
-Incidence rates not usually calculable
-Cannot assess effects of matching variables
Advantages of Cohort Studies
-Subjects in can be matched, which limits the influence of confounding variables
-Standardization of criteria/outcome is possible
-Easier and cheaper than a randomized controlled trial (RCT)
Disadvantages of Cohort Studies
-Matched groups can be difficult to identify due to confounding variables
-No randomization, which means that imbalances in patient characteristics could exist
-Blinding/masking is difficult
-Outcome of interest could take time to occur
Advantages of RCT
-Good randomization will "wash out" any population bias
-Easier to blind/mask than observational studies
-Results can be analyzed with well known statistical tools
-Populations of participating individuals are clearly identified
Disadvantages of RCT
-Expensive in terms of time and money
-Volunteer biases: the population that participates may not be representative of the whole
-Does not reveal causation
-Loss to follow-up attributed to treatment
Meta-Analysis
A subset of systematic reviews; a method for systematically combining pertinent qualitative and quantitative study data from several selected studies to develop a single conclusion that has greater statistical power. This conclusion is statistically stronger than the analysis of any single study, due to increased numbers of subjects, greater diversity among subjects, or accumulated effects and results
Advantages of Meta-Analysis
-Greater statistical power
-Confirmatory data analysis
-Greater ability to extrapolate to general population affected
-Considered an evidence-based resource
Disadvantages of Meta-Analysis
-Difficult and time consuming to identify appropriate studies
-Not all studies provide adequate data for inclusion and analysis
-Requires advanced statistical techniques
-Heterogeneity of study populations
Systematic Review
Similar to meta-analysis but does not involve statistical analysis
Main Source of Bias in Meta and Systematic Analysis
Publication bias:
-Positive results have a better chance at getting published
-Bias on part of sponsor organization
-Bias on part of editors
Sensitivity
Ability of the test to identify correctly those who have the disease
=True Positives/(True Positives + False Negatives)
Specificity
Ability of the test to identify correctly those who do not have the disease
=True Negatives/(True Negatives + False Positives)
Positive Predictive Value
Answers question: If a person tests positive, what is the probability that this person has the disease?
= True Positives/(True Positives + False Positives)
Negative Predictive Value
Answers question: If a person tests negative, what is the probability that this person does not have the disease?
= True Negatives/ (True Negatives + False Negatives)
Test Validity
The ability of a test to distinguish between who has a disease and who does not
Sequential testing
-Use less expensive, less invasive, less uncomfortable test first and then call those who screened positive for another test
-Increased specificity
Simultaneous testing
-Multiple tests used at the same time. Individual is positive if one of the results comes back positive
-Increased sensitivity
Relative Risk (RR)
Answers question: What is the ratio of risk of disease in exposed individuals to the risk of disease in non-exposed individuals?
-Derived from cohort studies
= Risk in exposed/Risk in non-exposed or
=Incidence in exposed/Incidence in non-exposed
Odds Ratio
=Probability of event occurring/Probability of event not occurring
=Odds that a case was exposed/Odds that a control was exposed
Nominal Scale
Categorical, "In Name Only"
Ordinal Scale
-Rank Ordering of Observations
-More or less of something
-Does not tell degree to which observations differ-No information about distance in between pts.
Interval Scale
Tells us how much things differ
-Intervals represent equal quantities
-33 to 34 same difference as 7 to 8
-Can add and subtract
-Cannot multiply or divide
-lack true absolute zero
Ratio Scale
-Tells us how much things differ
-Intervals represent equal quantities
-Scale has real absolute zero
-Can add and subtract
-Can multiply and divide
Kurtosis
Peakedness" or "Flatness" of the Distribution
Leptokurtic
Very sharp peak with extreme concentration of scores around the middle of the distribution
Platykurtic
Flatter Distribution: scores still concentrated in the middle, but with more scores located at the end of the distribution
Poisson Distribution
Distribution of VERY rare outcomes Picture changes based on Probability of rare occurrence
68%
In a normal distribution, this percentage of values will lie within 1 stdev of the mean
95%
In a normal distribution, this percentage of values will lie within 2 stdev of the mean
99%
In a normal distribution, this percentage of values will lie within 3 stdev of the mean
Z-score
(X - Xbar)/standard deviation
Or Rule
The addition rule is also know as this
Multiplication rule
To find the probability of independent events, the and rule is used and is also this
Negatively Skewed
In __________ data, the Mean is lower than the Median and Mode
Positively Skewed
In __________ data, the Mean is greater than the Median and Mode
Simple T Test
When comparing a single mean to a population mean this test is used
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