Epidemiology and Biostats Pt. 2 Flashcards
cohort study
-examines specific sub-populations (ie. age group) as they change over time and sees if they develop different outcomes
-pros: temporal relationship between exposure and disease easily established, possible to study associations of an exposure with several diseases, allows for direct measurement of incidence of disease in exposed and non-exposed groups, well suited for assessing the effects of rare exposures
-cons: expensive, need large amounts of subjects, selection of non-exposed cohort group difficult, can have loss to follow-up, not good for evaluating rare diseases
prospective cohort study
a select cohort group that is selected and does NOT have disease and is then tracked over time
Pros: can control data collection, good estimations of risks for group studied. Effective for common diseases. Provides strongest evidence for causation
Cons: time intensive, costly, can only evaluate what was identified as data at start of study
retrospective cohort study
Has a group of individuals with disease and goes back in time to evaluate risk factors (ie. church picnic scenario)
Pros: fast, cheap, good for rare diseases
Cons: data collection not controlled, documentation of risk factors questionable. Info may be biased or not available. Only gives relative risks.
Cross-sectional study
observational studies that analyze data from a population at a single point in time
-measures prevalence
-both disease and risk evaluated at the same time
PROS: quick, cheap, efficient, may be first step in assessing an association
CONS: does not give causal information, only correlation. Can’t determine temporal relationship. Data reflects determinants of survival as well as etiology
Case control study
case group and control groups are chosen based on outcome (those having the disease vs. those without the disease) then groups are compared as to frequency exposure to past risk (ie those with or without lung cancer and those who had or had not smoked)
PROS: quick, cheap, good for rare diseases, many risk factors can be evaluated
CONS: recall and selection bias can occur, inefficient for evaluating rare exposures, difficult to establish a temporal relationship between exposure and disease, can’t compute incident rates of disease in exposed and non-exposed groups
randomized controlled clinical trial
assigns subjects to groups randomly, one group gets treatment and one does not.
Pros: best test to study interventions such as drugs
best is when double blinded
Randomized controlled field trial
similar to randomized controlled clinical trial except the intervention is a preventative rather than a treatment. Used to evaluate effectiveness of vaccines.
Null hypothesis
the first step in testing for statistical significance in which it is assumed that the exposure is not related to the disease
Variance =
P (1-P) / N
P = Prevalence
Sensitivity
the ability of a test to detect a disease when it is present
-high sensitivity will have more false positives because its goal is to detect as many positives as possible, even if it has to reduce the threshold to capture them all
-usually screening tests have high sensitivity
= a/(a+c)
= TP/(TP + FN)
confirmatory tests usually have higher _____ so all negatives are identified as true negatives
specificity
specificity =
= d/(b+d)
= TN/(TN+FP)
the ability of a test to identify individuals who do NOT have disease
-a test with high specificity is good at detecting true negatives and will have few false positives
Prevalence =
(a+c)/(a+b+c+d)
positive predictive value
the proportion of patients who test positive and actually have the disease
= a/(a+b)
= TP/(TP+FP)
-the value depends on the prevalence of disease, therefore they cannot be estimated in case control designs
negative predictive value
proportion of patients who test negative and do not have the disease
= d/(c+d)
sequence of causal reasoning
must ascertain whether the independent variable (exposure factor) is statistically associated with the dependent variable (outcome)
Analysis of Variance (ANOVA)
used to determine statistical significance for multivariate analysis where there is a range of values with infinite values such as weights, temperatures
Chi square test
A test to determine statistical significance. It determines whether or not the results of an experiment may arise by chance or not
-used for BIVARIATE analysis (ie. male vs female, marital status)
-tests the independence of variables in a 2x2 table
Herd immunity
decreases probability that a group will develop an epidemic b/c the proportion of immune individuals reduces the chance of contact between infected and susceptible animals
study power
the probability of finding a real effect that is clinically important
-increased by increasing sample size
significance level
probability of a type I error, alpha (false positive)
alpha indicates the probability of rejecting the statistical hypothesis tested when its true
incidence density
of new cases over the total person time of observation. How frequently new cases of the condition develop in previously disease free people, in which the sum of the denominator consists of the sum of different times each person was at risk
= # of new cases/total person-time
cumulative incidence
of new cases over the mid year population (at risk). The proportion of a fixed population that becomes diseased within the stated time period.
= (a/a+b)/(c/c+d)
Epidemilogy
the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems; the study of the dynamics of health and disease determinants in a population with the goal of prevention
Hierarchy of evidence
opinions < quantitative descriptive or qualitative study < systematic reviews of descriptive or qualitative studies < case-control, cohort or cross-sectional study < well-designed controlled trial without randomization < well-designed RCT < systematic review or meta-analysis of all relevant RCTs, evidence-based CPGs based on systematic reviews of RCTs
natural history of disease process (in the absence of treatment)
1) stage of susceptibility (exposure occurs)
3) stage of subclinical disease (pathologic changes occurring)
4) stage of clinical disease (onset of symptoms, diagnosis made after)
5) stage of recovery-disability or death
incubation vs. latency period
incubation period: time from exposure to onset of disease symptoms for infectious diseases
latency period: time from exposure to onset of disease symptoms for chronic diseases
spectrum of disease
the range of symptoms caused by an illness ranging from mild to severe or fatal
infectivity vs. pathogenicity
infectivity: proportion of exposed persons who become infected
pathogenicity: proportion of infected individuals who develop clinically apparent disease
persons who are infectious but have subclinical disease
carriers
the chain of infection
