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Design Strategies and Statistical Methods in Analytic Epidemiology
Chapter 7 Design Strategies and Statistical Methods in Analytic Epidemiology
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Meningitis Outbreak Update: List Of Hospitals Released by Richard Knox, NPR news
The government has named 75 medical facilities that received a potentially contaminated drug suspected of infecting 91 patients with meningitis nationwide. The hospitals and clinics that have used the possibly tainted steroid are in 23 states, from New Hampshire to California and Idaho to Florida. The number of meningitis cases went up by 12 on Friday, the number of deaths now at seven. The CDC says all 42 known survivors are still hospitalized, and officials expect more cases to emerge over the coming weeks.
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Fungal meningitis: What is it?
Fungal meningitis is rare and usually the result of spread of a fungus through blood to the spinal cord. People with weak immune systems, like those with AIDS or cancer, are at higher risk. Pathogen: Aspergillus, Exserohilum meningitis Sx: Fever, headache, stiff neck, nausea and vomiting, photophobia, altered mental status Dx: lumbar puncture with testing of cerebrospinal fluid Tx: long course of antifungal drugs, hospitalization, IVs
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Analytic epidemiology
© 2010 Jones and Bartlett Publishers, LLC Analytic epidemiology An analytic study attempts to answer why and how a health-related state or event occurred Tests specific a priori hypotheses Uses a comparison group
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Analytic observational studies
© 2010 Jones and Bartlett Publishers, LLC Analytic observational studies Case-control studies Cohort (prospective and retrospective) studies
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I. Case-control study: The outcome is always identified prior to the exposure
Identify cases (persons experiencing a health- related state or event) Identify controls (similar except not cases) Investigate whether the cases are more or less likely than controls to have had similar past experiences, lifestyle behaviors, or exposures
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In our meningitis outbreak:
The first known case in the meningitis outbreak was diagnosed about two weeks ago in Tennessee In all, 47 people have contracted fungal meningitis (CDC) Michigan became the seventh state to report cases, with four. Tennessee's cases now total 29; Virginia, six; Indiana, 3; two each in Maryland and Florida and one in North Carolina. Three people have died in Tennessee; one death in Virginia and Maryland. All had received a steroid injection in the spine between July 1 and September 28 this year.
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Case-control study: Selection of cases
First, must define the disease Next, establish the diagnostic criteria So, in this particular outbreak: Pathogen(s): Aspergillus, Exserohilum meningitis Dx: lumbar puncture, testing of cerebrospinal fluid
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Selection of cases May consist of new cases (incidence) that show selected characteristics during a specific time period in a specified population and a particular area. Cases may also consist of existing cases at a point in time (prevalence). .
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Sources of cases Cases come from
Records from public health clinics Physician offices Health maintenance organizations Hospitals Industrial and government sources Cases should be representative of all persons with the disease
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Selection of controls Control subjects should look like the case subjects with the exception of not having the disease An epidemiologic assumption is that controls are representative of the general population in terms of probability of exposure and that controls have the same possibility of being selected or exposed as the cases
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Measuring the association between exposure and outcome variables
The appropriate measure of association to use depends on the nature of the data When exposure and outcome variables are dichotomous (two level nominal data) Odds ratio – use with case-control study Risk ratio – use with cohort study
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OR = Case Control Studies Odds for exposure among cases
Typically, compare the proportions of exposure by means of a ratio: ODDS RATIO (relative odds) OR = Odds for exposure among cases Odds for exposure among controls d c E- b a E+ D- D+ (a / c) OR = (b / d)
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Odds Ratio Can have a value of zero to infinity
© 2010 Jones and Bartlett Publishers, LLC Odds Ratio Can have a value of zero to infinity If the OR = 1, no association between exposure and the disease If the OR > 1, this indicates a positive relationship between the exposure and disease If the OR < 1, this indicates a negative relationship between the exposure and the disease
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OR = Case Control Studies (8/2) OR = -------
Typically, compare the proportions of exposure by means of a ratio: ODDS RATIO (relative odds) OR = Odds for exposure among meningitis cases Odds for exposure among healthy patients 8 2 E- E+ D- D+ (8/2) OR = (2/8)
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Odds Ratio Can have a value of zero to infinity
© 2010 Jones and Bartlett Publishers, LLC Odds Ratio Can have a value of zero to infinity If the OR = 1, no association between exposure and the disease If the OR > 1, this indicates a positive relationship between the exposure and disease If the OR < 1, this indicates a negative relationship between the exposure and the disease
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In our meningitis epidemic:
Each one of the infected patients had been injected with a preservative-free steroid called methylprednisolone acetate manufactured by New England Compounding Center (NECC) in Framingham Massachusetts The government has named 75 medical facilities that received a potentially contaminated drug Close to 18,000 doses of the drug, methylprednisolone acetate, have been recalled by the Massachusetts pharmacy
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Bias Systematic error in the collection or interpretation of epidemiologic data Results in inaccurate (over or under) estimation of the association between exposure and disease Avoiding bias at the design stage of a study is paramount because of the difficulty to identify and account for it thereafter
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Types of bias in case-control studies
© 2010 Jones and Bartlett Publishers, LLC Types of bias in case-control studies Selection Observation Recall Interviewer
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Confounding Occurs when an extrinsic factor is associated with a disease outcome and, independent of that association is also associated with the exposure Exposure Outcome Confounder
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Confounding Coffee Heart Disease Smoking
© 2010 Jones and Bartlett Publishers, LLC Confounding Coffee Heart Disease Smoking
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Selected strengths and weaknesses of case-control studies
© 2010 Jones and Bartlett Publishers, LLC Selected strengths and weaknesses of case-control studies Strengths Weaknesses Useful for studying rare outcomes Short duration Relatively inexpensive Relatively small Yields odds ratio (usually a good approximation of relative risk) Does not establish sequence of events Potential bias in measuring exposure variables Limited to a single outcome variable Does not yield prevalence, incidence or excess risk Prone to selection and observation bias
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II.Cohort studies Cohorts of persons placed in a group can be studied as a group, forward in time (prospectively) or backward in time (retrospectively)
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I. Cohort Studies: Cohort studies come in two types:
prospective and retrospective. Studies in which the exposure and outcome have already occurred are termed retrospective Studies in which the outcome has yet to occur are called prospective.
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The term “cohort” is derived from the fact that, in these studies, one begins with the “exposure” by choosing a cohort of people with an exposure and comparing the number of new cases of disease in this group with the number of new cases in a cohort of non-exposed people
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Cohort effect Also called generation effect
© 2010 Jones and Bartlett Publishers, LLC Cohort effect Also called generation effect Is the change and variation in the disease or health status of a study population as the study group moves through time Cohort effects include any exposure or influence from environmental effects to societal changes
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Measures of association in cohort studies
© 2010 Jones and Bartlett Publishers, LLC Measures of association in cohort studies Ratio of attack rates Risk ratio Ratio of person-time rates Rate ratio
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Risk ratio (relative risk)
It is defined as the incidence of disease in the exposed divided by the incidence in the non- exposed. Incidence in the exposed Relative Risk = Incidence in the non-exposed 28
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Hypothesis: Depression is associated with risk of hip fracture (cohort study)
40 180 220 E- 30 215 245 70 395 465 RR = (40 / 220) / (30 / 245) RR = 1.48 •Depressed persons appear to be at 1.48 times higher risk of hip fracture than non-depressed persons. However, is this elevated risk similar among persons with low and high body mass index (BMI)? Modification effect 29 29 29 29
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LOW BMI HIGH BMI D+ D- E+ 6 50 56 E- 144 150 12 194 206 D+ D- E+ 34
130 164 E- 24 71 95 58 201 259 RR = (6 / 56) / (6 / 150) RR = / = 2.68 RR = (34 / 164) / (24 / 95) RR = / = 0.82 30 30 30 30
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Attributable Risk If relative risk measures the strength of an association, then attributable risk measures the actual amount of illness or disease we can ascribe to a given exposure, i.e. the amount of disease attributable to the exposure. Attributable risk is defined as : AR = Incidence in the exposed (E+) - Incidence in the non-exposed (E-) 31
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OA + or OA -. Heights and weights were also measured.
Researchers, wanting to study the relationship between obesity and osteoarthritis (OA) of the knees, recruited 20,000 women to participate in a 15-year follow-up study. Subjects were screened at the beginning of the study for any evidence of existing OA of the knees as well as for obesity. Women with pre-existing OA were eliminated from the study. The subjects were subsequently examined annually for evidence of OA and classified as either OA + or OA -. Heights and weights were also measured. At the conclusion of the study, 240 of the 8,000 women who were classified as obese had been diagnosed as having OA , while 130 of the normal weight (12.000) women showed evidence of OA of the knees. 32
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Example: From the OA scenario, the attributable risk of developing OA if one were obese can be defined as: or .02 (or 20 per 1,000 per 15 years) Interpretation: Approximately 20 cases of OA per 1,000 people exposed (obese) are the result of obesity 33
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Selecting the study cohort
© 2010 Jones and Bartlett Publishers, LLC Selecting the study cohort From population choose those at risk of becoming a case Exclude Individuals who already have a disease outcome of interest Those not at risk (e.g., they have had an organ removed such that they cannot become a case)
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Bias in cohort studies Selection bias Healthy worker effect
© 2010 Jones and Bartlett Publishers, LLC Bias in cohort studies Selection bias Healthy worker effect Loss to follow-up
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Healthy worker effect Occurs in cohort studies when workers represent the exposed group and a sample from the general population represents the unexposed group This is because workers tend to be healthier, on average, than the general population
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Loss to follow-up A circumstance where researchers lose contact with study participants, resulting in unavailable outcome data on those people A common problem in cohort studies, increasingly so in cohorts with longer follow-up times Reasons Refusal to participate Unable to locate Unable to be interviewed Death
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Misclassification Also may result in cohort studies
© 2010 Jones and Bartlett Publishers, LLC Misclassification Also may result in cohort studies Differential (non-random) Non-differential (random)
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Misclassification Differential misclassification arises if exposure classification influences differential accuracy in ascertaining outcome information (Ex. Association between hypertension and stroke) Non-differential misclassification may arise by inaccuracies in classifying exposure status of individuals, but these misclassifications occur similarly between exposed and unexposed groups
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