Feldmand. Module 3 Study design Flashcards
Experimental Studies
Non-observational or experimental studies are intervention studies and the basic principle is that the design of the study involves deliberately changing population parameters and assessing the effect.
• Laboratory experiments
– Researcher designs and implements study
• Clinical / Field trials
– Therapeutics
– Vaccine efficacy
– Health promotion programs
• Community intervention trials – Insecticide impregnated bednets
Observational Studies: Differences between descriptive and analytic
• Descriptive
– Estimate disease frequency or time trend
– Used to generate hypotheses
– No comparisons or statistical analyses
– Correlational studies, case reports and series
• Analytic
– Identify risk factors for disease
– Estimate and quantify effect
– Suggest possible interventions
Types of Analytic Observational Studies
Most common designs you’ll encounter in observational epidemiology (1 -3)
1 • Case-control: Retrospective or prospective – Selection based on case status
2 • Cohort: Retrospective or prospective – Selection based on exposure
3 • Cross-sectional - snapshot
4 • Ecologic – individual level data missing
Case-control Studies
- Study participants selected based on disease status: Exposure status in diseased individuals (cases) is compared to exposure status in well individuals (controls)
- Most commonly conducted observational analytic epidemiologic study
When should we do a case-control study?
- Can be a useful 1st step to evaluate relationship between an exposure and disease
- When the disease is rare
- When efficiency is needed (i.e., there isn’t time to do a cohort study)
Selection of Participants in case study
• Cases: Many sources, including: – Hospital patients – Clinical practice – Diagnostic labs – Disease registries
• Controls: The comparability of cases and controls is essential
– Controls should be chosen from population which gives rise to cases
– Can be very tricky!
Control Selection - Matching (case study)
- Select controls so they are “matched” to cases on certain characteristics, such as age, race, sex, socioeconomic status and occupation
- Done to adjust for the effect of the “matched” variable
- Frequency matching (aka group matching): select controls so proportion of controls with a certain characteristic is identical to proportion of cases with same characteristic. E.g., If cases are 25% male, make control population 25% male
- Individual matching (aka pairwise matching): select a control for each case, so that case and control are similar with respect to variable(s) of concern. E.g., Match 25 y.o. female case with 25 y.o. female control. Pairwise matching requires a matched analysis
- Potential limitation is that you can no longer assess the effect of the matched variable because cases and controls are deliberately manipulated so there is no difference between the two groups
Case-control Studies - Analysis
- Because the participants are selected based on disease status, there is no denominator population with which we can calculate risk
- We estimate risk by comparing the odds of exposure among the diseased to the odds of exposure among the well
Odds ratio = ad / bc
Remember that the reduced formula for the OR ad/bc is the CROSS-PRODUCT ratio in a 2-by-2 table
Case-control Studies - Bias
• Case-control studies are particularly prone to bias
– Selection bias: A problem with who gets into your study. Can happen when inclusion of cases or controls somehow depends on exposure of interest
– Recall bias and limitations of recall: When cases and controls recall their experiences differently • It may be difficult to remember things that happened in the past or the information might not exist
Case-control Studies – Strengths and Limitations
• Strengths
– Relatively quick and inexpensive
– Particularly well-suited to diseases with long latent periods
– Optimal for evaluating rare diseases
– Can examine multiple etiologic factors for a single disease
• Limitations
– Inefficient for evaluating rare exposures
– Cannot directly compute incidence rates of disease in exposed and nonexposed individuals, unless study is population based
– May be difficult to establish a temporal relationship between exposure and disease
– Is particularly prone to bias, in particular selection and recall bias
Cohort Studies
- Study participants selected based on exposure status: Risk of disease in exposed individuals is compared to risk of disease in unexposed individuals
- Often conducted after hypothesis has been explored in case-control study
Cohort Studies – Selection of Study Population
Select groups on the basis of whether or not they were exposed: – E.g., To assess effects of an occupational exposure such as a solvent, the exposed group is the group that works with the solvent and the unexposed group might be office staff at the parent company
OR
Select a defined population before any of the members become exposed or before the exposures are identified:
– Selection could be made on basis of some factor not related to exposure, such as community of residence
– Take histories of, or perform blood tests or other assays on, the entire population
– Using the results of the histories or the tests, the population can be separated into exposed and nonexposed groups
Retrospective vs. Prospective Cohort Studies
• Cohort studies may be prospective or retrospective, depending on temporal relationship between initiation of study and disease occurrence
• Retrospective cohort
– All relevant events (exposures and outcomes of interest) have occurred when the study is initiated
• Prospective cohort (aka concurrent cohort or longitudinal studies)
– Relevant exposure may or may not have occurred when study initiated but the outcomes have definitely not yet occurred
– The cohort must be followed into the future
Cohort Studies - Analysis of RR
• If a positive association exists between exposure and disease, then the proportion of the exposed group that develops disease (risk in the exposed group) is greater that the proportion of the nonexposed group in which disease develops
Riskexposed > Riskunexposed
RR > 1
Cohort Studies - Bias
- Bias in assessment of the outcome: The person who determines the disease status of each subject may be biased by knowing the study hypothesis and the exposure status of each subject
- Information bias: If the quality and extent of information obtained is different for exposed and nonexposed subjects, bias can be introduced
- Bias from nonparticipation: Generally, only a proportion of those who are eligible to participate actually do so. How do those who do not participate differ from those who participate?
- Bias from loss to follow-up: The incidence rates (risk) for exposed and nonexposed groups may be difficult to calculate
