Study Designs Flashcards
How to make a cohort study based on cross-sectional study
Exclude prevalent cases, implement follow-up. Hypothesis changes to: Is there a difference in disease incidence between exposed and non-exposed?
Measurements and interpretations for cohort studies
Risk Ratio: (2.78) The risk of outcome in the 2-year folllow up is 2-fold higher in exposure than unexposed;
Attributable Risk (22.61 cases per 1,000 population at risk): 22.61 cases per 1,000 at risk is due to their exposure, assuming there’s a causal relationship between exposure and outcome.
Incidence Rate (person-year)
2 types of exposure misclassification (measurement error) and their impacts
- Nondifferential: The degree of exposure misclassification is similar in cases and in controls. The bias is toward the null. Underestimate the association.
- Differential: the bias is away from the null. Overestimate the association.
Note: Whether bias results, and the direction of the bias, depends on the actual pattern of misclassification in cases and in controls. Need to examine the data!
In RTC, what will be considered as unplanned cross-over?
- Controls intentionally or unintentionally exposed to intervention
- Treatment group stop or refuse further intervention
In RTC, what is a commonly used strategy to allocate participants to study groups? Steps? (3)
Stratified Randomization (Blocking):
- Eligible & willing participants characterized (e.g., sex, age)
- Grouped into stratum of each characteristic
- THEN randomized to study group
T/F Randomization can affect statistical power.
False
The process of randomization does not affect power.
Special Groups controls ( Example, Pro 1, Con 1)
Example: Relatives, friends, co-worker
Pro: Likely high level of comparability; come from same residential area as cases; similar SES, lifestyles
Con: Not good for lifestyle exposures: similarities may result in small differences in proportion exposed in cases and controls
2 Major Assumptions in Life Table Survival Analysis
Censored are similar to those followed up
Stable Population Survivorship
Survival Curve (come from Kaplan-Meier Method)
RTC: Major Methodological Components (7)
- Selection of study sample
- Allocation to study groups
- Compliance
- Ascertainment of outcomes
- Monitoring adverse effects
- Stopping rules
- Measures of effect
Interpretation of Number needed to treat
To prevent one case of xxx during a period of xx years, xx persons would have to receive the intervention.
Population Surveillance
1) Systematic collection, recording, analysis, interpretation, and dissemination of data reflecting the current health status of a community or population;
2) Monitor changes in disease frequency and prevalence of risk factors within overall population or subgroups;
3) Fundamental role in disease prevention and control, health promotion, recommendations and policy
Measures in case-control studies
OR: AD/BC; proportion of exposed cases: A/A+C proportion of exposed controls: B/B+D
How to adjust for effects of other factors in prognosis
Use Multivariable regression model (Logistic; Possion)
Frequency matching definition
Controls selected to match proportion of cases with certain characteristic. More relaxed than individual matching.
Cross-sectional Studies cons
1) Prevalence only; 2)Temporality between exposure and disease; 3) Sicker cases of disease may have died (Survivor bias); 4) Severe exposures may be hospitalized (not counted)
Case-control study pro (4) and con (4)
pro:
- Efficient in regards to time, costs, effort
- Diseases with long latency
- Good for rare diseases
- Multiple exposures with single outcome
Con:
- Inefficient for rare exposures
- No direct measure of incidence
- Temporality may be hard to establish
- Particularly prone to selection bias and recall bias
Case-Control Null hypo
OR=1.0; The odds of exposure to […] are not different between cases and controls.
How to assess exposure (3) and their pro/con
- Pre-existing records
- Advantage: inexpensive, large samples
- Disadvantage: data quality (missing data; diagnostic criteria)
2. Interviews & Questionnaires
- Advantage: inexpensive, low burden, large samples
- Disadvantage: Response Bias (social desirability), transportability across population subgroups
3. Clinical examinations
- Advantage: accuracy & reliability; things that can’t be assessed by questionnaire (e.g., blood, ECG, fitness)
- Disadvantage: costs, burden, risks, standard interpretation
Corhort studies pro (6) and con (4)
Pro:
- Rare exposures
- Multiple exposures with multiple outcomes
- Minimizes bias in exposure assessment (prospective)
- Temporality between exposure and disease occurrence
- Direct measure of risk
- Nested studies
Con:
- Inefficient for rare disease;
- Feasibility issues: sample size, time, costs
- Data quality (retrospective)
- Loss to follow-up bias
Ecological Study [data, exposure, outcome, traits]
Data: Aggregated group data are the units of observation(no individual measures)
Exposure: Average exposure in group
Outcome: Average disease experience in group
Traits:
1) Cost- and time-efficient relative to a de novo study;
2) Preliminary evidence for confirmation by individual-level study;
3) Correlation between exposure and disease (by correlation coefficient. <0.3 week; 03-0.7 moderate; >0.7 strong)
RTC: Study population
- Sample of base population who meet eligibility, inclusion and exclusion criteria and are willing to participate in study protocol
- Large enough for sufficient number of events
- High likelihood of compliance & completion
Cross-sectional Studies: Research question
Is exposure status related to the presence of disease when measured at the same time point?
Ecological Study Shortcomings
Because Aggregate data are being analyzed: 1) Lack temporal information for associations; 2) Lack adjustment for differences in other characteristics (confounding); 3) Measurement differences (diagnosis, recording, treatment); 4) Composite ecological measures are less variable than individual measures, which could mask relationships
Difference between Observational and Experimental studies?
exposures not assigned/assigned by researcher
RTC: how to ascertain outcomes?
- Questionnaires, repeat clinic examinations, NDI
- Standardized case definition, and case verification
- Data gatherers blinded to study group status
3 types of information bias in exposure assessment
- recall bias - accuracy of recall differs between case and control;
- observation bias – data gathering differs between case and control;
- social desirability bias – under/over report behaviors
National Health Objectives two Overreaching goals:
- Increase quality and years of healthy life; 2. Eliminate health disparities
Effective surveillance requires
reliable flow of information
Major bias in cohort study (6)
- Losses to Follow-up (the major bias)
- Non-response (non-participation) bias
- Selection bias (less concerning as Exposure assessment precedes occurrence of Outcome; mostly threatens external validity)
- Exposure misclassification
- Outcomes ascertainment bias (blinding of gatherers)
- Outcomes misclassification
Control selection issues (2)
- selection must be independent of exposure 2. Four Sources of Controls each have their pro and con (Hospital-based; Community-based; Neighborhood; Special Groups)
Cohort study: design layout
- define base population
- select study sample and exclude prevalent cases
- assess exposures
- follow-up to ascertain disease cases
How to assess exposure in case-control studies?
- Use Questionnaire, interview, medical records, proxy 2. Exposure assessment should be comparable for cases and controls (method, place, and circumstances) 3. Data gatherers blinded to case-control status
Analytic studies
determinants of disease distribution and whether exposures are causally associated with disease
RTC: allocation to study groups (After? Pro? How?)
After:
- Determining eligible & willing; consented
- Baseline assessments (prognostic profile at entry)
Pro:
- Characteristic that makes experimental designs useful.
- Maximize comparability between intervention & control groups.
- Balance distribution of extraneous factors (confounders), measured and unmeasured, that could affect intervention.
How to randomization to study groups
- Each individual has same chance of group assignment.
- Random numbers table; draw from hat; computer program
Broad categories for RTC and their definition (maybe will have matching questions)
- Primary prevention: Examine whether an intervention reduces the risk of first disease occurrence. Study sample often has increased risk of outcome (elevated risk factors; preclinical disease) .
- Secondary prevention: Examine whether an intervention reduces symptoms, risk of recurrence or death in those with existing disease (prognostic trials).
- Efficacy trial: Examine the extent to which an intervention produces benefit under ideal circumstances.
- Effectiveness trial: Examine if the benefit of intervention is obtained by reasonable percentage of participants in a more pragmatic setting?
What factors can influence prognosis (4)?
- type and stage of disease
- timing of diagnosis or intervention
- initial health status
- age, sex, etc
Matching (Advantages 2; Types 2)
Pro: Enhances study efficiency ; Can provide control for confounding. Types: Individual matching; Frequency (“group”) matching
2 Methods of Population Surveillance
Passive and Active surveillance
Cross-sectional Studies pros
1) Feasible (sample size, time, costs);
2) Multiple exposures and multiple outcomes;
3) Surveillance of exposure and outcome distributions(monitor person, place, time trends)
4) Hypothesis generation for etiologic studies
5) Potential for Prospective cohort (if exclude prevalent cases and implement follow-up)
Median Survival Time (measure prognosis)
- Survival time for half of the study population
- Less affected than mean by skewed survival distribution (e.g., extreme low or high survival)
- Only need deaths on half study sample
- Relatively broad view of survival differences between groups
Hospital-based controls ( Con 4)
Con: 1. Difficult to define source population of hospital cases; 2. By definition are ill; thus, differ from base population in ways that could affect exposure prevalence; 3. Factors that influence hospital selection may be DIFFERENT than for cases 4. Exposures (esp. lifestyle factors) may be related to the disease requiring hospital visit