Epidemiology Week 13 Flashcards
Necessary
Without the factor, disease never develops
Sufficient
In presence of the factor, disease always develops
Necessary & Sufficient
Disease always develops in presence of the factor, but never without it. Least likely; rarely if ever happens.
Necessary but not sufficient
The factor is necessary to cause the disease, but other factors are required as well. Disease will not always occur just because factor is present.
Sufficient but not necessary
The factor alone can produce the disease, but it is not the only thing that can cause it; other factors also can.
Neither necessary nor sufficient
No one factor working alone can cause disease, & many combinations possible. Most likely.
Guidelines for proof of casaul relationship
1) Temporal relationship
2) Strength of association
3) Dose-response relationship
4) Replication of the findings
5) Biologic plausibility
6) Consideration of alternate explanations
7) Cessation of exposure
8) Consistency with other knowledge
9) Specificity of the association
Temporal relationship
Factor occurred before the disease onset.
Easier to establish in prospective cohort than case-control or retrospective
Strength of association
Relative risk or odds ratio. The stronger, the more likely to be causal.
Dose-response relationship
As dose of exposure increases, so does risk of disease
Replication of findings
Consistent between subgroups, between studies, between populations
Biologic plausibility
Coherence with current body of biologic knowledge. Some examples where clinical findings have preceded biologic knowledge.
Consideration of alternate explanations
Potential confounders have been accounted for & ruled out
Cessation of exposure
Risk decreases as exposure decreases
Consistency with other knowledge
Findings consistent with other data (such as lung cancer rates & cigarette sales)
Specificity of the association
When one disease is associated with one factor. Weakest of all guidelines.
Selection bias
The way in which cases & controls are selected is not random
Exclusion bias
Results from applying different criteria to cases & controls in regard to inclusion in the study
Information bias
Way of gathering information among subjects is inadequate, so some of the information is incorrect
Misclassification bias
Some cases are classified as controls or vice versa
Differential misclassification
Rates of misclassification are different for control vs case groups
Non-differential misclassification
Results from data collection methods
Surveillance bias
Disease ascertainment better in the monitored population than in general population
Recall bias
Potential exposure recalled by cases, forgotten by controls
Wish bias
Under-reporting of exposures related to lifestyle, overemphasis of exposures related to work or environment
Confounder
In a study of whether factor A causes disease B, factor X is a confounder if
1) Factor X is a known risk factor for disease B
2) Factor X is associated with factor A, but is not a result of factor A
True or false: a confounder is an error in the study.
False. It is a valid finding that must be taken into account in the study of the disease.
Interaction
When the incidence rate in the presence of 2 factors differs from the incidence rate we would expect to find from their individual effects
