Global Patterns of Disease I - Hierarchy of evidence, association vs causation, confounding Flashcards Preview

Epidemiology > Global Patterns of Disease I - Hierarchy of evidence, association vs causation, confounding > Flashcards

Flashcards in Global Patterns of Disease I - Hierarchy of evidence, association vs causation, confounding Deck (18):

Hierarchy of studies (from highest to lowest)

1. Systematic reviews and meta-analysis
2. Randomised controlled study
3. Cohort studies
4. Case-control studies
5. Ecological studies
6. Descriptive/cross-sectional studies
7. Case report/studies


Why EBM matters to clinicians

- Patient Care
- Medical Knowledge
- Practice-Based Learning and Improvement
- Interpersonal and Communication skills
- Professionalism

Evidence based medicine does NOT replace clinical decision making but is only a tool. ​


Criticism of EBM

- It is impossible for any clinician to have the time to critically appraise even one article per week let alone the number that would need to be appraised to answer questions (estimated at 3.5 per clinical session) arising in a busy practice.

- Governments, healthcare commissioners and providers have used the jargon of EBM to justify decisions, directives, or incentives that are seen by clinicians as inappropriate


Association definition

Association refers to the statistical dependence between two variables, that is the degree to which the rate of disease in persons with a specific exposure is either higher or lower than the rate of disease without that exposure.
A link, relationship or correlation


Things to think of when evaluating statistical association

Consider chance, bias, confounding, cause


Check for chance and avoid it

Make inference from samples rather than whole populations
- Sample size
- Power calculations
- P values and statistical significance



A systematic error
- Selection bias
- Measurement bias

Also, recall bias



Mixing of effects between exposure, the disease and a third factor. Account for confounding using matching, randomisation, stratification and multivariate analysis.


Factors considered for an association to be causal (Bradford Hill 1965)

1. Strength
2. Consistency
3. Specificity
4. Temporal relationship - ESSENTIAL
5. Dose-response relationship
6. Plausibility
7. Coherence
8. Experimental evidence
9. Analogy


Strength (Bradford Hill 1965)

Measured by the magnitude of relative risk. A strong association is more likely to be causal than a weak association. The weaker association could be more likely due to confounding or bias. A weak bias, however, does not rule out a causal relationship - e.g. passive smoking and lung cancer.


Consistency (Bradford Hill 1965)

If different types of studies (study designs) on different populations came to the same results - it is more likely to be a causal relationship, as it is unlikely that the different studies were subject to the same errors. A lack of consistency, however, does not rule out causal relationship, since different exposure levels and other conditions may reduce the impact of the causal factor in certain studies.


Specificity (Bradford Hill 1965)

If a particular exposure increases the risk of a certain disease but not the risk of other diseases then this is strong evidence in favour of a cause-effect relationship e.g. Mesothelioma (cancer of the mesothelial tissue on exposure to asbestos). However, one-to-one relationships between exposure and disease are rare and lack of specificity should not be used to refute a causal relationship; for example cigarette smoking causes many diseases.


Temporal relationship (Bradford Hill 1965)

For a risk factor to be the cause of a disease, it has to precede the disease.
This is generally easier to establish from cohort studies but rather difficult to establish from cross-sectional or case-control studies when measurements of the possible cause and the effect are made at the same time. However, it does not follow that a reverse time order is evidence against the hypothesis.


Dose-response relationship (Bradford Hill 1965)

Further evidence of a causal relationship is provided if increasing levels of exposure lead to increasing risks of disease. Some causal associations, however, show a single jump (threshold) rather than a monotonic trend.


Plausibility (Bradford Hill 1965)

The association is more likely to be causal if consistent with other knowledge (e.g. animal experiments, biological mechanisms, etc.). However, this criterion should not be taken too seriously because lack of plausibility may simply reflect lack of scientific knowledge. The idea of microscopic animals or animalcules as cause of disease was distinctly implausible before Van Leeuwenhoek’s microscope


Coherence (Bradford Hill 1965)

Coherence implies that a cause and effect interpretation does not conflict with what is known of the natural history. However absence of coherent information as distinguished from the presence of conflicting information, should not be taken as evidence against an association being causal.


Experimental evidence (Bradford Hill 1965)

Experimental evidence on humans or animals. Evidence from human experiments is seldom available and animal research relates to different species and different levels of exposure.


Analogy (Bradford Hill 1965)

At best analogy provides a source of more elaborate hypotheses about the association in question. Absence of such analogies only reflects lack of imagination or experience, not falsity of the hypothesis (Bradford Hill 1965).