8 - Why evidence-based medicine?

Question 1

Criticism of Evidence based medicine

Answer 1

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

Question 2

Why EBM matters to Clinicians

Answer 2

BETTER SERVICE FOR PATIENTS (most important reason)
Patient Care
Medical Knowledge
Practice-Based Learning and Improvement 
Interpersonal and Communication skills 
Professionalism

Question 3

Association

Answer 3

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

Question 4

What should be considered when considering statistical association?

Answer 4

chance
bias
confounding
cause
N.B. MUST consider first three before you look at causal relationship!

Question 5

Chance

Answer 5

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

Question 6

Bias

Answer 6

A systematic error:
Selection bias
Measurement bias

Question 7

Confounding

Answer 7

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

Question 8

Causal Effect

Answer 8

Judgement of a cause-effect relationship
Judgement is based on a chain of logic that addresses two main areas:
Observed association between an exposure and a disease is valid
Totality of evidence taken from a number of sources supports a judgement of causality

Question 9

Factors to consider in Bradford-Hill Criteria for Causation

Answer 9

Strength
Consistency
Specificity
Temporal relationship
Dose-response relationship
Plausibility
Coherence
Experimental evidence
Analogy

Question 10

Strength

Answer 10

strength of an association is measured by the magnitude of the relative risk.
A strong association is more likely to be causal than is a weak association, which could more easily be
the result of confounding or bias.
However, a weak association does, nor rule out a causal connection.
e.g. passive smoking and lung cancer

Question 11

Consistency

Answer 11

If similar results have been found in different populations using different study designs then the association is more likely to be causal since it is unlikely that all studies were subject to the same type of errors. However, a lack of consistency does not exclude a causal association since different exposure levels and other conditions may reduce the impact of the causal factor in certain studies.

Question 12

Specificity

Answer 12

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. 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.

Question 13

Temporal relationship

Answer 13

This is an essential criterion. For a putative 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.

Question 14

Dose-response relationship

Answer 14

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.

Question 15

Plausibility

Answer 15

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

Question 16

Coherence

Answer 16

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.

Question 17

Experimental evidence

Answer 17

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.

Question 18

Analogy

Answer 18

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).