Establishing Causal Claims in Medicine

Figures & data

Figure 1. T cell effector mechanisms in a lung infected by influenza A virus (Gruta and Turner 2014).

Table 1. Examples of sources of evidence of mechanisms in medicine (Clarke et al. 2014).

Direct manipulation: e.g. in vitro experiments

Direct observation: e.g. biomedical imaging, autopsy

Clinical studies: e.g. RCTs, cohort studies, case control studies, case series

Confirmed theory: e.g. established immunological theory

Analogy: e.g. animal experiments

Simulation: e.g. agent-based models

Figure 2. Common cause C is a potential confounder.

Table 2. Possible explanations of an observed correlation between A and B.

Causation	A is a cause of B
Reverse causation	B is a cause of A
Confounding (selection bias)	There is some confounder C that has not been adequately controlled for by the study
Performance bias	Those in the A-group are identified and treated differently to those in the $\mathrm{\neg }A$-group
Detection bias	B is measured differently in the A-group in comparison to the $\mathrm{\neg }A$-group
Chance	Sheer coincidence, attributable to too small a sample
Fishing	Measuring so many outcomes that there is likely to be a chance correlation between A and some such B
Temporal trends	A and B both increase over time for independent reasons. E.g. prevalence of coeliac disease & spread of HIV
Semantic relationships	Overlapping meaning. E.g. phthiasis, consumption, scrofula (all of which refer to tuberculosis)
Constitutive relationships	One variable is a part or component of the other
Logical relationships	Measurable variables A and B are logically complex and logically overlapping. E.g. A is $C\wedge D$ and B is $D\vee E$
Physical laws	E.g. conservation of total energy can induce a correlation between two energy measurements
Mathematical relationships	E.g. mean and variance variables from the same distribution will often be correlated

Figure 3. SUNY Downstate Medical Center EBM Tutorial (SUNY 2004).

Figure 4. Oxford Centre for Evidence-Based Medicine 2011 Levels of Evidence (OCEBM Levels of Evidence Working Group 2011).

Figure 5. Treating evidence of mechanisms alongside evidence of correlation, as motivated by RWT.

Table

There are sufficiently many independent clinical studies

They are of sufficient quality

Sufficiently many studies point in the same direction

They observe a large enough correlation

Fishing, temporal trends and non-causal relationships are ruled out

No other evidence suggests a lack of a suitable mechanism

There must be some underlying mechanism that explains the correlation

Figure 6. Clinical studies can, in the right circumstances, establish a causal claim.

Figure 7. One way to establish a causal claim without RCTs.

Figure 8. The ECMO mechanism, as depicted by Bartlett et al. (1976).

Table

The mechanisms involved are established

Observational studies suggest a sufficiently large effect size

Sufficiently many studies point in the same direction

The mechanisms involved can clearly account for the effect size

Fishing, temporal trends and non-causal relationships are ruled out

No other evidence suggests a lack of a correlation

There is a genuine correlation

Figure 9. Evidence of a lack of mechanism can trump RCTs.

Table

The causal relationship holds in the source population

The source and target populations are similar in causally relevant respects

The causal relationship holds in the target population

Table

High quality CSs establish a causal relationship in the source population

Lower quality CSs in the target population are consistent with this relationship

The causal relationship holds in the target population

Figure 10. The logic of extrapolation as motivated by RWT.

Gruta, Nicole L. La, and Stephen J. Turner. 2014. “T Cell Mediated Immunity to Influenza: Mechanisms of Viral Control.” Trends in Immunology 35: 396–402. doi: 10.1016/j.it.2014.06.004

 PubMed Web of Science ®Google Scholar

Clarke, Brendan, Donald Gillies, Phyllis Illari, Federica Russo, and Jon Williamson. 2014. “Mechanisms and the Evidence Hierarchy.” Topoi 33: 339–360. doi: 10.1007/s11245-013-9220-9

 Web of Science ®Google Scholar

SUNY. 2004. “Suny Downstate Medical Center Evidence Based Medicine Tutorial.” The Medical Research Library of Brooklyn. http://library.downstate.edu/EBM2/contents.htm.

 Google Scholar

OCEBM Levels of Evidence Working Group. 2011. “The Oxford 2011 Levels of Evidence.” Oxford Centre for Evidence-Based Medicine, Oxford. http://www.cebm.net/index.aspx?o=5653.

 Google Scholar

Bartlett, R. H., A. B. Gazzaniga, M. R. Jefferies, R. F. Huxtable, N. J. Haiduc, and S. W. Fong. 1976. “Extracorporeal Membrane Oxygenation (ECMO) Cardiopulmonary Support in Infancy.” ASAIO Journal 22: 80–92.

 Google Scholar