Dave Grimmond thinks a medical researcher's warning highlights a similar problem in economics; how to avoid the problem of self-selection. Your view?

By Dave Grimmond*

It was with concern that I read a recent news article about the dangers of non-steroidal anti-inflammatory drugs (NSAID), in which a medical researcher is quoted as stating

"If you look at it internationally, diclofenac is the single most widely used NSAID,"

and that

"Clearly thousands of people die as a result of using [diclofenac]".

What the study reportedly found was that use of NSAIDs increased risks of heart attacks and strokes, and that diclofenac (also sold in New Zealand under the brand name of Voltarin) was identified as one of the higher risk NSAIDs. 

Now as an active, but ageing, cyclist and footballer I have often made use of diclofenac to nurse various soft-tissue joint injuries over the years, and so this news caused me some alarm that this use of medication might be imposing some unintended health risks for me.

However on a little reflection about the statistical issues underpinning the analysis I am instead beginning to have doubts about the strength of the conclusions and the authors recommendation that diclofenac should be banned.

The first thing that nagged at me is the growing evidence that inflammation of the arteries is being observed as being associated with the onset of heart attacks and strokes. This would suggest that the use of anti-inflammatory drugs should be associated with a reduction in the risk of cardiac events, not an increase. 

The next thing is that it is very difficult in fields like medicine and economics to isolate the true transmission path between cause and effect.

This is because it can be unethical to undertake fully controlled experiments and even when this can be done the complexities of human bodies (or economies) can mask the true transmission paths. A result of these analytical limitations is that while many studies can identify correlations between different observations, it is a far more difficult task to attribute causation.

Thus although the use of anti-inflammatory drugs may be associated with more cardiac events, this does not mean that the drugs cause the cardiac events. This is just the same as saying that as patients in hospitals have a higher probability of dying than people in their homes, then this means that hospitals cause people to die. Such an inference is of course nonsensical.

Thus returning to anti-inflammatory drugs, by definition people taking these drugs have a high probability of suffering from inflammation. Could these episodes of inflammation perhaps also heighten their risks of experiencing a cardiac event? If this is the case one might well observe a heightened correlation between people using anti-inflammatory drugs and cardiac events, yet there may be no causal relationship between the drug use and the cardiac event. Indeed it might even be the case that the use of the drugs might actually reduce the risk of cardiac events. Again this is analogous to patients in hospitals. By being a patient one potentially has an inherent heightened risk of dying, however the care one receives at the hospital will actually reduce this risk.

In economics we refer to situations like these described as “self-selection”.

At risk people are self-selecting their use of a drug or their visit to the hospital precisely because of their awareness of their heightened risk. The drug use or hospital visit is thus a proxy for this heightened risk and should not be confused with being a cause for the problem. 

Now it may be the case that the intervention exacerbates the risk, say by taking an inappropriate drug, but establishing that this is the case is usually a very onerous task and one that is unlikely to be achieved by a meta-analysis like the one underpinning the quoted news article.

This does not mean that the research undertaken is not useful, but rather that one should be circumspect with the conclusions drawn and with any resulting policy recommendations that you make.

In calling for a ban on specific types of drugs the authors here appear to have over played their hand.

The next step should be further investigation about the inter-linkage between inflammation, anti-inflammatory drug use and cardiac events.

It could be that these drugs are indeed responsible for heightened risk, but it is also possible that they mitigate inherent risk. In which case the banning of these drugs would have the perverse effect of both reducing consumer choice for anti-inflammatory drugs and increasing people’s risk of experiencing a life threatening cardiac event.

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By Dave Grimmond a director and senior economist at Infometrics, an economic consultancy and forecasting service. You can contact him here »