Simulation in medical research

I have come across an interesting article by Mancini et al. (2012), of the University of Amsterdam, in which the authors use simulations instead of clinical trials in order to estimate the effects of (non-)usage of a specific drug.

The use of statistics in medicine is one of my main areas of interest, and something I will try to cover quite a lot on this blog.

Generally, to examine whether a drug or treatment has an effect, medical researchers perform clinical trials in which patients with similar characteristics are split into groups. One group will receive the treatment and one group will not (this last group is often again divided in two, one part which gets a placebo-treatment, and one part which gets no, or traditional, treatment). If statistically significant differences in outcome between the sub-groups are found, the drug or treatment is said to have an effect, and will be launched to the market or studied further.

As can be understood, such an approach takes a lot of time and resources, and there are also ethical difficulties with giving some patients one treatment and other patients another. This is why it is so interesting to find a simulation study used in medicine (this might be commonly applied, but I have not seen it before now). As the authors of the study write:

“Performing this test in silico [simulations, Hedg.] allows us to use the same
virtual patients for each group, whereas in clinical trials the control
groups consist of different individuals. Such choice enables us to
directly relate the survival of rates of each group to the effect of the
different therapies.”

Using this approach, the authors simulate the effect of differences in drug dosage on HIV-patients, something which would be both dangerous and unethical to do on real patients. Their simulations show that if a treatment with pauses in the use of drugs, will be conducted, the optimal plan of dosage is two weeks with drugs and one week without.

Using mathematical and statistical tools (of which simulations is only one example) to describe and model biological processes is increasingly popular, but can at the same time be very challenging, all the time both body and nature are dynamic systems. However, this is also perhaps the area where these methods have the most to offer in terms of human benefits, and I am hoping that it will be possible to conduct even more such simulation studies in the future.

 

A European Open Data Source Website

Blogstats has written about the fact that the EU now has an open-source data portal (although still in beta version), which can be found here.

There are currently almost 6000 datasets available, most provided by Eurostat, but also other EU organs are uploading their statistics. This is really great news for all researchers out there. Even if much of this data has been available for free also earlier, the fact that it can now all be found through one portal, makes things much easier.

There is also a nice program available that can make graphs out of some of the available data, called CubeViz.

An example can be found below.

The graphs are made instantly, but unfortunately there are still large limitations to the number of indicators available.

Such an open data source has so much data available, that, with a bit of data manipulation and combination of datasets almost anything can be studied.

One of the next days, I will present one example of this, with a step-by-step explanation of how I did it and what I was searching for.

UPDATE December 30th: Mathbabe is asking whether open source data actually is beneficial for the general population. Her main argument is that such data most commonly will be used by large, for profit-organisations (using Goldman Sachs as an example) for their own benefit, and not for the common good.

I do disagree a bit with this argument, and believe that this data would have been available to large corporations in one way or another anyways. So, if they are open source, it means that also others (like statistically interested hedgehogs) can use them.