Drowning In Risk Factors…

As I discussed previously, we don’t have a clear idea of the causes of many of the degenerative diseases we face today, like heart disease and cancer; all we have are risk factors. In some cases, we have a lot of risk factors. For example did you know there are now over a thousand known risk factors for heart disease? But which of these thousand risk factors actually cause heart disease? All of them? None of them? Why don’t we know what the causes of these diseases are yet?

Unfortunately, these diseases are extremely difficult to study because their causes are non-trivial. The biggest difficulty in studying them is they don’t develop overnight. Some scientists believe that diseases like heart disease and cancer can take 20+ years to develop. So how can we possibly know which combination of factors during all that time caused or contributed to the disease? Hmm…

Observational Studies

The field of epidemiology has been around for hundreds of years. Originally, it was used to study outbreaks of infectious diseases (i.e. epidemics). Today it’s a staple of scientific research, and there are thousands of studies published every year. Unfortunately, as Dr. George Davey Smith and Dr. Shah Ebrahim discuss in their editorial “Epidemiology — Is It Time to Call It a Day?“, the track-record for observational studies correctly identifying the causes of degenerative diseases is less than stellar. In fact, not only do they often find spurious associations, but sometimes they find the opposite of the correct answer. For example, as detailed in the New York Times article “Do We Really Know What Makes Us Healthy?“, doctors for many years prescribed hormone replacement therapy to older women to reduce their risk of heart disease, only to find out recently that it actually increases their risk.

The problem is observational studies are inherently limited. Observational studies involve monitoring a large group of people for some period of time, asking them questions or giving them medical exams at regular intervals, and recording mortality and disease rates. But how often do they monitor the people in these long-term studies? Certainly not every week. In the famous on-going Nurse’s Health Study, for example, they send out questionnaires every two years. Even if you’re monitoring something simple like birth control usage, how do you boil all the variations or permutations of potential usage down into a multiple choice question?

And after the researchers have collected their data, they plug it all into a computer and hope to find correlations. The better studies (prospective studies) as least decide what they’re testing before running the study so they can attempt to minimize confounding factors in the design of their study. The more dubious ones (retrospective studies) go looking for associations in data from studies designed for completely different purposes. Sandy Szwarc from the Junkfood Science blog has a long list of examples of this type of weak “data-dredge” study.

By definition, observational studies are largely uncontrolled (i.e no intervention and no randomization) and thus will have many confounding factors. This is where the judgement and biases of the researchers come in. It’s possible to get different results depending on how the researchers manipulate or “interpret” the data. If the associations being studied are small, the adjustments made to the data can easily skew the data to reveal associations where there are none.

And even if the studies find compelling associations, they’re still just associations. We don’t know why the association exists. They may be causative or could simply be correlated.

In the end, observational studies are like excavators. If you’re looking for big obvious things, like rocks, you’ll find them. But if you’re looking small subtle things, like fossils, you’re going to miss them. It’s the wrong tool for the job.

Clinical Trials

So if observational studies aren’t good at discovering the causes of diseases, what about clinical trials? Clinical trials avoid a number of the limitations of observational studies by design. The best clinical studies are double-blind so neither the doctor nor the patient know whether they’re in the study group or the control group. Clinical studies also are typically short and small in order to control for as many confounding factors as possible.

But if it can take 20+ years to develop these diseases, how much is it going to cost to run clinical studies for that length of time? This, of course, ignores the problem that people won’t like strict controls on how they live their lives for long periods of time either. In the old days, they experimented on patients in mental hospitals since they were a captive audience and not likely to object; but we can’t do that anymore…

Also, some things, like diet, aren’t suitable for double-blind studies because people know whether they’re eating low-fat or low-carb foods, for example, which introduces an additional set of confounding factors.

Clinical trials are useful for testing new drugs because they can use placebos to make the study double-blind, and the experimenters can focus on one specific variable. But for monitoring lifestyle or other human behaviors, clinical studies don’t seem particularly suited…

Biological Research

Our best hope for really understanding these degenerative diseases is to understand them at the molecular level – by understanding the biological mechanisms at work in our bodies. Observational studies and clinical trials can help to at least point us in the right direction since biological research is very expensive and time-consuming. I’ll explore some of the findings of current biological research in future posts.

But what can we do in the meantime? Who should we believe? That’s the hard part…

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