Designing a valid study, however, is difficult because there are many potential biases that can render its conclusions inaccurate. Here are some examples:
- Selection bias occurs when subjects are assigned in a nonrandom manner to different study groups.
If a physician runs a trial to test the efficacy of a drug he may put those who have a better prognosis in the treatment group, as opposed to the
non-treatment group. Consequently, scientists can claim this new treatment is successful even though it was tested on those who were most likely to improve
- Sampling bias, where subjects chosen for the study do not represent the general
population, can mean that a study’s findings do not apply to the general population.
- The Hawthorne effect arises when subjects change their behavior because they know they’re being
watched by a researcher or physician.
- Confounding bias describes a situation in which one factor can
distort the effect of another. If a researcher studies the effects of alcohol on health but ignores the fact that many people who drink alcohol also smoke, alcohol
will appear to have a worse effect on one’s health due to the consequences of smoking.
Lead-time bias suggests that the natural history of the disease is not truly affected by screening. For example, a patient may be diagnosed with prostate cancer at 50 years of age through ... screening. He then undergoes treatment but ultimately progresses and dies at 60 years of age. Accordingly, the same patient without screening develops symptomatic bony metastases [late stage cancer] at age 58, undergoes treatment with androgen deprivation therapy, and dies at age 60. Thus, in this theoretical scenario, even though he was diagnosed 8 years prior through screening, his death was not affected by screening or early detection.
In other words, early detection of cancer makes it seem as if your lifespan is increased simply because you know that you have cancer for a longer period of time. But you don’t necessarily live longer because of that.
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|A statue of Avicenna in Tajikistan|
Nikita Maykov / Shutterstock.com
As for the powers only known through experiment, these were not deduced from the qualities or the appearance of pharmaceutical ingredients, but they rather acted through their whole form or substance. Their action could only be revealed by an experimental test. Yet this did not mean that ordinary physicians themselves had to undertake such experiments. Rather, they relied upon experiments carried out by their predecessors.
Similarly, when today’s physicians choose, say, an antibiotic for a bacterial infection, they rely upon experiments carried out by their predecessors.
When I started medical school, I assumed that everything in medicine was evidence-based; that scientists rigorously studied and validated every treatment. After all, we should not treat a patient with a drug unless we know it works. But it turns out that there is not always evidence to support every decision physicians make. Perhaps a study has simply not been done or the evidence collected was equivocal or inconclusive. Or perhaps some real-life situation has arisen that is complicated in ways that could not possibly have been tested in an experiment. In these cases, physicians must base their decisions on experience.
Let’s take the example of IV fluids, which are a basic staple of medical care, as I’ve mentioned in multiple posts. One would think that the data would be fairly clear on which types of IV fluids are best. Unfortunately, it’s not at all evident. Some background: there are two major types of IV fluids, colloids and crystalloids. Crystalloids contain water and electrolytes that are similar to those circulating in the blood. Some examples of these are Lactated Ringer’s and Normal Saline. Colloid fluids contain water and electrolytes, too, but they also contain osmotic substances like albumin, which draw fluid into the vascular space. Fluid in the body can be inside the blood vessels or outside the blood vessels, and colloids keep fluids in the vessels.
Ostensibly, colloid fluids ought to work better in certain situations. For instance, when a patient has very low blood pressure, the way to increase blood pressure is to increase fluid within the vasculature. However two studies, one in the New England Journal of Medicine in 2004, and one in the Annals of Internal Medicine in 2001, concluded that there were no significant differences in mortality in various medical situations when using one type of fluid versus the other. So, barring significant differences in cost, which fluids does one use in the hospital when patients need hydration or increased blood pressure?
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Let’s also look at an example of how evidence-based medicine changes medical practice rapidly on a day-to-day basis. This past summer, the treatment for Parkinson’s disease (PD), a disease of certain neurons in the brain, underwent a change. Previously, movement disorder neurologists recommended dopamine agonists as a first-line treatment for the disease. The alternative is carbidopa-levodopa, a medication that is more effective at controlling PD symptoms. However, carbidopa-levodopa causes more side effects, such as dyskinesias, or compulsive and uncontrollable movements (some of these can be irreversible), the longer one takes the medication. And, given that patients with PD can live a long time, neurologists wanted to put off using it so that patients would not experience these effects so soon after starting medication.
But this past June, a study in The Lancet compared starting a dopamine agonist with starting carbidopa-levodopa in patients with newly diagnosed, early PD. And the researchers found that there is not a significant difference in patient-rated mobility scores (a fancy way of saying movement difficulties as well as quality of life) when starting with levodopa rather than dopamine agonists. I observed the direct practice changes as a result of this study. In the neurology clinic, the attending, after reading this article, changed the way he spoke to patients with newly diagnosed PD. Instead of saying that it is better to avoid carbidopa-levodopa first, he told patients that it was their choice what drug they wanted to start taking. This is a wonderful example of why evidence-based medicine and research is so important and how it can affect the practice of medicine — very concretely, very directly, and very soon after the research is published.