Epidemiology needs transparency
Epidemiological studies are often used inappropriately for common illnesses like cardiovascular disease and cancer, according to British cardiologist Guy Lloyd.
Randomized controlled trials are more reliable. Epidemiology is most effective in identifying large risks in rare diseases. Just in the field of cardiology, the results of observational studies are often seriously flawed.Observational studies of the cardioprotective effects of female sex hormones, the usefulness of antioxidants or homocysteine lowering strategies, and rhythm control for atrial fibrillation suggested a clear treatment effect and greatly influenced practice. But subsequent randomised trials refuted each hypothesis.
The main problem, he explained, is all of the interacting factors among cohorts that can’t be statistically accounted for in an epidemiological study.
Concerns with the reporting of medical studies are multiplying. A recent blog on Junkfoodscience highlights the efforts of a new project, STROBE (Strengthening the Reporting of Observational Studies in Epidemiology). We wish them all success.
“Over the past 20 years statistical associations have implicated almost every aspect of people's everyday lives in some lethal disease or other,” wrote Dr. James Le Fanu, physician and author of The Rise and Fall of Modern Medicine:
But most of these alleged hazards, about which we read everyday in the newspapers, cannot possibly be true. The human organism is —as it has to be [for the species to have survived!] — robust and impervious to small changes in the external world. The notion that subtle alterations in patterns of food consumption or undetectable levels of pollutants can be harmful is contrary to the fundamental laws of human biology.Sadly, epidemiological studies are also the most poorly understood. The biggest misconception — besides knowing when a correlation is big enough to suggest a true effect that even deserves our attention (hint: it is much bigger than most people would guess) — is mistaking that correlation for causation. Epidemiological studies can never show causation because they can’t account for all sorts of confounding factors — a related factor that’s the true cause.
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