Networks of Statisticians and the Transformation of Medicine

Abstract

There is a statistical paradox at the heart of twentieth-century medicine. In 1900 physicians largely ignored the tools of statistical analysis. Clinicians and laboratory researchers saw themselves as fundamentally opposed to the burgeoning field of academic statistics: they were interested in biomedical causation, statisticians were focused on numerical correlation; they were focused on exceptions and idiosyncrasies, statisticians were focused on norms and averages; they were determinists, statisticians were probabilists. There were essentially no statistical articles in medical journals, no statistical training required for the M.D., no well-known statistical interpretations of laboratory experiments. The American Medical Association lamented that questions about therapeutic efficacy were largely addressed by anecdotal accounts from influential physicians (and drug companies themselves).1 The burgeoning field of public health (sometimes under the title of “sanitation” or “hygiene”) drew on epidemiological measures of disease, and questions of inoculation and epidemic infection had long been resolved with statistical calculations.2 But these were seen as limited to large outbreaks where people could be treated as interchangeable; in the clinic, the opposite was true. Patients were unique and the aggregative methods of epidemiology irrelevant.3 By 2000 the situation was seemingly reversed. A statistically significant randomized clinical trial was the gold standard of therapeutic efficacy, and such proof was required by the Food and Drug Administration (FDA) prior to licensing drugs.4 Reformers now promoted “evidence-based” medicine (as if medicine had never before been based on evidence), an initiative which claimed best practices should be determined solely on the basis of statistically