Science-Based Medicine

Part IV of the ongoing Homeopathy series will have to wait a day or two, because it is superceded by a recent, comment-worthy publication. Nevertheless, “H series” fans will find here a bit of grist for that mill, too.

An important role for this blog is to discuss problems of interpreting data from clinical studies. Academic medicine has committed itself, on the whole, to scientific rigor—to the extent that this is possible in messy, clinical (especially human) trials. Several tools have been proposed, and to a varying extent used, to enhance the rigor of clinical research and the reporting of clinical research. One of those tools is the registering of clinical trials prior to recruiting subjects. Registration would stipulate a trial’s a priori hypothesis(es), design, planned endpoints, and planned statistical methods, among other things. This would guard against several problems: publication bias—the tendency for some trials, usually “negative” ones, to go unreported; selective reporting of the results of a trial, if some are pleasing but others are not; and post hoc data analysis—finding data after the fact to suggest a novel hypothesis that will falsely be portrayed as an a priori hypothesis. Publication bias is also known as “selective publication” or the “file drawer problem”; post hoc analysis is also known as “data dredging” or “HARKing” (Hypothesizing After the Results are Known).

An article in the Jan. 17 issue of the New England Journal of Medicine demonstrates the usefulness of a trial registry:

Selective Publication of Antidepressant Trials and Its Influence on Apparent Efficacy

Erick H. Turner, M.D., Annette M. Matthews, M.D., Eftihia Linardatos, B.S., Robert A. Tell, L.C.S.W., and Robert Rosenthal, Ph.D.

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