The Swedish system for the classification of fetal risk of drugs was t
he first of its kind and was implemented in 1978. Drugs for use in pre
gnant women are classified in 4 general categories - A to D. The US Fo
od and Drug Administration (FDA) introduced a system in 1979 also usin
g the letters A to D, together with an X category. However, the defini
tions differ considerably between the FDA system and the Swedish syste
m, resulting in a very different allocation of drugs to the respective
categories. In the Swedish system, category A includes drugs that hav
e been extensively used and/or for which there are reliable clinical d
ata indicating no evidence of disturbance of the reproductive process.
Category B includes drugs for which data from pregnant women are insu
fficient for making any solid estimation of human teratogenic risk, an
d classification is therefore based on animal data, with allocation to
3 subgroups. For products in category C, the pharmacological action o
f the drug may have undesirable effects on the human fetus or newborn
infant. Finally, category D contains drugs for which human data indica
te an increased incidence of malformations. The categorisation stateme
nt is always followed by a short explanatory text. In contrast to the
FDA system, the Swedish system has been well accepted, as judged by an
interview study including 934 physicians and pharmacists. We believe
that much of the American dissatisfaction may be a consequence of shor
tcomings in the category definitions of the FDA system. The FDA system
requires an unrealistically high quality of data, e.g. the availabili
ty of controlled studies in pregnant women that fail to demonstrate a
risk to the fetus are needed for a drug to be assigned to category A.
Consequently, the majority of drugs on the US market are allocated to
category C, interpreted as 'risk cannot be ruled out'. The distributio
n of drugs into the various categories is thus very different between
the Swedish and FDA systems. We think that the issue of this debate re
flects a fundamental problem related to public health information: how
should a large, compounded, changing and difficult to evaluate databa
nk be organised before it is made available to professionals and secon
darily to lay people?