On the scientific inference from clinical trials

• We have not been able to describe clearly how we generalize findings from a study to our own 'everyday patients'. This difficulty is not surprising, since generalization deals with how empirical observations are related to the growth of scientific knowledge, which is a major philosophical problem. An argument, sometimes used to discard evidence from a trial, is that the patient sample was too selected and therefore not 'representative' enough for the results to be meaningful for generalization. In this paper, we discuss issues of representativeness and generalizability. Other authors have shown that generalization cannot only depend on statistical inference. Then, how do randomized clinical trials contribute to the growth of knowledge? We discuss three aspects of the randomized clinical trial (Mant 1999), First, the trial is an empirical experiment set up to study the intervention on the question as specifically and as much in isolation from other -- biasing and confounding -- factors as possible (Rothman & Greenland 1998). Second, the trial is set up to challenge our prevailing hypotheses (or prejudices) and the trial is above all a help in error elimination (Popper 1992). Third, we need to learn to see new, unexpected and thought-provoking patterns in the data from a trial. Point one -- and partly point two -- refers to the paradigm of the controlled experiment in scientific method. How much a study contributes to our knowledge, with respect to points two and three, relates to its originality. In none of these respects is the representativeness of the patients, or the clinical situations, crucial for judging the study and its possible inferences. However, we also discuss that the biological domain of disease that was studied in a particular trial has to be taken into account. Thus, the inference drawn from a clinical study is not only a question of statistical generalization, but must include a jump from the world of experiences into the world of reason, assessment and theoretical judgement.

Nyckelord

inference

evidence-based medicine

randomized controlled trials

knowledge

MEDICINE

MEDICIN

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