Statins: the risks and statistics

The application of medical statistics has the potential to achieve life-saving outcomes. Thus, Spiegelhalter (2019: 294) noted that if a statistic called a sequential probability ratio test had been applied routinely to the accumulating recorded mortality data of the patients of murderous GP Harold Shipman, 175 lives could have been saved.

Less dramatic, but with possible far-reaching consequences for patients' health, is how statistics – especially in relation to the use of relative and absolute risk – can invite certain inferences, for example, in relation to the effectiveness of statins. Let us assume that drug X prevents heart attacks in 1% of a population given drug X, but that 2% of a population given a placebo have heart attacks. Then, in terms of absolute risk (AR) reduction, the benefit conferred on the treated population by drug X is a mere one percentage point better that not being treated. However, the relative risk (RR) reduction conferred by drug X is 50% since one is 50% of two. And as Gigerenzer et al (2010) pointed out, RRs say nothing about the baseline risk ie, does ‘twofold’ mean from one to two or from 50 to 100 in, say, 7000? It is an important question to be answered when benefits are being weighed against harms.