Quantitative methods have been proposed to assess and compare the benefit-risk balance of treatments. Among them, multicriteria decision analysis (MCDA) is a popular decision tool as it permits to summarise the benefits and the risks of a drug in a single utility score, accounting for the preferences of the decision-makers. However, the utility score is often derived using a linear model which might lead to counter-intuitive conclusions; for example, drugs with no benefit or extreme risk could be recommended. Moreover, it assumes that the relative importance of benefits against risks is constant for all levels of benefit or risk, which might not hold for all drugs. We propose Scale Loss Score (SLoS) as a new tool for the benefit–risk assessment, which offers the same advantages as the linear multicriteria decision analysis utility score but has, in addition, desirable properties permitting to avoid recommendations of non-effective or extremely unsafe treatments, and to tolerate larger increases in risk for a given increase in benefit when the amount of benefit is small than when it is high. We present an application to a real case study on telithromycin in Community Acquired Pneumonia and Acute Bacterial Sinusitis, and we investigated the patterns of behaviour of Scale Loss Score, as compared to the linear multicriteria decision analysis, in a comprehensive simulation study.