We should move away from using risk factors as individual binary variables within acute lymphoblastic leukemia (ALL) research, suggests Anthony Moorman, PhD, of Newcastle University, Newcastle, UK, at the 23rd congress of European Hematology Association (EHA) 2018, held in Stockholm, Sweden. Using variables such as age, measurable residual disease (MRD) status and white cell count as aggregated continuous variables gives us more information in order to predict relapse, allowing us to develop numeric risk scores. Prof. Moorman notes that this prognostic index has been validated in a separate cohort from the discovery cohort, presenting with a similar distribution. This prognostic index is more powerful than current risk algorithms in predicting relapse, meaning it can be used to generate risk groups of any size and outcome for clinical trials – for instance, the best performing 20% of individuals. Ultimately, this gives us greater flexibility when designing new trials.