In a recent study published in the BJD, Geifman et al. demarcated subgroups or ‘trajectories’ of patients with psoriasis with similar patterns of disease severity. The patients were considered over time using a data-driven latent class mixed-modelling approach. This modelling approach can be used to divide a heterogeneous population into a few homogeneous groups or ‘trajectories’. As such, patient characteristics in specific trajectories can be used to predict health outcomes such as treatment success.

The ambitious data-driven approach used in the study of Geifman et al. is a favorable first step in the use and evaluation of big (observational) data for the prediction of psoriasis treatment responses and treatment optimization in the future. Back-translation and implementation of such results into clinical practice will be an important future challenge. The ongoing rise of big data brings multiple opportunities, which require us to embrace an intensive collaboration between data scientists and clinicians.