Resumen
In this manuscript, we present a statistical model for reliable and early prediction of treatment failure in patients with diffuse large B-cell lymphoma. The model combines measurable parameters?namely, the metabolic tumor volume and the metabolic heterogeneity, from baseline PET/CT with the presence or absence of mutations in SOCS1 and CREBBP/EP300 and represents a promising tool for the design of clinical trials focused on tailoring treatment to the individual risk. According to our bioinformatics analysis, mutation profiling may not be needed in patients with high-risk PET/CT metrics. Hence, the proposed approach may help optimize economic resources avoiding costly, and likely unnecessary, DNA analysis in many patients.