Description of a Clinical Score to Identify PMBL Patients at High Risk of Early-Failure after Rituximab Doxorubicin Back-Bone Chemoimmunotherapy. a FIL Real-World Study

Introduction. Primary Mediastinal B Lymphoma (PMBL) is a rare and aggressive neoplasia that typically occurs in young women and is primarily located in the mediastinum. Although the combination of anthracycline and rituximab immunochemotherapy, and PET-guided consolidation radiotherapy, results in a high cure rate, approximately 10-20% of patients show refractoriness or early failure to front-line treatment with a rapid clinical deterioration and a dismal prognosis. These cases, if promptly identified, could benefit from early treatment shift. Therefore, we addressed the development of a clinical score aimed at estimating the risk of early failure of PMBL patients treated with anthracycline-rituximab-based chemoimmunotherapy in a real-world nationwide setting. Material and Methods This is a retrospective cohort study of an unselected population of 931 adult PMBL patients treated in 37 FIL centers. To qualify for this research, patients had to have a confirmed diagnosis of PMBL, display typical symptoms and have been included in the local databases from 01/01/2007 to 31/12/2019. All patients received treatment with rituximab plus CHOP21 (n=98), CHOP14 (n=181), megaCHOP (n=31), MACOPB (225), VACOPB (n=179), DAEPOCH (n=179). Patients were excluded from this analysis if they received suboptimal treatment (22) or ASCT as consolidation of first-line therapy (12) or were censored within 365 days of treatment initiation (22). We defined early failure (EF) as any relapse or progression within 365 days of treatment initiation. Candidate predictors were clinical factors at the time of diagnosis, including: age, ECOG PS (a 4-level scale), LDH higher than Upper Limit of Normal, Ann Arbor Stage (a 4-level scale), systemic B symptoms, bulky mediastinum > 10 cm, number of Extra-Nodal sites (a 4-level scale: 0, 1, 2, or >=3), and pericardial or pleural effusion. Missing data in the evaluated predictors were multiple-imputed, and combined estimates were obtained from 20 imputed data sets. We used a multivariable logistic model with Backward Selection (level to stay p