A novel scoring model (SII-MSKCC) to better predict the clinical outcomes of primary central nervous system lymphoma

Abstract Currently, risk stratification and prognosis stratification of primary central nervous system lymphoma (PCNSL) is predominantly based on the Memorial Sloan-Kettering Cancer Center (MSKCC) model, but the prognostic value is controversial. Recently, the systemic immune-inflammation index (SII) has been considered as an important prognostic factor in PCNSL. 174 newly diagnosed PCNSL patients treated with methotrexate-based combination immunochemotherapy were analyzed in two retrospective discovery cohorts (n=128) and one prospective validation cohort (n=46) to determine whether the SII-MSKCC model could better predict the clinical outcomes. Generalized additive model, Kaplan–Meier curve, and Cox analysis were performed. The scores of SII-MSKCC model were: 890>SII>450, score=0; SII＜450, score=1; SII>890, score=2; Age≦50, score=0; age >50 + KPS≧70, score=1; age >50 + KPS≦70, score=2. Here, we report the results of discovery cohort that SII-MSKCC model provided higher prognostic performance compared with the MSKCC model. We further validate the prognosis value of the SII-MSKCC model with an external dataset from an independent prospective cohort, which confirmed its robustness. In multivariable analysis, the SII-MSKCC model remained significantly independently associated with clinical outcomes. Thus, SII-MSKCC model could be used across centers to better predict prognosis in PCNSL.