Validating the Systemic Inmmune-Inflamation Index (SII) As a Prognostic Biomarker of Overall Survival in Diffuse Large B-Cell Lymphoma: A Retrospective Analyses By the Gruppo De Estudio Latinoamericano De Linfoproliferativos (GELL)

Abstract

Introduction: Diffuse Large B-cell lymphoma (DLBCL) is an aggressive malignancy and the most common type of non-hodgkin´s lymphoma. Biologically, survival of neoplastic lymphoid cells depends on self-mediated mechanisms and the tumor microenvironment ( Steen CB,2021) leading to an inflammatory state. Although a better understanding of lymphoma biology has helped predict outcomes in DLBCL, modern tools such as next generation sequencing are not available in Latin America ( LATAM). The systemic immune-inflammation index (SII) is a score based on neutrophil, platelet, and lymphocyte counts that has proven to be useful in DLBCL ( ZanZan W, 2021 & Xiao-Bo,2021). Moreover, its variables can be easily evaluated at resource-limited healthcare setting. Thus, we aim to validate this new SII score in our LATAM DLBCL population. Methods. A retrospective analysis of patients aged ≥18 years with a new diagnosis of DLBCL between 2010 and 2018 were included. Data were obtained from 7 LATAM countries: Argentina, Colombia, Chile Mexico, Peru, Uruguay, and Venezuela. Clinical features including the international Prognostic Index (IPI) variables (i.e. age≥60 years, ECOG performance status ≥2, >1 site extranodal involvement, elevated serum LDH, and advanced clinical stage) and low serum albumin defined as <3.5mg/dL (divided in low 3.4-2.5mg/dL & very low <2.5mg/dL) were recorded. We calculated the neutrophil/lymphocyte ratio (NLR) and use the cut-off previously published by our group (Beltran&Villela,2020). The SII score was calculated using the following formula: (absolute neutrophil count x platelet count) divided by absolute lymphocyte count x100; The cut-off was calculated by the ROC method. Demographics characteristics are reported using descriptive statistics. Cox proportional-harzard regression model was used to evaluate parameters associated with OS curves estimated with the Kaplan-Meier (KM) method. Outcomes. A total of 1032 patients were identified of whom 1029 received standard dose RCHOP (n=862,84%), R-miniCHOP (43,4.17%), R-EPOCH (n=61,5.92%) and CHOP (n=63,6.12%) with a curative intent. A total of 992 patients had suffcient data for analysis. Median follow.up for all cohort was 45 months (IQR: 7 to 60). Median age at diagnosis was 63 years (58.4%, age ≥60;IQR: 50 to 73), 50% was female, 33% had ECOG ≥2, 22% extranodal involvement (EN) >1 sites, 48% elevated serum lactate dehydrogenase (LDH), 41% advanced stage (Stage III/IV). Patients with hypoalbuminemia (Low & very low) were 25% & 6%, respectively; NLR >4 was 14%. The median calculated SII score for the entire cohort was 1774 (IQR:523 to 1856) with a cut-off of >1636 (AUC 0.55[95%C.I. 0.53 to 0.59], p=0.004). The clinical characteristics of non-inflammation group [NIG,n=736,71.5%] (below cut-off) and inflammation group [IG,n=293,28.5%] (above cut-off) are presented in Table 1. ECOG ≥2; elevated serum LDH, advanced stage; low & very low albumin; and NLR >4 were assocated to de IG ( all of them p<0.0001). The KM for NIG and IG showed better OS for the NIG at 3 years (67% vs. 49%, p<0.0001). Table 2 shows the univariate and multivariate analysis of variables with independent influence on OS. All but EN involvement were independent factors to prognosticate OS with a Harrell´s C-Index of 0.73 (95% C.I. 0.69 to 0.76). Conclusions. In this large cohort of LATAM DLBCL patients, we were able to validate the SII score. We found the SII score was able to discriminate low from hogh risk DLBCL inflammatory groups. Moreover, these findings were coupled to the validation of other prognostic factors such as the IPI score, hypoalbuminemia, and high NLR.