Mantle cell lymphoma (MCL) exhibits a heterogenous clinical course. The MCL International Prognostic Index (MIPI) is the most commonly used risk classification system in MCL. However, it does not contain a parameter associated with the tumor microenvironment. The aim of this study was to develop a more powerful prognostic index by evaluating the absolute monocyte count (AMC), neutrophil/lymphocyte ratio (NLR), and platelet/lymphocyte ratio (PLR) at diagnosis in conjunction with the clinical and laboratory parameters.
The data of 96 MCL patients with newly diagnosed from January 2014 to December 2018 were retrospectively evaluated in this study. The AMC, NLR, and PLR cut-off values were determined using the receiver operating characteristic (ROC) analysis.
The clinical behavior and results of the disease exhibited significant variation in high and low value groups at the time of diagnosis. In univariate analysis, the AMC ≥ 580, NLR ≥ 2.43, and PLR ≥ 120.85 were determined as negative prognostic factors for 5-year progression free survival (PFS) (AMC: PFS,
P
< .001; NLR: PFS,
P
< .001; PLR: PFS,
P
< .001) and for 5-year overall survival (OS) (
P
< .001,
P
< .001,
P
< .001, respectively). Beta-2 microglobulin (B2-MG), and MIPI for PFS, and for OS were found to be independent risk factors in the multivariate analysis (for PFS:
P
= .006,
P
= .002, respectively; and for OS:
P
= .007,
P
= .001, respectively). The 5-year OS was 20% in the group with B2-MG ≥ 3.5. The patients in high-risk MIPI group had poorer 5-year OS (median OS: 40 months,
P
< .001).
The results stated that the use of B2-MG in conjunction with MIPI was a more sensitive method in determining the prognosis in MCL (median OS: 12 months in high-risk MIPI group with a B2-MG ≥3.5,
P
< .001). Additionally, it was found that parameters reflecting the tumor microenvironment such as AMC, NLR, and PLR increased the risk of progression in MCL. In view of these findings, in addition B2-MG to the MIPI to create a more sensitive prognostic scoring system may provide an insight into personalization of treatment with early recognition of patients with poor prognosis.