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Objective To investigate the risk stratification of aggressive B cell lymphoma using the immune microenvironment and clinical factors. Methods A total of 127 patients with aggressive B cell lymphoma between 2014 and 2015 were enrolled in this study. CD4, Foxp3, CD8, CD68, CD163, PD-1, and PD-L1 expression levels were evaluated in paraffin-embedded lymphoma tissues to identify their roles in the risk stratification. Eleven factors were identified for further evaluation using analysis of variance, chi-square, and multinomial logistic regression analysis. Results Significant differences in 11 factors(age, Ann Arbor stage, B symptom, ECOG performance status, infiltrating CD8+ T cells, PD-L1 expression, absolute blood monocyte count, serum lactate dehydrogenase, serum iron, serum albumin, and serum β2-microglobulin) were observed among patient groups stratified by at least two risk stratification methods [International Prognostic Index(IPI), revised IPI, and NCCN-IPI models](P < 0.05). Concordance rates were high(81.4%-100.0%) when these factors were used for the risk stratification. No difference in the risk stratification results was observed with or without the Ann Arbor stage data. Conclusion We developed a convenient and inexpensive tool for use in risk stratification of aggressive B cell lymphomas, although further studies on the role of immune microenvironmental factors are needed.
Methods A total of 127 patients with aggressive B cell lymphoma between 2014 and 2015 were enrolled in this study. CD4, Foxp3, CD8, CD68, CD163, PD-1, and PD-L1 expression levels were evaluated in paraffin-embedded lymphoma tissues to identify their roles in the risk stratification. Eleven factors were identified for further evaluation using analysis of variance, chi-square, and multinomial logistic regression analysis. Significant differences in 11 factors (age, Ann Arbor stage, B symptom, ECOG performance status, infiltrating CD8 + T cells, PD- L1 expression, absolute blood monocyte count, serum lactate dehydrogenase, serum iron, serum albumin, and serum β2- microglobulin) were observed among patient groups stratified by at least two risk stratification methods [International Prognostic Index (IPI), revised IPI, and NCCN-IPI models] (P <0.05). Con No difference in the risk stratification results was observed with or without the Ann Arbor stage data. Conclusion We developed a convenient and inexpensive tool for use in risk stratification of aggressive B cell lymphomas, although further studies on the role of immune microenvironmental factors are needed.