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Low lymphocyte-to-monocyte ratio predicts unfavorable prognosis in non-germinal center type diffuse large B-cell lymphoma

Leukemia Research, 6, 38, pages 694 - 698

Abstract

The peripheral blood lymphocyte to monocyte ratio (LMR) at diagnosis has been used to predict survival in diffuse large B-cell lymphoma (DLBCL) patients, but its prognostic significance with respect to different cell-of-origin (COO) subtypes remains unknown. We retrospectively analyzed 168 de novo DLBCL patients in this study and found that a low LMR (≤2.6) correlates with B symptoms, elevated LDH, advanced Ann Arbor stage and higher international prognostic index (IPI) score (p < 0.05). The low LMR is a negative prognostic parameter for overall survival (OS) and event-free survival (EFS) in non-germinal center (GC) type DLBCL patients, as compared with the high LMR, especially in those treated with R-CHOP. However, the LMR has less correlation with the OS and EFS in GC type DLBCL patients (p = 0.545 and 0.547, respectively). Multivariate analysis adjusting for IPI revealed that the low LMR indicates a shorter survival retain both OS and EFS in non-GC subtypes (p = 0.023 and 0.005, respectively). In the non-GC DLBCL patients treated with R-CHOP a low LMR still showed a trend to predict poor EFS (p = 0.052). In conclusion, these data suggest that a low LMR at diagnosis may imply a poor prognosis in non-GC subtype DLBCL patients, especially in those treated with R-CHOP, but not in those GC subtype DLBCL patients.

Keywords: Diffuse large B-cell lymphoma, Lymphocyte-to-monocyte ratio, Cell-of-origin, Prognosis.

1. Introduction

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin's lymphoma and is characterized by a high degree of heterogeneity in terms of immunophenotype, pathogenetics, and clinical response [1] and [2]. According to gene expression profiling, DLBCL can be identified as at least 3 distinct subtypes: germinal center-type (GC), activated B-cell-type, and type 3, with different cell-of-origin (COO) and survival [3] and [4].

The study on the relationship between lymphoma biology and the host immune system indicates that intra-tumoral microenvironment may play an important role in the outcomes of patients with lymphoma [5], [6], and [7]. The absolute lymphocyte count (ALC) and absolute monocyte count (AMC) have been used to predict survival in patients with DLBCL [8], [9], [10], [11], and [12]. Recent study indicates that the lymphocyte to monocyte ratio (LMR) may predict the prognosis of DLBCL patients who are treated with immunochemotherapy [13] , but not of those receiving chemotherapy alone [14] . It remains unclear how the LMR correlates with different COO subtypes of DLBCL. In the present study, we performed this retrospective analysis to investigate the prognostic significance of LMR in DLBCL patients with different COO subtypes.

2. Materials and methods

2.1. Patient selection

In the present study, all 168 patients who were diagnosed with diffuse large B-cell lymphoma (DLBCL) from January, 2001 to February, 2011 in Nan fang Hospital were further confirmed according to WHO classification. Patients with immunodeficiency-associated tumors and various types of lymphoma, including primary central nervous system lymphoma, posttransplant lymphoproliferative disorder and transformed NHL were excluded from the study. Among this cohort, 63 patients were treated with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) and 105 patients were treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP), either alone, in combination with surgery, or involved-field radiation. This study was performed in accordance with the modified Helsinki declaration, and the protocol was approved by the Ethics Committee of Southern Medical University affiliated Nanfang Hospital before study initiation. All patients provided written informed consent themselves prior to treatment.

2.2. Immunohistochemistry

Immunohistochemistry (IHC) was carried out using a peroxidase-conjugated labeled dextran polymer method. After deparaffinization in xylene and rehydration in alcohol endogenous peroxidase was blocked by incubation with 0.3% H2O2 in methanol for 20 min.The tissue sections were incubated in a microwave oven at 100 °C for 20 min in citrate buffer (0.01 M, pH = 6). After washed with PBS, sections were then incubated with primary antibody for 1 h at room temperature followed by a labeled polymer conjugated to goat anti-mouse immunoglobulins for 30 min. Bound antibody was detected with DAB+ substrate kit (Zhongsan Biotechnology Ltd., China). Slides were then counterstained with hematoxylin. The following primary monoclonal antibodies were used: CD10 (Santa Cruz Biological Company, USA), BCL6 (Santa Cruz Biological Company, USA), MUM1 (Santa Cruz Biological Company, USA). The cases were considered positive if 30% or more of the tumor cells were stained with CD10, BCL6 and MUM1. GCB and non-GCB subtypes were classified according to the algorithm described by Hans et al. [15] .

2.3. Statistical analysis

Statistical analysis was done using the Statistical Package of Social Sciences version 13.0 for Windows. Spearman test was used to analyze relationships between the markers. Mann–Whitney test and Fisher's exact test were applied to assess mean differences between groups. The optimal cutoff value of ALC was determined by receiver operating characteristics curves and area under the curve. Overall survival (OS) was calculated from the date of diagnosis until death from any cause or the last follow-up. Event-free survival (EFS) was calculated from the date of diagnosis to the date of documented disease progression, relapse or death from any cause. OS and EFS were estimated using the method of Kaplan–Meier and were compared using the log-rank test. Multivariate modeling was carried out based on the Cox regression analysis. p < 0.05 was considered to indicate statistical significance.

3. Results

3.1. Patient characteristics

We retrospectively analyzed data from a total of 168 DLBCL patients in this study. The median follow-up was 52 months (range 1–133 months). The male-to-female ratio was 1.55:1 and the median age of patients at diagnosis was 49 years old (range 19–80 years old). Thirty-nine patients (23.2%) were ≥60 years old and 93 patients (55.4%) were in advanced stage (stages III and IV). Based on the IPI score, 98 patients (58.3%) were in the intermediate or high-risk groups. Eighty-eight patients (52.4%) had an elevated LDH level and 35 patients (20.8%) had bone marrow involvement. The GC subtype was applied to 59 of 168 cases (35.1%); the other 109 were of the non-GC subtype.

Patients were divided into high and low groups using the ALC and AMC cut-off points of 1.0 × 109/L and 0.63 × 109/L at diagnosis, respectively. Thirty-nine patients (23.2%) were included in the low ALC group (<1.0 × 109/L) and 62 patients (36.9%) were in the high AMC group (>0.63 × 109/L). The most sensitive (73%) and specific (50%) LMR cutoff value for survival analysis was 2.603, with an area under the curve (AUC) value of 0.699 ± 0.052 (p = 0.001, Fig. S1), which is consistent with the optimal LMR cutoff value (2.6) reported in previous studies [13] and [14]. In this cohort, eighty-seven patients were included in the high LMR group (>2.6), whereas the other 81 patients were in the low LMR group (≤2.6). Patients with low LMR had a higher incidence of B symptoms, elevated LDH, higher IPI score and advanced Ann Arbor stage (p < 0.001, p = 0.006, p < 0.001, p = 0.012, respectively). No difference was observed in the two COO subtypes (p = 0.430). The clinical characteristics of the DLBCL patients are presented in Table 1 .

Table 1 Patient characteristics according to LMR value.

Characteristics LMR p Value
  N (%) ≤2.6 >2.6  
Gender       0.955
 Female 66 (39.3%) 32 (39.5%) 34 (39.1%)  
 Male 102 (60.7%) 49 (60.5%) 53 (60.9%)  
Age (years)       0.423
 <60y 129 (76.8%) 60 (74.1%) 69 (79.3%)  
 ≥60y 39 (23.2%) 21 (25.9%) 18 (20.7%)  
Systemic symptoms       <0.001
 A 105 (62.5%) 36 (44.4%) 69 (79.3%)  
 B 63 (37.5%) 45 (55.6%) 18 (20.7%)  
IPI score       0.006
 0–2 70 (41.7%) 25 (30.9%) 45 (51.7%)  
 3–5 98 (58.3%) 56 (69.1%) 42 (48.3%)  
Bone marrow involvement       0.184
 Yes 35 (20.8%) 20 (24.7%) 15 (17.2%)  
 No 133 (79.2%) 61 (75.3%) 72 (82.8%)  
Lactate dehydrogenase       <0.001
 Normal 80 (47.6%) 27 (33.3%) 53 (60.9%)  
 High 88 (52.4%) 54 (66.7%) 34 (39.1%)  
Ann Arbor stage       0.012
 I or II 75 (44.6%) 28 (34.6%) 47 (54.0%)  
 III or IV 93 (55.4%) 53 (65.4%) 40 (46.0%)  
No. of extranodal sites       0.099
 0–1 94 (56.0%) 40 (49.4%) 54 (62.1%)  
 ≥2 74 (44.0%) 41 (50.6%) 33 (37.9%)  
Cell-of-origin subtype       0.430
 GC 59 (35.1%) 26 (32.1%) 33 (37.9%)  
 Non-GC 109 (64.8%) 55 (67.9%) 54 (62.1%)  
Absolute lymphocyte count       <0.001
 ≥1.0 × 109/L 129 (76.8%) 49 (60.5%) 80 (92.0%)  
 <1.0 × 109/L 39 (23.2%) 32 (39.5%) 7 (8.0%)  
Absolute monocyte count       <0.001
 ≤0.63 × 109/L 106 (63.1%) 29 (35.8%) 77 (88.5%)  
 >0.63 × 109/L 62 (36.9%) 52 (64.2%) 10 (11.5%)  

Abbreviations: LMR, lymphocyte to monocyte ratio; IPI, international prognostic index; GC, germinal center.

3.2. Survival analysis

Univariate survival analysis showed that patients in the low LMR group had significantly shorter overall survival (OS) and event-free-survival (EFS) rate than those in the high LMR group, as analyzed and compared in all the patients (p = 0.001, with 5-year OS of 70.8% versus 89.7%, Fig. S2A; p < 0.001, with 5-year EFS of 60.7% versus 83.9%, Fig. S2B) and the patients who received R-CHOP (p = 0.081, with 5-year OS of 80.6% versus 94.2%, Fig. S3A; p = 0.010, with 5-year EFS of 65.4% versus 88.5%%, Fig. S3B). But no significant difference was found in the patients who were treated with CHOP (p = 0.071, with 5-year OS of 60.1% versus 76.2%%, Fig. S3C; p = 0.061, with 5-year EFS of 55.9% versus 70.6%%, Fig. S3D). We further analyzed the statistical significance of LMR in survival prognosis for different COO subtype DLBCL patients. The low LMR was associated with a shorter OS and EFS rate, when compared with a high LMR, in the non-GC group (65.1% versus 85.2% of 5-year OS, p = 0.002, Fig. 1 A; 49.2% versus 78.2% of 5-year EFS, p < 0.001, Fig. 1 B), while no significant difference was observed in the GC group (83.6% versus 96.8% of 5-year OS, p = 0.545, Fig. 1 C; 76.3% versus 92.6% of 5-year EFS, p = 0.547, Fig. 1 D). Furthermore, in the non-GC group, the low LMR was also associated with a shorter OS and EFS rate, as compared with a high LMR (77.0% versus 93.3% of 5-year OS, p = 0.033, Fig. 2 A; 55.8% versus 87.3% of 5-year EFS, p = 0.006, Fig. 2 B), for patients who were treated with R-CHOP, but not for those treated with CHOP (p = 0.092, with 5-year OS of 50.5% versus 64.1%, Fig. 2 C; p = 0.075, with 5-year EFS of 43.9% versus 54.1%, Fig. 2 D).

gr1

Fig. 1 Kaplan–Meier survival analysis of LMR in different COO subtype DLBCL patients. Overall survival (A) and event-free survival (B) according to LMR in non-GC type DLBCL patients. Overall survival (C) and event-free survival (D) according to LMR in GC type DLBCL patients.

gr2

Fig. 2 Kaplan–Meier survival analysis of LMR in non-GC type DLBCL patients with different treatment. Overall survival (A) and event -free survival (B) according to LMR in non-GC subtype DLBCL patients treated with R-CHOP. Overall survival (C) and event-free survival (D) according to LMR in non-GC subtype DLBCL patients treated with CHOP.

Multivariate analysis confirmed that the low LMR remained a significant prognostic factor for OS (relative ratio [RR] 2.789; 95% confidence interval [CI], 1.151–6.756, p = 0.023) and EFS (RR, 2.828; 95% CI, 1.374–5.822, p = 0.005) in the non-GC group, independent of IPI. In the non-GC DLBCL patients treated with R-CHOP a low LMR still showed a trend to predict poor EFS (RR, 2.920; 95% CI, 0.991–8.606, p = 0. 0.052), but not OS (RR, 1.975; 95% CI, 0.977–3.993, p = 0.199). The multivariate survival analysis is shown in Table 2 .

Table 2 Multivariable analysis of prognostic factors for survival.

Variable OS EFS
  RR 95%CI p Value RR 95%CI p Value
Covariates in the entire group (n = 168)
IPI > 2 1.435 1.077–1.911 0.014 1.314 1.035–1.669 0.025
LMR ≤ 2.6 2.434 1.128–5.254 0.023 2.456 1.297–4.649 0.006
 
Covariates in the non-GC group (n = 109)
IPI > 2 1.467 1.039–2.071 0.029 1.325 0.997–1.761 0.053
LMR ≤ 2.6 2.789 1.151–6.756 0.023 2.828 1.374–5.822 0.005
Covariates in the non-GC group treated with R-CHOP (n = 67)
 
IPI > 2 2.938 0.567–15.214 0.058 1.658 1.062–2.590 0.026
LMR ≤ 2.6 1.975 0.977–3.993 0.199 2.920 0.991–8.606 0.052

Abbreviations: OS, overall survival; EFS, event -free survival; RR, relative risk; CI, confidence interval; IPI, international prognostic index; non-GC, non-germinal center; LMR, lymphocyte-to-monocyte ratio.

4. Discussion

Recent studies indicate that lymphopenia or monocytosis at diagnosis in DLBCL patients is associated with poor clinical outcome [16], [17], [18], and [19]. These findings indicate the role of host immune in DLBCL patients. It is also reported that LMR at diagnosis can predict prognosis of de novo DLBCL patients [13] and [14], suggesting a correlation between LMR and DLBCL prognosis. In this study, we found that patients with low LMR had more aggressive clinical presentation. A low LMR showed significantly shorter survival in all patients, particularly in those treated with R-CHOP.

DLBCLs can be divided into germinal center B cell-like (GCB) and activated B cell-like (ABC) subtypes with different cell of origin and clinical outcome by gene-expression profiling (GEP) [3] . Because GEP techniques are expensive and not generally available, different method using immunophenotypic algorithms have been developed to reproduce GEP subtypes. However the results about immunophenotypic algorithms predicting GEP analysis are controversial [20] . Several factors may account for this disagreement. First, a small panel of immunohistochemical stains may not completely capture information obtained from GFP. Second, the discrepancies in the immunostaining methodologies and evaluation of the results may confound the results. Despite these limitations, Hans algorithm [15] with a correlation of 71% for GCB and 88% for non-GCB with GEP results has been widely used in routine clinical practice. In our study, 59 of 168 cases were categorized into the GC subtype and the other 109 were the non-GC subtype based on Hans algorithm. Patients treated with CHOP alone in GC subtype experienced better survival compared with patients in non-GC subtype. We found no association between the COO subtypes and outcome in the patients treated with R-CHOP, as previous study [21] and [22].

In our study, we found that a low LMR is associated with poor survival in non-GC subtype patients. But LMR value has less prognostic value in GC subtype patients. Furthermore, in the non-GC group, low LMR is a poor predictive factor of survival in patients who receive R-CHOP, but not in those treated with CHOP. It is known that induction of programmed cell death, antibody dependent cellular cytotoxicity (ADCC), and complement-dependent cytotoxicity may play a role in rituximab efficacy. Lymphopenia may impact the efficacy of rituximab by impairing ADCC, as the result of a lack of effector cells. Lymphoma B cells can recruit monocytes to support the survival and proliferation of neoplastic B cells and suppress the proliferation of normal T cells [23] . These results suggest that host immune status affects the survival in DLBCL patients, especially the non-GC subtype DLBCL patients. In the study by Luis et al. [19] , the AMC/ALC score can predict survival in DLBCL independent of COO and was able to further stratify patients by low-, intermediate- and high-risk groups in patients presenting with either ABC or GCB subtype. However in our study the LMR is only associated with survival in non-GC subtype patients. The AMC/ALC score was calculated by the count of absolute lymphocyte and monocyte respectively, while the LMR was calculated by the ratio of lymphocyte to monocyte. The LMR was less vulnerable to the absolute lymphocyte and monocyte count compared with AMC/ALC score. Therefore, LMR, derived from automated complete blood count, can more easily used as a routine prognosticator in the prediction of non-GC type DLBCL patients and identify high-risk patients with R-CHOP treatment.

However, it should be noted that this was a retrospective analysis and the results need to be validated by future prospective study. The number of events was relatively small to confirm conclusions. To minimize the inherent biases of the study, we selected only patients with de novo DLBCL treated with standard first-line chemotherapy and excluded other presentations of DLBCL such as primary central nervous system lymphoma, posttransplant lymphoproliferative disorder or transformed NHL, because these presentations are not treated uniformly.

In conclusion, our results suggest that a low LMR at diagnosis can predict a poor prognosis in non-GC type DLBCL patients, especially in those treated with R-CHOP, but not in those GC subtype DLBCL patients. Therefore, LMR, derived from automated complete blood count, can easily be used as a routine prognosticator in the prediction of non-GC type DLBCL patients and identify high-risk patients with R-CHOP treatment.

Conflict of interest statement

The authors declare no conflict of interest.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 81028013), the Science and Technology Project of Guangdong Province (Grant No. 2010B050700020), and the Science and Technology Project of Guangzhou City (Grant No. 12C22121553).

Appendix A. Supplementary data

The following are the supplementary data to this article:

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Footnotes

Department of Hematology, Nanfang Hospital, Southern Medical University, Guangzhou, China

lowast Corresponding author at: Department of Hematology, Nanfang Hospital, Southern Medical University, Guangzhou Dadao North Street No. 1838, Guangzhou 510515, China. Tel.: +86 20 61641613; fax: +86 20 87280761.