Abstract
Background
We evaluated the prognostic significance of neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) in patients with multiple myeloma (MM).
Methods
In total, we retrospectively analyzed 315 newly diagnosed MM patients and calculated NLR and PLR from the complete blood count of the untreated patients. We further assessed the role of pretreatment NLR and PLR on overall survival (OS) and progression‐free survival (PFS).
Results
Multiple myeloma patients with high NLR (≥2) experienced shorter OS (P=.02) and PFS (P=.01) compared with patients with low NLR (<2). Furthermore, among the patients with conventional chemotherapy, elderly patients, or patients with advanced stages, high NLR (≥2) was found to have a negative prognostic impact on OS and PFS. In the multivariate Cox analysis, we confirmed that the NLR was an independent prognostic factor for both OS and PFS (P=.000). But the differences in OS or PFS by PLR were not found in MM patients.
Conclusions
Our study suggests that NLR not PLR can be acted as an independent prognostic factor for analyzing the clinical outcome of MM patients.
Keywords: multiple myeloma, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, prognostic factor
1. Introduction
Multiple myeloma (MM) is a hematological malignant disease characterized by proliferation of plasma cells. Although salvage therapy including stem cell transplant (SCT) and new drugs have improved the clinical outcome, the rate of recurrence and mortality remains high. A number of prognostic factors such as cytogenetics and international staging system (ISS) have been proposed recently. In addition, a few tumor markers have been found to monitor and predict the recurrence and poor prognosis.1, 2, 3 The clinical symptom of MM patients is very complex, despite multifactorial risk stratification; additional identifying indicators associated with prognosis may complement the prognosis system in prognostication of patients with MM. We still need some convenient and independent prognostic markers for the clinical outcome of MM patients. At present, the viewpoint of inflammatory response playing an important role in the development and metastasis of tumor has been accepted. Many types of inflammatory cells can secrete high levels of proinflammatory cytokines and mediators to influence the survival outcomes of patients with tumor.4, 5 Some studies have shown that increased lymphocytic infiltrates toward the tumor site may contribute to good prognosis.6, 7, 8 When neutrophils were increased or lymphatic was decreased, the ability to kill tumor cells activated by lymphopenia was suppressed and the tendency of distant metastasis was enhanced.9 As the evaluation index of inflammatory reaction, some reports suggested neutrophils/lymphatic ratio (NLR) may be associated with survival of patients with some malignancies. In more studies of solid tumors, elevated NLR has been explored to associate with poor clinical outcomes.10, 11 Meanwhile, it was reported that NLR has prognostic value in patients with diffuse large B‐cell lymphoma and MM.12, 13
Similarly, many recent studies have shown that platelet/lymphocyte ratio (PLR) can be used as a biomarker to provide additional prognostic information for tumor, including ovarian cancer, colorectal cancer, natural killer T (NK/T)‐cell lymphomas, and so on.14, 15, 16 About 16%‐60% of the malignant tumor associated with thrombocytosis plays an important role in the progression, metastasis and prognosis of tumor.17, 18, 19 On one hand, the increased platelets can activate the coagulation system and increase the metastasis tendency of tumor cells. On the other hand, they can activate a variety of signal transduction mechanisms at the same time to promote proliferation and metastasis of tumor cells.19
In recent years, some reports suggested that NLR and PLR have prognostic value in solid tumors.20, 21 However, the prognostic values of NLR and PLR at diagnosis have been less explored in MM patients. In the study, we present the retrospective analysis of a single institution series of newly diagnosed patients with MM in China to clarify the prognostic value of NLR and PLR in MM.
2. Materials and Methods
2.1. Patients and data collection
Informed consents were obtained from patients and the study was complied with the Declaration of Helsinki and its amendments. In total, 315 newly diagnosed patients with MM were enrolled in this study, which were collected from the Department of Hematology Affiliated Hospital of Xuzhou Medical College during the period 2010 through 2015. According to the International Staging System (ISS), the MM patients were divided into three groups including 43 cases of stage I, 125 cases of stage II, and 147 cases of stage III. The data regarding these 315 patients including complete blood count (CBC), beta‐2 microglobulin (β2‐MG), the percent of plasma cell in bone marrow (BMPC), albumin (ALB), lactate dehydrogenase (LDH), blood urea nitrogen (BUN), creatinine (Cr), and Ca2+ before treatment were reviewed from the database of hematology department. NLR and PLR were calculated using data obtained from CBC. All patients were required to be originally diagnosed, based on 2001 World Health Organization diagnostic criteria of multiple myeloma.22 The final date for overall survival (OS) was defined as the day of death from any cause or the last day the patient was known to be alive and progression‐free survival (PFS) was defined as the day from treatment to the first observation of local or regional recurrence or distant metastasis.
2.2. Statistical analysis
Differences among groups were analyzed by Mann‐Whitney U test or Wilcoxon signed‐rank test for continuous parameters, and by Chi‐square tests for categorical data. The OS and PFS were measured and they were estimated using the methods of Kaplan‐Meier. Differences between survival curves were assessed for statistical significance using the two‐tailed log‐rank test. Potential risk factors for OS and PFS were evaluated in univariate and multivariate analysis with the Cox proportional hazards regression model. Hazard ratios (HRs) were estimated with 95% confidence intervals (CI) for the survival analysis. Meanwhile, NLR and PLR were analyzed through receiver operating characteristic (ROC) curves with calculation of the area under curve (AUC). All data were analyzed using the Statistical Package for the Social Sciences (SPSS 16.0, IBM Corp. Armonk NY, USA) and all P values represented were two‐sided, and statistical significance was declared at P<.05.
3. Results
3.1. Prognostic variables according to NLR and PLR
The median count of neutrophil was 3.06×109/L (range: 0‐58.80×109/L), lymphocyte was 1.50×109/L (range: 0‐14.50×109/L), and platelet was 155×109/L (range: 2‐454×109/L), respectively. For all the enrolled patients, the 1‐, 2‐, and 3‐year OS rates were 76%, 50%, 20%, and PFS rate were 58%, 23%, and 8%, respectively.
Receiver operating characteristic curves for OS prediction were plotted to verify the optimum cutoff point for NLR and PLR in MM patients. The cutoff values provided by ROC analysis were 2 for NLR and 119 for PLR. As shown in Figure 1A and B, areas under the curves of NLR and PLR were 67.2% (P=.000) and 59.4% (P=.004).
Figure 1.
The cutoff values provided by ROC analysis for NLR and PLR, respectively, for the prediction of OS in MM patients. (A) The area under the ROC curve for NLR was 67.2%, P=.000. The optimal cutoff value was 2 for NLR. (B) The area under the ROC curve for PLR was 59.4%, P=.004. The optimal cutoff value was 119 for PLR. ROC, receiver operating characteristic; NLR, neutrophil/lymphocyte ratio; PLR, platelet/lymphocyte ratio; OS, overall survival; MM, multiple myeloma
3.2. Patient characteristics according to the NLR and PLR
A total of 315 patients were enrolled in the study. Correlations between the NLR, PLR, and clinical characteristics are shown in Table 1. The patients were divided into different groups according to NLR and PLR at presentation. In particular, 155 patients presented values of NLR ≥2 and 160 patients with NLR <2. We found the significant correlations between NLR and WBC, NE, PLT, Cr, LDH, and BUN (P<.05). Meanwhile, there were 129 patients with PLR ≥119 and 186 patients with PLR <119. The significant association was observed in BMPC, β2‐MG, ALB, Hb, ALC, PLT, BUN, and ISS between the high‐PLR group and low‐PLR group (P<.05). Sixty‐nine patients received bortezomib‐based systemic chemotherapy and others received conventional chemotherapy, such as thalidomide, doxorubicin, or vincristine. Among the evaluable patients who received the bortezomib‐based therapy, the overall response rates were not different between NLR ≥2 group and NLR <2 group (P=.143). However, among the patients without bortezomib, the overall response rates were significantly higher in the low‐NLR group compared to the high‐NLR group (P=.002). On the contrary, the PLR was also assessed on the outcomes for different therapies and no significant correlations were noted between PLR and therapies (P=.531 and P=.302, respectively).
Table 1.
Baseline characteristics based on neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) at diagnosis for patients with multiple myeloma
| Characteristics | NLR | PLR | ||||
|---|---|---|---|---|---|---|
| NLR ≥2 (n=155) | NLR <2 (n=160) | P value | PLR ≥119 (n=129) | PLR <119 (n=186) | P value | |
| Age (y) | ||||||
| ≥65 | 59 | 62 | .900 | 52 | 69 | .564 |
| <65 | 96 | 98 | 77 | 117 | ||
| Gender | ||||||
| Male | 102 | 94 | .197 | 84 | 112 | .378 |
| Female | 53 | 66 | 45 | 74 | ||
| Bone destruction | ||||||
| Yes | 95 | 96 | .815 | 78 | 113 | .959 |
| No | 60 | 64 | 51 | 73 | ||
| BMPC (%) | ||||||
| ≥30 | 88 | 85 | .515 | 59 | 114 | .006 |
| <30 | 67 | 75 | 70 | 72 | ||
| β2‐MG (mg/L) | ||||||
| <3.5 | 38 | 46 | .396 | 42 | 42 | .049 |
| ≥3.5 | 117 | 114 | 87 | 144 | ||
| ALB (g/L) | ||||||
| <35 | 80 | 98 | .085 | 62 | 116 | .012 |
| ≥35 | 75 | 62 | 67 | 70 | ||
| Hb (g/L) | ||||||
| >100 | 54 | 43 | .126 | 51 | 46 | .005 |
| ≤100 | 101 | 117 | 78 | 140 | ||
| WBC (×109/L) | ||||||
| >10 | 25 | 8 | .000 | 9 | 24 | .074 |
| 4‐10 | 102 | 95 | 78 | 119 | ||
| <4 | 28 | 57 | 42 | 43 | ||
| NE (×109/L) | ||||||
| ≥1.5 | 152 | 116 | .000 | 113 | 155 | .296 |
| <1.5 | 3 | 44 | 16 | 31 | ||
| ALC (×109/L) | ||||||
| ≥1.0 | 102 | 150 | .000 | 80 | 172 | .000 |
| <1.0 | 53 | 10 | 49 | 14 | ||
| PLT (×109/L) | ||||||
| ≥100 | 131 | 110 | .016 | 122 | 119 | .000 |
| <100 | 24 | 50 | 7 | 67 | ||
| Ca2+ (mmol/L) | ||||||
| Normal | 133 | 144 | .253 | 115 | 162 | .583 |
| >Normal | 22 | 16 | 14 | 24 | ||
| Cr (mg/dL) | ||||||
| <2.0 | 101 | 135 | .000 | 99 | 137 | .534 |
| ≥2.0 | 54 | 25 | 30 | 49 | ||
| LDH (IU/L) | ||||||
| Normal | 86 | 116 | .002 | 86 | 116 | .434 |
| >Normal | 69 | 44 | 43 | 70 | ||
| BUN (U/L) | ||||||
| Normal | 90 | 68 | .006 | 80 | 78 | .000 |
| >Normal | 65 | 92 | 49 | 108 | ||
| ISS | ||||||
| I | 21 | 22 | .277 | 25 | 18 | .038 |
| II | 55 | 70 | 45 | 80 | ||
| III | 79 | 68 | 59 | 88 | ||
| D‐S | ||||||
| I | 8 | 10 | .262 | 9 | 9 | .581 |
| II | 27 | 39 | 29 | 37 | ||
| III | 120 | 111 | 91 | 140 | ||
| Isotype | ||||||
| IgG | 62 | 81 | .184 | 56 | 87 | .895 |
| IgA | 30 | 30 | 27 | 33 | ||
| Light chain only | 56 | 41 | 40 | 57 | ||
| Non‐secrete isotype | 7 | 8 | 6 | 9 | ||
| Bortezomib‐based | ||||||
| Effective | 23 | 29 | .143 | 20 | 32 | .531 |
| Ineffective | 11 | 6 | 8 | 9 | ||
| Conventional chemotherapy | ||||||
| Effective | 70 | 95 | .002 | 64 | 101 | .302 |
| Ineffective | 51 | 30 | 37 | 44 | ||
P<.05 are indicated in bold.
3.3. The impact of NLR, PLR at diagnosis on OS and PFS
With a median follow‐up of 25 months (range: 1‐64), Kaplan‐Meier analysis was performed to determine if the NLR and PLR were associated with OS and PFS. Patients with NLR <2 experienced a superior median OS and PFS compared to those with NLR ≥2 (the median OS, 29 months vs 18 months, the median PFS, 20 months vs 12 months, respectively, P=.000). Considering the OS and PFS probability, we found there were significant differences between the two groups. The log‐rank test represented P=.020 and P=.010 (Figure 2A and B). These results suggested that NLR levels at diagnosis were able to discriminate MM patients with regard to survival. As shown in Figure 2C and D, similar tendency was showed for OS and PFS between the groups according to PLR, but the difference was not statistically significant in patients with high‐PLR compared to low‐PLR patients (P=.290 and P=.354, respectively). The baseline PLR could not be used to predict the OS and PFS of the patients with MM.
Figure 2.
Kaplan‐Meier curves for OS and PFS according to NLR and PLR in newly diagnosed patients with MM. (A) OS stratified by NLR (χ2=5.437, P=.020). (B) PFS stratified by NLR (χ2=6.670, P=.010). (C) OS stratified by PLR (χ2=1.118, P=.290). (D) PFS stratified by PLR (χ2=0.858, P=0.354). NLR, neutrophil/lymphocyte ratio; PLR. platelet/lymphocyte ratio; OS, overall survival; MM, multiple myeloma; PFS, progression‐free survival
3.4. NLR was associated with OS and PFS in patients with conventional chemotherapy
Furthermore, the patients were divided into two groups according to the therapy. Among the patients with bortezomib‐based chemotherapy (n=69), the Kaplan‐Meier analysis suggested that NLR and PLR at diagnosis were not associated with OS and PFS (Figure 3A‐D). However, among the patients with conventional chemotherapy (n=246), it showed that the elevated NLR was associated with shorter OS and PFS (P=.003 and P=.010, respectively; Figure 3E‐F). This study showed that PLR was not a prognostic factor on clinical outcome in MM patients with conventional chemotherapy (Figure 3G‐H).
Figure 3.
Kaplan‐Meier curves for OS and PFS according to NLR and PLR in MM patients with different therapies. (A‐D) Patients with bortezomib‐based systemic chemotherapy. OS stratified by NLR (χ2=3.045, P=.081; A). PFS stratified by NLR (χ2=2.971, P=.160; B). OS stratified by PLR (χ2=1.355, P=.244; C). PFS stratified by PLR (χ2=0.712, P=.399; D). (E‐H) Patients with conventional chemotherapy. OS stratified by NLR (χ2=9.125, P=.003; E). PFS stratified by NLR (χ2=11.959, P=.010; F). OS stratified by PLR (χ2=0.397, P=.528; G). PFS stratified by PLR (χ2=0.377, P=.539; H). NLR, neutrophil/lymphocyte ratio; PLR. platelet/lymphocyte ratio; OS, overall survival; MM, multiple myeloma; PFS, progression‐free survival
3.5. NLR was related to OS and PFS among newly diagnosed elderly patients with MM
To exclude the effect of NLR in MM patients with different age, we analyzed the data on 121 patients with MM aged ≥65 years and 194 patients aged <65 years, respectively, and as shown in Figure 4, we found NLR was associated with OS and PFS in elderly patients with MM (χ2=6.738, P=.009; χ2=5.502, P=.019), but not in younger patients (χ2 =0.625, P=.429; χ2 =1.932, P=.164). These results suggested that the elevated NLR was associated with shorter OS and PFS in elderly MM patients (Figure 4).
Figure 4.
The impact of NLR on survival time in MM patients with different age. (A) OS stratified by NLR in patients with ≥65 years (χ2=6.738, P=.009). (B) PFS stratified by NLR in patients with ≥65 years (χ2=5.502, P=.019). (C) OS stratified by NLR in patients with <65 years (χ2=0.625, P=.429). (D) PFS stratified by NLR in patients with <65 years (χ2=1.932, P=.164). NLR, neutrophil/lymphocyte ratio; OS, overall survival; MM, multiple myeloma; PFS, progression‐free survival
3.6. NLR was associated with OS and PFS of MM patients in advanced stages
We further evaluated the prognostic effects of NLR in MM patients with different clinical stages according to ISS. As shown in Figure 5A and B, in the early stage (ISS I stage), there was no statistical significance for OS and PFS between high‐NLR group and low‐NLR group (P=.716 for OS and P=.326 for PFS). However, in the advanced stages (ISS II and III stages), patients with NLR <2 had significant superior OS and PFS (ISS II: P=.045 for OS and P=.038 for PFS; ISS III: P=.004 for OS and P=.003 for PFS, respectively; Figure 5C‐F).
Figure 5.
Kaplan‐Meier curves for OS and PFS according to NLR in MM patients with different ISS stages. OS (A) and PFS (B) stratified by NLR in MM patients with ISS I stage (n=43). OS (C) and PFS (D) stratified by NLR in MM patients with ISS II stage (n=125). OS (E) and PFS (F) stratified by NLR in MM patients with ISS III stage (n=147). NLR, neutrophil/lymphocyte ratio; OS, overall survival; MM, multiple myeloma; PFS, progression‐free survival; ISS, international staging system
3.7. Subgroup analysis of the prognostic effects of PLR in MM patients according to age and clinical stages
As in shown in Figure 6, PLR did not show the prognostic information for elderly and younger patients with MM. In patients aged ≥65 years, χ2 =2.509, P=.113 for OS and χ2 =2.142, P=.143 for PFS (Figure 6A and B). In patients aged <65 years, χ2 =1.097, P=.295 for OS and χ2 =1.370, P=.242 for PFS (Figure 6C and D). These results demonstrated again that the baseline PLR could not be a predictive factor for patients with MM. To further explore the prognostic effect of PLR, we performed subgroup analysis according to ISS stages. Interestingly, no statistical significance was observed for OS and PFS in different clinical stages between patients with PLR ≥119 and patients with PLR <119 (data not shown).
Figure 6.
Kaplan‐Meier curves for OS and PFS according to PLR in MM patients with different age. (A) OS stratified by PLR in patients with ≥65 years (χ2=2.509, P=.113). (B) PFS stratified by PLR in patients with ≥65 years (χ2=2.142, P=.143). (C) OS stratified by PLR in patients with <65 years (χ2=1.097, P=.295). (D) PFS stratified by PLR in patients with <65 years (χ2=1.370, P=.242). PLR, platelet/lymphocyte ratio; OS, overall survival; MM, multiple myeloma; PFS, progression‐free survival
3.8. Univariate and multivariate analysis
Univariate analysis was performed to investigate whether NLR and PLR can be the prognostic factors in MM. Baseline NLR level (95%CI 1.019‐1.054 and 1.045‐1.131, P=.000), age, bone destruction, ISS stage, WBC, Hb, NE, Cr, BUN, LDH, and Ca2+ were significantly associated with OS and PFS. In multivariate analysis for OS and PFS, NLR at diagnosis was an independent prognostic factor for MM patients (95%CI 1.045‐1.131 and 1.032‐1.118, P=.000). Other potential prognostic factors for OS and PFS in MM patients such as age, ISS, Cr, LDH, and Ca2+ are shown in Table 2. However, univariate and multivariate analysis revealed that OS and PFS did not correlate significantly with PLR (95%CI 0.999‐1.002 and 0.999‐1.001, P>.05). PLR was not an independent prognostic factor for OS and PFS in MM patients.
Table 2.
Cox regression analysis to predict overall survival (OS) and progression‐free survival (PFS) for patients with multiple myeloma
| Variable | OS | PFS | ||||||
|---|---|---|---|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | Univariate analysis | Multivariate analysis | |||||
| HR (95%CI) | P | HR (95%CI) | P | HR (95%CI) | P | HR (95%CI) | P | |
| Age | 1.012‐1.055 | .002 | 1.013‐1.057 | .007 | 1.010‐1.052 | .004 | 1.009‐1.051 | .005 |
| Sex | 0.885‐2.280 | .146 | 0.453‐1.167 | .187 | ||||
| Bone destruction | 1.047‐2.529 | .030 | .154 | 0.385‐0.931 | .023 | .186 | ||
| D‐S | 1.013‐2.629 | .044 | .515 | 0.981‐2.565 | .060 | |||
| ISS | 1.024‐2.435 | .003 | 1.045‐2.084 | .027 | 1.206‐2.424 | .003 | 1.040‐2.073 | .029 |
| BMPC | 0.993‐1.014 | .500 | 0.994‐1.014 | .429 | ||||
| RBC | 0.608‐1.035 | .088 | 0.609‐1.028 | .080 | ||||
| WBC | 1.015‐1.052 | .000 | .298 | 1.012‐1.048 | .001 | .363 | ||
| Hb | 0.982‐0.999 | .029 | .743 | 0.982‐0.999 | .032 | .864 | ||
| PLT | 0.996‐1.002 | .420 | 0.996‐1.001 | .265 | ||||
| NE | 1.015‐1.057 | .001 | .346 | 1.011‐1.054 | .002 | .412 | ||
| ALC | 1.025‐1.387 | .023 | .263 | 0.979‐1.352 | .089 | |||
| NLR | 1.019‐1.054 | .000 | 1.045‐1.131 | .000 | 1.018‐1.054 | .000 | 1.032‐1.118 | .000 |
| PLR | 0.999‐1.002 | .826 | 0.999‐1.001 | .987 | ||||
| β2‐MG | 1.000‐1.000 | .138 | 1.000‐1.000 | .229 | ||||
| Cr | 1.001‐1.002 | .000 | 1.000‐1.002 | .033 | 1.001‐1.002 | .000 | 1.000‐1.002 | .015 |
| BUN | 1.004‐1.016 | .001 | .794 | 1.003‐1.015 | .002 | .886 | ||
| LDH | 1.000‐1.001 | .000 | 1.000‐1.001 | .000 | 1.001‐1.001 | .000 | 1.001‐1.001 | .000 |
| ALB | 0.963‐1.021 | .576 | 0.962‐1.020 | .533 | ||||
| Ca2+ | 1.042‐1.164 | .001 | 1.033‐1.163 | .003 | 1.040‐1.164 | .001 | 1.033‐1.166 | .003 |
P<.05 are indicated in bold.
4. Discussion
In the study, we examined the relationships between the pretreatment NLR, PLR, and various clinical, and further explored the prognostic value of NLR and PLR in MM patients. This retrospective study showed that a lower NLR (<2) at diagnosis experienced superior OS and PFS in patients with MM. Notably, NLR remains a strong independent predictor for the MM patients in multivariate analysis with the known prognostic factors. The choice of NLR (≥2 vs <2) as the cutoff point was consisted with the previous study.23
The association between blood cell count and prognosis in patients with tumor has been reported. The NLR has been previously evaluated as an adverse prognostic factor in patients with solid cancers and hematological cancers.12, 19, 24 More recently, it showed that NLR was associated with an adverse OS in MM and it improved the risk assessment of ISS staging in newly diagnosed MM patients treated upfront with novel agents.13, 18 The mechanism may be that neutrophils are considered to participate in the tumor development via promoting tumor angiogenesis,25 while lymphocytes which are responsible for the immune surveillance resulting in the elimination of tumor cells is correlated with good prognosis.26
Platelet/lymphocyte ratio, which takes both protumor status and antitumor immune status into consideration, has been identified as an independent prognostic factor in many cancers.27 A combined index of NLR and PLR has been reported as prognostic factor for some cancers.11 High NLR and PLR indicated that the balance between inflammation and antiinflammation in tumor might be disturbed, and the inflammatory response promoted tumor formation and correlated with poor prognosis. Some researches showed that pretreatment NLR could be a better predictor than PLR in breast cancer, metastatic gastric cancer.27, 28 However, few studies regarding NLR and PLR in MM are available, and their roles are still controversial. The presence of both neutrophilia and thrombocytosis tends to represent a nonspecific response to cancer‐related inflammation and its associated release of cytokines.29 However, in our study, the elevated PLR did not show a significant effect on OS and PFS in MM patients. This result was consistent with the previous report.30 It is possible that M protein produced in MM may adhere to the surface of platelet and result in the decrease in the platelet activation and function. These observations suggest that neutrophilia compared with thrombocytosis is the most sensitive response, which best indicated the inflammatory activity of the tumor and caused a reduced OS and PFS through a multifactorial progress.31
This study demonstrated that the response rate for treatment with conventional chemotherapy was significantly higher in the patients with low‐NLR group (<2) compared with those with high‐NLR group (≥2). However, there was no significant difference between the two groups in the response rate for treatment with bortezomib.
The impact of NLR and PLR in MM patients was assessed on the outcomes for different therapies. The negative prognostic impact of high NLR was seen in MM patients with conventional chemotherapy but not bortezomib‐based therapy. We will further expand the cohort of MM patients treated with bortezomib‐based chemotherapy to confirm the results.
In the subgroup analysis, associations of NLR with OS and PFS were sought in elderly patients and in advanced clinical stages. Elderly patients or patients in advanced stages with NLR <2 tend to have a longer OS and PFS. Given the high heterogeneity of MM, differences in survival exist among patients. One of the prognostic factors in MM is the function of host immune system. Lymphatic was increased in young patients whose immune system is better represented than elderly patients. In spite of the uncertainty of NLR value in young MM patients, NLR plays an important role in maintaining the balance between tumor‐promoting inflammation response and antitumor inflammation. However, our analysis showed that PLR did not appear as an independent prognostic factor in this patient population.
In the multivariate analysis, the prognostic significance of NLR was demonstrated in newly diagnosed MM patients. To improve the evaluation of the prognosis of patients with MM, NLR can be combined with other currently identified prognostic indicators (eg age, ISS, LDH, and cytogenetics). The results of the study demonstrated that NLR ≥2 had a negative prognostic impact on OS and PFS in elderly MM patients or in advanced disease stages. So, NLR ≥2 can be a significant factor for risk stratification in MM patients. Recently, researchers have proposed that ISS can be combined with NLR could improve the predictive value of ISS and assist in individualizing therapies.18
The parameter NLR can be calculated easily from peripheral blood and it is inexpensive for MM patients. High NLR might contribute to a decrease in the antitumor response in MM. So, the marker NLR can be allowed for widespread clinical use to estimate the prognosis of MM in the future. Platelets were also reported to have a role in cancer‐related inflammatory response.29 But, our study does not support that PLR can play a significant role in determining the prognosis in MM.
However, the data came from a single institution and the number of patients was limited. We further need to enlarge the sample size and extend the follow‐up time to clarify the viewpoint. At the same time, further studies are needed to evaluate the mechanism through basic clinical trials.
In conclusion, this study suggested that NLR not PLR may have the prognostic value in MM patients. Increased NLR is a poor prognostic factor in elderly patients or in advanced stages of MM. The marker can improve the prognostic evaluation of MM patients.
Acknowledgments
This study was supported by National Natural Science Foundation of China (Grant No. 81570183), Nature Science Foundation Research Project of Jiangsu Province Education Commission, China (Grant No. 15KJB320017), and Science and Technology Special Project in Clinical Medicine of Jiangsu Province (Grant No. SBL201330199).
Contributor Information
Kailin Xu, Email: lihmd@163.com.
Zhenyu Li, Email: lizhenyumd@163.com.
References
- 1. Cox MC, Nofroni I, Laverde G, et al. Absolute lymphocyte count is a prognostic factor for diffuse large B‐cell lymphoma. Br J Haematol. 2008;141:265–268. [DOI] [PubMed] [Google Scholar]
- 2. Cox MC, Nofroni I, Ruco L, et al. Low absolute lymphocyte count is a poor prognostic factor in diffuse large B‐cell lymphoma. Leuk Lymphoma. 2008;49:1745–1751. [DOI] [PubMed] [Google Scholar]
- 3. Oki Y, Yamamoto K, Kato H, et al. Low absolute lymphocyte count is a poor prognostic marker in patients with diffuse large B‐cell lymphoma and suggests patients’ survival benefit from rituximab. Eur J Haematol. 2008;81:448–453. [DOI] [PubMed] [Google Scholar]
- 4. Büttner C, Skupin A, Reimann T, et al. Local production of interleukin‐4 during radiation‐induced pneumonitis and pulmonary fibrosis in rats: macrophages as a prominent source of interleukin‐4. Am J Respir Cell Mol Biol. 1997;17:315–325. [DOI] [PubMed] [Google Scholar]
- 5. Grivennikov SI, Greten FR, Karin M. Immunity, inflammation, and cancer. Cell. 2010;140:883–899. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Coussens LM, Tinkle CL, Hanahan D, et al. MMP‐9 supplied by bone marrow‐derived cells contributes to skin carcinogenesis. Cell. 2000;103:481–490. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Kishi Y, Kopets S, Chun YS, et al. Blood neutrophil‐to‐lymphocyte ratio predicts survival in patients with colorectal metastases treated with systemic chemotherapy. Ann Surg Oncol. 2009;16:614–622. [DOI] [PubMed] [Google Scholar]
- 8. Shau HY, Kim A. Suppression of lymphokine‐activated killer induction by neutrophils. J Immunol. 1988;141:4395–4402. [PubMed] [Google Scholar]
- 9. Shimada H, Takjguchi N, Kainuma O, et al. High preoperative neutrophil/lymphocyte ratio predicts poor survival in patients with gastric cancer. Gastric Cancer. 2010;13:170–176. [DOI] [PubMed] [Google Scholar]
- 10. el Aziz LM. Blood neutrophil‐lymphocyte ratio predicts survival in locally advanced cancer stomach treated with neoadjuvant chemotherapy FOLFOX 4. Med Oncol. 2014;31:311. [DOI] [PubMed] [Google Scholar]
- 11. Cannon NA, Meyer J, Iyengar P, et al. Neutrophil‐lymphocyte and platelet‐lymphocyte ratios as prognostic factors after stereotactic radiation therapy for early‐stage non‐small‐cell lung cancer. J Thorac Oncol. 2015;10:280–285. [DOI] [PubMed] [Google Scholar]
- 12. Porrata LF, Ristow K, Habermann T, et al. Predicting survival for diffuse large B‐cell lymphoma patients using baseline neutrophil/lymphocyte ratio. Am J Hematol. 2010;85:896–899. [DOI] [PubMed] [Google Scholar]
- 13. Kelkitli E, Atay H, Cilinqir F, et al. Predicting survival for multiple myeloma patients using baseline neutrophil/lymphocyte ratio. Ann Hematol. 2014;93:841–846. [DOI] [PubMed] [Google Scholar]
- 14. Asher V, Lee J, Innamaa A, et al. Preoperative platelet lymphocyte ratio as an independent prognostic marker in ovarian cancer. Clin Transl Oncol. 2011;13:499–503. [DOI] [PubMed] [Google Scholar]
- 15. Azab B, Mohammad F, Shah N, et al. The value of the pretreatment neutrophil lymphocyte ratio vs. platelet lymphocyte ratio in predicting the long‐term survival in colorectal cancer. Cancer. 2014;14:303–312. [DOI] [PubMed] [Google Scholar]
- 16. Wang KF, Chang BY, Chen XQ, et al. A prognostic model based on pretreatment platelet lymphocyte ratio for stage IE/IIE upper aerodigestive tract extranodal NK/T cell lymphoma, nasal type. Med Oncol. 2014;31:318. [DOI] [PubMed] [Google Scholar]
- 17. Ikeda M, Furukawa H, Imamura H, et al. Poor prognosis associated with thrombocytosis in patients with gastric cancer. Ann Surg Oncol. 2002;9:287–291. [DOI] [PubMed] [Google Scholar]
- 18. Romano A, Parrinello NL, Consoli ML, et al. Neutrophil to lymphocyte ratio (NLR) improves the risk assessment of ISS staging in newly diagnosed MM patients treated upfront with novel agents. Ann Hematol. 2015;94:1875–1883. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Templeton AJ, McNamara MG, Šeruga B, et al. Prognostic role of neutrophil‐to‐lymphocyte ratio in solid tumors: a systematic review and meta‐analysis. J Natl Cancer Inst. 2014;106:dju124. [DOI] [PubMed] [Google Scholar]
- 20. Feng JF, Huang Y, Liu JS. Combination of neutrophil lymphocyte ratio and platelet lymphocyte ratio is a useful predictor of postoperative survival in patients with esophageal squamous cell carcinoma. Onco Targets Ther. 2013;6:1605–1612. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Koh CH, Bhoo‐Pathy N, Ng KL, et al. Utility of pre‐treatment neutrophil‐lymphocyte ratio and platelet‐lymphocyte ratio as prognostic factors in breast cancer. Br J Cancer. 2015;113:150–158. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Grogan TM, Van Camp B, Kyle RA, et al. Plasma cell neoplasms In: Jaffe ES, Harris NL, Stein H, et al., eds. World Health Organization Classification of Tumours. Pathology and Genetics of Tumours of Haematopoietic and Lymphoid Tissues. Lyon: IARC Press; 2001:142–156. [Google Scholar]
- 23. Nappolitano M, Saccullo G, Bono R, et al. Absolute lymphocyte count is unrelated to overall survival in newly diagnosed elderly patients with multiple myeloma treated with immunomodulatory drugs. Leuk Lymphoma. 2015;56:1507–1509. [DOI] [PubMed] [Google Scholar]
- 24. Paramanathan A, Saxena A, Morris DL. A systematic review and meta‐analysis on the impact of pre‐operative neutrophil lymphocyte ratio on long term outcomes after curative intent resection of solid tumours. Surg Oncol. 2013;23:31–39. [DOI] [PubMed] [Google Scholar]
- 25. Tecchio C, Cassatella MA. Neutrophil‐derived cytokines involved in physiological and pathological angiogenesis. Chem Immunol Allergy. 2014;99:123–137. [DOI] [PubMed] [Google Scholar]
- 26. Basso S, Zecca M, Merli P, et al. T cell therapy for nasopharyngeal carcinoma. J Cancer. 2011;2:341–346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Dogan M, Eren T, Ozdemir N, et al. The relationship between platelet‐lymphocyte ratio, neutrophil‐lymphocyte ratio, and survival in metastatic gastric cancer on firstline modified docetaxel and cisplatinum plus 5 Fluorourasil Regimen: a single institute experience. Saudi J Gastroenterol. 2015;21:320–324. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Krenn‐Pilko S, Langsenlehner U, Thurner EM, et al. The elevated preoperative platelet‐to‐lymphocyte ratio predicts poor prognosis in breast cancer patients. Br J Cancer. 2014;110:2524–2530. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Bhatti I, Peacock O, Lloyd G, et al. Preoperative hematologic markers as independent predictors of prognosis in resected pancreatic ductal adenocarcinoma: neutrophil‐lymphocyte versus platelet‐lymphocyte ratio. Am J Surg. 2010;200:197–203. [DOI] [PubMed] [Google Scholar]
- 30. Wongrakpanich S, George G, Chaiwatcharayut W, et al. The prognostic significance of neutrophil‐to‐lymphocyte and platelet‐to‐lymphocyte ratios in patients with multiple myeloma. J Clin Lab Anal. 2016;30:1208–1213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Lee S, Oh SY, Kim SH, et al. Prognostic significance of neutrophil lymphocyte ratio and platelet lymphocyte ratio in advanced gastric cancer patients treated with FOLFOX chemotherapy. BMC Cancer. 2013;13:350. [DOI] [PMC free article] [PubMed] [Google Scholar]