Introduction
Multiple myeloma (MM) is the second most common hematological neoplasm, characterized by the accumulation of malignant plasma cells in the bone marrow leading to anemia, bone pain, renal impairment, hypercalcemia, and infections.
It accounts for about 1% of all malignancies and about 10% of hematologic malignancies. It most often occurs in people in the 7th and 8th decade of life, significantly more often in men [
1]. The advances made in the treatment of multiple myeloma in the last few decades, starting from the use of autologous hematopoietic stem cell transplantation, followed by the introduction of innovative therapies based on immunomodulatory drugs and proteasome inhibitors, radically improved the prognosis in this group of patients. According to current statistics, the percentage of 5-year survival is currently 48.5% and the median overall survival (OS) exceeded 6 years. Unfortunately, MM is still considered to be an incurable disease [
2].
Traditional, classic prognostic factors for multiple myeloma patients include the stage of the disease, performance status, age, and comorbidities. There is a high interest in a number of factors, both genetic, biochemical and hematological, and their potential use as prognostic markers [
3,
4]. Markers of inflammation are particularly interesting. It is believed that they can indirectly reflect the status of the bone marrow microenvironment, which affects the processes of regulation and promotion of growth, survival, migration, and even drug resistance of myeloma cells [
5].
The aim of the study was to assess the prognostic and predictive value of NLR and PLR ratios calculated on the basis of the absolute number of neutrophils, lymphocytes, and platelets in patients with multiple myeloma treated with thalidomide-based induction chemotherapy.
Materials and methods
The study group consisted of 100 multiple myeloma (MM) patients aged 53–69 years (median 64). All patients received triplet CTD induction therapy in 28-day cycles, in the following doses: thalidomide 100 mg/day p.o., cyclophosphamide 300–500 mg/week p.o., and dexamethasone 10–20 mg/day p.o. on days 1–4 and 8–11. The median of cycles of chemotherapy was 6. The median follow-up was 41.5 months. Demographic and clinical data including sex, age, stage, and type of disease were collected. An analysis of classic cytogenetic and biochemical prognostic factors (deletion of 17p, t(4;14) translocation, t(14;16) translocation, β2 microglobulin, LDH, CRP), NLR, and PLR (calculated as ratios of absolute neutrophil count to lymphocyte and platelet counts before treatment) was performed. In publications on the importance of NLR and PLR in assessing the prognosis of solid tumors, authors provide various cut-off points for NLR and PLR. To find the optimal values, we analyzed the ROC curves, which allowed to set the cut-off points: 2.86 for NLR and 157.66 for PLR. Data regarding treatment, such as the number of chemotherapy cycles, type of response, progression-free survival (PFS), and overall survival (OS), were also documented.
Statistical analysis of the obtained data was carried out using MedCalc 15.8 (MedCalc Software, Belgium) and Statistica 10 (Statsoft, USA) computer software. The comparison of the values of selected laboratory markers, demographic, and clinical factors was carried out using the non-parametric U Mann-Whitney test. The correlation between selected demographic, clinical and laboratory factors, as well as NLR and PLR was carried out using Spearman’s rank correlation. The analysis of ROC curves was used to determine the cut-off points for NLR and PLR. The Kaplan-Meier estimation method and Cox logistic regression were used to assess the probability of survival and the occurrence of progression depending on the distribution of the studied factors. In all used tests, results with p values < 0.05 were considered statistically significant.
Discussion
A number of both experimental and clinical studies confirm the existence of a close relationship between chronic inflammation and malignancy, in virtually all of its stages: initiation, promotion, and progression [
6‐
9]. Inflammatory cells capable of releasing a number of cytokines and growth factors cause damage to DNA, promote angiogenesis and lymphangiogenesis, and stimulate complex mechanisms of “escape” of malignant cells [
10].
It has been reported that an increased number of lymphocytes infiltrating a tumor may be one of the markers of good prognosis [
11‐
13]. In turn, the increase in the number of neutrophils or lymphopenia weakens the mechanisms of destruction of malignant cells, which promotes the formation of distant metastases [
14]. Elevated values of neutrophils to lymphocytes ratio (NLR)—as an indicator of active infection—are associated with worse prognosis, weaker response to treatment, and shorter survival in patients with solid tumors [
15].
Similar significance is attributed to the platelet to lymphocytes ratio (PLR)) [
16,
17]. According to estimates, in up to 60% of patients with malignant tumors, thrombocythemia has a significant, unfavorable impact on the prognosis. Through complex mechanisms of hemostasis activation as well as cell signal transduction, an increased number of PLT stimulates cell proliferation and promotes metastasis [
18,
19].
Bone marrow microenvironment and the way it interacts with myeloma cells are crucial in the pathogenesis of MM. The stromal environment determines the processes of growth, survival, migration, proliferation, and resistance to the treatment of neoplastically changed plasmocytes. Bone marrow stromal cells (BMSC), endothelial cells, and especially adhesion molecules on their surface have been shown to be critically important for the development of the disease. Their interactions through a series of proinflammatory cytokines released by BMSC and/or myeloma cells induce signaling pathways of proliferation and survival of monoclonal plasmocytes [
20]. Therefore, all cells involved in the development of the so-called systemic inflammatory response could be important in the course of the disease.
There are only a few reports in the literature in which the NLR and PLR ratios were assessed in the context of prognosis or treatment efficacy in patients with MM.
Kelkitli et al. were the first to evaluate the value of NLR in patients with MM. The study included 151 patients and 151 healthy volunteers, appropriately selected for age and sex. NLR was significantly higher in myeloma patients than in the control group (2.79 ± 1.82 vs. 1.9 ± 0.61, respectively,
p < 0.0001). It has been shown that NLR is an independent prognostic factor for OS and EFS (event-free survival) estimation. Patients with NLR < 2 at the time of diagnosis obtained longer OS compared to patients with NLR ≥ 2 (5-year OS were 87.5 and 42.4%, respectively,
p < 0.0001). Similarly, longer EFS was observed in patients with NLR < 2 compared to patients with NLR ≥ 2 (5-year EFS rates were 88.4 and 41.8%, respectively,
p < 0.0001) [
21].
Onec et al. performed a retrospective analysis of 52 patients with MM. They showed that the NLR index depends on the concentration of CRP and β2-microglobin (
p = 0.02,
p = 0.001). They observed that patients with NLR > 1.72 were in a significantly higher stage of disease and had worse performance status and renal function. Median OS for the whole group was estimated at 35.1 months, and there was a significant difference in OS depending on the NLR (42.75 months for patients with NLR ≤ 1.72 and 26.14 months for patients with NLR > 1.72,
p = 0.04) [
22].
Romano et al. assessed the importance of the NLR index in relation to the efficacy of myeloma treatment with the use of immunomodulatory drugs (IMiDs) and proteasome inhibitors in various regimens with or without glucocorticoids. Three hundred nine patients were recruited for the study. Authors did not show a relationship between the NLR and the efficacy of single or double drug treatment regimens. However, they observed significant differences in the prognosis of patients treated with autologous bone marrow transplantation (ASCT). The median PFS was 22.1 in patients with NLR ≥ 2, versus 43.4 months in the NLR < 2 group (
p = 0.017). In the group of patients with NLR ≥ 2 OS was 57.6 months, in the remaining subjects median OS was not reached (
p = 0.002). Based on those findings, the authors proposed adding NLR to the ISS classification. They divided the subjects into three groups: very low risk—ISS1 and NLR < 2, very high risk—ISS3 and NLR ≥ 2, and the others were qualified for the standard risk group. They observed significant differences in the 5-year PFS depending on the ISS-NLR classification, respectively 39.3, 19.4, and 10.9% for the very low, standard, and very high risk groups. Five-year OS was 95.8, 50.9, and 23.6% for very low, standard, and very high risk patients according to ISS-NLR. Interestingly, the ISS classification itself was insufficient to differentiate patients against PFS and OS [
23].
The results of two meta-analyses assessing the prognostic value of NLR in the course of the disease have also been published. Mu et al. analyzed 7 clinical trials involving a cohort of 1971 patients with myeloma and observed that elevated pre-treatment NLR was significantly associated with high stage of the disease according to the ISS (III vs. ISS I-II: OR 2427, 95% CI 1.268–4.467) as well as Durie-Salmon (III vs. I-II: OR 1.738, 95% CI 1.123–2.665) scales. Elevated NLR was associated with shorter OS (HR 2.084, 95% CI 1.341–3.238) and median PFS (HR 1.029, 95% CI 1.016–1.042). A linear relationship was found between increased NLR and mortality risk in patients with MM [
24]. Zeng et al. analyzed the PubMed, Cochrane, and Embase databases. They studied data from eight clinical trials conducted jointly on a group of 1886 patients in 2013–2017. They reached the same conclusions—significantly shorter OS (HR 1.73, 95% CI 1.23–2.44,
p = 0.002) and PFS (HR 1.74, 95% CI 1.11–2.73,
p = 0.015) were noted in patients with NLR elevated prior to treatment. They also suggested that NLR correlates with the ISS stage of disease, the isotype of the disease, and the response to treatment [
25].
The evaluation of the prognostic value of NLR and PLR in MM was also the subject of research by Li et al. Three hundred fifteen patients were randomized to receive regimens with bortezomib, thalidomide, and classic cytostatics. The cut-off points for the indicators were determined based on the analysis of the ROC curve—for NLR–2, for PLR–155. The authors confirmed that high NLR observed before treatment is an independent, unfavorable prognostic factor. However, they did not demonstrate a relationship between the PLR value, PFS, and OS time [
26].
In a similar publication evaluating the importance of hematological indices of inflammation, Shi et al. confirmed the relationship between high NLR and MLR (monocyte-to-lymphocyte ratio) with unfavorable prognosis. In the case of PLR, they observed an inverse correlation; low values were associated with a shorter PFS: 32.3 vs. 40.4 months (
p = 0.005) and OS 49.4 vs. 53.2 months (
p = 0.008). The study was conducted in a group of 559 patients; the authors did not refer to the type of treatment used. Four (NLR), 100 (PLR), and 0.3 (MLR) were set as cut-off points [
27].
The relationship between decreased PLR and prognosis in myeloma patients was confirmed in another study by Solmaz et al. Researchers recruited a cohort of 186 patients treated with chemotherapy containing vincristine/doxorubicine/dexamethasone (
n = 100), cyclophosphamide/dexamethasone (
n = 34), bortezomib/dexamethasone (
n = 21), and others. They set following cut off points: 1.9 (NLR), 120.00 (PLR), and 0.27 (MLR) [
28].
In contrast to the cited publications, in our study, we found a relationship between elevated PLR and shorter OS (40 vs. 78 months; HR = 2.15, 95% CI 1.07–4.33; p = 0.0058). Interestingly, high PLRs were observed in patients with low BMI and high serum CRP. In the current studies, patients treated with thalidomide-based regimen have not been isolated, which makes interpretation of the obtained results much more difficult.
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