Evaluation of pretreatment red cell distribution width in patients with multiple myeloma

Abstract

BACKGROUND:

Red blood cell distribution width (RDW) has been reported as an inflammatory biomarker and a predictor of prognosis in different types of cancer. However, the role of RDW at diagnosis in patients with multiple myeloma (MM) has been less explored.

OBJECTIVE:

We aimed to investigate the association between RDW and the response to treatment and overall survival (OS) in patients with MM.

METHODS:

We retrospectively analyzed the data for 196 MM patients between January 1, 2007 and December 31, 2015. Kaplan-Meier analysis and Cox regression model were used.

RESULTS:

High RDW values were associated with lower platelet count, lower hemoglobin levels, lower albumin levels, and higher lactate dehydrogenase (LDH) level. Among the entire cohort, the overall response rates (ORR) and complete response (CR) rate of initial therapy were markedly higher in the low-RDW group compared to the high-RDW group. RDW was significant lower in CR in comparison to Non-CR groups in patients treated with bortezomib-based regimens as induction therapy. The patients with low-RDW at diagnosis had better OS when compared to those with high-RDW.

CONCLUSIONS:

Elevated RDW was associated with worse survival in patients with MM and could predict treatment responses. Further larger and prospective studies are required.

Keywords

Multiple myeloma red cell distribution width survival prognostic

Table 1
Demographics of multiple myeloma patients by RDW

Characteristics	RDW $<$ 18.05	RDW $\geqslant$ 18.05	$P$ value
Number of patient	146	50
Median age (year)	65 (33–78)	65 (40–82)	0.453
Male (%)	81/55.5	29/58	0.757
Myeloma type (%)			0.073
IgG	71/48.6	22/44
IgA	37/25.4	22/44
Light chain	23/15.8	5/10
Non-secretory	11/7.5	1/2
Others	4/2.7	0/0
ISS Stage (%)			0.755
I	6/4.1	1/2
II	69/47.3	23/46
III	71/48.6	26/52
RDW (Median, range)	14.85 (11.7–18)	19.45 (18.1–31.3)	0.000
CRP, mg/L (Median, range) protein	5 (1–124)	4 (1–98)	0.268
Hemoglobin (g/L, Median, range)	91 (37–149)	72 (46–112)	0.000
MCV (fL, Median, range)	94.2 (78.2–107.7)	95.85 (68.8–116.6)	0.099
Platelet (x10 ${}^{9}$ /L, Median, range)	154.5 (16–329)	103 (17–279)	0.000
Albumin $<$ 3.5 g/L (%)	122/83.6	48/96	0.046
Lactate dehydrogenase $>$ normal (%)	23/15.8	15/30	0.028
Creatinine $>$ 177 $\mu$ mmol/L (%)	46/31.5	8/16	0.034
Calcium $>$ 2.75 mmol/L (%)	25/17.1	3/6	0.052
WHO performance status $\geqslant$ 3 (%)	50/34.2	16/32	0.772
Bortezomib as initial therapy (%)	77/52.7	26/52	0.928

Ig, Immunoglobulin; ISS, International Staging System; PDW, platelet distribution width; RDW, red blood cell distribution width; CRP, C-reactive protein; WHO, World Health Organization.

1. Introduction

Multiple myeloma (MM) is a disease of the elderly, and the median age at diagnosis is approximately 70 years. The disease is characterized by uncontrolled neoplastic plasma cells proliferation in bone marrow, resulting to the presence of monoclonal paraprotein in the blood or urine or both. Typical clinical symptoms of MM include hypercalcemia, renal failure, anemia and bone lesions. The intrinsic genetic abnormalities in tumor cells and bone marrow microenvironment changes play a pivotal role in MM pathogenesis. MM microenvironment is chiefly harmonized by inflammatory cells, which participated in the process of tumor growth, survival, invasion, and migration [1, 2, 3]. Some inflammatory parameters such as C-reactive protein (CRP) and neutrophil-lymphocyte ratio (NLR) at diagnosis have been reported as prognostic in patients with MM [4, 5].

Red blood cell distribution width (RDW) is a parameter of the complete blood count (CBC) measured automatically by hemocytometers to reflect the heterogeneity of red blood cell dimensions. RDW is regarded as an important inflammatory biomarker [6]. In recent years, accumulating studies have demonstrated that an elevated RDW has a high negative predictive value for outcomes in various cancers [7, 8].

However, there are only a study that has investigated the association between RDW and adverse outcomes in patients with MM [9]. This needs to be confirmed in other patient cohorts. Therefore, we retrospectively analyzed the clinical data of MM patients to evaluate the impact of RDW on the response to treatment and survival.

2. Patients and methods

2.1 Patients

We performed a retrospective analysis of patients with MM who were diagnosed and treated in our Department between January 1, 2007 and December 31, 2015. MM was diagnosed according to the International Myeloma Working Group criteria [10]. Patients with amyloidosis at the time of diagnosis, inflammatory conditions including infections or collagen diseases, previous malignancy, or who had received a blood transfusion within the previous three months were excluded. RDW values at diagnosis were obtained before treatment. Finally, 196 patients were enrolled and followed until December 30, 2016. This retrospective study was approved by the Institutional Review Board of Wuxi People’s Hospital in accordance with the Helsinki Declaration.

2.2 Clinical and laboratory information

The patients’ baseline demographics as well as clinical and laboratory data were obtained from their medical records. Clinical stages were determined based on the International Staging System (ISS) [11]. Treatment responses were evaluated according to the International Myeloma Working Group (IMWG) criteria [12]. RDW was reported as a coefficient of variation (percentage) of red blood cell volume.

Figure 1.

(a) Treatment response in patients with different baseline red blood cell distribution width (RDW) (N $=$ 196) and (b) Baseline RDW in patients treated with bortezomib-based regimens according to treatment response (N $=$ 103).

2.3 Statistical analyses

The collected data were analyzed using SPSS statistical software (version 19.0). Overall survival (OS) was calculated from the time of diagnosis of symptomatic myeloma to the time of death or last follow-up. ROC analysis was used to determine the cut-off value of RDW for OS. The chi-square test and Mann-Whitney test were used for group comparison of categorical variables. Survival was analyzed with Kaplan-Meier curves and survival variables were compared with log-rank test. Prognostic variables for OS were analyzed using the Cox proportional hazards model, and variables with $P<$ 0.2 in univariate analysis were used in the multivariate analysis. A backward selection method was used to remove variables with a $P>$ 0.05. $P$ -values $<$ 0.05 were considered statistically significant.

3. Results

3.1 Patient characteristics

The median age of patients in this study was 65 (range, 33–82) years, and 110 (56.1%) were male. The most prevalent MM type was IgG (47.4%), and 30.1% of patients had IgA disease. Regarding ISS stage, 49.5% of patients had stage III, and 46.9% had stage II disease. The median of pre-treatment RDW level was 15.4% (ranged, 11.7–31.3%), while the normal range for RDW obtained from CBC test in our laboratory was 11.5% to 14.9%. RDW $\geqslant$ 18.05% was selected as the cut-off point based on ROC analysis. The area under the curve for RDW was 0.554 [95% confidence interval (CI): 0.473–0.636]. The patients were grouped as high-RDW ( $\geqslant$ 18.05%) and low-RDW ( $<$ 18.05%). The baseline characteristics of the patients stratified according to the RDW are presented in Table 1. High RDW values were associated with lower platelet count, lower hemoglobin levels, lower albumin levels, and higher lactate dehydrogenase (LDH) level. While patients of low-RDW group presented with renal insufficiency more often when compared to high-RDW group ( $P=$ 0.034).

Table 2
Univariate and Multivariate analysis of factors associated with overall survival

	Univariate analysis		Multivariate analysis
	OR (95% CI)	$P$ Value	OR (95% CI)	$P$ value
Age (yr) $\geqslant$ 70	2.146 (1.084–4.251)	0.029	1.632 (0.789–3.377)	0.186
Men	1.985 (1.114–3.535)	0.020	2.145 (1.170–3.935)	0.014
IgA	1.792 (0.944–3.403)	0.074	1.839 (0.943–3.587)	0.074
ISS III	1.142 (0.647–2.015)	0.647
WHO performance status $\geqslant$ 3	1.164 (0.637–2.129)	0.621
RDW $\geqslant$ 18.05	1.753 (0.890–3.453)	0.104	1.383 (0.669–2.86)	0.381
C-reactive protein $\geqslant$ 10 mg/L	1.096 (0.594–2.021)	0.770
Hemoglobin $<$ 10 g/L	1.496 (0.793–2.822 )	0.213
Platelet $<$ 100 $\times$ 10 ${}^{9}$ /L	1.158 (0.590–2.273)	0.671
Albumin (g/L) $<$ 3.5 g/L	1.750 (0.763–4.013)	0.186	1.036 (0.417–2.573)	0.939
Lactate dehydrogenase $>$ normal	3.304 (1.426–7.654)	0.005	3.991 (1.673–9.523)	0.002
Creatinine $>$ 177 $\mu$ mmol/L	1.641 (0.852–3.160)	0.138	1.399 (0.678–2.888)	0.363
Calcium $>$ 2.75 mmol/L	1.471 (0.659–3.280)	0.344

ISS, international staging system; WHO, World Health Organization; OR, odds ratio; CI, confidence interval.

3.2 Response and RDW

Thirteen (6.6%) patients were administered with MPT (melphalan-prednisolone-thalidomide) or TD(thali-domide-dexamethasone) as an induction regimen. One hundred and three patients (52.6%) were administered with bortezomib-based regimens as induction therapy [13]. Others (40.8%) received the conventional chemotherapy, such as VCMP (vincristine-cyclophosphamide-melphalan-prednisolone), VAD (vincristine-adriamycin-dexamethasone), DVD (vincr- istine-pegylated liposomaldoxorubicin-dexamethas-one). Among the entire cohort, the overall response rates (ORR) were significantly different between the low-RDW and high-RDW groups (94.5% versus 88%, $P=$ 0.019, Fig. 1a). Moreover, the complete response (CR) rate was markedly higher in the low-RDW group compared to the high-RDW group (32.2% versus 12%, $P=$ 0.006, Fig. 1a). In patients treated with bortezomib-based regimens, the groups of CR and Non-CR were distinguished according to RDW. RDW was significant lower in CR patients in comparison to Non-CR subjects ( $P=$ 0.03, Fig. 1b). However, we did not find a significant difference between the RDW in CR and Non-CR groups in patients treated with non-bortezomib regimens ( $P=$ 0.164).

3.3 Impact of RDW on OS

The median follow-up of all patients was 33.5 (range, 1–120) months, and 82 of 196 (41.8%) patients were alive at the time of data collection. The median OS of the entire cohort was estimated as 48 months. The patients with low-RDW at diagnosis had better OS when compared to those with high-RDW (50 and 40 months, $P=$ 0.01; Fig. 2). Results of the univariate and multivariate analysis for the prognostic factors influencing OS were reported in Table 2. In univariate analysis, older age ( $\geqslant$ 70 years), man and LDH level were significantly associated with OS, but not with RDW ( $P=$ 0.104). Multivariate analysis that included all the parameters having a $P$ value of less than 0.2 in the univariate analysis revealed that man and LDH were the independent predictors for OS. While higher RDW at diagnosis was also not an efficacious factor for poor survival.

Figure 2.

Overall survival according to red cell distribution width (RDW) at diagnosis.

4. Discussion

It is recognized that inflammation is a hallmark of cancer and contributes to carcinogenesis, dedifferentiation, and tumor development and progression [14]. RDW has been investigated as prognostic biochemical marker being easily accessible and relatively inexpensive in hematological malignancies, and there has been few studies done [7, 8].

Recently, Podhorecka et al. [15] reported that RDW was in correlation with advanced disease and the presence of other poor prognostic factors in untreated patients with chronic lymphocytic leukemia (CLL). In multivariate analysis, the RDW level was the independent predictors of shorter survival. A study of patients with chronic myeloid leukemia (CML) in the chronic phase (CP) treated with any tyrosine kinase inhibitor (TKI), showed that the 5-year event-free survival (EFS) and transformation-free survival (TFS) rates were lower in high- in comparison to low-RDW group [16]. In another study that investigated patients with diffuse large B cell lymphoma (DLBCL), higher RDW levels were found in patients with advanced clinical stage and in those with poor response to therapy and RDW was an independent prognostic factor for OS and EFS [17].

The current study demonstrated that the patients with high-RDW at diagnosis had shorter OS when compared to those with low-RDW. However, RDW was not an independent predictor for MM survival. Moreover, the ORR and CR rate of initial therapy were markedly higher in the low-RDW group compared to the high-RDW group. Our results were partly consistent with Lee et al. investigations [9].

Anemia is a common clinical symptom in patients with MM. Most of myeloma patients is anemic at the time of diagnosis with hemoglobin levels between 8 and 10 g/dl. Anemia in MM does not only reflect a decrease in erythrocytes number but also be a parameter of inflammation conditions [18]. RDW level can be influenced by anemia. The over production of cytokines in response to inflammatory stress might impair iron metabolism, inhibit erythrocyte maturation and shorten red blood cell survival, thus elevate RDW [18, 19]. RDW might bridge the relationship between inflammation and poorer prognosis in MM. The present data showed that elevated RDW was in correlation with lower hemoglobin and albumin levels, which reflected chronic inflammation and poor nutritional status in patients with MM.

Bortezomib, a reversible proteasome inhibitor, has been shown to be effective for the treatment of both newly diagnosed and relapsed/refractory MM and led to significant improvements in outcomes for these patients. Bortezomib-containing regimens have thus emerged as important therapeutic options for MM patients [20]. However, several patients are intrinsically or become bortezomib-resistant [21]. Recently, it has been reported that cellular iron homeostasis directly correlates with resistance to bortezomib in MM cells [22]. The study confirmed that iron increased the susceptibility of MM cells to bortezomib and that ferritin reduction overcame bortezomib resistance in MM cells [22]. Importantly, iron studies in myeloma-associated anemia have demonstrated low to normal serum iron levels and elevated serum ferritin levels [18]. Bone marrow biopsy also showed an increase in hemosiderin-laden macrophages with normal to increased iron stores [18]. Increasing RDW indicated impaired iron mobilization and release. In our study, bortezomib as initial therapy was the independent predictors for OS and RDW was significant lower in CR in comparison to Non-CR groups in patients treated with bortezomib-based regimens. These results suggested a possible role for risk stratification based on RDW in bortezomib-treated patients.

There were some limitations in this analysis. First, this was a retrospective study in a single center. Progression-free survival (PFS) could not be investigated because of the missing data for the progression time. Second, sample size was comparatively small and the data for the cytogenetic risk factors was not available for most of the patients. Finally, we only focused on RDW level at diagnosis and did not analyze the change of RDW level in other points such as the disease progression and the end of chemotherapy. A single measurement of RDW could not predict OS, which may be influenced by more confounding factors.

In conclusion, the presented study indicated that elevated RDW was associated with worse survival in patients with MM and could predict treatment responses. The stratification of MM patients according to their RDW value would be expected to be more sensitive to the treatment with bortezomib. Future larger, prospective studies are required to confirm the prognostic value of RDW in MM.

Disclosures

The article is not under consideration for publication elsewhere. Publication is approved by all authors. None of the authors have any financial and personal relationships with other people or organizations that could inappropriately influence (bias) their work.

Conflict of interest

The authors declare that they have no conflict of interest.

Footnotes

Acknowledgments

The authors thank all of the doctors and nursing staff of Department of Hematology in Wuxi people’s Hospital for their dedicated patient care.

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Evaluation of pretreatment red cell distribution width in patients with multiple myeloma

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

Table 1 Demographics of multiple myeloma patients by RDW

2. Patients and methods

2.1 Patients

2.2 Clinical and laboratory information

3. Results

3.1 Patient characteristics

Table 2 Univariate and Multivariate analysis of factors associated with overall survival

3.3 Impact of RDW on OS

Disclosures

Conflict of interest

Footnotes

Acknowledgments

References

Table 1
Demographics of multiple myeloma patients by RDW

Table 2
Univariate and Multivariate analysis of factors associated with overall survival