Case Control Study Open Access
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Aug 26, 2023; 11(24): 5643-5652
Published online Aug 26, 2023. doi: 10.12998/wjcc.v11.i24.5643
Reduction rate of monoclonal protein as a useful prognostic factor in standard-risk group of newly diagnosed multiple myeloma
Min Liu, Jun-Yu Zhang, Department of Hematology, Lishui Municipal Central Hospital, Lishui 323000, Zhejiang Province, China
ORCID number: Min Liu (0000-0002-8540-5095); Jun-Yu Zhang (0000-0002-1013-8172).
Author contributions: Zhang JY and Liu M contributed equally to this work; Zhang JY designed the research study; Liu M performed the research; Zhang JY and Liu M analyzed the data and wrote the manuscript; all authors have read and approved the final manuscript.
Institutional review board statement: The study was reviewed and approved by the Lishui Central Hospital Institutional Review Board (Approval No. 2020.3).
Conflict-of-interest statement: Both authors have nothing to disclose.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Jun-Yu Zhang, MM, Chief Doctor, Department of Hematology, Lishui Municipal Central Hospital, No. 289 Kuocang Road, Lishui 323000, Zhejiang Province, China. zhangjunyu815@163.com
Received: March 17, 2023
Peer-review started: March 17, 2023
First decision: June 19, 2023
Revised: July 2, 2023
Accepted: August 1, 2023
Article in press: August 1, 2023
Published online: August 26, 2023

Abstract
BACKGROUND

Multiple myeloma (MM) is a common hematologic malignancy that originates from a malignant clone of plasma cells. Solitary plasmacytoma, history of diabetes, and platelet count are considered as prognostic factors for MM. But some patients are still associated with much worse outcomes without any prognostic predictors. This study aimed to observe the reduction rate of monoclonal protein (M protein) after the first and fourth chemotherapy cycles, which is considered as a new prognostic factor for progression-free survival (PFS) in standard-risk group of newly diagnosed MM patients.

AIM

To investigate the reduction rate of M protein after first and fourth cycle chemotherapy as a useful prognostic factor.

METHODS

A total of 316 patients diagnosed with MM for the first time between 2010 and 2019 at the Lishui Municipal Central Hospital were included. All patients were diagnosed according to the National Comprehensive Cancer Network (NCCN) 2020.V1 diagnostic criteria. The risk assessment was performed by the Mayo Stratification for Macroglobulinemia and Risk-Adapted Therapy guidelines. After diagnosis, 164 patients were evaluated and underwent treatment with four to eight courses of continuous induction chemotherapy. The patients with no response after induction treatment were administered additional therapy following the NCCN 2020.V1 criteria. The following baseline data from the patients were collected: Gender, age at diagnosis, Durie-Salmon stage, glutamic-pyruvic transaminase, glutamic-oxaloacetic transaminase, catabolite activator protein, albumin/globulin ratio, lactate dehydrogenase, translocation (t)(6;14), t(11;14), maintenance regimen, total cholesterol (TC), triglyceride, and phosphorous. All baseline data and the reduction rate of M protein after each chemotherapy cycle from the first to fourth were assessed by univariate analysis. The factors influencing the overall survival and PFS were then assessed by multivariate analysis. We found the first cycle (C1) reduction rate and the fourth cycle (C4) reduction rate as predictors of PFS. Then, PFS was compared between patients with a C1 reduction rate of M protein of ≥ 25% vs < 25% and ≥ 50% vs < 50%, and between patients with a C4 reduction rate of ≥ 25% vs < 25%, ≥ 50% vs < 50%, and ≥ 75% vs < 75%.

RESULTS

Multivariate analysis revealed age [hazard ratio (HR): 1.059, 95% confidence interval (95%CI): 1.033-1.085, P ≤ 0.001], International Staging System stage (HR: 2.136, 95%CI: 1.500-3.041, P ≤ 0.001), autotransplantion (HR: 0.201, 95%CI: 0.069-0.583, P = 0.019), TC (HR: 0.689, 95%CI: 0.533-0.891, P = 0.019), C1 reduction rate (HR: 0474, 95%CI: 0.293-0.767, P = 0.019), and C4 reduction rate (HR: 0.254, 95%CI: 0.139-0.463, P = 0.019) as predictors of PFS. The Kaplan-Meier survival analysis and the log-rank tests revealed that a higher reduction rate of M protein after first cycle (≥ 50%) and fourth cycle (≥ 75%) chemotherapy was associated with a longer PFS than the lower one.

CONCLUSION

Higher reduction rates of M protein after the first and fourth chemotherapy cycles can act as advantageous prognostic factors for PFS in standard-risk group of MM patients during initial diagnosis.

Key Words: Multiple myeloma, Monoclonal protein, Progression-free survival, Chemotherapy

Core Tip: Multiple myeloma (MM) is a common hematologic malignancy that originates from a malignant clone of plasma cells. Solitary plasmacytoma, history of diabetes, and platelet count are considered as prognostic factors for MM. But some patients are still associated with much worse outcomes without any prognostic predictors. This study aimed to observe the reduction rate of monoclonal protein after the first and fourth chemotherapy cycles, which is considered as a new prognostic factor for progression-free survival in standard-risk group of newly diagnosed MM patients.



INTRODUCTION

Multiple myeloma (MM) is the second common hematologic malignancy that originates from B cells, and accounted for approximately 1.8% of all malignancies and led to the death of 30000 patients in 2018[1]. MM can cause kidney injury, anemia, lytic bone disease, hypercalcemia, abnormal functioning of blood coagulation, and damage of other organs[2]. Bone pain is the most common symptom that significantly impairs the quality of life in approximately 60% of patients[3]. Over the past decade, many studies have revealed nonoverlapping and overlapping genetic abnormalities in the myeloma cells and also demonstrated their impact on patient outcomes[4,5]. Del17p, translocation (t)(4;14), t(14;16), and t(14; 20) were considered as predictors of significantly shortened survival in patients with newly diagnosed MM[6-9]. In addition, according to geriatric assessment[10], due to the absence of high-risk cytogenetic abnormalities[11], both the International Staging System (ISS) and the Revised-ISS (R-ISS) were used as prognostic factors for the overall survival (OS) and progression-free survival (PFS) in patients. And ISS 1 and R-ISS 1 patients had a significantly longer PFS and OS[12], while conventional factors such as age below 80 years, beta-2-microglobulin levels, normal hemoglobin, and normal lactate dehydrogenase (LDH) levels were identified as predictors of PFS and OS[13,14]. However, the median survival of patients with MM showed great improvement after undergoing chemotherapy, which consists of proteasome inhibitors, immunomodulatory drugs, and monoclonal antibodies[15], while few patients without these predictors still demonstrated poorer outcomes. Our research revealed that the reduction rate of monoclonal protein (M protein) after the first and fourth chemotherapy cycles could act as a new advantageous prognostic factor for PFS in standard-risk group of MM patients during initial diagnosis.

MATERIALS AND METHODS

A total of 316 patients diagnosed with MM for the first time between 2010 and 2019 at the Lishui Municipal Central Hospital were included. All patients were diagnosed according to the National Comprehensive Cancer Network (NCCN) 2020.V1 diagnostic criteria. The risk assessment was performed by the Mayo Stratification of Myeloma and Risk-adapted Therapy guidelines. After diagnosis, 164 patients were evaluated and underwent treatment with four to eight cycles of continuous induction chemotherapy. The patients with no response after induction treatment were administered additional therapy following the NCCN 2020.V1 criteria. The following baseline data from the patients were collected: Gender, age at diagnosis, Durie-Salmon (DS) stage, glutamic-pyruvic transaminase (GPT), glutamic-oxaloacetic transaminase (GOT), catabolite activator protein (CRP), albumin/globulin ratio, LDH, t(6;14), t(11;14), maintenance regimen, total cholesterol (TC), triglyceride (TG), and phosphorous (P). All baseline data and the reduction rate of M protein after each chemotherapy cycle from the first to the fourth were assessed by univariate analysis. The factors influencing the OS and PFS were then assessed by multivariate analysis. We found the first cycle (C1) reduction rate and the fourth cycle (C4) reduction rate as predictors of PFS. Then, PFS was compared between patients with a C1 reduction rate of M protein of ≥ 25% vs < 25% and ≥ 50% and < 50%, and betweeb patients with a C4 reduction rate of ≥ 25% vs < 25%, ≥ 50% vs < 50%, and ≥ 75% vs < 75%.

RESULTS
Patient characteristics

We retrospectively analyzed data from a total of 164 patients in this study, and all patients underwent treatment with four to eight cycles of continuous induction chemotherapy. The median observation time was 48.4 mo (range, 9-114 mo). The baseline characteristics for 164 MM patients diagnosed for the first time based on the reduction rate of M protein after first and fourth chemotherapy cycles are presented in Table 1. There were no significant differences in gender, DS stage, GPT, GOT, CRP, LDH, t(6;14), t(11;14), maintenance regimen, TC, TG, and P concentrations between the groups with different reduction rates of M protein after the first and fourth chemotherapy cycles (Table 1).

Table 1 Baseline characteristics of multiple myeloma patients with a reduction rate of monoclonal protein after first and fourth cycles of chemotherapy.
CharacteristicC1 reduction rate
P valueC4 reduction rate
P value
< 50
≥ 50
< 75
≥ 75
Age (yr)≤ 0.0010.003
    < 6525562160
    ≥ 6549344043
Gender0.9120.903
    Male36433742
    Female38473946
ISS stage≤ 0.001≤ 0.001
    I539242
    II31342342
    III38173619
DS stage0.0870.783
    I1111
    II720919
    III66705183
GPT0.6570.985
    ≤ 4071855898
    > 403535
GOT0.5100.617
    ≤ 4067845794
    > 407649
CRP0.7040.880
    ≤ 1053624283
    > 1021281920
A/G0.9160.041
    ≤ 0.529361847
    > 0.545544356
LDH0.2150.530
    ≤ 24554734682
    > 24520171521
t(6;14)331.000240.405
t(11;14)221.000130.615
Platelet count≤ 0.001≤ 0.001
    ≥ 10055884598
    < 100192165
Herpes13190.569923
Autotransplantation5200.0065200.020
TC (mmol/L)0.9030.767
    < 5.263765286
    ≥ 5.21114917
TG (mmol/L)0.5460.778
    < 1.7151584167
    ≥ 1.7123322036
P (mmol/L)0.5870.568
    < 1.0717241326
    ≥ 1.0757664877
Prognostic impact of reduction rate of M protein after first and fourth cycle chemotherapy for standard-risk group of newly diagnosed MM

Table 2 shows the results of the univariate analysis of the factors influencing the OS and PFS. Multivariate analysis revealed age [hazard ratio (HR): 1.059, 95% confidence interval (95%CI): 1.033-1.085, P ≤ 0.001], ISS stage (HR: 2.136, 95%CI: 1.500-3.041, P ≤ 0.001), autotransplantion (HR: 0.201, 95%CI: 0.069-0.583, P = 0.019), TC (HR: 0.689, 95%CI: 0.533-0.891, P = 0.019), C1 reduction rate (HR: 0474, 95%CI: 0.293-0.767, P = 0.019), and C4 reduction rate (HR: 0.254, 95%CI: 0.139-0.463, P = 0.019) as predictors of PFS (Table 3).

Table 2 Univariate analysis of progression-free survival and overall survival.
Prognostic factorPFS
OS
HR (95%CI)
P value
HR (95%CI)
P value
Age (yr)1.051 (1.031-1.071)≤ 0.0011.034 (1.012-1.055)0.002
Gender1.265 (0.828-1.931)0.2771.412 (0.926-2.152)0.109
Classification1.037 (0.949-1.132)1.0371.093 (0.999-1.196)0.053
ISS stage1.718 (1.247-2.366)0.0012.093 (1.520-2.883)≤ 0.001
DS stage2.094 (1.082-4.054)0.0281.982 (1.015-3.869)0.045
GPT1.011 (1.002-1.021)0.0191.009 (0.999-1.019)0.082
GOT1.022 (1.011-1.033)≤ 0.0011.025 (1.013-1.038)≤ 0.001
CRP1.002 (0.996-1.007)0.5931.002 (0.996-1.008)0.491
A/G1.041 (0.698-1.553)0.8441.149 (0.754-1.751)0.518
LDH1.003 (1.001-1.004)≤ 0.0011.003 (1.002-1.005)≤ 0.001
t(6;14)1.021 (0.319-3.266)0.9721.285 (0.399-4.134)0.674
t(11;14)1.149 (0.281-4.708)0.8471.188 (0.290-4.871)0.811
Platelet count9.604 (4.965-18.578)≤ 0.0018.437 (4.528-15.721)≤ 0.001
Herpes0.821 (0.451-1.495)0.520.908 (0.498-1.653)0.751
Chemotherapy regimen1.005 (0.856-1.180)0.9520.949 (0.795-1.133)0.564
Autotransplantation0.339 (0.137-0.842)0.0200.347 (0.140-0.860)0.022
TC0.773 (0.631-0.947)0.0130.757 (0.617-0.927)0.007
TG0.861 (0.666-1.114)0.2550.846 (0.642-1.113)0.232
P1.143 (0.953-1.370)0.151.113 (0.934-1.325)0.232
C1 reduction rate0.412 (0.325-0.521)≤ 0.0010.438 (0.346-0.554)≤ 0.001
C2 reduction rate0.412 (0.325-0.523)≤ 0.0010.441 (0.351-0.553)≤ 0.001
C3 reduction rate0.390 (0.303-0.501)≤ 0.0010.377 (0.290-0.490)≤ 0.001
C4 reduction rate0.358 (0.283-0.455)≤ 0.0010.345 (0.267-0.445)≤ 0.001
Table 3 Multivariate analysis of progression-free survival.
Prognostic factor
HR (95%CI)
P value
Age1.059 (1.033-1.085)≤ 0.001
ISS stage2.136 (1.500-3.041)≤ 0.001
DS stage1.622 (0.264-1.622)0.264
GPT1.017 (0.997-1.036)0.097
GOT1.002 (0.977-1.028)0.857
LDH1.000 (0.997-1.003)0.944
Platelet count1.880 (0.732-4.830)0.189
Maintenance regimen0.410 (0.236-0.710)0.001
Autotransplantation0.201 (0.069-0.583)0.003
TC0.689 (0.533-0.891)0.005
C1 reduction rate0.474 (0.293-0.767)0.002
C2 reduction rate0.792 (0.440-1.427)0.438
C3 reduction rate1.974 (0.921-4.230)0.08
C4 reduction rate0.254 (0.139-0.463)≤ 0.001

The Kaplan-Meier survive analysis and the log-rank tests revealed that there was no difference in PFS between patients with a C1 reduction rate of M protein of ≥ 25% vs < 25% (P = 0.319), but there was a significant difference between patients with a C1 reduction rate of M protein of ≥ 50% vs < 50% (P ≤ 0.001) (Figure 1). PFS did not differ significantly between patients with a C4 reduction rate of M protein of ≥ 25% vs < 25% (P = 0.248) and ≥ 50% vs < 50% (P = 0.228), but it had a significant difference between patients with a C4 reduction rate of ≥ 75% vs < 75% (P ≤ 0.001) (Figure 2).

Figure 1
Figure 1 Kaplan-Meier analysis of progression-free survival of patients with different reduction rates of monoclonal protein after the first cycle of chemotherapy (P < 0.001). A: Progression-free survival (PFS) of patients with a reduction rate of monoclonal protein (M protein) after first chemotherapy of ≥ 25% vs < 25%; B: PFS of patients with a reduction rate of M protein after first chemotherapy of ≥ 50% vs < 50%. PFS: Progression-free survival.
Figure 2
Figure 2 Kaplan-Meier analysis of progression-free survival of patients with different reduction rates of monoclonal protein after the fourth cycle of chemotherapy (P < 0.001). A: Progression-free survival (PFS) of patients with a reduction rate of monoclonal protein (M protein) after the fourth chemotherapy cycle of ≥ 25% vs < 25%; B: PFS of patients with a reduction rate of M protein after fourth chemotherapy of ≥ 50% vs < 50%; C: PFS of patients with a reduction rate of M protein after fourth chemotherapy of ≥ 75% vs < 75%. PFS: Progression-free survival.

Age (HR: 1.054, 95%CI: 1.027-1.081, P = 0.024), ISS stage (HR: 1.879, 95%CI: 1.315-2.686, P = 0.001), platelet count (HR: 2.929, 95%CI: 1.269-6.756, P = 0.012), autotransplantion (HR: 0.211, 95%CI: 0.069-0.647, P = 0.006), and TC (HR: 0.735, 95%CI: 0.573-0.943, P = 0.016) were identified as predictors of OS (Table 4).

Table 4 Multivariate analysis of overall survival.
Prognostic factor
HR (95%CI)
P value
ISS stage1.879 (1.315-2.686)0.001
Age1.054 (1.027-1.081)0.024
DS stage1.829 (0.791-4.233)0.158
GOT1.009 (0.988-1.031)0.395
LDH0.998 (0.996-1.001)0.264
Platelet count2.929 (1.269-6.756)0.012
Autotransplantation0.211 (0.069-0.647)0.006
TC0.735 (0.573-0.943)0.016
C1 reduction rate0.868 (0.543-1.387)0.553
C2 reduction rate0.680 (0.386-1.197)0.181
C3 reduction rate1.055 (0.592-1.879)0.856
C4 reduction rate0.608 (0.350-1.058)
DISCUSSION

MM is a heterogeneous disease with adverse clinical course, and is characterized by uncontrolled proliferation and accumulation of plasma cells in the bone marrow, which is usually connected with the production of M protein and the differences in the effectiveness of therapeutic strategies and the ability to develop chemoresistance. Risk stratification factors can assist in creating a personalized therapy, thereby improving the treatment outcomes. Prognostic markers such as cytogenetics, molecular biology, and ISS stage showed an association with OS and PFS in MM patients[16]. But there are still many patients with much worse outcomes without any prognostic markers. This study aimed to find more prognostic markers that might help doctors to adjust the therapeutic strategies in time.

M protein refers to monoclonal immunoglobulins or fragments created by abnormal monoclonal B cells or plasma cells to define ISS stage in MM[12]. Its deposition could cause destruction of organs such as the kidneys and skin[17]. The M protein level as a clonal burden is considered to be helpful in predicting the risk of progression of monoclonal gammopathy of undetermined significance (MGUS) to symptomatic diseases[18]. Furthermore, monoclonal gammopathy could affect bone marrow microenvironment, resulting in increased risk of infections, osteoporosis, venous and arterial thrombosis, and bone fractures[18]. In addition, the production of M protein that has autoantibody activity or its deposition in tissues are considered responsible for severe organ damage[18]. González-Calle et al[19] have found Bence-Jones proteinuria as a kind of M protein disorder, and it can act as a tumor burden marker, showing a significant association with the risk of progression to symptomatic progression. Caers et al[20] demonstrated M protein as a significant risk factor in most of the patients with Smoldering MM (SMM) evolving into MM. Another study from Spain revealed that M protein with an increase of ≥ 10% in the first 12 mo of diagnosis was associated with progression to symptomatic MM in 71% of cases at 3 years with a median period of 1.1 year[21]. Gassiot et al[22] found that in patients presenting both a prior MGUS/SMM and partial remission (PR) (PR was defined as a ≥ 90% reduction of urinary M protein in 24 h or < 200 mg per 24 h and a reduction of ≥ 50% of serum M protein) after the first cycle of therapy, the PFS and OS showed significant differences from those of the remaining patients. Another study revealing that a fast response to the first treatment cycle in MM patients is the major predictor of long-term response to lenalidomide and dexamethasone therapy also supported the same concept[22]. Atkin et al[23] believed that M protein production is reduced by treatment with chemotherapy, which improved the outcomes of MGUS.

In this retrospective analysis, we found a significant difference in the outcomes between a standard-risk group of newly diagnosed MM patients with a C1 reduction rate of M protein of ≥ 50% vs < 50%, and between those with a C4 reduction rate of M protein of ≥ 75% vs < 75%; the median PFS was 20 mo vs 33 mo and 18 mo vs 30 mo, respectively, showing a significant difference between groups. In multivariate analysis, a higher reduction rate of M protein after the first and fourth chemotherapy cycles was demonstrated to be advantageous factors for PFS, with the reduction rate of M protein after the fourth chemotherapy cycle of ≥ 75% being stronger. Although the reduction rate of M protein after the first and fourth chemotherapy cycles were not identified as independent prognostic factors for OS in multivariate analysis, there is a trend of a longer OS associated with a higher reduction rate of M protein after the fourth chemotherapy cycle (≥ 75%). It has been more than 30 years since chemotherapy was initially combined with autologous stem cell transplantation (ASCT) for the treatment of MM, which remained to be standard care for few patients with newly diagnosed MM[24-26]. Our study also supported this, and ASCT after chemotherapy was regarded as a protective factor for both PFS and OS. This might be one of the reasons for the association of a higher reduction rate of M protein with a longer PFS. After achieving a high reduction rate, more patients will have a chance to undergo ASCT. Furthermore, our study found TC as a protective factor for both PFS and OS. Jafri et al[27] revealed an inverse correlation between cholesterol level and the risk of hematologic malignancy, but the mechanism remains unclear. A previous study revealed that low platelet count is associated with an unfavorable OS[28]. Similar to previous studies, high ISS stage and age were identified as disadvantageous factors for PFS and OS in this study[29-31].

CONCLUSION

Our study have identified new independent prognostic factors for patients with newly diagnosed MM, and a higher reduction rate of M protein after the first chemotherapy cycle (≥ 50%) and the fourth chemotherapy cycle (≥ 75%) is associated with a longer PFS. The high reduction rate of M protein after the fourth chemotherapy cycle is associated with OS. To our knowledge, this is the first study to analyze the effects of the reduction rate of M protein after chemotherapy in MM patients. The new prognostic factors could help doctors to administer the treatment in time.

ARTICLE HIGHLIGHTS
Research background

Multiple myeloma (MM) is a common hematologic malignancy that originates from a malignant clone of plasma cells. Solitary plasmacytoma, history of diabetes, and platelet count are considered as prognostic factors for MM. But some patients are still associated with much worse outcomes without any prognostic factors.

Research motivation

To study the potential prognostic factors in MM patients.

Research objectives

This study aimed to observe the reduction rate of monoclonal protein (M protein) after the first and fourth chemotherapy cycles, which is considered as a new prognostic factor for progression-free survival (PFS) in standard-risk group of newly diagnosed MM patients.

Research methods

We retrospectively analyzed 164 patients diagnosed with standard-risk MM for the first time, and compared the PFS and overall survival (OS) between patients with a reduction rate of M protein after first chemotherapy of ≥ 50% vs < 50% and between patients with a reduction rate of M protein after the fourth chemotherapy cycle of ≥ 75% vs < 75%.

Research results

Multivariate analysis revealed age [hazard ratio (HR): 1.059, 95% confidence intervals (95%CI): 1.033-1.085, P ≤ 0.001], International Staging System stage (HR: 2.136, 95%CI: 1.500-3.041, P ≤ 0.001), autotransplantion (HR: 0.201, 95%CI: 0.069-0.583, P = 0.019), total cholesterol (HR: 0.689, 95%CI: 0.533-0.891, P = 0.019), the first cycle reduction rate (HR: 0474, 95%CI: 0.293-0.767, P = 0.019), and the fourth cycle reduction rate (HR: 0.254, 95%CI: 0.139-0.463, P = 0.019) as predictors of PFS. The Kaplan-Meier survival analysis and the log-rank tests revealed that a higher reduction rate of M protein after the first cycle (≥ 50%) and fourth cycle (≥ 75%) chemotherapy was associated with a longer PFS than the lower one.

Research conclusions

Our study have identified new prognostic factors for patients with initially diagnosed MM, and a higher reduction rate of M protein after the first chemotherapy cycle (≥ 50%) and the fourth chemotherapy cycle (≥ 75%) is associated with a longer PFS. The high reduction rate of M protein after the fourth chemotherapy cycle could is associated with the OS.

Research perspectives

To our knowledge, this is the first study to analyze the effects of the reduction rate of M protein after chemotherapy in MM patients. The new prognostic factors could help doctors to administer the treatment in time.

Footnotes

Provenance and peer review: Unsolicited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Medicine, research and experimental

Country/Territory of origin: China

Peer-review report’s scientific quality classification

Grade A (Excellent): 0

Grade B (Very good): 0

Grade C (Good): C

Grade D (Fair): 0

Grade E (Poor): 0

P-Reviewer: Roganovic J, Croatia S-Editor: Lin C L-Editor: Wang TQ P-Editor: Zhang YL

References
1.  Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin. 2018;68:7-30.  [PubMed]  [DOI]  [Cited in This Article: ]
2.  Rajkumar SV, Kumar S. Multiple Myeloma: Diagnosis and Treatment. Mayo Clin Proc. 2016;91:101-119.  [PubMed]  [DOI]  [Cited in This Article: ]
3.  Kyle RA, Gertz MA, Witzig TE, Lust JA, Lacy MQ, Dispenzieri A, Fonseca R, Rajkumar SV, Offord JR, Larson DR, Plevak ME, Therneau TM, Greipp PR. Review of 1027 patients with newly diagnosed multiple myeloma. Mayo Clin Proc. 2003;78:21-33.  [PubMed]  [DOI]  [Cited in This Article: ]
4.  Fonseca R, Bergsagel PL, Drach J, Shaughnessy J, Gutierrez N, Stewart AK, Morgan G, Van Ness B, Chesi M, Minvielle S, Neri A, Barlogie B, Kuehl WM, Liebisch P, Davies F, Chen-Kiang S, Durie BG, Carrasco R, Sezer O, Reiman T, Pilarski L, Avet-Loiseau H; International Myeloma Working Group. International Myeloma Working Group molecular classification of multiple myeloma: spotlight review. Leukemia. 2009;23:2210-2221.  [PubMed]  [DOI]  [Cited in This Article: ]
5.  Avet-Loiseau H, Attal M, Moreau P, Charbonnel C, Garban F, Hulin C, Leyvraz S, Michallet M, Yakoub-Agha I, Garderet L, Marit G, Michaux L, Voillat L, Renaud M, Grosbois B, Guillerm G, Benboubker L, Monconduit M, Thieblemont C, Casassus P, Caillot D, Stoppa AM, Sotto JJ, Wetterwald M, Dumontet C, Fuzibet JG, Azais I, Dorvaux V, Zandecki M, Bataille R, Minvielle S, Harousseau JL, Facon T, Mathiot C. Genetic abnormalities and survival in multiple myeloma: the experience of the Intergroupe Francophone du Myélome. Blood. 2007;109:3489-3495.  [PubMed]  [DOI]  [Cited in This Article: ]
6.  Dispenzieri A, Rajkumar SV, Gertz MA, Fonseca R, Lacy MQ, Bergsagel PL, Kyle RA, Greipp PR, Witzig TE, Reeder CB, Lust JA, Russell SJ, Hayman SR, Roy V, Kumar S, Zeldenrust SR, Dalton RJ, Stewart AK. Treatment of newly diagnosed multiple myeloma based on Mayo Stratification of Myeloma and Risk-adapted Therapy (mSMART): consensus statement. Mayo Clin Proc. 2007;82:323-341.  [PubMed]  [DOI]  [Cited in This Article: ]
7.  Stewart AK, Bergsagel PL, Greipp PR, Dispenzieri A, Gertz MA, Hayman SR, Kumar S, Lacy MQ, Lust JA, Russell SJ, Witzig TE, Zeldenrust SR, Dingli D, Reeder CB, Roy V, Kyle RA, Rajkumar SV, Fonseca R. A practical guide to defining high-risk myeloma for clinical trials, patient counseling and choice of therapy. Leukemia. 2007;21:529-534.  [PubMed]  [DOI]  [Cited in This Article: ]
8.  Rajkumar SV. Multiple myeloma: 2012 update on diagnosis, risk-stratification, and management. Am J Hematol. 2012;87:78-88.  [PubMed]  [DOI]  [Cited in This Article: ]
9.  Avet-Loiseau H, Hulin C, Campion L, Rodon P, Marit G, Attal M, Royer B, Dib M, Voillat L, Bouscary D, Caillot D, Wetterwald M, Pegourie B, Lepeu G, Corront B, Karlin L, Stoppa AM, Fuzibet JG, Delbrel X, Guilhot F, Kolb B, Decaux O, Lamy T, Garderet L, Allangba O, Lifermann F, Anglaret B, Moreau P, Harousseau JL, Facon T. Chromosomal abnormalities are major prognostic factors in elderly patients with multiple myeloma: the intergroupe francophone du myélome experience. J Clin Oncol. 2013;31:2806-2809.  [PubMed]  [DOI]  [Cited in This Article: ]
10.  Palumbo A, Bringhen S, Mateos MV, Larocca A, Facon T, Kumar SK, Offidani M, McCarthy P, Evangelista A, Lonial S, Zweegman S, Musto P, Terpos E, Belch A, Hajek R, Ludwig H, Stewart AK, Moreau P, Anderson K, Einsele H, Durie BGM, Dimopoulos MA, Landgren O, Miguel JFS, Richardson P, Sonneveld P, Rajkumar SV. Geriatric assessment predicts survival and toxicities in elderly myeloma patients: an International Myeloma Working Group report. Blood. 2015;125:2068-2074.  [PubMed]  [DOI]  [Cited in This Article: ]
11.  Gutiérrez NC, Castellanos MV, Martín ML, Mateos MV, Hernández JM, Fernández M, Carrera D, Rosiñol L, Ribera JM, Ojanguren JM, Palomera L, Gardella S, Escoda L, Hernández-Boluda JC, Bello JL, de la Rubia J, Lahuerta JJ, San Miguel JF; GEM/PETHEMA Spanish Group. Prognostic and biological implications of genetic abnormalities in multiple myeloma undergoing autologous stem cell transplantation: t(4;14) is the most relevant adverse prognostic factor, whereas RB deletion as a unique abnormality is not associated with adverse prognosis. Leukemia. 2007;21:143-150.  [PubMed]  [DOI]  [Cited in This Article: ]
12.  Greipp PR, San Miguel J, Durie BG, Crowley JJ, Barlogie B, Bladé J, Boccadoro M, Child JA, Avet-Loiseau H, Kyle RA, Lahuerta JJ, Ludwig H, Morgan G, Powles R, Shimizu K, Shustik C, Sonneveld P, Tosi P, Turesson I, Westin J. International staging system for multiple myeloma. J Clin Oncol. 2005;23:3412-3420.  [PubMed]  [DOI]  [Cited in This Article: ]
13.  Ludwig H, Durie BG, Bolejack V, Turesson I, Kyle RA, Blade J, Fonseca R, Dimopoulos M, Shimizu K, San Miguel J, Westin J, Harousseau JL, Beksac M, Boccadoro M, Palumbo A, Barlogie B, Shustik C, Cavo M, Greipp PR, Joshua D, Attal M, Sonneveld P, Crowley J. Myeloma in patients younger than age 50 years presents with more favorable features and shows better survival: an analysis of 10 549 patients from the International Myeloma Working Group. Blood. 2008;111:4039-4047.  [PubMed]  [DOI]  [Cited in This Article: ]
14.  Stella-Holowiecka B, Czerw T, Holowiecka-Goral A, Giebel S, Wojnar J, Holowiecki J. Beta-2-microglobulin level predicts outcome following autologous hematopoietic stem cell transplantation in patients with multiple myeloma. Transplant Proc. 2007;39:2893-2897.  [PubMed]  [DOI]  [Cited in This Article: ]
15.  Palumbo A, Anderson K. Multiple myeloma. N Engl J Med. 2011;364:1046-1060.  [PubMed]  [DOI]  [Cited in This Article: ]
16.  Kumar SK, Rajkumar SV. The multiple myelomas - current concepts in cytogenetic classification and therapy. Nat Rev Clin Oncol. 2018;15:409-421.  [PubMed]  [DOI]  [Cited in This Article: ]
17.  Sethi S, Fervenza FC, Rajkumar SV. Spectrum of manifestations of monoclonal gammopathy-associated renal lesions. Curr Opin Nephrol Hypertens. 2016;25:127-137.  [PubMed]  [DOI]  [Cited in This Article: ]
18.  van de Donk NW, Palumbo A, Johnsen HE, Engelhardt M, Gay F, Gregersen H, Hajek R, Kleber M, Ludwig H, Morgan G, Musto P, Plesner T, Sezer O, Terpos E, Waage A, Zweegman S, Einsele H, Sonneveld P, Lokhorst HM; European Myeloma Network. The clinical relevance and management of monoclonal gammopathy of undetermined significance and related disorders: recommendations from the European Myeloma Network. Haematologica. 2014;99:984-996.  [PubMed]  [DOI]  [Cited in This Article: ]
19.  González-Calle V, Dávila J, Escalante F, de Coca AG, Aguilera C, López R, Bárez A, Alonso JM, Hernández R, Hernández JM, de la Fuente P, Puig N, Ocio EM, Gutiérrez NC, García-Sanz R, Mateos MV. Bence Jones proteinuria in smoldering multiple myeloma as a predictor marker of progression to symptomatic multiple myeloma. Leukemia. 2016;30:2026-2031.  [PubMed]  [DOI]  [Cited in This Article: ]
20.  Caers J, Fernández de Larrea C, Leleu X, Heusschen R, Zojer N, Decaux O, Kastritis E, Minnema M, Jurczyszyn A, Beguin Y, Wäsch R, Palumbo A, Dimopoulos M, Mateos MV, Ludwig H, Engelhardt M. The Changing Landscape of Smoldering Multiple Myeloma: A European Perspective. Oncologist. 2016;21:333-342.  [PubMed]  [DOI]  [Cited in This Article: ]
21.  Fernández de Larrea C, Isola I, Pereira A, Cibeira MT, Magnano L, Tovar N, Rodríguez-Lobato LG, Calvo X, Aróstegui JI, Díaz T, Lozano E, Rozman M, Yagüe J, Bladé J, Rosiñol L. Evolving M-protein pattern in patients with smoldering multiple myeloma: impact on early progression. Leukemia. 2018;32:1427-1434.  [PubMed]  [DOI]  [Cited in This Article: ]
22.  Gassiot S, González Y, Morgades M, Motlló C, Clapés V, Maluquer C, Ibarra G, Abril L, Ribera JM, Oriol A. Response to First Cycle Is the Major Predictor of Long-Term Response to Lenalidomide and Dexamethasone Therapy in Relapsed and Refractory Multiple Myeloma: Can We Spare Patients the Toxicity and Costs of Additional Agents? Clin Lymphoma Myeloma Leuk. 2019;19:585-592.e1.  [PubMed]  [DOI]  [Cited in This Article: ]
23.  Atkin C, Richter A, Sapey E. What is the significance of monoclonal gammopathy of undetermined significance? Clin Med (Lond). 2018;18:391-396.  [PubMed]  [DOI]  [Cited in This Article: ]
24.  Choi T. Is autologous stem cell transplantation still relevant for multiple myeloma? Curr Opin Hematol. 2019;26:386-391.  [PubMed]  [DOI]  [Cited in This Article: ]
25.  Al Hamed R, Bazarbachi AH, Malard F, Harousseau JL, Mohty M. Current status of autologous stem cell transplantation for multiple myeloma. Blood Cancer J. 2019;9:44.  [PubMed]  [DOI]  [Cited in This Article: ]
26.  Soekojo CY, Kumar SK. Stem-cell transplantation in multiple myeloma: how far have we come? Ther Adv Hematol. 2019;10:2040620719888111.  [PubMed]  [DOI]  [Cited in This Article: ]
27.  Jafri H, Alsheikh-Ali AA, Karas RH. Baseline and on-treatment high-density lipoprotein cholesterol and the risk of cancer in randomized controlled trials of lipid-altering therapy. J Am Coll Cardiol. 2010;55:2846-2854.  [PubMed]  [DOI]  [Cited in This Article: ]
28.  Kim DS, Yu ES, Kang KW, Lee SR, Park Y, Sung HJ, Choi CW, Kim BS. Myeloma prognostic index at diagnosis might be a prognostic marker in patients newly diagnosed with multiple myeloma. Korean J Intern Med. 2017;32:711-721.  [PubMed]  [DOI]  [Cited in This Article: ]
29.  Sørrig R, Klausen TW, Salomo M, Vangsted AJ, Frølund UC, Andersen KT, Klostergaard A, Helleberg C, Pedersen RS, Pedersen PT, Helm-Petersen S, Teodorescu EM, Preiss B, Abildgaard N, Gimsing P; Danish Myeloma Study Group. Immunoparesis in newly diagnosed Multiple Myeloma patients: Effects on overall survival and progression free survival in the Danish population. PLoS One. 2017;12:e0188988.  [PubMed]  [DOI]  [Cited in This Article: ]
30.  Andriandi, Kamal AF. Survival rate of multiple myeloma patients in Indonesia: A retrospective study in multiple myeloma at a single institution. Ann Med Surg (Lond). 2019;41:11-15.  [PubMed]  [DOI]  [Cited in This Article: ]
31.  Chretien ML, Hebraud B, Cances-Lauwers V, Hulin C, Marit G, Leleu X, Karlin L, Roussel M, Stoppa AM, Guilhot F, Lamy T, Garderet L, Pegourie B, Dib M, Sebban C, Lenain P, Brechignac S, Royer B, Wetterwald M, Legros L, Orsini-Piocelle F, Voillat L, Delbrel X, Caillot D, Macro M, Facon T, Attal M, Moreau P, Avet-Loiseau H, Corre J. Age is a prognostic factor even among patients with multiple myeloma younger than 66 years treated with high-dose melphalan: the IFM experience on 2316 patients. Haematologica. 2014;99:1236-1238.  [PubMed]  [DOI]  [Cited in This Article: ]