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. 2025 Sep 24;19:11795549251377882. doi: 10.1177/11795549251377882

Comparative Analysis of Primary and Second Primary Multiple Myeloma: A Propensity Score-Matched Study

Yoon Jung Jang 1,*, Joonseog Kong 2,*, Heyjin Kim 3, Chulkue Pak 1,4, Im Il Na 1, Hyo-Rak Lee 1, Hye Jin Kang 1,5,
PMCID: PMC12461090  PMID: 41019013

Abstract

Background:

With the increasing number of cancer survivors, second primary malignancies (SPMs) are attracting clinical interest. Although SPMs following multiple myeloma (MM) have been studied, data on second primary multiple myeloma (SPMM) remain limited. This study aimed to compare the clinical characteristics and outcomes of SPMM with those of primary MM through a retrospective analysis.

Methods:

We retrospectively reviewed 183 patients with primary MM and 12 patients with SPMM treated at a single center between 2003 and 2022. To reduce selection bias, propensity score matching (1:3) was performed based on age, sex, year of MM diagnosis, and International Staging System stage. Survival outcomes were assessed using Kaplan–Meier analysis and Cox proportional hazards models.

Results:

After matching, 48 patients (36 with primary MM and 12 with SPMM) were included in the final analysis. At the time of MM diagnosis, 83.3% of patients with SPMM had achieved complete remission of their primary malignancy. All but one received standard MM treatment. The median overall survival (OS) was 45.1 months for the primary MM group and 41.5 months for the SPMM group. There was no statistically significant difference in OS between the groups (hazard ratio: 0.72; 95% confidence interval: 0.33-1.56).

Conclusions:

Patients with SPMM, most of whom had well-controlled primary cancers, received active treatment and demonstrated clinical outcomes not significantly different from those with primary MM. These findings support the use of aggressive treatment strategies for SPMM. Larger prospective studies are warranted to establish optimal treatment strategies.

Keywords: Second primary multiple myeloma, primary multiple myeloma, secondary malignancy, survival outcomes, propensity score matching

Introduction

Recent advancements in cancer treatments have significantly improved survival rates across a broad spectrum of malignancies. As long-term survival becomes more common, attention has increasingly shifted toward the late effects of cancer treatment, particularly the development of second primary malignancies (SPMs). SPMs are defined as distinct neoplasms that occur either synchronously or metachronously in individuals who have survived a first primary malignancy. 1 The reported incidence of SPMs ranges from 7.04% to approximately 20%, with prior exposure to chemotherapy or radiotherapy, as well as genetic predisposition, recognized as major contributing factors.2-5

Multiple myeloma (MM) is a malignant plasma cell disorder, with approximately 160,000 new cases and 106,000 deaths estimated annually, worldwide. 6 According to the 2021 Korean cancer statistics, 2018 individuals were newly diagnosed with MM. 7 MM is a multifactorial condition influenced by factors such as advanced age, male sex, African American ethnicity, and occupational and genetic predispositions.8,9

The development of SPMs in MM survivors has been increasingly recognized. Identified risk factors include patient-related characteristics (for example, older age, smoking history, obesity, male sex, and ethnicity), disease-related mechanisms (notably clonal hematopoiesis), and treatment-related exposures (e.g., alkylating agents, radiation therapy, lenalidomide, and bortezomib).10,11 Recent studies have reported the incidence, risk stratification, and outcomes of SPMs in MM survivors, underscoring the need for ongoing surveillance.12-14 However, only a limited number of retrospective studies have examined second primary multiple myeloma (SPMM) that developed after other primary cancers.15,16 This study aimed to investigate the clinical characteristics and outcomes of patients with SPMM in comparison to those with primary MM.

Methods

Study design and patient selection

We conducted a retrospective analysis of patients diagnosed and treated for MM at Korea Cancer Center Hospital between January 2003 and December 2022. Eligible cases were selected consecutively during the study period based on predefined inclusion and exclusion criteria. Primary MM was defined as a pathologically confirmed diagnosis of MM. SPMM was defined as MM diagnosed either synchronously or metachronously in individuals with a history of a prior primary malignancy. Patients without pathological confirmation or those diagnosed without a treatment plan were excluded. Patients with missing data for key variables were excluded from the corresponding analyses. In total, 183 patients with primary MM and 12 patients with SPMM were included in the study. This study adheres to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for observational studies. A completed STROBE checklist is provided as Supplementary File 1. 17

Propensity score matching and statistical analysis

To reduce potential confounding and improve comparability between the 2 groups, propensity score matching was performed using a 1:3 nearest-neighbor algorithm without replacement and with a caliper width of 0.1. The propensity scores were calculated based on sex, age, year of MM diagnosis, and International Staging System (ISS) stage. Balance between groups before and after matching was assessed using absolute standardized mean differences (SMDs), with values below 0.1 indicating acceptable balance. 18 Categorical variables were presented as frequencies and percentages, while continuous variables were reported as medians with ranges. Group comparisons were performed using Fisher’s exact or chi-square tests, as appropriate, for categorical variables. Survival outcomes were evaluated using Kaplan–Meier curves, and comparisons between groups were made using the Cox proportional hazards model. All statistical analyses were conducted using the R software version 4.1.2 (R Core Team).

Outcome measures

The primary objective of this study was to compare the clinical characteristics and survival outcomes between patients with primary MM and those with SPMM. Treatment response was assessed according to the criteria established by the International Myeloma Working Group.19,20 Progression-free survival (PFS) was defined as the time from the diagnosis of MM to either disease progression or death from any cause, whichever occurred first. Overall survival (OS) was defined as the time from MM diagnosis to death from any cause. Survival outcomes were compared between the propensity score–matched primary MM and SPMM groups using Cox proportional hazards models, with the SPMM group designated as the reference category for hazard ratio estimation. The data cutoff date for the analysis was November 30, 2024.

Results

Study cohort and baseline characteristics

Between January 2003 and December 2022, 183 patients were diagnosed with primary MM and received treatment planning. Twelve patients developed SPMM following a prior malignancy. After 1:3 propensity score matching, 36 patients with primary MM were selected, resulting in a final cohort of 48 patients for analysis (Figure 1). Baseline characteristics of the matched cohorts are presented in Table 1. The median age at diagnosis was 72 years (range: 53-85), with 22 male patients (45.8%) and 26 female patients (54.2%). According to the ISS, 16 patients (33.0%) were classified as stage I, 21 (43.8%) as stage II, and 11 (22.9%) as stage III. The distribution by year of MM diagnosis was as follows: 14 patients (29.1%) were diagnosed between 2003 and 2010, 7 (14.6%) between 2011 and 2015, 17 (35.4%) between 2016 and 2020, and 10 (20.8%) between 2021 and 2022.

Figure 1.

Diagram of derivation of study population, showing numbers and MM, second primary multiple myeloma.

Diagram of derivation of the study population. MM, multiple myeloma; SPMM, second primary multiple myeloma.

Table 1.

Baseline characteristics of the propensity score-matched cohorts.

Variables Primary MM SPMM Total SMD
Patient number 36 12 48
Sex, n (%)
 Male 16 (44.4%) 6 (50.0%) 22 (45.8%) 0.11
 Female 20 (55.6%) 6 (50.0%) 26 (54.2%) 0.11
Median age at the time of MM diagnosis, years (range) 72 (53-84) 73 (54-85) 72 (53-85) 0.02
Time of MM diagnosis, n (%) 0.03
 2003-2010 11 (30.5%) 3 (25.0%) 14 (29.1%)
 2011-2015 5 (13.9%) 2 (16.6%) 7 (14.6%)
 2016-2021 15 (41.7%) 6 (50.0%) 21 (43.8%)
 2022 5 (13.9%) 1 (8.3%) 6 (12.5%)
ISS Stage, n (%)
 I 12 (33.3%) 4 (33.3%) 16 (33.3%) 0
 II 16 (44.4%) 5 (41.6%) 21 (43.8%) 0.05
 III 8 (22.2%) 3 (25.0%) 11 (22.9%) 0.06

Abbreviations: ISS, International staging system stage; MM, multiple myeloma; SPMM, second primary multiple myeloma; SMD, standardized mean difference.

MM characteristics and treatment

The characteristics and treatment outcomes of MM are summarized in Table 2. Among the 48 patients, the most common MM subtype was IgG (n = 28, 58.3%), followed by IgA (n = 11, 22.9%), and free light chain (n = 8, 16.7%). In the SPMM group, all but one patient had the IgG subtype (P = 0.052). Regarding cytogenetic abnormalities, 8 patients (32.0%) in the primary MM group exhibited trisomy 1q. In the SPMM group, 2 patients had t(4;14), and 2 others had trisomy 1q (33.3%). Hemoglobin levels <10 g/dL were observed in 17 patients (47.2%) in the primary MM group and 8 patients (66.7%) in the SPMM group (P = .404). Hypercalcemia, defined as serum calcium >11 mg/dL, was recorded in 2 patients (5.6%) in the primary MM group and in none of the SPMM group (P = 1.000). Elevated creatinine levels (>2.0 mg/dL) were found in 3 patients each in the the primary MM (8.3%) and SPMM (25.0%) groups (P = .313).

Table 2.

Clinical and laboratory characteristics at the time of multiple myeloma diagnosis.

Variables Total (n = 48) Primary MM (n = 36) SPMM (n = 12) P value
MM Subtype by IFE, n (%) .052
 IgG 28 (58.3%) 17 (47.2%) 11 (91.7%)
 IgA 11 (22.9%) 11 (30.5%) 0 (0.0%)
 Free light chain 8 (16.7%) 7 (19.4%) 1 (8.3%)
 N/A 1 (2.2%) 1 (2.8%) 0 (0.0%)
Cytogenetic features by FISH n = 31 n = 25 n = 6 .030
 Del(17p) 0 (0.0%) 0 (0.0%) 0 (0.0%)
 t(4;14) 3 (9.7%) 1 (4.0%) 2 (33.3%)
 t(11;14) 2 (6.5%) 2 (8.0%) 0 (0.0%)
 Trisomy 1q 10 (32.2%) 8 (32.0%) 2 (33.3%)
 Others 4 (12.9%) 4 (16.0%) 0 (0.0%)
 Negative 12 (38.7%) 10 (40.0%) 2 (33.3%)
 N/A 17 (35.4%) 11 (30.6%) 6 (50.0%)
Hemoglobin (g/dL), <10 25 (52.1%) 17 (47.2%) 8 (66.7%) .404
Calcium (mg/dL), >11 2 (4.2%) 2 (5.6%) 0 (0.0%) 1.000
Creatinine (mg/dL), >2.0 6 (12.5%) 3 (8.3%) 3 (25.0%) .313
Albumin (g/dL), <3.5 20 (41.6%) 11 (30.6%) 9 (75.0%) .018
Beta-2 MG (ug/mL), >3.5 22 (45.8%) 17 (47.2%) 5 (41.7%) 1.000
MM treatment, n (%) n = 46 n = 35 n = 11
 Proteasome inhibitor 25 (54.3%) 20 (57.1%) 6 (54.5%) 1.000
 Immunomodulatory agent 24 (52.1%) 21 (60.0%) 3 (27.3%) .096
 Chemotherapy 28 (60.8%) 19 (52.8%) 9 (81.8%) .310
 ASCT 5 (10.8%) 4 (11.4%) 1 (9.1%) 1.000
 Untreated (N/A) 2 (4.2%) 1 (2.8%) 1 (8.3%)
Best response to first-line treatment in MM n = 46 n = 35 n = 11 .268
 CR 8 (17.3%) 7 (20.0%) 1 (9.1%)
 VGPR 1 (2.2%) 0 (0.0%) 1 (9.1%)
 PR 26 (56.5%) 20 (57.1%) 6 (54.5%)
 SD 6 (13.0%) 5 (14.3%) 1 (9.1%)
 PD 4 (8.7%) 3 (8.6%) 1 (9.1%)
 N/A 1 (2.2%) 0 (0.0%) 1 (9.1%)
Untreated (N/A) 2 (4.2%) 1 (2.8%) 1 (8.3%)

Abbreviations: ASCT, autologous stem cell transplantation; Beta-2 MG, Beta-2 microglobulin; CR, complete response; FISH, fluorescence in situ hybridization; IFE, immuno fixation electrophoresis; MM, multiple myeloma; N/A, not available; PD, progressive disease; PR, partial response; SD, stable disease; SPMM, second primary multiple myeloma; VGPR, very good partial response.

Patients with missing data were not included in statistical comparisons.

Treatment was administered to 35 patients (97.2%) in the primary MM group, and 11 (91.6%) in the SPMM group, with one patient from each group not undergoing treatment. Proteasome inhibitors were administered to 20 patients (57.1%) in the primary MM group and 6 (54.5%) in the SPMM group (P = 1.000). Immunomodulatory agents were administered to 21 patients (60.0%) in the primary MM group and 3 (27.2%) in the SPMM group (P = .096). Chemotherapy was administered to 19 patients (52.8%) in the primary MM group and 9 (81.8%) in the SPMM group (P = .310). Autologous stem cell transplantation (ASCT) was performed in 4 patients (11.1%) in the primary MM group and 1 (8.3%) in the SPMM group (P = 1.000).

The best response to first-line therapy was partial response (PR), achieved by 20 patients (57.1%) with primary MM and 6 (54.5%) with SPMM. Complete response (CR) was observed in 7 patients (20.0%) in the primary MM group and 1 (9.1%) in the SPMM group. Very good partial response (VGPR) was observed in one patient (9.1%) with SPMM but none with primary MM. Stable disease (SD) was recorded in 5 patients (14.3%) in the primary MM group and 1 (9.1%) in the SPMM group. Progressive disease (PD) was observed in 3 patients (8.6%) in the primary MM group and 1 (9.1%) in the SPMM group.

Clinical characteristics and treatment of patients with SPMM

Among the 12 patients with SPMM, the prior primary malignancies included cervical cancer (n = 3, 25.0%), breast cancer (n = 2, 16.7%), colorectal cancer (n = 2, 16.7%), non-small cell lung cancer (NSCLC) (n = 1, 8.3%), myxofibrosarcoma (n = 1, 8.3%), prostate cancer (n = 1, 8.3%), gastric cancer (n = 1, 8.3%), gastrointestinal stromal tumor (GIST) (n = 1, 8.3%), and hypopharyngeal cancer (n = 1, 8.3%) (Table 3). One patient (8.3%) had a history of both colon and hypopharyngeal cancers.

Table 3.

Clinical characteristics and treatment for patients with second primary multiple myeloma.

Serial number Age at diagnosis of primary cancer, years Primary cancer Age at diagnosis of MM Chemotherapy for the treatment of primary cancer Radiotherapy for the treatment of primary cancer Interval between primary cancer and MM diagnosis (months) Primary cancer status at the time of MM diagnosis ISS stage Treatment status of MM Year of diagnosis for MM, Initial treatment regimen for MM ASCT status Current status OS after MM diagnosis
1 76 NSCLC 76 Yes No 5.1 Presence 1 No 2021 No 0 Dead 12.2
2 68 Myxofibrosarcoma 69 No No 18.6 Presence 2 Yes 2021 Rd 0 Alive 36.6
3 53 Breast cancer 54 Yes Yes 8.3 CR 1 Yes 2019 VTD 1 Alive 66.0
4 66 Cervix cancer 70 No No 45.1 CR 1 Yes 2020 VMP 0 Dead 13.9
5 74 Prostate cancer 77 No No 33.8 CR 3 Yes 2016 MPT 0 Dead 0.3
6 67 Cervix cancer 75 Yes yes 90.2 CR 2 Yes 2018 VMP 0 Dead 42.6
7 63 Gastric cancer 66 No No 47.5 CR 2 Yes 2015 VMP 0 Dead 41.5
8 68 Rectal cancer 71 Yes Yes 39.0 CR 1 Yes 2010 MP 0 Dead 47.2
9 77 GIST 85 No No 88.3 CR 2 Yes 2013 VMP 0 Dead 62.4
10 61 Colon cancer
Hypopharynx cancer
80 No No 233.8 CR 3 Yes 2022 VMP 0 Alive 29.5
11 71 Breast cancer 75 Yes Yes 54.1 CR 3 Yes 2008 MP 0 Dead 17.5
12 64 Cervix cancer 71 No No 91.0 CR 2 Yes 2005 MP 0 Dead 18.1

Abbreviations: ASCT, autologous stem cell transplantation; CR, complete response; GIST, Gastro Intestinal stromal tumor; ISS, International staging system stage; MM, multiple myeloma; MP, melphalan-prednisone; MPT, melphalan-prednisone-thalidomide; NSCLC, non-small cell lung cancer; OS, overall survival; RD, lenalidomide-dexamethasone; VMP, bortezomib-melphalan-prednisone; VTD, bortezomib-thalidomide-dexamethasone.

The median age at diagnosis of the primary cancer was 67.5 years (range: 53-77 years). Among the 12 patients, 5 (41.7%) received chemotherapy, and 4 (33.3%) received radiotherapy for their primary malignancy. The median interval between diagnosis of the primary cancer and SPMM was 46.3 months (range: 5.1-233.8 months). At the time of MM diagnosis, 10 patients (83.3%) had achieved CR of their primary cancer, while 2 patients (16.7%) had persistent disease. Multiple myeloma-specific treatment was administered to 11 patients (91.7%), while 1 patient (8.3%) did not receive treatment owing to poor performance status and ongoing disease activity. One patient (8.3%) underwent ASCT.

Treatment outcome

With a median follow-up duration of 77.3 months (95% confidence interval [CI]: 57.3-97.4), Figure 2 presents the median PFS and OS curves. The median PFS following first-line chemotherapy was 10.6 months (95% CI: 3.4-17.8) in the primary MM group and 13.4 months (95% CI: 2.8-24.0) in the SPMM group. The median OS was 45.1 months (95% CI: 24.8-65.3) in the primary MM group and 41.5 months (95% CI: 9.7-73.3) in the SPMM group. However, survival analyses showed no statistically significant differences in either PFS (hazard ratio [HR]: 0.75; 95% CI: 0.37-1.51) or OS (HR: 0.72; 95% CI: 0.33-1.56) between the 2 groups.

Figure 2.

Comparison of progression-free survival between primary multiple myeloma and second primary multiple myeloma groups after initial treatment. (A) PFS of Primary MM and SPMM group following first-line treatment. (B) OS of Primary MM and SPMM group. HR, hazard ratio; m, months; MM, multiple myeloma; SPMM, second primary multiple myeloma; OS, overall survival; PFS, progression-free survival.

(A) PFS of primary MM and SPMM group following first-line treatment. (B) OS of primary MM and SPMM group. HR, hazard ratio; m, months; MM, multiple myeloma; SPMM, second primary multiple myeloma; OS, overall survival; PFS, progression-free survival.

Discussion

Second primary multiple myeloma remains a relatively underexplored clinical entity, with most existing data derived from small, retrospective studies. In this study, 12 patients were diagnosed with SPMM over the study period. Notably, 10 of these patients had achieved CR of their primary malignancy at the time of SPMM diagnosis. All but one patient received active treatment (chemotherapy) for MM, indicating that SPMM was managed with therapeutic intent. Importantly, no statistically significant difference in OS was observed between patients with primary MM and SPMM, suggesting that SPMM may share similar clinical characteristics and prognosis with primary MM. However, this finding should be interpreted cautiously, as the small sample size may have limited the ability to detect statistically significant differences.

Previous studies have primarily focused on SPMs arising after treatment for MM, identifying several associated risk factors such as age, smoking, and clonal hematopoiesis of indeterminate potential (CHIP), as well as specific therapeutic agents. 11 However, risk factors specific to SPMM have not yet been clearly established. With regard to prognosis, SPMs following MM treatment have been associated with poor outcomes, with reported median OS ranging from 8.5 months to 1.1 years.21,22 In particular, patients with secondary myeloid neoplasms, such as acute myeloid leukemia (AML) or myelodysplastic syndromes (MDS), showed extremely poor survival, with a median OS of approximately 2.4 months. 22

In contrast, only a few studies have investigated SPMM, which appears to be associated with relatively longer OS compared with other SPMs. One previous study found that most primary malignancies occurred before MM diagnosis and were predominantly early-stage neoplasms with favorable outcomes. In addition, the median OS differed significantly based on the presence of a prior malignancy (36.5 vs 21.4 months). 15 Another study also reported a notable difference in OS between primary MM and SPMM (46.5 months vs 24.5 months). 16 Our findings, showing a median OS of 45.1 months in the primary MM group and 41.5 months in the SPMM group, did not show a statistically significant difference. This finding aligns with prior studies showing that SPMM has longer OS than other SPMs. However, our observation of no significant difference in OS between SPMM and primary MM contrasts with previous studies. This discrepancy may be attributed to our use of propensity score matching to adjust for confounding variables such as age, sex, ISS stage, and evolving national insurance policies.

In our study, most patients had achieved CR of their primary malignancy at the time of SPMM diagnosis, and all but one received active treatment for SPMM. Although guidelines provide specific recommendations, such as CPX-351 for therapy-related AML, no standardized treatment protocols have been established for SPMM. 23 Similar to other SPMs, SPMM is generally managed according to the treatment regimens established for the corresponding primary cancer. Consistent with this approach, most patients in our cohort were treated with conventional frontline MM therapies.

Currently, quadruplet regimens that include monoclonal antibodies are recommended for newly diagnosed MM. 24 While direct evidence supporting their use in SPMM is limited, it is plausible that regimens proven effective in primary MM may provide similar clinical benefits in SPMM. Therefore, such regimens may be considered a viable option for patients with SPMM. However, as with primary MM, real-world treatment decisions for SPMM must consider the availability of therapeutic agents and health care system constraints, particularly in resource-limited settings.

Our study has certain limitations. First, it is a retrospective analysis with a relatively small cohort. Second, the limited sample size precluded the use of multivariate analysis to identify independent risk factors for SPMM. Moreover, no formal sample size calculation was performed prior to the analysis, which may have further limited the statistical power to detect significant differences between groups. Third, owing to the unavailability of fluorescence in situ hybridization and complete cytogenetic data in many cases, risk stratification was constrained. A fourth limitation of our study is the absence of a universally accepted definition of SPMM. We adopted a definition based on previously reported criteria for second primary cancers. However, this may introduce variability in interpretation and limit comparability across studies. Finally, although propensity score matching was performed to account for changes in Korea’s national insurance policy over the 20-year study period, it was not possible to fully adjust for all relevant variables, such as the approval of novel therapeutic agents for reimbursement and changes in age eligibility criteria for ASCT. These factors may have contributed to differences in OS.

Despite these limitations, to our knowledge, this is the first study in Korea to compare the clinical characteristics of SPMM with those of primary MM. Another important consideration is the small sample size in both our study and previous studies, which may have limited the ability to detect statistically significant differences. Although propensity score matching was employed to minimize the effects of confounding variables, residual imbalances, such as differences in cytogenetic abnormalities and hypoalbuminemia (Table 2), may have influenced PFS and OS. Larger, prospective studies are needed to further characterize SPMM.

Conclusion

Our findings suggest that actively treated patients with SPMM did not show significantly different clinical outcomes compared with those with primary MM. The remission status of their primary malignancies may have enabled this therapeutic approach. As treatment strategies for MM develop, active management of SPMM may be appropriate in selected cases. Further prospective studies are needed to better define optimal treatment strategies.

Supplemental Material

sj-docx-1-onc-10.1177_11795549251377882 – Supplemental material for Comparative Analysis of Primary and Second Primary Multiple Myeloma: A Propensity Score-Matched Study

Supplemental material, sj-docx-1-onc-10.1177_11795549251377882 for Comparative Analysis of Primary and Second Primary Multiple Myeloma: A Propensity Score-Matched Study by Yoon Jung Jang, Joonseog Kong, Heyjin Kim, Chulkue Pak, Im Il Na, Hyo-Rak Lee and Hye Jin Kang in Clinical Medicine Insights: Oncology

Acknowledgments

Not applicable.

Footnotes

ORCID iD: Yoon Jung Jang Inline graphic https://orcid.org/0000-0001-5186-136X

Ethical Considerations: This study was approved by the Institutional Review Board (IRB) of Korea Cancer Center Hospital on July 31, 2024. (IRB No.: 2024-07-004). This study was conducted in accordance with the Declaration of Helsinki and Good Clinical Practice.

Consent to Participate: The requirement for patient consent was waived by the Institutional Review Board of Korea Cancer Center Hospital due to the retrospective nature of the study.

Consent for Publication: Not applicable. This study does not contain any individual patient data, images, or other personally identifiable information requiring consent for publication.

Author Contributions: YJJ: data analysis and interpretation, statistical analysis, manuscript preparation, and editing. JK: data analysis and interpretation, manuscript review, and approval. HK: study design, manuscript editing, manuscript review, and approval. CP: data analysis and interpretation. IIN: data analysis and interpretation. H-RL: data analysis and interpretation. HJK: study concept, study design, data analysis and interpretation, manuscript editing, manuscript review, and approval. All authors commented on the previous versions of the manuscript and have read and approved the final manuscript.

Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Korean Institute of Radiological and Medical Sciences (KIRAMS), funded by the Ministry of Science, ICT (MSIT), Republic of Korea (grant no. 50574-2025).

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement: The datasets used in this study are not publicly available owing to institutional policy and patient confidentiality but are available from the corresponding author on reasonable request.

Supplemental Material: Supplemental material for this article is available online.

References

  • 1. Vogt A, Schmid S, Heinimann K, et al. Multiple primary tumours: challenges and approaches, a review. ESMO Open. 2017;2:e000172. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Rheingold SR, Neugut AI, Meadows AT. Incidence of Secondary Cancer. In: Kufe DW, Pollock RE, Weichselbaum RR, et al. , eds. Holland-Frei Cancer Medicine. 6th ed. BC Decker; 2003. Available from: https://www.ncbi.nlm.nih.gov/books/NBK13212/ [Google Scholar]
  • 3. Demoor-Goldschmidt C, de Vathaire F. Review of risk factors of secondary cancers among cancer survivors. Br J Radiol. 2019;92:20180390. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Wang X, Zeng M, Ju X, et al. Correlation between second and first primary cancer: systematic review and meta-analysis of 9 million cancer patients. Br J Surg. 2024;111:znae044. [DOI] [PubMed] [Google Scholar]
  • 5. Zeng M, Lin A, Jiang A, et al. Decoding the mechanisms behind second primary cancers. J Transl Med. 2025;23:115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Ferlay J, Colombet M, Soerjomataram I, et al. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer. 2019;144:1941-1953. [DOI] [PubMed] [Google Scholar]
  • 7. Park EH, Jung KW, Park NJ, et al. Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2021. Cancer Res Treat. 2024;56:357-371. doi: 10.4143/crt.2024.253 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Padala SA, Barsouk A, Barsouk A, et al. Epidemiology, staging, and management of multiple myeloma. Med Sci (Basel). 2021;9:3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Sergentanis TN, Zagouri F, Tsilimidos G, et al. Risk factors for multiple myeloma: a systematic review of meta-analyses. Clin Lymphoma Myeloma Leuk. 2015;15:563-577. [DOI] [PubMed] [Google Scholar]
  • 10. Poh C, Keegan T, Rosenberg AS. Second primary malignancies in multiple myeloma: a review. Blood Rev. 2021;46:100757. doi: 10.1016/j.blre.2020.100757 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Maclachlan K, Diamond B, Maura F, et al. Second malignancies in multiple myeloma; emerging patterns and future directions. Best Pract Res Clin Haematol. 2020;33:101144. doi: 10.1016/j.beha.2020.101144 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Musto P, Anderson KC, Attal M, et al. Second primary malignancies in multiple myeloma: an overview and IMWG consensus. Ann Oncol. 2018;29:1074. [DOI] [PubMed] [Google Scholar]
  • 13. Ipek Y, Karademir N, Yilmazer O, Yilmaz G. The effects of second primary malignancies and frailty on overall survival and mortality in geriatric Turkish patients with multiple myeloma. Curr Oncol. 2023;30:5615-5630. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Turgutkaya A, Yavaşoğlu İ, Şahin T, Sargin G, Bolaman AZ. Multiple myeloma and frequency of synchronous and second primary malignancies. J Hematopathol. 2021;14:197-203. [Google Scholar]
  • 15. Munker R, Shi R, Lin D, Guo S, Hayes TG. Multiple myeloma and other malignancies: a pilot study from the Houston VA. Clin Lymphoma Myeloma Leuk. 2014;14:102-106. [DOI] [PubMed] [Google Scholar]
  • 16. Zhao X, Ji J, Li Y, Cui Y, Sun Z, Qu X. The risk and survival of multiple myeloma as the second primary malignancy in a single Chinese center. Transl Cancer Res. 2024;13:2905-2912. doi: 10.21037/tcr-23 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Cuschieri S. The STROBE guidelines. Saudi J Anaesth. 2019;13:S31-S34. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Zhang Z, Kim HJ, Lonjon G, Zhu Y; written on behalf of AME Big-Data Clinical Trial Collaborative Group. Balance diagnostics after propensity score matching. Ann Transl Med. 2019;7:16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Rajkumar SV, Dimopoulos MA, Palumbo A, et al. International myeloma working group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. 2014;15:e538-e548. [DOI] [PubMed] [Google Scholar]
  • 20. Rajkumar SV. Updated diagnostic criteria and staging system for multiple myeloma. Am Soc Clin Oncol Educ Book. 2016;35:e418-e423. [DOI] [PubMed] [Google Scholar]
  • 21. Avivi I, Vesole DH, Davila-Valls J, et al. Outcome of second primary malignancies developing in multiple myeloma patients. Cancers (Basel). 2023;15:4359. doi: 10.3390/cancers15174359 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Jonsdottir G, Lund SH, Björkholm M, et al. Survival in multiple myeloma patients who develop second malignancies: a population-based cohort study. Haematologica. 2016;101:e145-e148. doi: 10.3324/haematol.2015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology: Acute Myeloid Leukemia. version 2.2024. NCCN; 2024. Accessed on June 18, 2025. https://www.nccn.org/professionals/physician_gls/pdf/aml.pdf
  • 24. National Comprehensive Cancer Network (2025). NCCN clinical practice guidelines in oncology: multiple myeloma (Version1.2025). Accessed June 18, 2025. https://www.nccn.org/professionals/physician_gls/pdf/myeloma.pdf [DOI] [PubMed]

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Supplementary Materials

sj-docx-1-onc-10.1177_11795549251377882 – Supplemental material for Comparative Analysis of Primary and Second Primary Multiple Myeloma: A Propensity Score-Matched Study

Supplemental material, sj-docx-1-onc-10.1177_11795549251377882 for Comparative Analysis of Primary and Second Primary Multiple Myeloma: A Propensity Score-Matched Study by Yoon Jung Jang, Joonseog Kong, Heyjin Kim, Chulkue Pak, Im Il Na, Hyo-Rak Lee and Hye Jin Kang in Clinical Medicine Insights: Oncology


Articles from Clinical Medicine Insights. Oncology are provided here courtesy of SAGE Publications

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