General Radiology - Original Article

Prognostic value of low muscle mass at the 12th thoracic vertebral level in multiple myeloma treated with transplantation: CAREMM-2101 study

10.4274/dir.2023.232097

  • Sung-Soo Park
  • Daehun Kwag
  • Jung Yeon Lee
  • Young-Woo Jeon
  • Seung-Ah Yahng
  • Seung-Hwan Shin
  • Seo Yeon Youn
  • Chang-Ki Min

Received Date: 10.01.2023 Accepted Date: 14.05.2023 Diagn Interv Radiol 2023;29(4):596-608 PMID: 37312491

PURPOSE

Autologous hematopoietic stem cell transplantation (ASCT) has been introduced as a standard treatment for newly diagnosed multiple myeloma (NDMM) following novel agent-based induction chemotherapy. This study investigated whether pre-ASCT low muscle mass evaluated using the paraspinal muscle index (PMI) at the 12th thoracic vertebra (T12) level is a reliable prognostic marker in NDMM after chemotherapy.

METHODS

A multi-center registry database was retrospectively analyzed. Between 2009 and 2020, 190 patients with chest computed tomography images underwent frontline ASCT following induction therapy. The PMI was defined as the value of the paraspinal muscle area at the T12 level divided by the square of the patient’s height. The cut-off value indicating a low muscle mass was sex-specific, using the lowest quintiles.

RESULTS

Of the 190 patients, 38 (20%) were in the low muscle mass group. The low muscle mass group had a lower 4-year overall survival (OS) rate than the non-low muscle mass group (68.5% vs. 81.2%; P = 0.074). The median progression-free survival (PFS) in the low muscle mass group was significantly shorter compared with the non-low muscle mass group (23.3 months vs. 29.2 months; P = 0.029). The cumulative incidence of transplant-related mortality (TRM) was significantly higher in the low muscle mass group than in the non-low muscle mass group (4-year probability of TRM incidence, 10.6% vs. 0.7%; P < 0.001). In contrast, no significant difference in the cumulative incidence of disease progression was found between the two groups. Multivariate analysis revealed that low muscle mass was associated with significant negative outcomes for OS [(hazard ratio (HR): 2.14; P = 0.047], PFS (HR: 1.78; P = 0.012), and TRM (HR: 12.05; P = 0.025).

CONCLUSION

Paraspinal muscle mass may have a prognostic role in NDMM patients who undergo ASCT. Patients with low paraspinal muscle mass have lower survival outcomes compared to non-low muscle mass group.

Keywords: Sarcopenia, myeloma, autologous, transplantation, computed tomography, thoracic

Main points

• Low muscle mass was defined based on a sex-specific cut-off using low-dose chest computed tomography before autologous hematopoietic stem cell transplantation (ASCT).

• Post-ASCT outcomes were significantly associated with low muscle mass in patients with multiple myeloma.

• NDMM patients undergoing ASCT with low paraspinal muscle mass have shorter progression-free survival, higher incidence of transplant-related mortality, and higher significant negative outcomes for overall survival.


Multiple myeloma (MM) is a hematologic malignancy characterized by the clonal proliferation of malignant plasma cells.1 The outcomes of MM have improved dramatically in the past two decades owing to the introduction of novel agents, such as immunomodulatory drugs, proteasome inhibitors, and targeted monoclonal antibodies.2,3 High-dose chemotherapy with autologous hematopoietic stem cell transplantation (ASCT) following upfront induction therapy using a novel agent is considered the standard of care for transplant-eligible and newly diagnosed MM (NDMM).4 Patient-related prognostic factors, such as age or comorbidities, can limit the eligibility for ASCT.5 Several prognostic tools based on multidisciplinary evaluation have been used to assess patient fitness for ASCT.5,6,7,8 However, these tools rely on patients self-reporting their comorbidities and are prone to reporting bias. Therefore, tools that can facilitate the standardization of individualized risk factors for MM need to be developed.

Sarcopenia has recently been defined by the European Working Group on Sarcopenia in Older People 2 as the combination of low muscle mass and poor muscle function.9 Furthermore, sarcopenia has been highlighted as an independent disorder based on individual cancer-related prognostic biomarkers in various malignancies.10,11 However, published studies reporting patients with MM and sarcopenia and survival outcomes have been unsatisfactory to date due to their retrospective designs and small sample sizes. Williams et al.12 measured psoas muscle mass at the third lumbar vertebra (L3) using computed tomography (CT) in 142 patients with MM treated with ASCT. They showed that low muscle mass was related to a higher incidence of post-ASCT cardiac complications but was not associated with survival outcomes. Takeoka et al.13 demonstrated that a low muscle mass at the L3 level did not result in a significant survival difference between 56 patients with NDMM. Although muscle mass at L3, commonly used for CT measurements, was not related to survival outcomes in patients with MM, the prognostic role of muscle mass measured at other sites and sex-specific approaches is yet to be elucidated.14 Previous studies have revealed that sarcopenia assessment using skeletal muscle measurements at the 12th thoracic vertebra (T12) level is a reliable biomarker for chest CT.15,16 In addition, the cut-off for low muscle mass should be determined differently based on sex because it is directly related to the total muscle mass.13,17,18 Therefore, further MM cohort studies are required to determine whether muscle mass is a useful prognostic indicator.

This study measured the paraspinal muscle mass area (PSMA) at T12 (12th-PSMA, the area corresponding to the iliocostalis thoracis, longissimus thoracis, spinalis thoracis, rotator thoracis, multifidus, and semispinalis thoracis muscles) on chest CT scans. Low muscle mass was defined as a lower paraspinal muscle index (PMI) (12th-PSMA divided by the height2) than the sex-specific cut-off. Further, the study explored the prognostic impact of low muscle mass on survival outcomes in patients with NDMM who underwent an ASCT.


Methods


Patient selection and data acquisition

The current study was a multi-center retrospective analysis of patient data from three centers. For patient with MM to be eligible for enrollment in the study, the following criteria had to be met: ND with symptomatic MM, treated with frontline ASCT after induction chemotherapy, aged 20 years or older, and having undergone chest CT within 60 days before the ASCT procedure. First, data from 1511 consecutive patients ND with plasma cell disorders between 2009 and 2020 were analyzed. Then, 264 patients diagnosed with plasma cell disorders other than symptomatic MM were excluded. Of the remaining 1,247 patients with symptomatic NDMM, 414 were transplant-eligible cases. The low-dose chest CT (LDCT) findings of selected patients with a history of pneumonia or airway disease were evaluated between 2009 and 2014. Since 2015, LDCT has been routinely performed to screen for malignancies involving the lungs and mediastinum, subclinical pneumonia, and airway diseases. Two hundred nine patients who lacked a LDCT image before ASCT and 15 patients who received ASCT as a salvage treatment following the failure of induction therapy were excluded. The final cohort included 190 patients with intention-to-treat NDMM who underwent frontline ASCT after induction chemotherapy (Figure 1). Since all centers participating in this study have used thalidomide- or bortezomib-based induction chemotherapy, alone or in combination, since 2009, all patients enrolled in the final cohort received novel agent-based induction therapy. Patient data were collected from August 2021 onward. This study was approved by the Institutional Review Board of Catholic Medical Center (IRB no. KC21RASI0352) and complied with the Declaration of Helsinki. Written informed consent was obtained from all patients.


Computed tomography image acquisition

The CT examinations were performed using multidetector CT scanners with 64 or more channels, either a SOMATOM Definition AS+ (Siemens Healthineers, Erlangen, Germany) or a Discovery CT750 HD (GE Healthcare, Milwaukee, WI, USA). All scans were obtained during a single breath-hold from the levels of the lower neck to the adrenal glands. The acquisition parameters were as follows: tube voltage 120 kV, tube current 35 mAs for the low-dose scan, automatic exposure control with 130 quality reference value mAs for the standard-dose scan (SOMATOM Definition AS+), a pitch of 1.1–1.2, rotation time of 0.5 s, detector collimation of 64 × 0.6 mm (SOMATOM Definition AS+), or 64 × 0.625 mm (Discovery CT750 HD).


Measurement of the paraspinal muscle at the 12th thoracic vertebra

The patients’ 12th-PSMA was evaluated using LDCT within two months before the date of the ASCT according to the strategies used at the participating centers. The LDCT was primarily performed to confirm ASCT eligibility after completing the scheduled induction chemotherapy.  A board-certified radiologist with nine years of experience, who was blinded to the clinical information, drew the region of interest using a semi-automated contouring tool available in a non-commercial prototype software (RADIOMICS, Siemens Healthineers, Erlangen, Germany) for all three centers’ cases. An axial CT image at the level of T12 was obtained for each patient. The contours of the erector spinae muscles (iliocostalis thoracis, longissimus thoracis, and spinalis thoracis) and transversospinales muscles (rotator thoracis, multifidus, and semispinalis thoracis) were drawn. The 12th-PSMA (mm2) was obtained from the contours (Figure 2). The mean densities (Hounsfield unit) of these muscles were also determined. Then, the patient’s individual PMI was calculated by dividing the 12th-PSMA by the square of the patient’s height (mm2/m2). The cut-off for low muscle mass was based on sex-specific PMI values using the lowest quintile in each subgroup of males and females.12


Treatments and transplantation procedures

All patients received an induction treatment consisting of dexamethasone (or prednisolone) together with bortezomib or thalidomide, individually or a combination, in chronological order of approval by the National Health Insurance Service. After the induction chemotherapy, the collected stem cells were mobilized with subcutaneous granulocyte colony stimulation factor (10 μg/kg/day) for five days with or without prior cyclophosphamide therapy (1.5 g/m2) for two days, etoposide (375 mg/m2) for one day, or plerixafor (0.24 mg/kg) for one to two days. According to the conditioning strategies implemented by the three centers, a conditioning regimen consisting of high-dose melphalan (70 or 100 mg/m2/day for two days) was commonly used. Occasionally, busulfan (3.2 mg/kg/day for three days), melphalan (70 mg/m2/day for two days), busulfan (3.2 mg/kg/day for three days), melphalan (100 mg/day)-thiotepa (150 mg/m2/day for one day), and busulfan (3.2 mg/kg/day for three days)-thiotepa (150 mg/m2/day for one day) were used when melphalan was unavailable, as described in a previous report.19 Some patients received an experimental regimen of bortezomib, busulfan, and melphalan in phase II clinical trials.20 Other supportive care, including prophylactic antibiotics, prophylaxis for hepatic sinusoidal obstruction syndrome, granulocyte colony stimulation factor, and bisphosphonates, was administered concurrently across the three centers, as described in a previous report.21,22 A maintenance therapy strategy was designed using thalidomide for 12 months;23 however, a few individuals rejected this strategy due to insufficient insurance coverage.19


Definitions

The patient’s MM stage was classified using the MM International Staging System,1 and the response to treatment was assessed according to the International Myeloma Working Group response criteria.24 High-risk cytogenetic abnormalities were defined as the presence of one or more of the following aberrations detected by fluorescent in situ hybridization: del(17p), t(4;14), or t(14;16).25

The PMI cut-off was based on sex-specific PMI values using the lowest quintile in each subgroup of males and females.12 The low muscle mass group was defined as patients with a lower PMI than the sex-specific cut-off. The overall survival (OS) was defined as the time from transplantation to death from any cause or the date of the last follow-up, and events for progression-free survival (PFS) included disease progression or death from any cause. The transplant-related mortality (TRM) probability and the progression rate were computed by estimating the cumulative incidence based on competing risks, including progression and TRM.


Statistical analysis

Categorical variables were presented as frequencies and percentages, and comparisons used the chi-squared or Fisher’s exact tests, as appropriate. Continuous variables were analyzed using the Kolmogorov–Smirnov test to evaluate the null hypothesis of a normal distribution. Normally distributed continuous variables were presented as the mean ± standard deviation and compared using the Student’s t-test. Non-normally distributed continuous variables were expressed as medians with interquartile ranges and were compared using the Mann–Whitney U test. Pearson’s correlation coefficients determined the statistical correlation between the continuous variables and the PMI. Multiple linear regression analyses were used to confirm the parameters related to the PMI. Regarding linear regression analysis, parameters with P < 0.050 on the Student’s t-test or Pearson correlation test were included as covariants.

The reverse Kaplan–Meier estimator was used to assess the median duration of the interval. The Kaplan–Meier survival curves were determined, and log-rank tests were performed to analyze time-to-event endpoints, such as the OS and PFS. Univariate survival analyses were performed using Kaplan–Meier estimates and log-rank tests. Cumulative incidence estimates and the Gray’s test were used to analyze the data, including competing risks. Variables with P < 0.150, according to the univariate analyses, were included in the multivariate models of OS, PFS, and TRM. The Cox proportional hazards model and the Fine–Gray regression model, both with backward stepwise selection, were generated with hazard ratios (HRs) and 95% confidence intervals (CIs) for multivariate analysis. All statistical analyses were performed using R software (ver. 3.6.1, Jul. 07, 2019; R Foundation for Statistical Computing, Vienna, Austria. https://cran.r-project.org/bin/windows/base/old/3.6.1/). A P value of <0.050 was considered statistically significant.


Results


Patient characteristics and outcomes

The final study cohort included 190 of the initial 1,511 consecutive patients, 104 (55.3%) males and 86 (45.3%) females, with a mean age of 55.9 ± 7.0. The mean interval between the LDCD assessment date and the date of the ASCT was 28 ± 16.1 days. As expected, the 12th-PSMA (3206 ± 648 mm2 for males vs. 2358.9 ± 538.8 mm2 for females; P < 0.001) and the PMI (1117.3 ± 232.8 mm2/m2 for males vs. 973.7 ± 220.2 mm2/m2 for females; P < 0.001) were significantly higher in males than in females (Figure 3a). Among the variables considered in the decision-making for ASCT, non-extramedullary plasmacytoma and lower levels of albumin at diagnosis related to lower PMI values (Supplementary Table 1). Supplementary Table 2 shows the results of multiple regression analysis for the PMI, where the dependent parameter was sex. Accordingly, the cut-offs for the 12th-PSMA were defined as 916.9 mm2/m2 for males and 807.2 mm2/m2 for females. The mean PMI of the low muscle (n = 38) and non-low muscle (n = 152) mass groups were 760.9 ± 103.2 and 1125.1 ± 203.4, respectively. The comparative data of the two groups based on the definition of low muscle mass are presented in Table 1. These characteristics were relatively similar between the two groups.

The median follow-up of the total cohort was 40.7 months (95% CI; 38.1–44.9 months). Among the 36 deaths in the entire cohort, 86.1% (n = 31) were progression-dependent, and 13.9% (n = 5) died of TRM. The TRM-related causes of death included three cases of sepsis, one of hepatic sinusoidal obstruction syndrome, and one of sudden death following fatal arrhythmia.


Survival outcomes of the low and non-low muscle mass groups

The estimated OS rate was poor in the low muscle compared with the non-low muscle mass group [4-year OS rate, 68.5% (95% CI; 49.9%–81.3%) vs. 81.2% (95% CI; 71.7%–87.8%); P = 0.074] (Figure 4a). The median PFS in the low muscle mass group was significantly poorer than in the non-low muscle mass group (23.3 months (95% CI, 14.5–31.4 months) vs. 29.2 months (95% CI, 24.3–38.7 months); P = 0.029) (Figure 4b). The cumulative incidence of TRM was significantly higher in the low muscle than in the non-low muscle mass group [4-year probability of incidence of TRM, 10.6% (95% CI, 3.3%–22.9%) vs. 0.7% (95% CI, 0.1%–3.3%); P < 0.001] (Figure 4c). No statistically significant cumulative incidence of progression was found between the two groups (P = 0.301) (Figure 4d).


Analyses of the factors affecting overall and progression-free survival, and transplant-related mortality

In the univariate analysis (Supplementary Table 3), some variables were identified as potentially related to OS, PFS, and TRM. Eight variables were potentially associated with OS, including low muscle mass, age (≥60 years), lambda chain type MM, high β2-microglobulin at diagnosis (≥5.5 mg/L), low albumin at diagnosis (<3.5 g/dL), mobilization of peripheral blood mononuclear cells using cyclophosphamide, low glomerular filtration rate at baseline (<60 mL/min/1.73 m2), and conditioning, except for melphalan plus busulfan. Seven variables were found to be potentially related to PFS, including low muscle mass and density, lambda chain type MM, high β2-microglobulin at diagnosis (≥5.5 mg/L), low albumin at diagnosis (<3.5 g/dL), poor response status at baseline, and low platelet at baseline (<150/mm3). Six variables were found to be potentially related to TRM, including low muscle mass, lambda chain type MM, high β2-microglobulin at diagnosis (≥5.5 mg/L), low albumin at diagnosis (<3.5 g/dL), high lactate dehydrogenase (> upper limit of normal), and low glomerular filtration rate at baseline (<60 mL/min/1.73 m2). The multivariate analysis (Table 2) showed that low muscle mass resulted in a significantly negative association with OS (HR of 2.14; 95% CI of 1.01–4.87; P = 0.047), PFS (HR of 1.78; 95% CI of 1.14–2.78; P = 0.012), and TRM (HR of 12.05; 95% CI of 1.36–104.93; P = 0.025), even after adjustment for other potential factors.


Discussion

This study evaluated the prognostic role of the PMI using the 12th-PSMA derived from LDCT images and height. Low muscle mass was defined as the sex-specific lowest quintile of the PMI. Low muscle mass was significantly associated with survival outcomes, even after adjusting for confounding factors; this suggests that the lower survival outcomes in the low muscle mass group resulted from a higher incidence of TRM.

Quantitative body composition measurements, including skeletal muscle and visceral and subcutaneous adipose tissue volumes, at various anatomical sites have been extensively performed to identify their role in predicting the outcomes and survival of cancer patients.14 Studies exploring the association between body composition at the L3 level and clinical outcomes are the most common in cancer cohorts, including MM cohort studies. Previous studies12,13,26 that applied low muscle mass at the L3 level in patients with MM showed that a low muscle index did not affect survival outcomes, contrary to the conclusion of this study. However, evidence associating low muscle mass at the L3 level with survival has been disputed in cohort studies of patients with MM. For example, Williams et al.12 and Takeoka et al.13 did not apply sex-specific cut-offs for the L3 low muscle index. Surov et al.26 used the sex-specific cut-off values suggested by Prado et al.27, which were derived for solid tumors of the respiratory or gastrointestinal tract rather than for MM. Although three previous studies on low muscle mass measured at the lumbar vertebral level were not linked to OS in a cohort of patients with MM,12,13,26 Umit et al.28 reported that low femoral muscle mass was significantly associated with poor OS, whereas measuring muscle mass in the lumbar area was not. Therefore, this study hypothesized that muscle volume measurements at different sites from the L3 level and the modality of abdominal CT were worthwhile to explore the prognostic impact in patients with MM.

First, pilot investigations were performed to identify which single muscle area could correspond to the entire muscle volume shown in the cross-sectional image at the T12 level. It was determined that measurements at one site of the paraspinal muscle could be a surrogate marker for the entire muscle volume shown at the T12 level (Supplementary Figure 1). In line with this study’s results, pectoralis muscle attenuation and low muscle mass evaluated at the T12 level were negatively associated with clinical outcomes, such as severe airflow obstruction in patients with chronic obstructive pulmonary disease and survival in patients who underwent lung transplantation.29,30 Furthermore, in several studies, LDCT image muscle mass measurements at the T12 level showed a prognostic role in clinical outcomes.31,32 Although understanding the pathogenic mechanism of sarcopenia according to the measured site on the clinical outcomes is still lacking, it is suggested that low muscle mass measured at sites other than L3 are valuable prognostic markers, even in patients with MM.

To the researchers’ knowledge, the current study is the first to investigate the association between low muscle mass at the T12 level and the survival of patients with MM. As LDCT is routinely performed before ASCT, an additional abdominal CT for muscle mass assessment at the lumbar level may be limited. Although it has been suggested that measuring one muscle area could assess the patient’s generalized muscle mass status,33 such an approach is inevitably linked to increased laboriousness, particularly when measuring larger areas in clinical practice. Furthermore, T12 level evaluation via LDCT is associated with the significant benefit of contrast-free assessment and minimization of radiation exposure compared with conventional abdominal CT of the lumbar region.34,35

Although the definition of low muscle mass is yet to be established,36 it is generally indicated by different cut-off levels based on sex and is closely related to body size. Furthermore, the revised European Working Group on Sarcopenia in Older People 2 guidelines state that sex-specific threshold values for sarcopenia diagnosis improve the prediction of outcomes.9 It is well known that the body composition index measured at the L3 level varies significantly depending on sex.17 Accordingly, most previous studies defined sex-specific cut-offs to investigate the associations between low muscle mass at the L3 level and the clinical outcomes of several cancers.37 However, most previous MM cohort studies defined low muscle mass with sex-specific cut-off values.12,13 Based on previous studies’ findings, the researchers believe this methodology is a decisive factor related to the lack of significant association with survival outcomes in this study’s MM cohort. Unfortunately, because of the lack of correlation between low muscle mass and survival of patients with MM in previous studies, CT muscle mass measurements have not received substantial attention in MM cohort studies.

No clinical impact of sex-non-specific muscle mass on clinical outcomes was observed in this MM cohort (data not shown). However, this study’s results showed that low muscle mass at the T12 level, defined by a sex-specific methodology, was negatively associated with comprehensive survival outcomes, including OS, PFS, and TRM, in patients with MM who received ASCT. The results of this study highlight the need for future studies to establish a reliable sex-specific approach for lowering the muscle mass in patients with MM undergoing ASCT.

Prognostic marker-based treatments are essential to improve the survival of patients with MM. Relevant prognostic parameters for each patient were divided into the patient-, disease-, and treatment-related factors.38 Patient-related factors, such as age, performance status, MM-specific comorbidity index of the revised myeloma comorbidity index,8 or the International Myeloma Working Group frailty scale,5 can predict individual tolerance to anti-MM treatment. It was hypothesized that the PMI using the 12th-PSMA in this study might be a patient-related parameter facilitating pretreatment decisions including its regimen and intensity. Further, the current study demonstrated that low muscle mass significantly contributed to high TRM and poor PFS and OS. The study cohort consisted of intention-to-treat patients with MM with frontline ASCT following the achievement of an overall response to induction chemotherapy. It is critical to avoid TRM after ASCT. Since no optimal conditioning regimen has been developed for ASCT in patients with MM, clinicians should adopt a weak conditioning regimen for individuals with low muscle mass. Evidence from cancer cohorts supports this study’s finding that muscle mass status is directly related to critical chemotherapeutic toxicity.12,37 Above all, MM appears to be strongly linked to low muscle mass because of multidimensional factors, such as epidemiologically old-age onset;39,40 therefore, patients with MM may face disability related to devastating bone destruction, including vertebral compression fractures41 or heavy exposure to high-dose steroids as part of anti-MM treatment.42 It is known that comprehensive rehabilitation with nutritional support and exercise programs treats and prevents low muscle mass.43 Moreover, nutritional therapy, including protein of approximately 1.2–1.5 g/kg/day and fat within 20%–30% of total energy content, and exercise therapy, such as resistance training, are recommended for patients with MM.43,44 Therefore, further studies are needed to investigate the potential clinical benefits of intensive rehabilitation programs for preventing or treating sarcopenia following the diagnosis of MM or before the initiation of induction treatment; this may provide a more comprehensive understanding of the effectiveness of such interventions in managing sarcopenia and enhancing patient outcomes.

This study was limited by its retrospective design and lack of prospective validation using another cohort. Potential selection bias exists as some patients without LDCT images before the ASCT were excluded from the initial cohort. The study’s population was also limited by confounding factors, such as heterogeneous induction treatment and the ASCT’s conditioning regimen. Further, as some data associated with cytogenetic risk were missing, statistical bias could exist in the association between the cytogenetic risk and clinical outcomes. Although the study’s results indicated a prognostic impact of low muscle mass at the T12 level, the optimal sites for computing muscle mass were not confirmed. Therefore, further studies are needed to identify the optimal site among the candidate muscle sites, such as the pectoralis or paraspinal muscles, at other thoracic levels. Nevertheless, the researchers believe the T12 level approach is preferable because it is simpler to measure muscle mass than at other sites. Further studies are warranted to validate the role of the PMI using the 12th-PSMA on outcomes in a larger cohort of transplant-eligible patients with NDMM based on the results of this study.

In conclusion, sex-specific low muscle mass evaluated at the T12 level could be related to the prognosis of patients with MM receiving ASCT. For patients with NDMM preparing for ASCT, an inspection of muscle mass using LDCT may contribute to developing individualized management, including conditioning intensity, rehabilitation, and nutrition.


Conflict of interest disclosure

The authors declared no conflicts of interest.

Funding

This study was supported by the National R&D Program for Cancer Control through the National Cancer Center, funded by the Ministry of Health & Welfare, Republic of Korea (HA21C0013). The authors wish to acknowledge the financial support of the Catholic Medical Center Research Foundation made in 2021.

  1. Greipp PR, San Miguel J, Durie BG, et al. International staging system for multiple myeloma. J Clin Oncol. 2005;23(15):3412-3420. Erratum in: J Clin Oncol. 2005;23(25):6281.
  2. Engelhardt M, Terpos E, Kleber M, et al. European Myeloma Network recommendations on the evaluation and treatment of newly diagnosed patients with multiple myeloma. Haematologica. 2014;99(2):232-242.
  3. Lee JH, Kim SH. Treatment of relapsed and refractory multiple myeloma. Blood Res. 2020;55(S1):S43-S53.
  4. Parrondo RD, Ailawadhi S, Sher T, Chanan-Khan AA, Roy V. Autologous stem-cell transplantation for multiple myeloma in the era of novel therapies. JCO Oncol Pract. 2020;16(2):56-66.
  5. Palumbo A, Bringhen S, Mateos MV, et al. Geriatric assessment predicts survival and toxicities in elderly myeloma patients: an International Myeloma Working Group report. Blood. 2015;125(13):2068-2074.
  6. Sorror ML, Maris MB, Storb R, et al. Hematopoietic cell transplantation (HCT)-specific comorbidity index: a new tool for risk assessment before allogeneic HCT. Blood. 2005;106(8):2912-2919.
  7. Kleber M, Ihorst G, Terhorst M, et al. Comorbidity as a prognostic variable in multiple myeloma: comparative evaluation of common comorbidity scores and use of a novel MM-comorbidity score. Blood Cancer J. 2011;1(9):e35.
  8. Engelhardt M, Domm AS, Dold SM, et al. A concise revised myeloma comorbidity index as a valid prognostic instrument in a large cohort of 801 multiple myeloma patients. Haematologica. 2017;102(5):910-921.
  9. Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16-31. Erratum in: Age Ageing. 2019;48(4):601.
  10. Catikkas NM, Bahat Z, Oren MM, Bahat G. Older cancer patients receiving radiotherapy: a systematic review for the role of sarcopenia in treatment outcomes. Aging Clin Exp Res. 2022;34(8):1747-1759.
  11. Surov A, Wienke A. Sarcopenia predicts overall survival in patients with malignant hematological diseases: a meta-analysis. Clin Nutr. 2021;40(3):1155-1160.
  12. Williams A, Baruah D, Patel J, et al. Prevalence and significance of sarcopenia in multiple myeloma patients undergoing autologous hematopoietic cell transplantation. Bone Marrow Transplant. 2021;56(1):225-231.
  13. Takeoka Y, Sakatoku K, Miura A, et al. Prognostic effect of low subcutaneous adipose tissue on survival outcome in patients with multiple myeloma. Clin Lymphoma Myeloma Leuk. 2016;16(8):434-441.
  14. Hemke R, Buckless C, Torriani M. Quantitative imaging of body composition. Semin Musculoskelet Radiol. 2020;24(4):375-385.
  15. Nemec U, Heidinger B, Sokas C, Chu L, Eisenberg RL. Diagnosing sarcopenia on thoracic computed tomography: quantitative assessment of skeletal muscle mass in patients undergoing transcatheter aortic valve replacement. Acad Radiol. 2017;24(9):1154-1161.
  16. Kim JW, Yoon JS, Kim EJ, et al. Prognostic implication of baseline sarcopenia for length of hospital stay and survival in patients with coronavirus disease 2019. J Gerontol A Biol Sci Med Sci. 2021;76(8):e110-e116.
  17. Martin L, Birdsell L, Macdonald N, et al. Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index. J Clin Oncol. 2013;31(12):1539-1547.
  18. Xia L, Zhao R, Wan Q, et al. Sarcopenia and adverse health-related outcomes: an umbrella review of meta-analyses of observational studies. Cancer Med. 2020;9(21):7964-7978.
  19. Park SS, Lim JY, Kim TW, et al. Predictive impact of circulating microRNA-193a-5p on early relapse after autologous stem cell transplantation in patients with multiple myeloma. Br J Haematol. 2020;189(3):518-523.
  20. Park SS, Kim K, Kim SJ, et al. A Phase I/II, open-label, prospective, multicenter study to evaluate the efficacy and safety of lower doses of bortezomib plus busulfan and melphalan as a conditioning regimen in patients with multiple myeloma undergoing autologous peripheral blood stem cell transplantation: the KMM103 study. Biol Blood Marrow Transplant. 2019;25(7):1312-1319.
  21. Lee SE, Yahng SA, Cho BS, et al. Lymphocyte subset analysis for the assessment of treatment-related complications after autologous stem cell transplantation in multiple myeloma. Cytotherapy. 2012;14(4):505-512.
  22. Kim Y, Park SS, Jeon YW, et al. Response and dynamics of renal function in transplantation-eligible multiple myeloma patients treated with a novel agent: the CAREMM-2201 study. Transplant Cell Ther. 2023;29(1):55.e1-55.e9.
  23. Lee HS, Min CK, Lee JJ, et al. The clinical impact of thalidomide maintenance after autologous stem cell transplantation in patients with newly diagnosed multiple myeloma in real clinical practice of Korea. Ann Hematol. 2016;95(6):911-919.
  24. Rajkumar SV, Harousseau JL, Durie B, et al. Consensus recommendations for the uniform reporting of clinical trials: report of the International Myeloma Workshop Consensus Panel 1. Blood. 2011;117(18):4691-4695.
  25. Palumbo A, Avet-Loiseau H, Oliva S, et al. Revised international staging system for multiple myeloma: a report from International Myeloma Working Group. J Clin Oncol. 2015;33(26):2863-2869.
  26. Surov A, Benkert F, Pönisch W, Meyer HJ. CT-defined body composition as a prognostic factor in multiple myeloma. Hematology. 2023;28(1):2191075.
  27. Prado CM, Lieffers JR, McCargar LJ, et al. Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study. Lancet Oncol. 2008;9(7):629-635.
  28. Umit EG, Korkmaz U, Baysal M, et al. Evaluation of sarcopenia with F-18 FDG PET/CT and relation with disease outcomes in patients with multiple myeloma. Eur J Cancer Care (Engl). 2020;29(6):e13318.
  29. Cho YH, Do KH, Chae EJ, et al. Association of Chest CT-based quantitative measures of muscle and fat with post-lung transplant survival and morbidity: a single institutional retrospective cohort study in Korean population. Korean J Radiol. 2019;20(3):522-530.
  30. Bak SH, Kwon SO, Han SS, Kim WJ. Computed tomography-derived area and density of pectoralis muscle associated disease severity and longitudinal changes in chronic obstructive pulmonary disease: a case control study. Respir Res. 2019;20(1):226.
  31. Panthofer AM, Olson SL, Harris DG, Matsumura JS. Derivation and validation of thoracic sarcopenia assessment in patients undergoing thoracic endovascular aortic repair. J Vasc Surg. 2019;69(5):1379-1386.
  32. Tan L, Ji G, Bao T, Fu H, Yang L, Yang M. Diagnosing sarcopenia and myosteatosis based on chest computed tomography images in healthy Chinese adults. Insights Imaging. 2021;12(1):163.
  33. Baracos VE. Psoas as a sentinel muscle for sarcopenia: a flawed premise. J Cachexia Sarcopenia Muscle. 2017;8(4):527-528.
  34. Smith-Bindman R, Lipson J, Marcus R, et al. Radiation dose associated with common computed tomography examinations and the associated lifetime attributable risk of cancer. Arch Intern Med. 2009;169(22):2078-2086.
  35. Larke FJ, Kruger RL, Cagnon CH, et al. Estimated radiation dose associated with low-dose chest CT of average-size participants in the National Lung Screening Trial. AJR Am J Roentgenol. 2011;197(5):1165-1169.
  36. Tanaka S, Imataki O, Kitaoka A, et al. Clinical impact of sarcopenia and relevance of nutritional intake in patients before and after allogeneic hematopoietic stem cell transplantation. J Cancer Res Clin Oncol. 2017;143(6):1083-1092.
  37. Hopkins JJ, Sawyer MB. Interactions of lean soft-tissue and chemotherapy toxicities in patients receiving anti-cancer treatments. Cancer Chemother Pharmacol. 2018;82(1):1-29.
  38. Gengenbach L, Graziani G, Reinhardt H, et al. Choosing the right therapy for patients with relapsed/refractory multiple myeloma (RRMM) in consideration of patient-, disease- and treatment-related factors. Cancers (Basel). 2021;13(17):4320.
  39. Tang CH, Liu HY, Hou HA, et al. Epidemiology of multiple myeloma in Taiwan, a population based study. Cancer Epidemiol. 2018;55:136-141.
  40. Hong J, Lee JH. Recent advances in multiple myeloma: a Korean perspective. Korean J Intern Med. 2016;31(5):820-834.
  41. Terpos E, Morgan G, Dimopoulos MA, et al. International Myeloma Working Group recommendations for the treatment of multiple myeloma-related bone disease. J Clin Oncol. 2013;31(18):2347-2357.
  42. Sharma S, Lichtenstein A. Dexamethasone-induced apoptotic mechanisms in myeloma cells investigated by analysis of mutant glucocorticoid receptors. Blood. 2008;112(4):1338-1345.
  43. Kakehi S, Wakabayashi H, Inuma H, et al. Rehabilitation nutrition and exercise therapy for sarcopenia. World J Mens Health. 2022;40(1):1-10.
  44. Burtin C, Clerckx B, Robbeets C, et al. Early exercise in critically ill patients enhances short-term functional recovery. Crit Care Med. 2009;37(9):2499-2505.