Саркопания у пожилых пациентов с новой диагностированной множественной миеломой.

Introduction

Sarcopenia is a skeletal muscle disorder associated with reduced quality of life (QoL), physical disability, and mortality, whose prevalence increases with age [ 1 – 3 ]. It has become of interest in oncology because of its high prevalence and association with adverse outcomes. Given the variety of definitions or cut-points applied, the prevalence of sarcopenia varies from 5 to 89%, being higher in older adults [ 4 ]. Cancer and its treatment may be the underlying causes of sarcopenia. Indirectly, they may potentiate factors contributing to age-related sarcopenia, such as anorexia, inactivity and a proinflammatory state. In another way, chemotherapy can also directly damage muscle tissue [ 4 ]. In haematologic malignancies, low muscle mass has been significantly associated with cancer recurrence, postoperative complications such as infections and length of hospitalisation, and chemotherapy toxicity [ 4 ].

The median age for multiple myeloma (MM) diagnosis is 69 years, and nearly 64.8% of new cases are present over the age of 65 years [ 5 ]. It is, therefore, not uncommon that sarcopenia may coexist in older patients with MM. Nevertheless, the prevalence in these patients remains unclear. According to the revised European consensus definition (EWGSOP2) [ 1 ], sarcopenia is probable when low muscle strength is detected, confirmed when low muscle quantity or quality is also present and considered severe when low physical performance is added. The first results of the Global Leadership Initiative in Sarcopenia (GLIS) have recently been published [ 6 ]. To establish the global conceptual definition of sarcopenia, they agreed that it comprises the concurrent combination of reduced muscle mass and strength. However, due to its extended use in cancer in general and in MM in particular, computed tomography (CT) scan-determined muscle mass has traditionally been the most common and the only diagnostic criterion used in research, which is an error, as low muscle mass in this setting may be due to malnutrition, cachexia, or sarcopenia [ 7 ]. Importantly, most of the studies published to date applied an outdated concept of sarcopenia – before 2010, when it was defined only by low muscle mass – without incorporating muscle strength or physical performance, and were often conducted in middle-aged rather than older adults.

The prevalence of low muscle mass in patients with haematological neoplasms ranges from 24.6% to 66.1% [ 8 ]. In patients with myeloma, it has been reported in up to 32.5% of cases [ 9 ] and may change after treatment [ 10 ]. However, according to data from the UK Biobank, the prevalence of sarcopenia (characterised by low muscle strength and low muscle mass) in patients with haematological neoplasms is less than 1% [ 11 ]. Several studies have demonstrated an association between low muscle mass and reduced overall survival (OS) [ 8 ]. Similar results have been obtained with other body composition parameters, such as subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) [ 12 ]. Nevertheless, other studies have reported conflicting results [ 9 , 13 ]. In this regard, no differences have been found in the incidence of post-transplant adverse events [ 14 ], whereas an association between low muscle mass and bone damage has been observed in MM patients undergoing transplantation [ 15 ]. Furthermore, skeletal muscle fat infiltration, or myosteatosis, appears to be associated with worse outcomes [ 16 ]. However, there are no studies that consider not only muscle mass but also strength and physical performance in older patients with MM [ 9 , 17 , 18 ].

Sarcopenia, malnutrition, and cachexia are commonly underdiagnosed and undertreated [ 19 ]. Sarcopenia is a potentially modifiable factor, and its identification may prevent associated unfavourable conditions and improve the efficacy and cost-efficiency of cancer treatments. Therefore, its assessment may be necessary for the treatment decisions of older MM patients. This study aimed to describe the prevalence of sarcopenia according to the EWGSOP2 in older patients with newly diagnosed MM and to analyse possible associations with other geriatric syndromes as well as with OS and progression-free survival (PFS).

Methods

Study Design

A prospective, single-centre observational study was performed. The protocol was approved by the Independent Research Ethics Committee of Hospital Universitario Ramón y Cajal, Spain (225-19) and conducted according to the Declaration of Helsinki. All patients included signed an informed consent form.

Inclusion and Exclusion Criteria

Patients aged 65 years or older with newly diagnosed MM based on the International Myeloma Working Group (IMWG) criteria [ 20 ] between 2019 and 2023 were eligible for the study inclusion. During this period in the oncogeriatric clinic, a total of 80 patients with suspected plasma cell neoplasia were evaluated. Six were excluded for not meeting the diagnostic criteria for MM, 2 due to amyloidosis, 2 due to monoclonal gammopathy of uncertain significance, and 2 who declined to undergo a bone marrow study. Additionally, 3 patients were assessed for relapse and were also excluded. Another 2 patients refused to participate in the study, and 1 received palliative care from the outset. Furthermore, 16 patients were excluded for not having a complete sarcopenia assessment: in 6 cases, no imaging test could be retrieved at diagnosis (≤1 month from the start of treatment), and in the other 10, no muscle strength measurement was available. Thus, 52 patients were included in the study.

Data Collection

Medical records were used to collect patients’ general data, including age and sex. Medical diseases were registered, and the Charlson Comorbidity Index (CCI) was calculated. Cancer-related information included the diagnostic date and stage (Revised International Staging System [r-ISS] [ 21 ]) at diagnosis.

All patients included in the study were referred for an oncogeriatric consultation. Weight and height were measured, and the body mass index (BMI) was calculated. A Comprehensive Geriatric Assessment (CGA) was performed. The CGA scales selected were the Barthel Index and the Lawton-Brody Index for functional status; the Mini-Mental State Examination (MMSE) and the Yesavage’s Geriatric Depression Scale (GDS) for mental status; and the Short Form of Mini Nutritional Assessment (MNA-SF) for nutritional status.

Geriatric syndromes such as malnutrition (GLIM criteria [ 22 ]), falls (number of falls in the last year [ 23 ]), and polypharmacy [ 24 ], defined as the consumption of ≥5 drugs, considering eye drops, laxatives, and over-the-counter, were assessed. Frailty was evaluated by the FRAIL scale [ 25 ] (0: robust; 1–2: pre-frail; ≥3: frail) and the Frail-VIG index [ 26 ] (<0.2: robust; 0.2–0.35: mild frail; 0.35–0.55: moderate frail; 0.55–0.7: severe frail).

According to the revised European consensus definition (EWGSOP2) [ 1 ], muscle strength was determined by quantifying handgrip strength with a hydraulic dynamometer (Jamar) under standardised conditions. We used the cutoff values proposed, considering low handgrip strength <16 kg for women and <27 kg for men. Muscle mass was estimated at the third lumbar vertebral level (L3) containing the psoas muscle measured by PET/CT at diagnosis. The muscle cross-sectional area was calculated using the free, open-source web-based software package CoreSlicer (version 1.0; Montreal, QC, Canada) [ 27 ]. The muscle area was identified employing the Hounsfield units (HU) threshold levels of −29 and 150 HU. Skeletal muscle mass index (SMI) was calculated based on each patient’s total skeletal muscle area and height. Patients were considered sarcopenic when SMI <34.4 cm 2 /m 2 for women and <45.4 cm 2 /m 2 for men [ 28 ]. Sarcopenia severity based on physical performance was evaluated using the 4-m gait speed. A gait speed below the cutoff value of ≤0.8 m/s was defined as a low gait speed. Figure 1 displays a representative patient of the study to show the sarcopenia-related quantifications. Other body composition parameters, such as SAT and VAT, were calculated at the same level as the muscle areas. The fat areas were semiautomatically identified employing the HU threshold levels of −190 and −30 HU [ 29 ]. The cutoff value used to classify SAT (low vs. high) was 100 cm 2 , and for VAT (low vs. high), it was also 100 cm 2 [ 14 ].

In January 2025, the medical records of all included patients were reviewed to ascertain survival status and follow-up data. OS was defined as the time from diagnosis to death from any cause, and patients alive at the data cutoff were censored at the date of their last known follow-up. PFS was defined as the time from diagnosis to documented disease progression, according to IMWG criteria [ 30 ], or death, whichever occurred first. Patients without an event were censored at the date of their last available clinical assessment.

Statistical Analyses

Normally distributed continuous variables were expressed as mean values and standard deviation, and categorical variables were presented as absolute and relative frequencies. Independent t -test or Mann-Whitney U test, Pearson’s χ 2 test or Fisher’s exact test, were applied to compare variables appropriately. OS and PFS were estimated using Kaplan-Meier curves and compared using the log-rank test. Cox proportional hazards regression models were applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for OS and PFS, adjusting for age, sex, BMI, sarcopenia and body composition parameters (SMI, SAT, and VAT). All reported p values were compared with a significance level of 5%. Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) software V.25.0 for Windows.

Results

Fifty-two patients with newly diagnosed MM between April 2019 and December 2023 were included in the study. A total of 29 (55.8%) were women with a median age at diagnosis of 77.6 ± 5.9 years. A total of 36 (69.2%) patients had a CCI score ≥3. More than half of the patients presented stage II according to the r-ISS criteria at diagnosis (31 [59.6%]). The median BMI was 28.8 ± 16.0 kg/m 2 .

Most patients were independent for basic and instrumental activities of daily living (59.6% Barthel 100; 38.5% Lawton 8), had no cognitive impairment (88.5% MMSE ≥24), and had no depressive symptoms (63.5% GDS 0–5). They were also well nourished according to GLIM criteria (65.4%), although at risk of malnutrition (MNA-SF ≤11, 67.3%). Moreover, most patients were robust or pre-frail (23.1% FRAIL 0; 51.9% FRAIL 1–2) or presented frailty to a low degree (48.1% Frail-VIG <0.2; 34.6% Frail-VIG 0.2–0.35). Additionally, most had not experienced falls in the previous year (78.8%). Nevertheless, only 9 patients (17.3%) were on less than 5 drugs.

Of the 52 patients included, 32 (61.5%) showed probable sarcopenia, defined as a low grip strength. Sarcopenia was confirmed with a low muscle mass in four cases (12.5%), two of them in a severe degree according to a low gait speed. The comparison between sarcopenic and non-sarcopenic is shown in Table 1 . Among non-sarcopenic patients, 83.3% and 75.5% had SAT and VAT areas greater than 100 cm 2 , respectively, whereas these proportions decreased to 50% for both measures in sarcopenic patients. However, these differences did not reach statistical significance (SAT: p = 0.104; VAT: p = 0.279). Despite being older and with more comorbidities, no statistically significant differences were seen concerning malnutrition, frailty, number of falls in the past year, or polypharmacy between sarcopenic and non-sarcopenic ( p ≥ 0.05). During the follow-up period, 11 patients (21.2%) died and 9 patients (17.3%) experienced disease progression. Mean OS was 43.1 months (95% CI: 38.1–48.0) for non-sarcopenic patients versus 18.0 months (95% CI: 0–36.1) for sarcopenic patients. The difference between groups was statistically significant (log-rank test, χ 2 = 10.35, p = 0.001). PFS analysis revealed no statistically significant differences according to sarcopenia status (41.9 months, 95% CI: 36.4–47.5 in non-sarcopenic patients vs. 35.4 months, 95% CI: 35.4–35.4 in sarcopenic patients; p = 0.491). In the multivariate Cox regression analysis, low SMI was strongly associated with an increased risk of event (HR: 46.8, 95% CI: 1.9–1,146.9, p = 0.018). BMI was independently protective (HR: 0.60, 95% CI: 0.41–0.89, p = 0.011). Sarcopenia, age, sex, and high SAT or VAT were not significantly associated with outcomes (see Fig. 2 ). For PFS, low SMI was the only variable significantly associated with an increased risk of progression (HR: 25.34, 95% CI: 1.72–374.27, p = 0.019) (see Fig. 3 ).

Discussion

This study describes the presence of sarcopenia in older patients with newly diagnosed MM. According to the EWGSOP2, only 4 patients from the 52 included presented confirmed sarcopenia and two of them had it in a severe degree. As described in Table 1 , no significant differences were found between sarcopenic and non-sarcopenic patients regarding baseline characteristics recorded in the CGA. Among these baseline variables, depression and cognition were also assessed, and although no significant differences were observed between groups, it is important to consider these domains as they may modulate functional status, are recognised risk factors for sarcopenia, and influence treatment tolerance in MM, ultimately impacting patients’ QoL [ 31 ] and potentially changing across treatment lines [ 32 ]. Moreover, sarcopenic patients showed significantly lower OS, and low muscle mass was associated with an increased risk of mortality and disease progression.

Several studies have shown the association between “sarcopenia” and poorer outcomes in patients with malignant haematological diseases, including myeloma. However, most of them used the pre-2010 concept of sarcopenia, considering only low muscle mass, without assessing strength or physical performance [ 8 , 17 ]. According to the current consensus [ 6 ], sarcopenia is not only the loss of muscle mass but also function [ 7 ]. Thereby, it has been found that low muscle mass, rather than sarcopenia, influences OS and PFS in patients with haematological malignancies [ 8 , 33 ]. In 2020, Umit et al. [ 10 ] retrospectively analysed muscle quantity by measuring psoas, quadriceps, and L3 muscle in PET/CT. They included 105 MM patients and observed a relationship between the loss of femoral muscle mass and survival. Nandakumar et al. [ 34 ] measured the skeletal muscle at L3 vertebrae in 322 MM patients. Patients with low muscle quantity (171, 53%) presented shorter median OS and higher 2-year mortality rates (44 months and 40% vs. 90 months and 18%, p < 0.0001 for both comparisons). By contrast, in a prospective study that included 341 MM newly diagnosed patients, no association was found between muscle area or radiodensity and OS [ 18 ].

Furthermore, low muscle mass is increasingly recognised as an independent risk factor for poor outcomes after haematopoietic stem cell transplantation (HSCT) [ 35 ]. In this line, Armenian et al. [ 36 ] proved its association with higher all-cause mortality (HR = 1.42, 95% CI = 1.09 to 1.78) in patients with haematological diseases. In patients with myeloma, low muscle mass detected by CT in the psoas at L3 has been associated with increased early post-transplant cardiovascular complications [ 17 ] and bone damage [ 15 ]. Further on, Park et al. [ 37 ] showed an association between a low paraspinal muscle index at the 12th thoracic vertebra and lower survival after HSCT in newly diagnosed MM patients. However, a growing number of studies find no differences. In a retrospective study by Surov et al. [ 9 ], CT-defined body composition, including skeletal muscle mass, did not influence MM patient’s survival after autologous stem cell therapy. Similar results were found by Annibali et al. [ 13 ] and Barajas Ordonez et al. [ 14 ] who did not demonstrate the relation between SMI and 2-year OS, PFS, or post-transplant adverse events in 129 patients with MM undergoing HSCT.

Other body composition parameters have also been correlated with poorer outcomes. In a systematic review conducted by Aleixo et al. [ 38 ] in 2022, seven studies were included in which adipopenia was associated with reduced OS in patients with haematologic malignancies. More specifically, high standardised uptake value and radiodensity (HU) in subcutaneous and VAT, as well as a low adipose area (cm 2 ) – that is, adipopenia – measured by PET-CT, have been linked to an increased risk of adverse events and mortality in MM [ 12 , 39 ]. Moreover, myosteatosis has been associated with an increased risk of fractures [ 40 ]. In our study, in addition to confirming an increased risk of mortality and disease progression in patients with MM and low muscle mass, we demonstrated significantly reduced survival in those who also presented low muscle strength. However, a high visceral and subcutaneous adipose area, or obesity, did not show an association with survival outcomes. Similar results have been reported in other studies.

On the other hand, few studies have been published showing functional results [ 41 , 42 ]. In a Danish cohort that included 100 newly diagnosed MM patients, six-minute walk test, sit-to-stand test (SST), grip strength, and knee extension strength were measured. In comparison to healthy and other cancer populations, these patients had poorer physical function but better grip strength [ 43 ]. Persoon et al. [ 44 ] published the physical results of a resistance and interval training program in patients with MM or lymphoma treated with HSCT. Grip strength, fat mass, fat-free mass, and body fat percentage by dual-energy X-ray absorptiometry and 30 s chair stand test were measured. They concluded that health-related physical fitness is comprised after recent HSCT. According to our results, most patients at MM diagnoses present probable sarcopenia due to a low handgrip (61.5%), a poor physical performance described by a Short Physical Performance Battery ≤8 (51.9%) but not a low 4-m gait speed (≤0.8 m/s 48.1%). Recently, Larsen et al. [ 45 ] have published the results of a randomised controlled trial studying the effect of an exercise program on physical function and activity in patients with MM. Despite SST, aerobic capacity, and QoL improved, knee extension strength declined, and no significant differences were observed between groups.

When low muscle mass is detected, a differential diagnosis might be made for malnutrition and cachexia [ 46 , 47 ]. It is considered one of the three phenotypic malnutrition criteria [ 21 ]. Therefore, reduced muscle mass accompanied by normal muscle strength suggests malnutrition rather than sarcopenia, whereas low muscle mass and impaired muscle function indicates sarcopenia instead. The incidence of malnutrition at haematological malignancies diagnosis varies between 30 and 50% [ 48 , 49 ]. On the other hand, cachexia describes severe weight loss and muscle wasting associated with cancer, HIV and AIDS, or end-stage organ failure [ 50 ]. Cachexia can coexist with sarcopenia, whereas inflammation and cytokines may be more critical in its pathophysiology [ 51 ].

As shown, much of the existing literature in MM based solely on body composition parameters should be interpreted with caution, and future studies should adopt these updated definitions to ensure conceptual accuracy and clinical applicability. Studies that include strength and muscle mass measurements are needed to adequately determine the prevalence of sarcopenia and its prognostic role in this subgroup of patients. Given the results of our small sample, the prevalence of sarcopenia may be overestimated so far, as not all determining factors have been evaluated. MM, unlike other haematologic malignancies such as acute myeloid leukaemia or lymphomas, is characterised by distinct features, most notably bone involvement driven by interleukin-6, a key growth factor for myeloma plasma cells. Lytic lesions extend beyond active haematopoietic sites and may also affect non-weight-bearing bones such as the skull, ultimately disrupting the biomechanics of the locomotor system [ 52 ]. Furthermore, corticosteroids such as dexamethasone, integral to standard treatment, exert independent effects on muscle metabolism and body composition. Together, disease-related bone damage and treatment-induced metabolic alterations contribute to muscle wasting, highlighting the need for systematic sarcopenia assessment in this setting.

The present study represents the first attempt to properly assess sarcopenia, incorporating both quantitative and functional measures. This approach allows for a more accurate differential diagnosis with other geriatric syndromes, such as malnutrition and frailty. Sarcopenia detection and treatment could help improve the functional status and quality of life of these patients [ 41 , 53 ]. Nevertheless, future studies should incorporate longitudinal assessments of muscle mass and strength, ideally at clinically relevant time points such as after first-line therapy, to better elucidate the impact of treatment on sarcopenia and to define its prognostic significance more accurately.

Statement of Ethics

The protocol was approved by the Independent Research Ethics Committee of Hospital Universitario Ramón y Cajal, Spain (225-19), and conducted according to the Declaration of Helsinki. All patients included signed an informed consent form.

Conflict of Interest Statement

The authors have no conflicts of interest to declare.

Funding Sources

This study was not supported by any sponsor or funder.

Author Contributions

P.S.-M.: conceptualisation, data curation, formal analysis, investigation, methodology, writing – original draft, and writing – review and editing. C.C.-T., C.S.-C., T.G.-B., M.J.B.-R., B.E.-G., C.N.-G., and J.M.L.: data curation, investigation, methodology, resources, and writing – review and editing. J.A.S.-R.: conceptualisation, data curation, formal analysis, investigation, methodology, supervision, and writing – review and editing. A.J.C.-J.: conceptualisation, data curation, formal analysis, investigation, methodology, supervision, writing – original draft, writing – review and editing, and resources. All authors approved the final version.

Data Availability Statement

The datasets generated and/or analysed during the current study are not publicly available due to patient privacy and confidentiality restrictions but are available from the corresponding author upon reasonable request.

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