Skip to main content
Download PDF

Sarcopenia defined by the global leadership initiative in sarcopenia (GLIS) consensus predicts adverse postoperative outcomes in patients undergoing radical gastrectomy for gastric cancer: analysis from a prospective cohort study

BMC Cancer volume 25, Article number: 679 (2025) Cite this article

Abstract

Background

Global Leadership Initiative in Sarcopenia (GLIS) has recently established a conceptional definition of sarcopenia, which incorporated muscle strength, mass, and muscle-specific strength as three components of sarcopenia. The present study aimed to investigate the value of sarcopenia defined by the GLIS consensus in predicting the postoperative outcomes.

Methods

Clinical data of 1654 patients who underwent radical gastrectomy for gastric cancer were prospectively collected. Muscle strength was measured by the grip strength test. Muscle mass was measured by calculating skeletal muscle index (SMI) using abdominal computed tomography images. Muscle-specific strength was determined by the ratio of grip strength to SMI. Sarcopenia was diagnosed by having low muscle-specific strength (criteria 1), or low muscle strength plus low muscle mass (criteria 2), or low muscle strength plus either low muscle mass or low muscle-specific strength (criteria 3).

Results

The incidence of sarcopenia identified by criteria 1, 2, and 3 were 24.2%, 17.0%, and 32.5%, respectively. All three criteria showed significant association with postoperative total complications, overall survival (OS), and disease-free survival (DFS). However, criteria 1 showed no significant association with severe complications. Criteria 2 did not remain significant in predicting DFS in the multivariate analyses. Criteria 3 showed the largest Youden index and area under receiver operating characteristic curve (AUC) in predicting total complications, 3-year and 5-year mortality, and low physical performance.

Conclusion

Sarcopenia defined by low muscle strength plus either low muscle mass or low muscle-specific strength showed optimal predictive value for postoperative outcomes in patients with gastric cancer.

Peer Review reports

Introduction

Sarcopenia is an age-related syndrome characterized by a progressive decline of skeletal muscle mass and function [1]. It is associated with a variety of adverse clinical outcomes such as frailty, falls, disability, and mortality [1, 2]. Moreover, sarcopenia is associated with a higher incidence of postoperative complications and worse long-term survival in patients with cancer [3,4,5]. Despite the large number of studies of sarcopenia conducted over the last two decades, the lack of a unified definition of sarcopenia led to discrepancies in the prevalence and consequence of sarcopenia reported between these studies. Moreover, it has impeded the construction of a standardized diagnosis and treatment protocol of sarcopenia in clinical settings. To address this issue, the Global Leadership Initiative in Sarcopenia (GLIS) was formed to establish a globally accepted definition of sarcopenia [6, 7]. A conceptional definition of sarcopenia was recently established by GLIS, which incorporated muscle mass, muscle strength and muscle-specific strength, as three components of sarcopenia [6].

Muscle-specific strength is a relatively new term, describing the muscle strength standardized to muscle mass [7]. There are few reports in the literature regarding the measurements and clinical significance of muscle-specific strength. Therefore, more data are needed to inform the optimum measurement of muscle-specific strength, as well as its association with clinical outcomes.

Despite the newly created conceptional definition of sarcopenia, the GLIS has not yet established an operational definition of sarcopenia. According to the statement from the GLIS consensus, the next steps are to carefully consider whether an operational definition should include one (muscle-specific strength), two (muscle mass and strength), or all three components (muscle mass, strength, and muscle-specific strength) of sarcopenia [6].

In the present study, we compared three operational criteria of sarcopenia developed from the GLIS consensus, based on their ability to identify sarcopenia, agreements between the criteria, and their prognostic value for clinical outcomes in patients undergoing radical gastrectomy for gastric cancer. The results provide helpful evidence for the future establishment of a global consensus operational definition of sarcopenia.

Material & methods

Patients

Patients who underwent radical gastrectomy for gastric cancer from July 2014 to December 2021 at the Department of Gastrointestinal Surgery, The First Affiliated Hospital of Wenzhou Medical University were included in this study. The inclusion criteria included patients who: (1) were older than 18 years old; (2) pathologically diagnosed with gastric adenocarcinoma before surgery; (3) planned to receive gastrectomy for gastric cancer with curative intent; (4) graded I to III according to the American Society of Anesthesiologists (ASA); and (5) had abdominal computed tomography (CT) images available within 1 month before surgery. The exclusion criteria included patients who: (1) were incapable of completing measurements of muscle strength and physical performance; and (2) were confirmed with cancer metastasis during surgery or underwent palliative operation. All patients were informed that their clinical information would be used anonymously for research purposes. A signed informed consent was achieved from each patient. This study was a part of a large prospective observational cohort study registered in the China Clinical Trial Registry (NO. ChiCTR1800019717). The research methods were approved by the Ethical Committee of The First Affiliated Hospital of Wenzhou Medical University. All patients received standard treatments under the management of professional oncology teams including oncologists, surgeons, radiation oncologists, nutrition specialists, etc [8]. The treatment protocols were made according to the Japanese gastric cancer treatment guidelines [9].

Data collection

The following data were prospectively collected: (1) patients’ baseline characteristics before surgery, including age, gender, body mass index (BMI), ASA grade, levels of blood hemoglobin and serum albumin, and Nutritional Risk Screening 2002 (NRS 2002) scores; (2) surgical information, including type of gastrectomy, laparoscopy-assisted surgery, and combined organ resection; (3) pathological characteristics of tumor, including tumor location, histological differentiation, and tumor–node–metastasis (TNM) stage; and (4) postoperative outcomes, including complications, length of hospital stay and costs. Postoperative complications were graded by the Clavien-Dindo classification. Only complications classified as grade II or above were analyzed, and severe complications were defined as complications graded III and above [10].

Follow-up

All patients were followed-up in the outpatient department after surgery. The timepoint for the routine followed-up was 1 month after surgery, and then every 3 months for the first 2 years, and every 6 months thereafter. The follow-up program included a regular physical examination, laboratory tests, imageological examinations such as ultrasonography and CT, and endoscopy as needed. Overall survival (OS) was defined as the period from surgery to death of any causes. Disease-free survival (DFS) was defined as the period from surgery to cancer re-occurrence or death from any causes, whichever came first.

Measurement of body composition

Preoperative abdominal CT images at the third lumbar vertebra level were used to measure the body compositional parameters. Different body compositions were distinguished by the Hounsfield unit (HU) using a specialized image processing system (GE ADW 4.5). Skeletal muscle was identified within a HU range of -29 to + 150. Skeletal muscle index (SMI) was calculated by normalization of skeletal muscle area to height square. The mean HU within the skeletal muscle area was calculated to determine skeletal muscle density (SMD) [7, 11]. Visceral fat area (VFA) and subcutaneous fat area (SFA) were identified within a HU range of -150 to -50, and − 190 to -30, respectively. As determined from our previous studies, the cut-off values for SMI to define low muscle mass were 34.9 cm2/m2 in females and 40.8 cm2/m2 in males [12], and the cut-off values for SMD to define low muscle quality were 28.6 HU in females and 38.5 HU in males [13].

Measurement of muscle strength and physical performance

Muscle strength was measured from a grip strength test before surgery by using electronic handgrip dynamometers (EH101, Camry, China). Physical performance was assessed before surgery by the 6-meters usual gait speed test. The cut-off values for low grip strength were 28 kg in males and 18 kg in females, and the cut-off for low gait speed was 1 m/s for both genders, based on reference values from the consensus of the Asian Working Group for Sarcopenia in 2019 [2].

Measurement of muscle-specific strength

Muscle-specific strength was determined by the ratio of grip strength to SMI. The sex-specific cut-off values for muscle-specific strength (grip strength/SMI) were calculated using the method of optimal stratification with respect to overall survival, which were 0.4939 kg/(cm2/m2) for males, and 0.4726 kg/(cm2/m2) for females.

Diagnosis of sarcopenia

Based on the GLIS conceptual definition, sarcopenia was diagnosed based on three different criteria containing one, two, or three conceptional components of sarcopenia, respectively. Criteria 1 included only low muscle-specific strength. Criteria 2 included low muscle strength plus low muscle mass. Criteria 3 included low muscle strength plus either low muscle mass or low muscle-specific strength. Based on the revised European consensus on definition and diagnosis of sarcopenia developed by European Working Group on Sarcopenia in Older People 2 (EWGSOP2), sarcopenia was diagnosed by low muscle strength plus either low muscle mass or quality [1]. According to the Asian Working Group for Sarcopenia (AWGS), sarcopenia was diagnosed by low muscle mass plus either low muscle strength or physical performance [2].

Statistical analysis

Continuous or categorical data were presented as medians with interquartile ranges (IQR) or numbers with percentages, respectively. Comparisons between two groups of continuous data were performed using a Mann–Whitney U-test. Comparisons between different groups of categorical data were performed using Pearson’s Chi-squared tests or Fisher’s exact tests. Spearman’s correlation coefficients were calculated to evaluate correlations between muscle-specific strength and other body compositional and functional parameters. Kappa coefficients were calculated to assess the agreement between the three sarcopenia criteria. Sensitivity, specificity, Youden index and area under receiver operating characteristic curve (AUC), were calculated to assess the predictive value of the three sarcopenia criteria for the adverse outcomes. Univariate or adjusted multivariate logistic analyses were performed to investigate the association between sarcopenia and postoperative complications. Survival curves were plotted using the Kaplan–Meier method, and survival between two groups were compared using the log-rank tests. Univariate and adjusted multivariate Cox hazards proportional regression analyses were performed to assess the relationship between sarcopenia and long-term survival. Confounders that were significantly associated with sarcopenia and were significantly associated with or commonly accepted to be relevant to the outcomes were selected for the construction of multivariate models. To avoid multicollinearity, factors that were highly correlated with sarcopenia, such as body composition and function parameters (SMI, SMD, grip strength, etc.) were not included in the multivariate models. Variance inflation factor (VIF) was calculated to estimate the multicollinearity. Factors with VIF ≥ 10 were excluded from multivariate analyses. The cut-off of muscle-specific strength was calculated based on the method of optimal stratification using the ‘survminer’ package of the R software. Categorized by the cut-off values, the two groups were best separated for overall survival. SPSS statistics 22.0, R (version 4.3.3), and Graphpad Prism 9 were used for data analyses. Two-tailed P values < 0.05 were considered statistically significant.

Results

A total of 1654 patients who underwent radical gastrectomy for gastric cancer were included in this study. There were 401 (24.2%) patients who were diagnosed with sarcopenia by criteria 1 (low muscle-specific strength), 282 (17.0%) patients were diagnosed with sarcopenia by criteria 2 (low muscle strength plus low muscle mass), and 538 (32.5%) patients by criteria 3 (low muscle strength plus either low muscle mass or low muscle-specific strength) (Fig. 1a). The correlations and overlaps among the three criteria were further shown in Fig. 1b. Criteria 2 were totally included in criteria 3, and the majority cases of criteria 1 (91.8%, 368/401) were included in criteria 3. Criteria 3 showed substantial agreement with criteria 1 (kappa coefficient 0.701) and moderate agreement with criteria 2 (kappa coefficient 0.598). However, the agreement between criteria 1 and criteria 2 was slight, with a kappa coefficient of 0.160.

As shown in Table 1, patients with sarcopenia identified by all three criteria had older age, lower levels of albumin and hemoglobin, and higher NRS 2002 scores, compared with those without sarcopenia. Sarcopenia identified by criteria 2 showed higher ASA grade. Females had a higher incidence of sarcopenia identified by criteria 1 and 3, but not by criteria 2. In body compositional and functional parameters, sarcopenia identified by all three criteria showed lower SMD, lower HGS, and lower gait speed. Sarcopenia diagnosed by criteria 2 and 3 showed lower BMI, SMI, and VFA, whereas sarcopenia diagnosed by criteria 1 did not show differences in these factors. Interestingly, patients with sarcopenia defined by criteria 1 showed higher SFA, whereas patients with sarcopenia defined by criteria 2 and 3 showed lower SFA. For the tumor characteristic factors, sarcopenia diagnosed by criteria 2 and 3 but not criteria 1 showed more advanced TNM stage. No difference was found in tumor location or histological differentiation of tumor between sarcopenic and non-sarcopenic patients diagnosed using either of these criteria. For the surgical procedure details, patients with sarcopenia diagnosed by criteria 2 received fewer laparoscopic surgeries compared with those without sarcopenia. No difference was found in the type of gastrectomy or combined organ resection between sarcopenia and non-sarcopenia groups identified by either of these criteria (Table 1).

Table 1 Baseline characteristics of patients defined by the three diagnostic criteria of sarcopenia
Full size table
Fig. 1
figure 1

Numbers of patients diagnosed with sarcopenia based on the three GLIS criteria

Full size image

Postoperative complications occurred in 423 (25.6%) patients, in which 98 (5.9%) were identified as having severe complications. Patients with sarcopenia diagnosed by all three criteria had a higher incidence of postoperative complications. However, criteria 1 did not show significant association with severe complications. Sarcopenia identified by all three criteria was associated with longer length of hospital stays and higher costs (Supplementary Table 1).

Logistic regression analyses were performed to further assess the association between sarcopenia criteria and postoperative complications (Table 2). Sarcopenia identified by all three criteria was an independent risk factor for total postoperative complications in multivariate logistic analyses adjusting for age, gender, BMI, ASA grade, and TNM stage of tumor. The odds ratio (OR) of criteria 1 was smaller than that of criteria 2 and criteria 3 both in the univariate and the multivariate analyses for total postoperative complications. Moreover, criteria 2 and criteria 3 were independently associated with the occurrence of severe complications, whereas no significant association was found between severe complications and criteria 1 either in the univariate or multivariate analyses.

The median follow-up period was 60.9 months for the whole cohort. Patients with sarcopenia identified by all three criteria showed worse OS and DFS (Fig. 2). Similarly, univariate Cox regression analyses showed that all three sarcopenia criteria were associated with worse OS and DFS. Moreover, sarcopenia diagnosed by either criteria 1 or criteria 3 was an independent predictor for OS and DFS in the multivariate analyses after adjusting for age, gender, BMI, ASA grade, TNM stage, and histological differentiation of tumor. However, sarcopenia identified by criteria 2 did not remain significant for DFS in the multivariate analyses (Table 3).

To minimize bias, propensity score matching (PSM) was performed to balance covariates between patients with and without sarcopenia with a matching ratio of 1:1. After PSM, there were 377, 272, and 477 pairs of patients with and without sarcopenia based on GLIS-Criteria 1, 2 and 3, respectively (Supplementary Tables S2–S4). The baseline characteristics of patients in the sarcopenic and non-sarcopenic groups were balanced after PSM as shown by the P value and the absolute standardized mean difference (Supplementary Tables S2–S4). Univariate analysis for complications and survivals were performed after PSM. The results of univariate analysis after PSM were generally consistent with the results of multivariate analysis before matching. To be specific, all three GLIS criteria were significantly associated with total complications before and after matching. Criteria 2 and 3 were significantly associated with severe complications before and after matching, whereas criteria 1 were not significantly associated with severe complications either before or after matching (Supplementary Table S5). Criteria 1 and 3 were significantly associated with OS and DFS both before and after matching. Criteria 2 were significantly associated with OS but not with DFS in the multivariate analysis before matching, whereas criteria 2 were not significantly associated with OS or DFS after matching (Supplementary Table S6). Collectively, both multivariate analysis before matching and univariate analysis after matching suggested that criteria 3 were the most consistent risk factor for complications and survivals, whereas criteria 1 were not predictive for severe complications, and criteria 2 were not predictive for survivals.

The prognostic values of the three criteria of sarcopenia were further assessed by comparing the sensitivity, specificity, Youden index, and AUC in predicting the adverse outcomes (Table 4). Criteria 3 showed the highest sensitivity in predicting total complications, severe complications, 3-year and 5-year mortality, and low physical performance. Despite the relatively low specificity, criteria 3 demonstrated the highest Youden index and AUC in the prediction of total complications, 3-year and 5-year mortality, and low physical performance.

The correlations between muscle-specific strength and body compositional and functional parameters are shown in the scatter diagrams (Fig. 3). Muscle strength had the strongest correlation with muscle-specific strength among all the parameters (Fig. 3a). However, SMI, another component of muscle-specific strength, showed only a weak negative correlation with muscle-specific strength (Fig. 3b). Muscle-specific strength showed a significant positive correlation with SMD (Fig. 3c), and a weak but significant negative correlation with VFA and SFA (Fig. 3d and e). There was a significant positive correlation between muscle-specific strength and gait speed (Fig. 3f). Multivariate logistic analysis showed that low muscle density was an independent risk factor for low muscle-specific strength (adjusted OR 1.468, 95% 1.124–1.917) (Supplementary Table S7).

To further demonstrate the value of muscle-specific strength compared with the other two components of sarcopenia, sub-group analyses were performed in patients with normal muscle mass or strength. Low muscle-specific strength was identified as an independent predictor for postoperative complications (adjusted OR 1.502, 95% CI 1.079–2.090, P = 0.016), OS (adjusted HR 1.612, 95% CI 1.224–2.123, P = 0.001) and DFS (adjusted HR 1.558, 95% CI 1.221–1.987, P < 0.001) in patients with normal muscle mass (Supplementary Tables S8–S10). However, there was a low prevalence of low muscle-specific strength in patients with normal muscle strength (3.4%, 33/980). Low muscle-specific strength was not significantly associated with postoperative complications (P = 0.245, chi-square test), OS (P = 0.152, Log-Rank test), or DFS (P = 0.348, Log-Rank test) in patients with normal muscle strength.

Table 2 Univariate and multivariate logistic regression analyses assessing the association between postoperative complications and sarcopenia identified by the three different criteria
Full size table
Fig. 2
figure 2

Kaplan–Meier survival curves of patients with or without sarcopenia based on the three criteria. (a) Overall survival and (d) disease-free survival of patients with or without sarcopenia based on criteria 1; (b) overall survival and (e) disease-free survival of patients with or without sarcopenia based on criteria 2; and (c) overall survival and (f) disease-free survival of patients with or without sarcopenia based on criteria 3

Full size image
Table 3 Univariate and multivariate Cox hazards proportional regression analyses assessing the association between long-term survival and sarcopenia identified by the three different criteria
Full size table
Table 4 Sensitivity, specificity, Youden index, and AUC of the three criteria of sarcopenia for the prediction of adverse outcomes
Full size table
Fig. 3
figure 3

Correlations between muscle-specific strength and body compositional and functional parameters. (a) Correlation between muscle-specific strength and grip strength; (b) between muscle-specific strength and SMI; (c) between muscle-specific strength and SMD; (d) between muscle-specific strength and VFA; (e) between muscle-specific strength and SFA; (f) between muscle-specific strength and gait speed

Full size image

.

Discussion

Grip strength standardized to SMI as a measurement of muscle-specific strength

Muscle-specific strength is a relatively new term, defined as strength standardized to muscle size [7]. In the present study, we used grip strength standardized to SMI to measure the muscle-specific strength. Although SMI as determined by abdominal CT did not reflect the volume of muscle that was directly responsible for grip strength, it correlated significantly with muscle mass of the entire body [14, 15]. CT is considered the gold standard for measuring muscle mass [1]. Moreover, in patients with diseases in which abdominal CT scan is routine tested for diagnostic purposes, SMI determined by CT is an easily accessible and accurate measure of muscle mass. Measurement of SMI by abdominal CT does not require additional examinations or costs for these patients. Grip strength is the most common measure for strength in sarcopenia research. Grip strength has been widely adopted as a singular indicator of overall strength, based on the consistency of grip strength measurements with strength measured in other body compartments [1, 16,17,18]. Compared with other measurements of strength such as leg extension strength, the grip strength test is simpler, making it more feasible for use in clinical settings. Since grip strength and SMI correlate well with overall muscle strength and mass, respectively, we contend that grip strength standardized to SMI could be a good measure of muscle-specific strength of the whole body. This notion is also supported by the significant predictive value of grip strength/SMI for the adverse outcomes described in the present study. Moreover, compared with other measurements such as leg extension strength standardized to quadriceps muscle volume, grip strength standardized to SMI is more feasible for application in clinical practice.

Relationship between muscle-specific strength, muscle density, and muscle quality

Fat infiltration in muscle is one of the hallmarks of sarcopenia [19]. Aging is associated with dysfunction of energy metabolism in skeletal muscle, which compromises muscle function and leads to an accumulation of lipids within muscle [19, 20]. Higher fat content within skeletal muscle is associated with lower muscle density [11]. In the present study, we found a significant positive correlation between muscle density and muscle-specific strength (Fig. 3c). Moreover, low muscle density was identified as an independent risk factor for low muscle-specific strength (Supplementary Table S2). Both muscle-specific strength [21, 22] and muscle density [23, 24] have been used to describe muscle quality in previous studies. Therefore, our findings reveal a close relationship between muscle density and muscle-specific strength, both of which are indicators of muscle quality. In summary, muscle density reflects muscle quality from a microstructure and pathological view, whereas muscle-specific strength reflects muscle quality from a macroscopic and functional perspective [1, 7].

Muscle-specific strength adds prognostic value to sarcopenia aside from muscle mass and strength

The impairment of muscle quality precedes the loss of muscle mass during aging [25]. Therefore, a decline in muscle-specific strength likely reflects impaired muscle health even before muscle wasting becomes apparent. As a consequence, adding muscle-specific strength to the diagnostic criteria of sarcopenia led to a significant increase in the incidence of sarcopenia in the present study. Based on criteria 3, an additional 256 patients were diagnosed with sarcopenia due to low muscle-specific strength (Fig. 1). This accounted for 47.6% of all patients diagnosed with sarcopenia by criteria 3. As for the clinical outcomes, criteria 3 demonstrated the best predictive value for postoperative total complications, 3-year and 5-year mortality, and low physical performance among the three criteria, as shown by the highest Youden index and AUC in predicting these outcomes (Table 4). Moreover, sub-group analyses revealed that low muscle-specific strength was predictive for postoperative complications and survival in patients with normal muscle mass (Supplementary Tables S3–S5). The results of sub-group analyses indicated that measurement of muscle-specific strength was necessary to identify patients at high risk of developing adverse outcomes even though muscle mass was normal. Therefore, the addition of muscle-specific strength to the diagnostic criteria of sarcopenia could promote the early identification of sarcopenia and reinforce the prognostic value of sarcopenia for adverse outcomes.

Low muscle strength as the premise condition for the diagnosis of sarcopenia

The present study focused on low muscle strength as the premise condition for the diagnosis of sarcopenia, which was in accordance with the revised European consensus on the definition and diagnosis of sarcopenia [1]. Low muscle strength was considered as the key characteristic of sarcopenia because of its superior predictive value for adverse outcomes than muscle mass [1, 26, 27]. Compared with the criteria containing low muscle strength (criteria 2 and criteria 3), criteria 1 (low muscle-specific strength alone) showed weaker predictive value for postoperative total complications, evident from the smaller OR in the logistic analyses (Table 2). Moreover, low muscle-specific strength showed no significant association with severe complications (Table 2). Thus, low muscle-specific strength alone was not sufficient in predicting adverse outcomes. Sub-group analyses showed that in patients with normal muscle strength, there was a low prevalence of low muscle-specific strength (3.4%). Moreover, low muscle-specific strength was not significantly associated with adverse outcomes in patients with normal muscle strength. The results of sub-group analyses indicated that there was little value measuring muscle-specific strength when muscle strength was normal. Thus, muscle strength should be measured before further assessments of muscle-specific strength. Therefore, our findings recommend that low muscle strength should be the premise condition for the diagnosis of sarcopenia.

Criteria 3 as the optimal GLIS operational diagnostic criteria for sarcopenia

Based on the results of the present study, criteria 3 provided the optimal operational diagnostic criteria of sarcopenia within the three GLIS criteria. First, the incidence of sarcopenia was highest when identified by criteria 3, indicating this as the best identification power of sarcopenia. Early identification of patients with sarcopenia could facilitate early interventions, which in turn, could improve clinical outcomes. Second, criteria 3 showed the best agreement with the other two criteria. Criteria 3 included all three conceptual components of sarcopenia, which comprehensively reflects the different aspects of sarcopenia. Third, sarcopenia diagnosed by criteria 3 showed the best predictive value for the adverse outcomes.

Comparison of GLIS-Criteria 3 with EWGSOP2 and AWGS sarcopenia definitions

EWGSOP2 and AWGS sarcopenia definitions were two commonly used criteria of sarcopenia in literature [1, 2]. Since the above analysis showed that criteria 3 had the optimal predictive value for the postoperative outcomes among the three GLIS criteria, we further compared GLIS-Criteria 3 with EWGSOP2 and AWGS sarcopenia definitions for the prediction of surgical outcomes (Supplementary Table S11). The incidence of sarcopenia based on GLIS-Criteria 3, EWGSOP2, and AWGS definitions were 32.5%, 28.7%, and 30.6%, respectively. The overlaps of patients diagnosed with sarcopenia based on the three criteria were shown in Supplementary Fig. S1. GLIS-Criteria 3 had the highest sensitivity in predicting total complications, severe complications, 3-year and 5-year mortality. However, the specificity in predicting adverse outcomes was the lowest for GLIS-Criteria 3. The Youden index and AUC were at similar levels for GLIS-Criteria 3, EWGSOP2, and AWGS definitions in predicting the adverse outcomes. Therefore, we concluded that GLIS-Criteria 3 had similar predictive power for adverse surgical outcomes compared with EWGSOP2 and AWGS definitions in patients undergoing radical gastrectomy for gastric cancer. GLIS-Criteria 3 had the highest incidence of sarcopenia and highest sensitivity for the prediction of adverse postoperative outcomes, which may facilitate screening and prehabilitation of patients with high surgical risk.

Value of grip strength in sarcopenia diagnosis and preoperative risk stratification

The present study showed that grip strength played a key role in sarcopenia assessment based on the GLIS criteria. Moreover, grip strength is a strong predictor of adverse postoperative outcomes. Marano et al. demonstrated that lower grip strength is significantly associated with prolonged length of hospital stay in patients undergoing abdominal surgeries, independent of age and other covariates [28]. Zhuang et al. reported that low grip strength was associated with overall mortality in various types of cancer [29]. Therefore, integrating grip strength measurements into routine preoperative assessments could aid in identifying patients at higher surgical risk, thereby facilitating targeted interventions to improve surgical outcomes.

Potential prehabilitation strategies to improve surgical outcomes

Prehabilitation strategies such as resistance training, nutrition optimization, and anabolic therapies have been reported to be effective in improving outcomes after major abdominal surgeries [30]. However, the optimal prehabilitation protocol for specific patients has not been fully established [30]. Our study demonstrated the strong correlations between GLIS-defined sarcopenia and surgical outcomes. Therefore, it is worthwhile investigating the effect of prehabilitation strategies on surgical outcomes in patients with GLIS-defined sarcopenia.

Advantages and limitations

To our knowledge, the present study represents the first clinical research to validate the GLIS conceptual definition of sarcopenia. Our findings provide evidence for the future development of a global consensus for operational definition of sarcopenia. Our prospectively collected data had a large sample size with detailed information on muscle strength, physical performance, and body compositional parameters, enabling us to perform more thorough data analyses and identify valid conclusions. The present study was limited by its single-center study design. The conclusion of our study was obtained only from patients with curative gastric cancer. More studies based on patients with other types of cancer or other surgical settings were needed to validate and generalize the GLIS definition of sarcopenia in different clinical settings. The study focused on the impact of sarcopenia on complications and survival. However, we did not include data on quality of life after surgery, which was another important postoperative outcome. Future studies were needed to investigate the influence of GLIS-defined sarcopenia on quality of life after gastrectomy for gastric cancer [31].

Conclusion

In conclusion, our study demonstrated that sarcopenia defined by the three components proposed by the GLIS consensus (muscle strength, mass, and muscle-specific strength) was predictive of adverse outcomes in patients undergoing radical gastrectomy for gastric cancer. Addition of muscle-specific strength to the diagnostic criteria of sarcopenia increased the identification power of sarcopenia and added prognostic value to the prediction of adverse outcomes. Low muscle strength plus either low muscle mass or low muscle-specific strength provided the optimal operational diagnostic criteria for sarcopenia, based on having the highest identification power of sarcopenia, the best agreement with the other two criteria, and the greatest predictive value for adverse outcomes.

Data availability

Data is available from the corresponding authors upon reasonable requests.

Abbreviations

GLIS:

Global Leadership Initiative in Sarcopenia

CT:

Computed tomography

BMI:

Body mass index

ASA:

American Society of Anesthesiologists

NRS 2002:

Nutritional Risk Screening 2002

TNM:

Tumor–node–metastasis

OS:

Overall survival

DFS:

Disease-free survival

HU:

Hounsfield unit

SMI:

Skeletal muscle index

SMD:

Skeletal muscle density

VFA:

Visceral fat area

SFA:

Subcutaneous fat area

IQR:

Interquartile ranges

AUC:

Area under receiver operating characteristic curve

VIF:

Variance inflation factor

References

  1. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, Cooper C, Landi F, Rolland Y, Sayer AA, Schneider SM, Sieber CC, Topinkova E, Vandewoude M, Visser M, Zamboni M. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(4):601.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, Jang HC, Kang L, Kim M, Kim S, Kojima T, Kuzuya M, Lee JSW, Lee SY, Lee WJ, Lee Y, Liang CK, Lim JY, Lim WS, Peng LN, Sugimoto K, Tanaka T, Won CW, Yamada M, Zhang T, Akishita M, Arai H. Asian working group for sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc. 2020;21(3):300–e307302.

    Article  PubMed  Google Scholar 

  3. Huang DD, Wang SL, Zhuang CL, Zheng BS, Lu JX, Chen FF, Zhou CJ, Shen X, Yu Z. Sarcopenia, as defined by low muscle mass, strength and physical performance, predicts complications after surgery for colorectal cancer. Colorectal Disease: Official J Association Coloproctology Great Br Irel. 2015;17(11):O256–264.

    Article  Google Scholar 

  4. Li ZZ, Yan XL, Jiang HJ, Ke HW, Chen ZT, Chen DH, Xu JY, Liu XC, Shen X, Huang DD. Sarcopenia predicts postoperative complications and survival in colorectal cancer patients with GLIM-defined malnutrition: analysis from a prospective cohort study. Eur J Surg Oncology: J Eur Soc Surg Oncol Br Association Surg Oncol. 2024;50(1):107295.

    Article  Google Scholar 

  5. Trejo-Avila M, Bozada-Gutiérrez K, Valenzuela-Salazar C, Herrera-Esquivel J, Moreno-Portillo M. Sarcopenia predicts worse postoperative outcomes and decreased survival rates in patients with colorectal cancer: a systematic review and meta-analysis. Int J Colorectal Dis. 2021;36(6):1077–96.

    Article  PubMed  Google Scholar 

  6. Kirk B, Cawthon PM, Arai H, Ávila-Funes JA, Barazzoni R, Bhasin S, Binder EF, Bruyere O, Cederholm T, Chen LK, Cooper C, Duque G, Fielding RA, Guralnik J, Kiel DP, Landi F, Reginster JY, Sayer AA, Visser M, von Haehling S, Woo J, Cruz-Jentoft AJ. The conceptual definition of sarcopenia: Delphi consensus from the global leadership initiative in sarcopenia (GLIS). Age Ageing 2024, 53(3).

  7. Cawthon PM, Visser M, Arai H, Ávila-Funes JA, Barazzoni R, Bhasin S, Binder E, Bruyère O, Cederholm T, Chen LK, Cooper C, Duque G, Fielding RA, Guralnik J, Kiel DP, Kirk B, Landi F, Sayer AA, Von Haehling S, Woo J, Cruz-Jentoft AJ. Defining terms commonly used in sarcopenia research: a glossary proposed by the global leadership in sarcopenia (GLIS) steering committee. Eur Geriatr Med. 2022;13(6):1239–44.

    Article  PubMed  PubMed Central  Google Scholar 

  8. De Felice F, Malerba S, Nardone V, Salvestrini V, Calomino N, Testini M, Boccardi V, Desideri I, Gentili C, De Luca R, Marano L. Progress and challenges in integrating nutritional care into oncology practice: results from a National survey on behalf of the nutrionc research group. Nutrients 2025, 17(1).

  9. Japanese gastric cancer treatment guidelines. 2010 (ver. 3). Gastric cancer: official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association 2011, 14(2):113–123.

  10. Dindo D, Demartines N, Clavien PA. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240(2):205–13.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Goodpaster BH, Kelley DE, Thaete FL, He J, Ross R. Skeletal muscle Attenuation determined by computed tomography is associated with skeletal muscle lipid content. J Appl Physiol (Bethesda Md: 1985). 2000;89(1):104–10.

    Article  CAS  Google Scholar 

  12. Zhuang CL, Huang DD, Pang WY, Zhou CJ, Wang SL, Lou N, Ma LL, Yu Z, Shen X. Sarcopenia is an independent predictor of severe postoperative complications and Long-Term survival after radical gastrectomy for gastric cancer: analysis from a Large-Scale cohort. Medicine. 2016;95(13):e3164.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Zhuang CL, Shen X, Huang YY, Zhang FM, Chen XY, Ma LL, Chen XL, Yu Z, Wang SL. Myosteatosis predicts prognosis after radical gastrectomy for gastric cancer: A propensity score-matched analysis from a large-scale cohort. Surgery. 2019;166(3):297–304.

    Article  PubMed  Google Scholar 

  14. Mourtzakis M, Prado CM, Lieffers JR, Reiman T, McCargar LJ, Baracos VE. A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme 2008, 33(5):997–1006.

  15. Fearon K, Strasser F, Anker SD, Bosaeus I, Bruera E, Fainsinger RL, Jatoi A, Loprinzi C, MacDonald N, Mantovani G, Davis M, Muscaritoli M, Ottery F, Radbruch L, Ravasco P, Walsh D, Wilcock A, Kaasa S, Baracos VE. Definition and classification of cancer cachexia: an international consensus. Lancet Oncol. 2011;12(5):489–95.

    Article  PubMed  Google Scholar 

  16. Bohannon RW. Grip strength: an indispensable biomarker for older adults. Clin Interv Aging. 2019;14:1681–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Takahashi J, Nishiyama T, Matsushima Y. Does grip strength on the unaffected side of patients with hemiparetic stroke reflect the strength of other ipsilateral muscles? J Phys Therapy Sci. 2017;29(1):64–6.

    Article  Google Scholar 

  18. Bohannon RW, Magasi SR, Bubela DJ, Wang YC, Gershon RC. Grip and knee extension muscle strength reflect a common construct among adults. Muscle Nerve. 2012;46(4):555–8.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Al Saedi A, Debruin DA, Hayes A, Hamrick M. Lipid metabolism in sarcopenia. Bone. 2022;164:116539.

    Article  CAS  PubMed  Google Scholar 

  20. Crane JD, Devries MC, Safdar A, Hamadeh MJ, Tarnopolsky MA. The effect of aging on human skeletal muscle mitochondrial and intramyocellular lipid ultrastructure. Journals Gerontol Ser Biol Sci Med Sci. 2010;65(2):119–28.

    Google Scholar 

  21. Lynch NA, Metter EJ, Lindle RS, Fozard JL, Tobin JD, Roy TA, Fleg JL, Hurley BF. Muscle quality. I. Age-associated differences between arm and leg muscle groups. J Appl Physiol (Bethesda Md: 1985). 1999;86(1):188–94.

    Article  CAS  Google Scholar 

  22. Tracy BL, Ivey FM, Hurlbut D, Martel GF, Lemmer JT, Siegel EL, Metter EJ, Fozard JL, Fleg JL, Hurley BF. Muscle quality. II. Effects Of strength training in 65- to 75-yr-old men and women. Journal of applied physiology (Bethesda, Md: 1985) 1999, 86(1):195–201.

  23. Huang DD, Wu GF, Luo X, Song HN, Wang WB, Liu NX, Yu Z, Dong QT, Chen XL, Yan JY. Value of muscle quality, strength and gait speed in supporting the predictive power of GLIM-defined malnutrition for postoperative outcomes in overweight patients with gastric cancer. Clin Nutr. 2021;40(6):4201–8.

    Article  CAS  PubMed  Google Scholar 

  24. Huang DD, Cai HY, Wang WB, Song HN, Luo X, Dong WX, Dong QT, Chen XL, Yan JY. Measurement of muscle quantity/quality has additional predictive value for postoperative complications and long-term survival after gastrectomy for gastric cancer in patients with probable sarcopenia as defined by the new EWGSOP2 consensus: analysis from a large-scale prospective study. Nutr (Burbank Los Angeles Cty Calif). 2021;86:111156.

    Article  Google Scholar 

  25. McGregor RA, Cameron-Smith D, Poppitt SD. It is not just muscle mass: a review of muscle quality, composition and metabolism during ageing as determinants of muscle function and mobility in later life. Longev Healthspan. 2014;3(1):9.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Schaap LA, van Schoor NM, Lips P, Visser M. Associations of sarcopenia definitions, and their components, with the incidence of recurrent falling and fractures: the longitudinal aging study Amsterdam. The journals of gerontology series A, biological sciences and medical sciences 2018, 73(9):1199–204.

  27. Schaap LA, Koster A, Visser M. Adiposity, muscle mass, and muscle strength in relation to functional decline in older persons. Epidemiol Rev. 2013;35:51–65.

    Article  PubMed  Google Scholar 

  28. Marano L, Carbone L, Poto GE, Gambelli M, Nguefack Noudem LL, Grassi G, Manasci F, Curreri G, Giuliani A, Piagnerelli R, Savelli V, Marrelli D, Roviello F, Boccardi V. Handgrip strength predicts length of hospital stay in an abdominal surgical setting: the role of frailty beyond age. Aging Clin Exp Res. 2022;34(4):811–7.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Zhuang CL, Zhang FM, Li W, Wang KH, Xu HX, Song CH, Guo ZQ, Shi HP. Associations of low handgrip strength with cancer mortality: a multicentre observational study. J cachexia Sarcopenia Muscle. 2020;11(6):1476–86.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Hughes MJ, Hackney RJ, Lamb PJ, Wigmore SJ, Christopher Deans DA, Skipworth RJE. Prehabilitation before major abdominal surgery: A systematic review and Meta-analysis. World J Surg. 2019;43(7):1661–8.

    Article  PubMed  Google Scholar 

  31. Calomino N, Malerba M, Tanzini G. [Total gastrectomy and quality of life]. Minerva Chirurgica. 1998;53(3):135–40.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This study was funded by Wenzhou Municipal Science and Technology Bureau (Y2023487) and the Natural Science Foundation of Zhejiang Province (Q24H070008).

Author information

Author notes

  1. Gao-Feng Wu and Chen-Hao He contributed equally to this work.

Authors and Affiliations

  1. Department of Gastrointestinal Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China

    Gao-Feng Wu, Chen-Hao He, Wen-Tao Xi, Wen-Bo Zhai, Zong-Ze Li, Xian Shen & Dong-Dong Huang

  2. First School of Clinical Medicine, Wenzhou Medical University, Wenzhou, China

    Ye-Cheng Zhu & Xiu-Bo Tang

  3. Department of Colorectal Anal Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China

    Xia-Lin Yan

  4. Centre for Muscle Research, Department of Anatomy and Physiology, University of Melbourne, Melbourne, VIC, Australia

    Gordon S. Lynch & Dong-Dong Huang

Authors
  1. Gao-Feng Wu
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Chen-Hao He
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Wen-Tao Xi
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Wen-Bo Zhai
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Zong-Ze Li
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Ye-Cheng Zhu
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Xiu-Bo Tang
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Xia-Lin Yan
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Gordon S. Lynch
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Xian Shen
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Dong-Dong Huang
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

G.F.W.: Data curation, Investigation, Software, Writing– original draft. C.H.H.: Investigation, Methodology, Writing– review & editing. W.T.X: Formal analysis, Investigation. W.B.Z.: Data curation, Investigation. Z.Z.L.: Data curation, Validation. Y.C.Z.: Data curation. X.B.T.: Data curation. X.L.Y.: Investigation, Funding acquisition. G.S.L.: Writing– review & editing. X.S.: Conceptualization, Project administration, Supervision. D.D.H.: Conceptualization, Funding acquisition, Supervision, Writing– review & editing.

Corresponding authors

Correspondence to Xian Shen or Dong-Dong Huang.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the Ethical Committee of The First Affiliated Hospital of Wenzhou Medical University (Ethics Document number: 2014-063). The study was carried out in compliance with the Helsinki Declaration. All patients were informed that their clinical information would be used anonymously for research purposes. A signed informed consent was achieved from each patient.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, GF., He, CH., Xi, WT. et al. Sarcopenia defined by the global leadership initiative in sarcopenia (GLIS) consensus predicts adverse postoperative outcomes in patients undergoing radical gastrectomy for gastric cancer: analysis from a prospective cohort study. BMC Cancer 25, 679 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12885-025-13967-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12885-025-13967-7

Keywords

BMC Cancer

ISSN: 1471-2407

Contact us