Purpose:

To investigate the prognostic relevance of temporal muscle thickness (TMT) as a surrogate parameter of skeletal muscle status in patients with newly diagnosed glioblastoma.

Experimental Design:

We assessed TMT in cranial MRI of 755 patients enrolled in the CENTRIC EORTC 26071–22072 study (n = 508) and CORE study (n = 247). We used predefined sex-specific TMT cut-off values to categorize “patients at risk of sarcopenia” and “patients with normal muscle status” at baseline. Furthermore, we categorized patients according to the extent of TMT loss over time. Associations with progression-free survival (PFS) and overall survival (OS) were evaluated using the Cox model adjusted for other exploratory variables.

Results:

Patients at risk of sarcopenia (CENTRIC; n = 158/508, 31.1%; CORE; n = 87/247, 35.2%) at baseline had significantly higher risk of progression and death than patients with normal muscle status in both study cohorts [CENTRIC: PFS = HR 0.16; 95% confidence interval (CI), 0.12–0.21; P < 0.001; OS = HR 0.341; 95% CI, 0.27–0.44; P < 0.001; CORE: PFS = HR 0.29; 95% CI, 0.21–0.39; P < 0.001; OS = HR, 0.365; 95% CI, 0.27–0.49; P < 0.001]. Similar results were obtained in multivariate Cox models adjusted for other important prognostic parameters. The extent of TMT loss over time showed a significant inverse correlation with median OS times in patients at risk for sarcopenia (CENTRIC: P < 0.001; CORE: P = 0.005), but not in patients with normal baseline muscle mass (CENTRIC: P = 0.538; CORE: P = 0.28).

Conclusions:

TMT identifies ambulatory patients with newly diagnosed glioblastoma at risk for progressive sarcopenia and adverse outcomes. Early intervention may prevent skeletal muscle loss and improve patient outcome.

Translational Relevance

Newly diagnosed glioblastoma patients at risk for sarcopenia, as defined by a temporal muscle thickness (TMT) below the sex-specific cut-off value, showed significantly shorter median progression-free and overall survival times than patients with normal skeletal muscle status. Moreover, the extent of temporal muscle wasting during chemoradiotherapy correlated inversely with medial overall survival times in patients at risk for sarcopenia, but not in patients with normal baseline skeletal muscle status. Thus, our findings suggest the incorporation of TMT, obtained on routinely performed cranial MRI examinations, in the routine workflow to optimize individual clinical treatment decision and patient stratification for clinical trials based on an objectively assessable parameter with regard to the patient's physical condition.

Glioblastoma is the most malignant primary brain tumor with a 5-year survival of < 5% (1). Despite a multimodal treatment scheme comprised of neurosurgical intervention and concurrent chemoradiotherapy with temozolomide, recurrence within 1 year occurs in most patients (2, 3). In the era of individualized therapy planning, stratification of patients with glioblastoma based on established prognostic parameters is relevant for patient management decision-making including clinical trial participation. Standardized parameters for outcome prognostication include age, performance status, tumor location, and size, as well as histopathologic and molecular tumor characteristics. Whereas most of these criteria are assessable objectively, the estimation of patient's physical performance is affected by the subjective evaluation of the attending physician, leading to inaccuracy and high interobserver variability (4, 5). Thus, to enhance the prognostic evaluation, objectively measurable criteria are needed to assess patient's performance status.

The measurement of skeletal muscle mass is an evolving parameter for the clinical evaluation of the physiologic condition of patients. A decrease in muscle quantity and quality is defined as sarcopenia and is primarily attributable to aging (6). However, sarcopenia has been secondarily identified in various disease entities, such as a central characteristic in cancer-related cachexia, as an objective parameter suggesting an adverse prognosis related to patient frailty (7–11).

Recently, temporal muscle thickness (TMT) obtained on cranial MRI has been introduced as a new surrogate marker with which to identify patients at risk of sarcopenia due to its high correlation with the skeletal muscle mass, muscle function and nutritional status (12–16). These studies suggest that the estimation of skeletal muscle mass can be derived from assessing craniofacial muscles including TMT directly from brain MRI scans that are routinely obtained for patients with glioblastoma.

The purpose of this study was to investigate the prognostic role of sex-specific TMT cut-off values and to identify patients at risk for progressive sarcopenia among newly diagnosed glioblastoma patients with methylated or unmethylated O(6)-methylguanine-DNA-methyltransferase (MGMT) promoter methylation. Thus, TMT was retrospectively analyzed in the CENTRIC EORTC 26071–22072 study (MGMT promoter-methylated glioblastoma) and the CORE trial (MGMT promoter-unmethylated glioblastoma), comprising a large homogenous dataset of two independent international prospective, randomized clinical trials (17, 18).

Patients

All data were retrieved from the clinical trial dataset held at EORTC which includes clinical and imaging data of the CENTRIC EORTC 26071–22072 and CORE trials (17, 18). The CENTRIC EORTC 26071–22072 study was conducted as a multicenter, randomized, open-label, phase III trial to investigate the efficacy of cilengitide combined with standard treatment for patients with newly diagnosed glioblastoma with methylated MGMT promoter. The CORE trial was designed as a multicenter, randomized, open-label, controlled, phase II trial to evaluate the safety and efficacy of two cilengitide regimens in combination with standard treatment for patients with newly diagnosed glioblastoma with unmethylated MGMT promoter. For both clinical trials utilized for this analysis, solely patients with an ECOG performance score of 0–1 were eligible. All patients were treated according to the study protocols. The study drug was given as intravenous infusion twice weekly in an ambulatory outpatient setting. The primary endpoint of both the CENTRIC EORTC 26071–22072 and the CORE trials, overall survival, was not met.

For the current study we used all 545 patients of the CENTRIC EORTC 26071–22072 trial and all 265 patients enrolled in the CORE study to investigate the association of sex-specific TMT cut-off values with progression-free survival (PFS) and overall survival (OS) in newly diagnosed glioblastoma with methylated and unmethylated MGMT promoter. All clinical data (comprising PFS and OS data, treatment group, MGMT methylation status, age, sex, Eastern Co-operative Oncology Group Performance Score (ECOG) performance status, mini mental state examination (MMSE) status, recursive partitioning analysis (RPA) class, steroid use at baseline, antiepileptic drug use at baseline, body mass index (BMI), and extent of resection) of both studies are listed in Supplementary Table S1.

All patients provided written informed consent and institutional review board approval including translational research studies was obtained at all sites. The study was conducted in accordance with the Declaration of Helsinki.

Assessment of TMT

Baseline MR images obtained at study enrollment, after histopathologic and molecular confirmation of the diagnosis and before initiation of study treatment, were retrospectively retrieved for all patients of the CENTRIC EORTC 26071–22072 and CORE trial (n = 810). In total, 55 patients (6.8%) were excluded from subsequent analyses because of missing baseline MRI examinations (n = 18), motion artifacts (n = 10), partial depiction of both temporal muscles (n = 8), or any prior therapeutic intervention with bilateral temporal muscle involvement (n = 19; Supplementary Fig. S1).

For this study, TMT was retrospectively analyzed on axial contrast-enhanced T1-weighted MR sequences by a board-certified radiologist blinded to clinical patient characteristics and outcome measures. The plane was oriented parallel to the anterior commissure–posterior commissure line and the measurements were conducted at each side at the level of the orbital roof (cranio–caudal landmark) and the lateral sulcus (anterior–posterior landmark) perpendicular to the long axis of the temporal muscle (19). For further statistical analyses, a mean TMT for each patient was calculated. In case of preceding interventions (e.g., previous craniotomy with subsequent muscle edema or atrophy) that could have affected the thickness of the temporal muscle, the measurement of this side was excluded.

Sex-specific TMT cut-off values were previously defined as 2.5 standard deviations (SD) below the mean TMT value of a normative reference, comprising a healthy volunteer cohort between 18 and 40 years, to identify patients at risk of sarcopenia (14). Those cut-off values were set as ≤ 6.3 mm in male patients and ≤ 5.2 mm in female patients and were used in this study to classify patients into two groups (“normal muscle status” > cut-off value; “at risk of sarcopenia” ≤ cut-off value; ref. 14).

Statistical analysis

Metric data are described using mean ± SD or standard error (SE) if normally distributed (e.g., TMT) or using median (range) if skewed (e.g., age, BMI).

A difference of 10% between MGMT promoter–methylated and unmethylated patients with glioblastoma was considered clinically relevant. To test for multicollinearity, tolerance measures were calculated (20).

Baseline TMT values

Based on the sex-specific TMT cut-off values, patients of both cohorts were divided into two groups (“at risk of sarcopenia” vs. “normal muscle status”). A log-rank test, visualized by a Kaplan–Meier plot separating the TMT cut-off groups, in patients with methylated and unmethylated MGMT promoter, was performed. Kaplan–Meier analysis was used to calculate the difference for OS and PFS between patients below and above the sex-specific TMT cut-off values. In a multivariate model, this step was replicated to verify whether the potential association of TMT was confounded by other variables using an automated stepwise backward selection of possible prognostic variables with a threshold P value of 5%.

Longitudinal TMT values

In patients with more than one MR examination, TMT values were measured over the course of the disease to evaluate potential changes of muscle thickness. Those changes were referred to as relative TMT (relTMT) values, using the baseline TMT of each patient as an individual reference value.

To investigate whether the extent of skeletal muscle loss during chemoradiotherapy was associated with OS of patients with newly diagnosed glioblastoma, the relative change in TMT between baseline and the first follow-up MR [mean time interval 84.6 days; 95% confidence interval (CI), 80.93–88.28] compared with the baseline TMT was calculated and subdivided in three groups: no TMT loss (relTMT = 100%), mild TMT loss (relTMT = 99–90%), and severe TMT loss (relTMT<90%). A log-rank test, visualized by a Kaplan–Meier plot separating those groups, was performed.

To investigate the association between corticosteroid use and TMT, we correlated the average corticosteroid dose per day during the whole course of the disease (total corticosteroid dose/days from diagnosis to death or lost to follow-up) with the reduction of the relative TMT loss between baseline MRI and last MRI before death or lost to follow-up, using a Spearman correlation.

Patients

The MGMT promoter–methylated glioblastoma cohort comprised 508 patients and the MGMT promoter-unmethylated glioblastoma cohort consisted of 247 patients. Patient characteristics did not differ above 10% for both cohorts (Supplementary Table S1) except for the ratio of study treatment group to control group which was higher in the 1:1:1 randomized CORE trial (study treatment group 67.2%:control group 32.8%) than the 1:1 randomized CENTRIC trial (study treatment group 50.2%:control group 49.8%). On the basis of the divergence in the MGMT methylation status as defined by the inclusion criteria of the two trials, the median PFS (P < 0.001) and OS (P < 0.001) times were significantly lower in patients with glioblastoma enrolled in CORE.

There were no relevant intercorrelations between the potential prognostic parameters as all tolerance measures were above 0.2 (see Supplementary Table S2).

Examples of TMT measurements on T1-weighted contrast-enhanced MR images are presented in Fig. 1.

Figure 1.

Axial T1-weighted contrast-enhanced cranial MR images representing TMT assessment in a 60-year-old male patient (A; mean TMT = 5.2 mm) with a PFS of 2.4 months and an OS of 6.8 months in comparison to a 57-year-old male patient (B; mean TMT value = 11.6 mm) with a PFS of 13.3 months and an OS of 23.4 months.

Figure 1.

Axial T1-weighted contrast-enhanced cranial MR images representing TMT assessment in a 60-year-old male patient (A; mean TMT = 5.2 mm) with a PFS of 2.4 months and an OS of 6.8 months in comparison to a 57-year-old male patient (B; mean TMT value = 11.6 mm) with a PFS of 13.3 months and an OS of 23.4 months.

Close modal

Baseline TMT measurements

MGMT promoter–methylated glioblastoma cohort (CENTRIC cohort)

The mean TMT value of newly diagnosed glioblastoma patients with a methylated MGMT promoter was 6.7 mm (SD: 1.6 mm). In male patients (7.2 mm, SD: 1.5 mm) the mean TMT was significantly higher (P < 0.001) than in female patients (6.2 mm, SD: 1.5 mm). A low negative correlation of TMT with age (male patients, ρ = −0.219, P = 0.001; female patients, ρ = −0.334, P < 0.001) and a low positive/or no correlation with BMI (male patients, ρ = 0.096, P = 0.114; female patients, ρ = 0.163, P = 0.014) were seen. Mean TMT values did not significantly differ between patients with steroid medication at baseline (6.7 mm, SD 1.7 mm) and without steroids at baseline (6.8 mm, SD = 1.6 mm; P = 0.557). Sex-specific TMT cut-off values were used to separate this cohort into patients “at risk for sarcopenia” (n = 158; 31%) and “normal” patients (n = 350, 69%).

For OS and PFS, Kaplan–Meier curves dividing patients “at risk for sarcopenia” (below sex-specific TMT cut-off values) and patients with “normal muscle status” (above sex-specific TMT cut-off values) are illustrated in Fig. 2A and B (log-rank test P < 0.001 for OS and PFS).

Figure 2.

Kaplan–Meier curves for OS (A) and PFS (B). Sex-specific TMT cut-off values separating patients into “at risk for sarcopenia” (below sex-specific TMT cut-off values = black line) and patients with “normal muscle status” (above sex-specific TMT cut-off values = gray line).

Figure 2.

Kaplan–Meier curves for OS (A) and PFS (B). Sex-specific TMT cut-off values separating patients into “at risk for sarcopenia” (below sex-specific TMT cut-off values = black line) and patients with “normal muscle status” (above sex-specific TMT cut-off values = gray line).

Close modal

Kaplan–Meier analysis revealed a significant difference between patients below and above the sex-specific TMT cut-off values for OS (HR, 0.341; 95% CI, 0.27–0.44; P < 0.001) and PFS (HR, 0.16; 95% CI, 0.12–0.21; P < 0.001). Stepwise multivariate Cox Regression Model revealed similar results. The significant explanatory variables are listed in Table 1.

Table 1.

Significant variables in the stepwise multivariate Cox regression model for OS and PFS of glioblastoma with methylated MGMT promoter.

PHR (95% CI)
OS Age > 50 years >0.001 0.522 (0.373–0.731) 
 MMSE score > 27 >0.001 1.870 (1.412–2.475) 
 Incomplete resection 0.001 0.646 (0.501–0.831) 
 At risk for sarcopeniaa >0.001 0.368 (0.285–0.474) 
PFS MMSE score > 27 0.002 1.512 (1.167–1.960) 
 Incomplete resection 0.059 0.814 (0.658–1.008) 
 At risk for sarcopeniaa >0.001 0.167 (0.128–0.219) 
PHR (95% CI)
OS Age > 50 years >0.001 0.522 (0.373–0.731) 
 MMSE score > 27 >0.001 1.870 (1.412–2.475) 
 Incomplete resection 0.001 0.646 (0.501–0.831) 
 At risk for sarcopeniaa >0.001 0.368 (0.285–0.474) 
PFS MMSE score > 27 0.002 1.512 (1.167–1.960) 
 Incomplete resection 0.059 0.814 (0.658–1.008) 
 At risk for sarcopeniaa >0.001 0.167 (0.128–0.219) 

aTMT below the sex-specific cut-off values.

MGMT promoter–unmethylated glioblastoma cohort (CORE cohort)

In patients with newly diagnosed glioblastoma with an unmethylated MGMT promoter, the mean TMT value was 6.7 mm (SD:1.6 mm). Similar to the glioblastoma patient cohort with MGMT promoter methylation, male patients (7.1 mm, SD:1.6 mm) showed significantly higher (P < 0.001) mean TMT values than female patients (6.1 mm, SD:1.3 mm). Mean TMT values did also not significantly differ between patients with steroid medication at baseline (6.7 mm, SD:1.4 mm) and without steroids at baseline (6.6 mm, SD:1.7 mm; P = 0.572). Furthermore, there was no significant difference between the sex-related TMT values in patients with glioblastoma with and without MGMT promoter methylation (P = 0.851).

In MGMT promoter-unmethylated glioblastoma, TMT at time of diagnosis showed only a low negative correlation with age (male patients, ρ = −0.247, P = 0.003; female patients, ρ = −0.296, P < 0.003) and no significant correlation with BMI (male patients, ρ = 0.144, P = 0.084; female patients, ρ = −0.073, P < 0.467).

Eighty-seven patients (35%) with a mean TMT value below the sex-specific cut-off value referred to as “patients at risk for sarcopenia” whereas 160 patients (65%) were defined as “patients with normal muscle status” based on a mean TMT value above the sex-specific cut-off value.

Kaplan–Meier curves for OS and PFS dividing glioblastoma patients without MGMT promoter methylation based on the sex-specific TMT cut-off values into “patients at risk for sarcopenia” and “normal” are presented in Fig. 3A and B (log-rank test P < 0.001 for OS and PFS).

Figure 3.

Kaplan–Meier curves for OS (A) and PFS (B). Sex-specific TMT cut-off values dividing patients into “at risk for sarcopenia” (below sex-specific TMT cut-off values = black line) and into patients with “normal muscle status” (above sex-specific TMT cut-off values = gray line).

Figure 3.

Kaplan–Meier curves for OS (A) and PFS (B). Sex-specific TMT cut-off values dividing patients into “at risk for sarcopenia” (below sex-specific TMT cut-off values = black line) and into patients with “normal muscle status” (above sex-specific TMT cut-off values = gray line).

Close modal

Kaplan–Meier analysis showed a significant difference between patients below and above the sex-specific TMT cut-off values for OS (HR, 0.365; 95% CI, 0.27–0.49; P < 0.001) and PFS (HR, 0.29; 95% CI, 0.21–0.39, P < 0.001). With a multivariate stepwise Cox Regression Model, similar findings were obtained. Table 2 presents significant explanatory variables.

Table 2.

Significant variables in the stepwise multivariate Cox regression model for OS and PFS of glioblastoma with unmethylated MGMT promoter.

PHR (95% CI)
OS Age >50 years 0.065 0.72 (0.50–1.02) 
 Steroid medication at baseline 0.008 0.66 (0.48–0.9) 
 ECOG 1 (vs. ECOG 0) 0.038 0.72 (0.53–0.98) 
 RPA Class 3/4 (vs. RPA 5) 0.031 1.532 (1.04–2.26) 
 At risk for sarcopeniaa <0.001 0.34 (0.25–0.47) 
PFS Steroid medication at baseline 0.010 0.73 (0.55–0.96) 
 Incomplete resection 0.024 0.73 (0.55–0.96) 
 At risk for sarcopeniaa <0.001 0.27 (0.2–0.37) 
PHR (95% CI)
OS Age >50 years 0.065 0.72 (0.50–1.02) 
 Steroid medication at baseline 0.008 0.66 (0.48–0.9) 
 ECOG 1 (vs. ECOG 0) 0.038 0.72 (0.53–0.98) 
 RPA Class 3/4 (vs. RPA 5) 0.031 1.532 (1.04–2.26) 
 At risk for sarcopeniaa <0.001 0.34 (0.25–0.47) 
PFS Steroid medication at baseline 0.010 0.73 (0.55–0.96) 
 Incomplete resection 0.024 0.73 (0.55–0.96) 
 At risk for sarcopeniaa <0.001 0.27 (0.2–0.37) 

aTMT below the sex-specific cut-off values.

Longitudinal TMT measurements

In 704 patients (CENTRIC cohort, n = 473; CORE cohort, n = 231), we had at least a second MR scan to assess the change of TMT values over the course of disease. The changes of TMT were expressed as relTMT values (using the baseline TMT value as reference). Herein, we identified two longitudinal TMT patterns. In approximately 60% of CENTRIC (n = 267, 56%) and CORE (n = 145, 63%) patients, the TMT values declined from the baseline MRI to the last MRI before death/lost to follow-up. In the remaining nearly 40% of patients in both cohorts (CENTRIC, n = 206, 44%; CORE, n = 86, 37%), the TMT value did not decrease during the course of disease.

Patients with a normal muscle status at time of diagnosis showed a significantly higher loss of muscle mass (lower relTMT values) than patients at risk for sarcopenia (CENTRIC, P < 0.001; CORE, P = 0.005) in both study cohorts.

However, the extent of the muscle decline between the baseline MRI and the last MRI before death/lost to follow-up showed no association with OS in both study cohorts in patients at risk for sarcopenia and patients with normal muscle status (CENTRIC: P = 0.425 in patients at risk for sarcopenia; P = 0.166 in patients with normal muscle mass; CORE: P = 0.499 in patients at risk for sarcopenia; P = 0.082 in patients with normal muscle mass).

TMT change during chemoradiotherapy

The distribution of the patients and the related OS are presented in Supplementary Table S3.

Kaplan–Meier curves for OS dividing patients with no TMT loss, mild TMT loss, and severe TMT loss (in addition subdivided into “patients with normal muscle mass” and “patients at risk for sarcopenia”) are illustrated in Fig. 4AD. The log-rank test was significant in “patients at risk for sarcopenia” in both CENCTRIC (P = 0.005) and CORE (P < 0.001) in comparison to “patients with normal muscle mass” (methylated MGMT promoter cohort, P = 0.28; unmethylated MGMT promoter cohort, P = 0.538).

Figure 4.

Kaplan–Meier curves for OS separating patients with regard to their degree of TMT loss (black line = rel TMT = 100%; dark gray = rel TMT 90%–99%; light gray line = relTMT > 90%) in patients in the following subcohorts: patients with a normal muscle status with methylated (A) and unmethylated (C) MGMT promoter as well as patients at risk for sarcopenia with methylated (B) and unmethylated (D) MGMT promoter.

Figure 4.

Kaplan–Meier curves for OS separating patients with regard to their degree of TMT loss (black line = rel TMT = 100%; dark gray = rel TMT 90%–99%; light gray line = relTMT > 90%) in patients in the following subcohorts: patients with a normal muscle status with methylated (A) and unmethylated (C) MGMT promoter as well as patients at risk for sarcopenia with methylated (B) and unmethylated (D) MGMT promoter.

Close modal

Association of TMT and corticosteroid dose

When investigating the association of the average corticosteroid dose per day (during the whole course of the disease) with the reduction of the relative TMT loss between baseline MRI and last MRI before death or lost to follow-up, no significant correlation was found in CENTRIC (ρ = −0.008; P = 0.863) or CORE (ρ = 0.114; P = 0.083) patients, respectively.

Sarcopenia is increasingly recognized as an adverse prognostic parameter in cancer treatment and outcome (8–10). In this study, a strong and independent role for sex-specific TMT cut-off values, reflecting patient muscle status was observed for PFS and OS in patients with newly diagnosed glioblastoma with methylated and unmethylated MGMT promoter.

Previous studies already recognized that TMT is associated with the outcome of patients with various neurologic disorders (19, 21–24). Smaller studies have also suggested that TMT is a potential outcome predictor in patients with newly diagnosed as well as recurrent glioblastoma (25–27). However, these studies solely revealed that there is an association of TMT with patient's outcome without using consistent TMT cut-off values, which are mandatory for integrating a novel biomarker into the routine clinical setting.

The sex-specific TMT cut-off values used in the current study for patient stratification were previously predefined as 2.5 SDs below a normative reference population (healthy volunteers between 18 and 40 years of age) in line with a recommendation of the European Working Group on Sarcopenia in Older People (EWGSOP; refs. 14, 28). Patients below those sex-specific cut-off values are determined as “patients at risk for sarcopenia” and should undergo further established diagnostic tests to confirm the presence of sarcopenia (28). This study fulfills all recommendations of the REMARK criteria. Further validation in blinded patient cohorts and prospective studies are necessary to validate the findings of this study to be able to integrate TMT measures into clinical workflow for assessment of sarcopenia in patients with glioblastoma in the future.

Another advantage of assessing TMT is that, due to the regular cranial MRI–based follow-up examination in this disease entity, the TMT skeletal muscle status can be monitored during the course of the disease. Thus, we also obtained serial TMT measurements in all available follow-up MR examinations in addition to the baseline MRI. Herein we found that patients with a normal muscle status at time of diagnoses showed a significantly pronounced relative loss of TMT (in relation to the baseline TMT value) compared with patients at risk for sarcopenia over the course of their disease. At the same time, we found that patients with low TMT at baseline experiencing TMT wasting during chemoradiotherapy have significantly higher risk of death. Therefore, implementation of appropriate interventions for muscle mass preservation including exercise and resistance training as well as nutritional support early in the disease course may be of high importance to reduce the decline in muscle mass and improve patient outcomes (29–31). Alternatively, the benefit of deintensification of first-line treatments, for example, by using reduced radiochemotherapy or chemo- or radiotherapy-only regimens, could be tested in clinical trials (32–34).

Despite the fact that we have been able to assess TMT values in two independent, large, international, prospective, randomized clinical trials, this study faces several limitations. In both clinical trials, patients were enrolled after the first tumor surgery, thus in only about 25% (CENTRIC cohort: 22%; CORE cohort: 27%) of the patients, a bilateral TMT assessment was feasible due to frequent post-treatment changes of the temporal muscle at least one side. Another limitation is that the thickness of the temporal muscle was assessed by a single experienced neuroradiologist, but not by multiple observers. Herein, we relied on previously published data that showed a high inter-rater (ICC>0.9) and intra-rater (ICC>0.9) agreement of TMT assessment (13, 14). To reduce the potential risk that the TMT measurements might be biased due to a lack of objective imaging review, the neuroradiologist was blinded to all clinical and demographic data at the time of image analysis. The advantage that the assessment of TMT is a fast technique, which can easily be integrated in the routine clinical setting comes with the limitation that it is potentially more prone to measurement inaccuracies, particularly due to its small muscle diameter, in comparison to the assessment of muscle cross sectional area or muscle volume. Further studies will be needed to compare these different approaches with a special focus on the temporal muscle.

Furthermore, we did not have information regarding the ethnicity of the patients, thus potential ethnic differences of the skeletal muscle mass could not be addressed in this study (35). In this study, we did not find a significant association between corticosteroid dose over time and TMT values; however, more detailed prospective studies focusing on the interaction of TMT and steroid therapy are required in the future. Also owing to the retrospective design of this study, in only about half of the patients (CENTRIC cohort: 46%; CORE cohort: 43%), isocitrate dehydrogenase (IDH) status was not reported and further could not be integrated in our data analysis. Further studies are needed to elucidate the pathobiology of sarcopenia in patients with glioblastoma, which is likely a complex process comprising therapy-related decline of muscle status, physical inactivity, malnutrition, and tumor-related inflammatory processes resulting in a procatabolic state where protein degradation takes precedence over protein synthesis leading a loss of skeletal muscle tissue (36, 37).

Conclusion

In this study, we present sex-specific TMT cut-off values as well as the degree of muscle mass loss during chemoradiotherapy, as an independent prognostic parameter in patients with newly diagnosed glioblastoma with and without MGMT promoter methylation. Thus, supplementation of clinical performance scores with additional prognostic factors, such as sarcopenia, could improve clinical decision-making and patient stratification for clinical trials.

M. Weller reports grants and personal fees from Apogenix, MSD, and Merck (EMD); grants from Quercis; and personal fees from Adastra, BMS, Medac, Nerviano, Novartis, Orbus, Philogen and yMabs outside the submitted work. L.B. Nabors reports other support from Univ Penn and personal fees from Karyopharm outside the submitted work. D.A. Reardon reports personal fees from Abbvie Pharmaceuticals, Advantagene, Agios, Amgen, AnHeart Therapeutics, Bayer, Boston Biomedical, Boehringer Ingelheim, Deciphera, Del Mar Pharma, DNAtrix, Ellipses Pharma, Genenta, Genentech/Roche, Imvax, Kintara, Kiyatec, Medicenna Biopharma, Merck, Merck KGaA, Monteris, Novocure, Oncorus, Oxigene, Regeneron, Stemline, Sumitono Dainippon Pharma, Pyramid, Taiho Oncology, Inc., Tragara, and Y-Mabs Therapeutics; grants from Acerta Pharmaceuticals, Epitopoietic Research Corporation, Enterome, Incyte, Insightec, and Omniox; and grants and personal fees from Agenus, Bristol-Myers Squibb, Celldex, EMD Serono, Inovio, and Novartis outside the submitted work. J. Tonn reports personal fees from CarThera; grants from Novocure; and non-financial support from Munich Surgical Imaging and BrainLab outside the submitted work. R. Stupp reports personal fees and non-financial support from CarThera and personal fees from Celularity, CranioVation/Alpheus, Hemispherian, Insightec, GT Medical Technologies, Northwest Biotherapeutics, TriAct, AstraZeneca, DNAtrix, Novocure/Zai Lab, and Northwest Biotherapeutics outside the submitted work. M. Preusser reports personal fees from Bayer, Bristol-Myers Squibb, Novartis, Gerson Lehrman Group (GLG), CMC Contrast, GlaxoSmithKline, Mundipharma, Roche, BMJ Journals, MedMedia, AstraZeneca, AbbVie, Lilly, Medahead, Daiichi Sankyo, Sanofi, Merck Sharp & Dome, Tocagen, Adastra, and Gan & Lee Pharmaceuticals and grants from Böehringer-Ingelheim, Bristol-Myers Squibb, Roche, Daiichi Sankyo, Merck Sharp & Dome, Novocure, GlaxoSmithKline, and AbbVie outside the submitted work. No disclosures were reported by the other authors.

J. Furtner: Conceptualization, resources, data curation, software, formal analysis, supervision, validation, investigation, visualization, methodology, writing–original draft, project administration, writing–review and editing. M. Weller: Data curation, supervision, writing–review and editing. M. Weber: Conceptualization, formal analysis, visualization, methodology, writing–review and editing. T. Gorlia: Resources, data curation, writing–review and editing. B. Nabors: Resources, data curation, writing–review and editing. D.A. Reardon: Resources, data curation, writing–review and editing. J.C. Tonn: Resources, data curation, writing–review and editing. R. Stupp: Resources, data curation, writing–review and editing. M. Preusser: Conceptualization, resources, data curation, supervision, investigation, methodology, writing–review and editing.

We are grateful to Merck KGaA from Germany for supporting the CENTRIC EORTC 26071-22072 and the CORE trials.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Ostrom
QT
,
Patil
N
,
Cioffi
G
,
Waite
K
,
Kruchko
C
,
Barnholtz-Sloan
JS
. 
CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2013–2017
.
Neuro Oncol
2020
;
22
:
iv1
iv96
.
2.
Wen
PY
,
Weller
M
,
Lee
EQ
,
Alexander
BM
,
Barnholtz-Sloan
JS
,
Barthel
FP
, et al
Glioblastoma in adults: a Society for Neuro-Oncology (SNO) and European Society of Neuro-Oncology (EANO) consensus review on current management and future directions
.
Neuro Oncol
2020
;
22
:
1073
113
.
3.
Weller
M
,
van den Bent
M
,
Preusser
M
,
Le Rhun
E
,
Tonn
JC
,
Minniti
G
, et al
EANO guidelines on the diagnosis and treatment of diffuse gliomas of adhulthood
.
Nat Rev Clin Oncol
2021
;
18
:
170
86
.
4.
Kondziolka
D
,
Parry
PV
,
Lunsford
LD
,
Kano
H
,
Flickinger
JC
,
Rakfal
S
, et al
The accuracy of predicting survival in individual patients with cancer
.
J Neurosurg
2014
;
120
:
24
30
.
5.
Taylor
AE
,
Olver
IN
,
Sivanthan
T
,
Chi
M
,
Purnell
C
. 
Observer error in grading performance status in cancer patients
.
Support Care Cancer
1999
;
7
:
332
5
.
6.
Cruz-Jentoft
AJ
,
Baeyens
JP
,
Bauer
JM
,
Boirie
Y
,
Cederholm
T
,
Landi
F
, et al
Sarcopenia: European consensus on definition and diagnosis—report of the European working group on sarcopenia in older people
.
Age Ageing
2010
;
39
:
412
23
.
7.
Fearon
K
,
Strasser
F
,
Anker
SD
,
Bosaeus
I
,
Bruera
E
,
Fainsinger
RL
, et al
Definition and classification of cancer cachexia: an international consensus
.
Lancet Oncol
2011
;
12
:
489
95
.
8.
Prado
CM
,
Lieffers
JR
,
McCargar
LJ
,
Reiman
T
,
Sawyer
MB
,
Martin
L
, et al
Prevalence and clinical implications of sarcopenic obesity in patients with solid tumors of the respiratory and gastrointestinal tracts: a population-based study
.
Lancet Oncol
2008
;
9
:
629
35
.
9.
Tamandl
D
,
Paireder
M
,
Asari
R
,
Baltzer
PA
,
Schoppmann
SF
,
Ba-Ssalamah
A
. 
Markers of sarcopenia quantified by computed tomography predict adverse long-term outcome in patients with resected oesophageal or gastro-oesophageal junction cancer
.
Eur Radiol
2016
;
26
:
1359
67
.
10.
Shachar
SS
,
Williams
GR
,
Muss
HB
,
Nishijima
TF
. 
Prognostic value of sarcopenia in adults with solid tumors: a meta-analysis and systematic review
.
Eur J Cancer
2016
;
57
:
58
67
.
11.
Zakaria
HM
,
Wilkinson
BM
,
Pennington
Z
,
Saadeh
YS
,
Lau
D
,
Chandra
A
, et al
Sarcopenia as a prognostic factor for 90-day and overall mortality in patients undergoing spine surgery for metastatic tumors: a multicenter retrospective cohort study
.
Neurosurgery
2020
;
87
:
1025
36
.
12.
Hasegawa
Y
,
Yoshida
M
,
Sato
A
,
Fujimoto
Y
,
Minematsu
T
,
Sugama
J
, et al
Temporal muscle thickness as a new indicator of nutritional status in older individuals
.
Geriatr Gerontol Int
2019
;
19
:
135
40
.
13.
Leitner
J
,
Pelster
S
,
Schöpf
V
,
Berghoff
AS
,
Woitek
R
,
Asenbaum
U
, et al
High correlation of temporal muscle thickness with lumbar skeletal muscle cross-sectional area in patients with brain metastases
.
PLoS One
2018
;
13
:
e0207849
.
14.
Steindl
A
,
Leitner
J
,
Schwarz
M
,
Nenning
K-H
,
Asenbaum
U
,
Mayer
S
, et al
Sarcopenia in neurological patients: standard values for temporal muscle thickness and muscle strength evaluation
.
Journl Clin Med
2020
;
9
:
1272
.
15.
Hasegawa
Y
,
Yoshida
M
,
Sato
A
,
Fujimoto
Y
,
Minematsu
T
,
Sugama
J
, et al
A change in temporal muscle thickness is correlated with past energy adequacy in bedridden older adults: a prospective cohort study
.
BMC Geriatr
2021
;
21
:
182
.
16.
Nozoe
M
,
Kubo
H
,
Kanai
M
,
Yamamoto
M
,
Okakita
M
,
Suzuki
H
, et al
Reliability and validity of measuring temporal muscle thickness as the evaluation of sarcopenia risk and the relationship with functional outcome in older patients with acute stroke
.
Clin Neurol Neurosurg
2021
;
201
:
106444
.
17.
Stupp
R
,
Hegi
ME
,
Gorlia
T
,
Erridge
SC
,
Perry
J
,
Hong
Y-K
, et al
Cilengitide combined with standard treatment for patients with newly diagnosed glioblastoma with methylated MGMT promoter (CENTRIC EORTC 26071–22072 study): a multicenter, randomized, open-label, phase III trial
.
Lancet Oncol
2014
;
15
:
1100
8
.
18.
Nabors
LB
,
Fink
KL
,
Mikkelsen
T
,
Grujicic
D
,
Tarnawski
R
,
Nam
DH
, et al
Two cilengitide regimes in combination with standard treatment for patients with newly diagnosed glioblastoma and unmethylated MGMT gene promoter: results of the open-label, controlled, randomized phase II CORE study
.
Neuro Oncol
2015
;
17
:
708
17
.
19.
Furtner
J
,
Berghoff
AS
,
Albtoush
OM
,
Woitek
R
,
Asenbaum
U
,
Prayer
D
, et al
Survival prediction using temporal muscle thickness measurements on cranial magnetic resonance images in patients with newly diagnosed brain metastases
.
Eur Radiol
2017
;
27
:
3167
73
.
20.
Field
A
.
Discovering Statistics using IBM SPSS Statistics, 4th edition
,
Sage
2013
;
p.
324
6
.
21.
Katsuki
M
,
Yamamoto
Y
,
Uchiyama
T
,
Wada
N
,
Kakizawa
Y
. 
Clinical characteristics of aneurysmal subarachnoid hemorrhage in the elderly over 75; would temporal muscle be a potential prognostic factor as an indicator of sarcopenia?
Clin Neurol Neurosurg
2019
;
186
:
105535
.
22.
Furtner
J
,
Berghoff
AS
,
Schöpf
V
,
Reumann
R
,
Pascher
B
,
Woitek
R
, et al
Temporal muscle thickness is an independent prognostic marker in melanoma patients with newly diagnosed brain metastases
.
J Neurooncol
2018
;
140
:
173
8
.
23.
Katsuki
M
,
Suzuki
Y
,
Kunitoki
K
,
Sato
Y
,
Sasaki
K
,
Mashiyama
S
, et al
Temporal muscle as an indicator of sarcopenia is independently associated with Hunt and Kosnik grade on admission and the modified rankin scale score at 6 months of patients with subarachnoid hemorrhage treated by endovascular coiling
.
World Neurosurg
2020
;
137
:
e526
34
.
24.
Katsuki
M
,
Kakizawa
Y
,
Nishikawa
A
,
Yamamoto
Y
,
Uchiyama
T
. 
Temporal muscle thickness and area are independent prognostic factors in patients aged 75 or younger with aneurysmal subarachnoid hemorrhage treated by clipping
.
Surg Neurol Int
2021
;
12
:
151
.
25.
An
G
,
Ahn
S
,
Park
J-S
,
Jeun
S-S
,
Hong
Y-K
. 
Association between temporal muscle thickness and clinical outcomes in patients with newly diagnosed glioblastoma
.
J Cancer Res Clin Oncol
2021
;
147
:
901
9
.
26.
Yesil
CH
,
HC
E
. 
Is temporal muscle thickness a survival predictor in newly diagnosed glioblastoma multiforme?
Asia Pac J Clin Oncol
2020
;
16
:
e223
7
.
27.
Furtner
J
,
Genbrugge
E
,
Gorlia
T
,
Bendszus
M
,
Nowosielski
M
,
Golfinopoulos
V
, et al
Temporal muscle thickness is an independent prognostic marker in patients with progressive glioblastoma: translational imaging analysis of the EORTC 26101 trial
.
Neuro Oncol
2019
;
21
:
1587
94
.
28.
Cruz-Jentoft
AJ
,
Bahat
G
,
Bauer
J
,
Boirie
Y
,
Bruyère
O
,
Cederholm
T
, et al
Sarcopenia: revised European consensus on definition and diagnosis
.
Age Ageing
2019
;
48
:
16
31
.
29.
Dent
E
,
Morley
JE
,
Cruz-Jentoft
AJ
,
Arai
H
,
Kritchevsky
SB
,
Guralnik
J
, et al
International clinical practice guidelines for sarcopenia (ICFSR): screening, diagnosis, and management
.
J Nutr Health Aging
2018
;
22
:
1148
61
.
30.
Storer
TW
,
Basaria
S
,
Traustadottir
T
,
Harman
SM
,
Pencina
K
,
Li
Z
, et al
Effects of testosterone supplementation for 3 years on muscle performance and physical function in older men
.
J Clin Endocinol Metab
2017
;
102
:
583
93
.
31.
Becker
C
,
Lord
SR
,
Studenski
SA
,
Warden
SJ
,
Fielding
RA
,
Recknor
CP
, et al
Myostation antibody (LY2495655) in older weak fallers: a proof-of-concept, randomized, phase II trial
.
Lancet Diabetes Endocinol
2015
;
3
:
948
57
.
32.
Roa
W
,
Kepka
L
,
Kumar
N
,
Sinaika
V
,
Matiello
J
,
Lomidze
D
, et al
International atomic energy agency randomized phase III study of radiation therapy in elderly and/or frail patients with newly diganosed glioblastoma multiforme
.
J Clin Oncol
2015
;
33
:
4145
50
.
33.
Malmström
A
,
Grønberg
BH
,
Marosi
C
,
Stupp
R
,
Frappaz
D
,
Schultz
H
, et al
Temozolomide versus standard 6-week radiotherapy in patients older than 60 years with glioblastoma: the Nordic randomised, phase 3 trail
.
Lancet Oncol
2012
;
13
:
916
26
.
34.
Chang
EL
,
Yi
W
,
Allen
PK
,
Levin
VA
,
Sawaya
RE
,
Maor
MH
. 
Hypofractionated radiotherapy for elderly or younger low-performance status glioblastoma pateints: outcome and prognostic factors
.
Int J Radiat Oncol Biol Phys
2003
;
56
:
519
28
.
35.
Silva
AM
,
Shen
W
,
Heo
M
,
Gallagher
D
,
Wang
Z
,
Sardinha
LB
, et al
Ethnicity-related skeletal muscle differences across the lifespan
.
Am J Hum Biol
2010
;
22
:
76
82
.
36.
Fukushima
H
,
Koga
F
. 
Impact of sarcopenia in the management of urological cancer patients
.
Expert Rev Anticancer Ther
2017
;
17
:
455
66
.
37.
Sandri
M
. 
Autophagy in skeletal muscle
.
FEBS Lett
2010
;
584
:
1411
6
.