ABSTRACT

Conclusion:

TMT greater than 4.38 mm was found to be an independent prognostic factor in de novo glioblastoma. However, studies with larger series are needed to generalize this result to the Turkish population.

Results:

The median right TMT was 4.4 (1.7-9.5) mm, the left TMT was 4.1 (1.5-9.6) mm. The median TMT was 4.38 (1.66-9.45) mm. Spearman correlation test revealed a slight correlation between the mean TMT value and the age at the diagnosis (p=0.044). Spearman correlation test for gender also showed a slight correlation between the mean TMT value and gender (p=0.024). In the multivariate analysis using the Cox regression model showed that increased TMT was a positive prognostic marker for OS in GBM patients (p=0.030).

Methods:

A total of 66 GBM patients were included in this retrospective study. Left and right TMT’s from pre-operative magnetic resonance images were measured separately by an experienced radiologist, and the mean TMT value for each patient was calculated. The survival times and rates were examined with the Kaplan-Meier method. Overall survival (OS) was calculated from the day of diagnosis. The correlation coefficients and their significance were calculated using the Spearman test.

Objective:

Glioblastoma multiforme (GBM) is the most aggressive and commonly seen primary malignant brain tumor in adults. In addition to clinical, molecular and histopathological prognostic factors, sarcopenia, defined as low skeletal muscle mass, has become one of the important parameters. The relationship between skeletal muscle mass and temporal muscle thickness (TMT) has been demonstrated. We evaluated the prognostic value of TMT in patients with newly diagnosed GBM.

INTRODUCTION

Glioblastoma multiforme (GBM) is the most aggressive and commonly seen primary malignant brain tumor in adults (1). GBM accounts for 52% of all primary brain tumors and 60%-70% of gliomas (2). Glioblastomas are more common in men than in women. The median age of patients at the time of diagnosis is 64 years (3). Median survival in GBM is usually 14,6 months after diagnosis, and long-term survival is rare (4). Surgical resection within safe limits followed by adjuvant radiotherapy (RT) and chemotherapy is the standard treatment approach for GBM. Concurrent and adjuvant temozolomide (TMZ) improves the median 2- and five-year survival of patients with glioblastoma (4). Prognostic factors are age at diagnosis, performance status (PS), the extent of resection, duration of symptoms, O-6-methylguanine-DNA methyltransferase (MGMT) status, and neurological functional/mental status (3).

In addition to all these clinical, molecular, and histopathological data, sarcopenia, defined as low skeletal muscle mass, has become one of the important parameters to be considered, particularly in cancer patients recently. However, objective measurement of sarcopenia is required. It is a parameter that indicates the prognosis and survival in various types of extracranial cancers (5-8). Previously, skeletal muscle mass measurement was performed on abdominal computed tomography (CT) at the third lumbar vertebra level (L3) (5,9,10). However, it was impossible to measure skeletal muscle mass, whereas routine abdominal CT scans are not performed, such as in head and neck or nervous system cancers. Therefore, muscle mass measurement from the third cervical vertebra (C3) level was presented as an alternative to the L3 vertebra level in head and neck cancer studies (11,12). Studies supporting sarcopenia regarding the prediction of clinical outcomes of brain tumor patients in the literature are limited compared with other cancers. After demonstrating a relationship between skeletal muscle mass and temporal muscle thickness (TMT), (13) studies were published reporting TMT as an independent prognostic parameters in patients with newly diagnosed brain metastases (14,15). Subsequently, based on these studies, researches have conducted that report TMT’s prognostic value in patients with recurrent GBM. There have also been studies on its use as a marker (15-18).

Our study aimed to evaluate the prognostic value of TMT for overall survival (OS) rate and to investigate the importance of TMT as a marker of muscle loss in patients with newly diagnosed GBM. Also, it is to retrospectively analyze the prognostic relationship of TMT with known factors such as age, resection type, and PS of GBM patients.

METHODS

Patients Selection and Treatment

The study included 66 patients with GBM diagnosis and pre-operative magnetic resonance (MR) images who received simultaneous/adjuvant TMZ and postoperative RT. Additionally, patients’ age, gender, The European Cooperative Oncology Group (ECOG) performance score, tumor diameter, Ki-67 index, tumor location, mean TMT, date of diagnosis, treatment details, last follow-up, and death information were recorded. Approval was obtained from the Clinical Research Ethics Committee of Bakırköy Dr. Sadi Konuk Training and Research Hospital for our study (decision no: 2021-11-14, date: 07.06.2021).

According to the planning target volume (PTV), all patients received a median dose of 60 Gy (59.4-64 Gy) of RT once a day, 2.0 Gy per fraction, according to the PTV, using the volumetric arc therapy treatment method with a 6 million volt linear accelerator. TMZ chemotherapy was planned for all patients. Concurrent 75 mg/m²/day TMZ RT was initiated from the first day of RT and continued throughout RT. Adjuvant TMZ was started four weeks after the end of RT. While the adjuvant TMZ dose was 150 mg/m² for the first cycle, it was increased to 200 mg/m² per day for five days every 28 days after the second cycle in patients without hematological toxicity.

Before surgery, all patients underwent 1.5 Tesla (Siemens Amira) contrast-enhanced MR imaging. TMT at diagnosis of GBM was measured on T1-weighted contrast-enhanced axial brain MR images, at the level of the orbital roof perpendicularly to the long axis of the temporal muscle on an axial plane, which was oriented parallel to the anterior-posterior commissure line. Left and right TMT’s were measured separately by an experienced radiologist, and the mean TMT value for each patient was calculated. The orbital roof and Sylvian fissure are used as anatomical landmarks for more accurate assessments. The radiologist was blinded to the patients’ results, clinical features, and survival data. Patients with post-therapeutic changes that affected TMT were excluded from further evaluation. The measurements also included the diameter of the mass before surgery and the cavity diameter in post-op patients (Figure 1).

Figure 1

Survival status and/or death dates were obtained by searching each patient’ file data. OS was defined as the number of days between the initial surgery and death. Patients who were confirmed as alive on December 31, 2021 were entered into the database.

Statistical Analysis

Statistical Package for the Social Sciences (SPSS) v.22 (SPSS, Chicago, IL, USA) was used for the statistical analysis. The mean TMT was calculated by taking the arithmetic mean of the right and left TMTs. Based on the median value of the mean TMT, the patients were divided into thin and thick temporal muscle groups. The descriptive and frequency statistics were calculated, and the chi-square test was conducted to evaluate the differences in categorical variables. The survival times and rates were examined with the Kaplan-Meier method. OS was calculated from the day of diagnosis. The correlation coefficients and their significance were calculated using the Spearman test. The factors affecting the OS were evaluated using Log-rank and Cox regression tests. A p-value <0.05 is considered statistically significant.

RESULTS

Sixty-six patients were included in the study, and their descriptive characteristics are listed in Table 1. The median age of the patients was 57 (24-83) years. Twenty-eight patients were female, and 38 patients were male. According to PS, 15 patients (54.9%) had an ECOG score of 0-1, while 52 patients had an ECOG score of ≥2. The most common tumor localizations were temporal lobe (23/66, 34.8%), frontal lobe (21/66, 31.8%), and parietal lobe (14/66, 18.2%), and less frequently other regions. Gross total resection was performed in approximately half of the patients (n=32, 48.5%). There were 19 (28.8%) patients who had an isocitrate dehydrogenase (IDH)1 mutation. The median PTV 60 volume was 265 (126.5-829.2) cc. The median right TMT was 4.4 (1.7-9.5) mm, the left TMT was 4.1 (1.5-9.6) mm. The median TMT was 4.38 (1.66-9.45) mm. Concomitant TMZ was applied to all patients. With adjuvant therapy, 50% of the patients received six cycles or less of TMZ, while the other half received more than six cycles of TMZ. The mean follow-up period was 14.0 months (1-123 months). Up to the last follow-up visit, 36 (54.5 %) patients died, and the median OS was 11.3 (1.2-49.4) months.

Table 1

The patients were divided into two groups according to the median TMT (4.38 mm). The characteristics of the two groups according to the median TMT are shown in Table 2.

Table 2

The strength of the association between the two variables was calculated using the Spearman correlation coefficient. Spearman correlation test revealed a slight correlation between the mean TMT value and the age at the diagnosis (r =-0.248, p=0.044). It was shown that TMT thickness decreased with increasing age. A slight correlation was not reflected in the log-rank test at the level of statistical significance (p=0.581). Spearman correlation test for gender also showed a slight correlation between the mean TMT value and gender (r =-0.277, p=0.024). The mean TMT in men [median 4.5 mm (2.3-9.4 mm)] was higher than in women [median 3.9 mm (1.6-8.8 mm)]. However, thicker TMT in men did not have a positive effect on survival (p=0.53).

A log-rank test was used to identify the factors on OS. The gender, age, tumor or cavity volume, PTV 60 volume, ECOG-PS, operation type, IDH 1 mutation, Ki-67 index, number of adjuvant TMZ cycles, and TMT were examined for univariate analysis. ECOG-PS ≤2 (p=0.036), IDH mutant type (p=0.05), >6 cycles of adjuvant TMZ treatment (p=0.006), and younger age (p=0.002) were found significant factors for OS.

In the multivariate survival analysis using a Cox regression model showed that ECOG ≤2 [hazard ratio (HR) 8.292; 95% confidence interval (CI) 1.684-40.834; p=0.009], gross total resection (HR 3.906; 95% CI 1.087-14.033; p=0.037), presence of IDH mutation (HR 4.656; 95% CI 1.332-16.273; p=0.016) and, >6 courses of adjuvant TMZ (HR 0.005; 95% CI 0.000-0.0.061; p=0.000) were significantly associated with the OS time of GBM patients. Additionally, TMT was a prognostic marker for OS in GBM patients (HR 10.786; 95% CI 1.257-92.544; p=0.030) (Figure 2). There was no significant association between the survival of GBM patients and gender, age at diagnosis, tumor or cavity volume, PTV 60 volume, and Ki-67 index (p>0.05).

Figure 2

DISCUSSION

Sarcopenia is defined as the loss of skeletal muscle mass. It is used as an important and independent biomarker in cancer prognosis. Sarcopenia has recently started to be used in neuro-oncological patients. In the study of Ranganathan et al. (13) on trauma patients in 2014, TMT was reported as an ideal marker of sarcopenia. TMT measurement studies in neuro-oncological patients were frequently conducted for brain metastases (14). Leitner et al. (14) suggested the use of TMT for sarcopenia in brain metastases, stating that L3 and TMT were correlated with brain metastases. In current studies, studies on TMT are performed on patients with progressive and newly diagnosed GBM (16,18-22).

In our study, 66 patients with de-novo GBM were examined with pre-operative MR images. When the mean TMT was calculated, the mean TMT of our study group was found to be lower than all other groups (16,20-22). Many factors affect TMT, such as tumor type, trauma, surgery, infection, nutrition, and age (21,23,24). However, the fact that the mean TMT value determined in our study was consistent with the value in the study of Yesil Cinkir and Colakoglu Er (18), which is also a Turkish study, showed that geographic and ethnic origin might also affect TMT. When the characteristics were examined, although the gender difference was not significant according to our study in contrast with other studies, TMT was higher in the male gender than in the female gender. However, this difference was not reflected in OS.

The median age of the patients included in the study was 57, which is consistent with the literature. The probability of developing sarcopenia increases with advancing age (8,25). In our study, we found a slight correlation between the TMT decrease and advancing age. In a report by The European Working Group on Sarcopenia in Older People, it was revealed that the cause of sarcopenia might be age-related primary sarcopenia, as well as decreased physical activity with a sedentary life, the patient’s comorbidities (inflammatory, oncological, endocrinological) and secondary causes such as malabsorption and nutrition (25). The slight correlation detected between increasing age and decreasing TMT in our study was not reflected in the log-rank test at the level of statistical significance. Similarly, age was not found as a significant prognostic factor in the studies by Yesil Cinkir and Colakoglu Er (18) and An et al. (21). Huq et al.’s (20) study consisting of 381 patients with newly diagnosed and progressive GBM reported that TMT was associated with age, albumin, body mass index (BMI), and Karnofsky perfomance score (KPS). Albumin and BMI are directly related to nutrition and sarcopenia (26). However, because of the retrospective design of our study, patients’ albumin and BMI levels were excluded from the analysis.

In the multivariate analysis of our study, ECOG ≤2, gross total resection (GTR), IDH mutation, TMZ more than six cycles, and thick TMT were found among the prognostic factors that positively affected OS. An et al. (21) reported low ECOG, GTR, and thick TMT, Liu et al. (22) reported thick TMT, age at diagnosis, and concomitant CRT, and Yesil Cinkir and Colakoglu Er (18) reported age and thick TMT to be good prognostic factors. Unlike these studies, which found a significant relationship between thick TMT and OS, Huq et al. (20) showed that TMT did not affect OS in newly diagnosed GBM but positively affected survival in progressive GBM. Muglia et al. (16) studied a small but homogeneous group of 51 patients diagnosed with methylated MGMT promoter, IDH1-2 wild-type glioblastoma, who underwent complete surgical resection followed by RT with concomitant and maintenance TMZ treatment. TMT of all patients was measured bilaterally from pre-operative MR images. The mean TMT was 8.43 mm. TMT was not associated with prognosis, age, or ECOG-PS. TMT has been argued to be an ineffective marker for predicting survival in GBM patients with newly diagnosed and untreated IDH1-2 wild-type, methylated-MGMT (16). However, the small number of patients and the fact that the patients are in the more aggressive group may be a reasons that suppress the effect of TMT.

Our study has some limitations. Initially, the patients included in the study caused a molecular and genetic heterogeneity pattern due to the retrospective design. Although our results were consistent with many studies in the literature, they differed from some studies examining a homogeneous patient group (16). Also, because of the retrospective study design, no additional research was conducted on other factors affecting TMT, such as patients’ nutritional status and oral-dental health. Further studies with a larger sample size are needed to support our results and represent the Turkish population.

CONCLUSION

TMT greater than 4.38 mm was found to be an independent prognostic factor in de-novo glioblastoma. However, studies with larger series are needed to generalize this result to the Turkish population.

ETHICS

Ethics Committee Approval: Approval was obtained from the Clinical Research Ethics Committee of Bakırköy Dr. Sadi Konuk Training and Research Hospital for our study (decision no: 2021-11-14, date: 07.06.2021).

Informed Consent: Retrospective study.

Authorship Contributions

Surgical and Medical Practices: E.E.Ö., M.O.N., E.K.U., Concept: E.E.Ö., M.K.B., G.P.S., E.K.U., Design: G.P.S., E.K.U., Data Collection or Processing: E.E.Ö., M.O.N., M.F., Analysis or Interpretation: M.K.B., E.K.U., Literature Search: E.E.Ö., M.O.N., M.F., E.K.U., Writing: E.E.Ö., G.P.S.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: The authors declared that this study received no financial support.

References

1Suzuki Y, Shirai K, Oka K, Mobaraki A, Yoshida Y, Noda SE, et al. Higher pAkt expression predicts a significant worse prognosis in glioblastomas. J Radiat Res 2010;51:343-8.

2Baur M, Preusser M, Piribauer M, Elandt K, Hassler M, Hudec M, et al. Frequent MGMT (0(6)-methylguanine-DNA methyltransferase) hypermethylation in long-term survivors of glioblastoma: a single institution experience. Radiol Oncol 2010;44:113-20.

3Curran WJ Jr, Scott CB, Horton J, Nelson JS, Weinstein AS, Fischbach AJ, et al. Recursive partitioning analysis of prognostic factors in three Radiation Therapy Oncology Group malignant glioma trials. J Natl Cancer Inst 1993;85:704-10.

4Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJ, et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med 2005;352:987-96.

5Panje CM, Höng L, Hayoz S, Baracos VE, Herrmann E, Garcia Schüler H, et al. Skeletal muscle mass correlates with increased toxicity during neoadjuvant radiochemotherapy in locally advanced esophageal cancer: A SAKK 75/08 substudy. Radiat Oncol 2019;14:166.

6Shachar SS, Williams GR, Muss HB, Nishijima TF. Prognostic value of sarcopenia in adults with solid tumours: A meta-analysis and systematic review. Eur J Cancer 2016;57:58-67.

7Huang X, Ma J, Li L, Zhu XD. Severe muscle loss during radical chemoradiotherapy for non-metastatic nasopharyngeal carcinoma predicts poor survival. Cancer Med 2019;8:6604-13.

8Park SE, Hwang IG, Choi CH, Kang H, Kim BG, Park BK, et al. Sarcopenia is poor prognostic factor in older patients with locally advanced rectal cancer who received preoperative or postoperative chemoradiotherapy. Medicine (Baltimore) 2018;97:e13363.

9Grossberg AJ, Chamchod S, Fuller CD, Mohamed AS, Heukelom J, Eichelberger H, et al. Association of Body Composition With Survival and Locoregional Control of Radiotherapy-Treated Head and Neck Squamous Cell Carcinoma. JAMA Oncol 2016;2:782-9.

10Prado CM, Baracos VE, McCargar LJ, Reiman T, Mourtzakis M, Tonkin K, et al. Sarcopenia as a determinant of chemotherapy toxicity and time to tumor progression in metastatic breast cancer patients receiving capecitabine treatment. Clin Cancer Res 2009;15:2920-6.

11Swartz JE, Pothen AJ, Wegner I, Smid EJ, Swart KM, de Bree R, et al. Feasibility of using head and neck CT imaging to assess skeletal muscle mass in head and neck cancer patients. Oral Oncol 2016;62:28-33.

12Zwart AT, van der Hoorn A, van Ooijen PMA, Steenbakkers RJHM, de Bock GH, Halmos GB. CT-measured skeletal muscle mass used to assess frailty in patients with head and neck cancer. J Cachexia Sarcopenia Muscle 2019;10:1060-9.

13Ranganathan K, Terjimanian M, Lisiecki J, Rinkinen J, Mukkamala A, Brownley C, et al. Temporalis muscle morphomics: the psoas of the craniofacial skeleton. J Surg Res 2014;186:246-52.

14Leitner 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.

15Furtner 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.

16Muglia R, Simonelli M, Pessina F, Morenghi E, Navarria P, Persico P, et al. Prognostic relevance of temporal muscle thickness as a marker of sarcopenia in patients with glioblastoma at diagnosis. Eur Radiol 2021;31:4079-86.

17Zhang F, Wang Y, Xu W, Jiang H, Liu Q, Gao J, et al. Dosimetric Evaluation of Different Intensity-Modulated Radiotherapy Techniques for Breast Cancer After Conservative Surgery. Technol Cancer Res Treat 2015;14:515-23.

18Yesil Cinkir H, Colakoglu Er H. Is temporal muscle thickness a survival predictor in newly diagnosed glioblastoma multiforme? Asia Pac J Clin Oncol 2020;16:e223-7.

19Furtner 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.

20Huq S, Khalafallah AM, Ruiz-Cardozo MA, Botros D, Oliveira LAP, Dux H, et al. A novel radiographic marker of sarcopenia with prognostic value in glioblastoma. Clin Neurol Neurosurg 2021;207:106782.

21An G, Ahn S, Park JS, Jeun SS, Hong YK. Association between temporal muscle thickness and clinical outcomes in patients with newly diagnosed glioblastoma. J Cancer Res Clin Oncol 2021;147:901-9.

22Liu F, Xing D, Zha Y, Wang L, Dong W, Li L, et al. Predictive Value of Temporal Muscle Thickness Measurements on Cranial Magnetic Resonance Images in the Prognosis of Patients With Primary Glioblastoma. Front Neurol 2020;11:523292.

23Dallmann R, Weyermann P, Anklin C, Boroff M, Bray-French K, Cardel B, et al. The orally active melanocortin-4 receptor antagonist BL-6020/979: a promising candidate for the treatment of cancer cachexia. J Cachexia Sarcopenia Muscle 2011;2:163-74.

24Dunne RF, Loh KP, Williams GR, Jatoi A, Mustian KM, Mohile SG. Cachexia and Sarcopenia in Older Adults with Cancer: A Comprehensive Review. Cancers (Basel) 2019;11:1861.

25Cruz-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.

26Dasenbrock HH, Liu KX, Chavakula V, Devine CA, Gormley WB, Claus EB, et al. Body habitus, serum albumin, and the outcomes after craniotomy for tumor: a National Surgical Quality Improvement Program analysis. J Neurosurg 2017;126:677-89.

Can Temporal Muscle Thickness Be a New Prognostic Factor for De Novo Glioblastoma?