Research ArticleClinical Studies
Open Access

CT Attenuation and Cross-sectional-area Index of the Pectoralis Are Associated With Prognosis in Sarcoma Patients

STEPHANIE JO and RONNIE SEBRO
Anticancer Research April 2021, 41 (4) 1927-1935; DOI: https://doi.org/10.21873/anticanres.14959

Abstract

Background/Aim: To identify prognostic imaging biomarkers from staging chest computed tomography (CT) in patients with sarcomas. Patients and Methods: CT scans for baseline staging, and surveillance 1-year CT scans in patients newly diagnosed with sarcoma were evaluated. Pectoralis muscle area (PMA), pectoralis muscle index (PMI) and pectoralis CT attenuation density (PMT) were measured. Cox proportional-hazard models were used to determine the association with progression-free survival (PFS) and overall survival (OS). Results: There were 147 patients (53.1% male) who were followed for a median 1,414 days (range=219-4851 days). Approximately 47.6% (70/147) of patients progressed and 29.9% (44/147) died. Multivariable Cox-proportional hazards models adjusting for gender, tumor grade and chemotherapy treatment showed that a higher baseline PMT and baseline PMI were associated with increased OS. Conclusion: Higher baseline PMI and PMT are associated with increased overall survival in patients with sarcoma.

Key Words:

Sarcomas are rare tumors of mesenchymal origin, and there are approximately 15,000 new cases of bone or soft tissue sarcoma diagnosed annually in the United States (1-3). Sarcomas have a propensity to primarily metastasize to the lungs (3-7). Patients with localized disease have a 5-year life expectancy of approximately 81%, however, patients with metastatic disease have a 5-year life expectancy that is closer to 16% (3-7). Sarcopenia is the loss of muscle mass, quality and strength (8). Patients with cancer often experience muscle loss, which is a key component of cancer cachexia (8). Recent reports have shown that measurements from computed tomography (CT) studies of the abdomen and pelvis can be utilized to evaluate muscle loss (9-15). The L3 skeletal muscle index (SMI) (areal lumbar muscle area at the third lumbar vertebra adjusted for height in meters squared) is commonly used as a proxy for sarcopenia (9-15). Low SMI at L3 has been associated with poor outcomes – decreased overall survival in patients with multiple cancers, including melanoma, breast, uterine, colon and esophageal cancer (9-15).

The accepted treatment for local control of sarcomas is radiation therapy and wide local surgical excision or amputation. Because over 70% of sarcomas occur in the legs/thigh (1-4), patients with sarcomas often undergo surgery/amputations of the extremities, in particular the lower extremity. These patients experience asymmetric muscle mass loss in the ipsilateral psoas – the predominant hip flexor after amputation/surgical reconstruction of the lower extremity (Figure 1). Because the SMI at L3 includes the psoas, the SMI at L3 is often an inappropriate marker for sarcopenia in most patients with sarcoma.

Figure 1.
Figure 1.

Unenhanced computed tomography (CT) of the abdomen and pelvis demonstrating asymmetric atrophy of the right psoas muscle (white arrow) relative to the left at L3, in a 36-year-old male with an undifferentiated pleomorphic sarcoma of the right thigh after amputation of the right lower extremity 5 years prior. The patient has no evidence of disease.

Patients with other cancers (including melanoma, breast, uterine, colon and esophageal cancer) undergo surveillance CT studies of the abdomen/pelvis as part of routine clinical care (11-15). However, patients with sarcomas usually undergo surveillance chest CT studies because the lung is the most common site of sarcoma metastasis (6, 7). The National Comprehensive Cancer Network (NCCN) guidelines recommend considering CT studies of the abdomen and pelvis only for surveillance in patients with retroperitoneal liposarcoma, myxoid/round cell liposarcoma, epithelioid sarcoma, angiosarcoma, and leiomyosarcoma. Because of this, most patients with sarcomas do not routinely undergo CT scans of the abdomen/pelvis for surveillance, and therefore, the SMI at L3 cannot be calculated for all sarcoma patients (11-15).

We hypothesized that imaging biomarkers that are predictive of prognosis in patients with sarcoma, could be obtained opportunistically from these surveillance chest CT studies. The aim of this paper was to assess if there exists a relationship between CT bone and muscle parameters, and progression-free survival (PFS) and overall survival (OS) in patients with sarcoma.

Patients and Methods

This retrospective study was Health Insurance Portability and Accountability Act of 1996 (HIPAA) compliant and the study protocol was reviewed and approved by the local institutional review board (IRB). The requirement for signed informed consent from each patient was waived by the IRB.

Patients. This study evaluated patients with newly diagnosed histologically confirmed bone or soft tissue sarcoma, who were treated at a single tertiary academic center between 01/01/2006 and 06/01/2018. Patients’ age, sex, height and weight at the time of diagnosis were extracted from the medical record. The maximum size of the primary tumor in centimeters at diagnosis, tumor grade, and sarcoma tumor subtype were recorded. Patients were excluded if they had sarcoma involving the T12 vertebral body, thoracic muscles at T12, or the pectoralis muscles.

Progression-free survival. The length of time in days from the date of histological diagnosis to the development of local recurrence or the development of pulmonary metastases was defined as the progression-free survival (PFS). The time to the development of pulmonary metastases in days was calculated as the time from the date of histological diagnosis (the date the diagnosis was confirmed histologically) until the time pulmonary nodules appeared on the first surveillance chest CT study. If the pulmonary nodules were indeterminate on that chest CT study, then the subsequent surveillance chest CT was reviewed. If the pulmonary nodules were growing in size or if they decreased in size after systemic chemotherapy on the subsequent surveillance chest CT and if the oncologist decided they were clinically consistent with metastases, then the date of the surveillance chest CT where the nodules were first identified was used to define the date of development of pulmonary nodules. If the pulmonary nodules were biopsied and histologically confirmed as metastases, then this date (the date the nodule was first identified on CT) was used as the date of development of pulmonary nodules. The time in days, from diagnosis to histologically confirmed local recurrence was calculated. The minimum time (time to the development of pulmonary metastases compared to the time to local recurrence) was used for the progression-free survival if both conditions occurred. If the patient was lost to follow-up, then the patient was considered censored at the last documented clinic visit/correspondence.

Overall survival. OS was calculated from the date the sarcoma diagnosis was first confirmed histologically until the date the patient was deceased. If the patient was lost to follow-up, then the patient was considered censored at the last documented clinic visit/correspondence.

Chest CT parameters. Unenhanced chest CTs were performed using a Siemens Somatom AS definition 128 slice CT scanner (Siemens Healthineers, Erlagen, Germany). The following parameters were used: 120 kVp, and slice thickness 1.25 mm. The tube current automatically varied depending on body part imaged and patient habitus to limit the radiation dose to the patient. Images were evaluated using the soft tissue kernel. Patients were imaged in the supine position with the arms placed above the head. Scanners were calibrated (tolerance±4.0 HU) per the American College of Radiology (ACR) guidelines using phantoms. All scans were obtained in the supine position.

Skeletal muscle measurements. The Digital Imaging and Communications in Medicine (DICOM) files from the CT studies were transferred into a database. CT images were processed using 3D Slicer software, and a previously published semi-automated image analysis method was used to calculate the muscle cross-sectional areas (16-26). The thoracic skeletal muscle area (TMA) was first calculated. The vertebral body, ribs, outer and inner thoracic fascia were identified at the T12 vertebral level to create an enclosed region of interest. The TMA was the total cross-sectional area of pixels within −29 to +150 Hounsfield Units (HU). TMA was then normalized by the patient’s height in meters, squared, to obtain the T12 skeletal muscle index (TMI). The mean CT attenuation of the T12 skeletal muscle (TMT) was also calculated (Figure 2A and B). The pectoralis muscle skeletal muscle area (PMA) at the level of the sternomanubrial joint and pectoralis muscle index (PMI) were calculated similarly. The mean CT attenuation of the pectoralis muscles (PMT) were also utilized as predictors in the analysis. The pectoralis muscle was chosen because it is a large muscle that is clearly visible on all chest CT studies. The 1-year change in the TMI (delta TMI), TMT (delta TMT), PMI (delta PMI) and PMT (delta TMT) were calculated by subtracting the initial values from the initial surveillance chest CT study from values from the corresponding 1-year surveillance chest CT study.

Figure 2.
Figure 2.

Measurement of muscle cross-sectional area. A) Unenhanced computed tomography (CT) of the chest demonstrating measurement of the pectoralis cross-sectional area (PMA). Green shaded area represents muscle area measured. B) Unenhanced CT of the chest demonstrating measurement of the skeletal muscle cross-sectional area (TMA) at T12. Yellow shaded area represents muscle area measured.

Bone measurements. The CT attenuation of a vertebral body is associated with the bone mineral density (BMD) (27, 28), and has been associated with poor outcomes in patients with prostate cancer (27, 28). A large region of interest (ROI) measuring approximately 1 cm in diameter was placed over the vertebral body, taking care to avoid the cortex or hemangiomas. The CT attenuation of T12 at the initial surveillance CT study (T12 HU) and the 1-year change in the T12 HU were used as predictors in the analysis.

Statistical analyses. Summary statistics for all variables were calculated. Clinical and demographic variables were compared between genders using t-tests with unequal variances for quantitative variables, and Fisher’s exact tests for qualitative variables. Pearson’s correlations were used to assess the correlations between TMI, TMT, PMI, PMT, and T12 HU. Univariate Cox proportional hazards models were used to evaluate the association between the demographic/clinical variables and OS and PFS, analyzing males and females separately. After adjusting for the variables, which were significant in the univariate analysis (grade, chemotherapy), age and gender were used to assess whether the CT muscle and bone measurements remained predictors of PFS and OS in patients with sarcoma. Statistical analysis was performed using R statistical software v3.4 (Vienna, Austria). All statistical tests were two-sided. The Bonferroni correction was utilized to preserve the Type I error rate, and a p-value<0.005 was considered statistically significant for the multivariable Cox proportional hazards models.

Results

There were 147 patients retrospectively identified and followed for an average 1,708 days (range=219-4,851 days). Undifferentiated pleomorphic sarcoma (UPS)/Malignant fibrous histiocytoma (MFH) was the most common subtype (27/147=18.4%), followed by Ewing sarcoma (19/147=12.9%), leiomyosarcoma (18/147=12.2%), synovial sarcoma (15/147=10.2%) and myxofibrosarcoma (14/147=9.5%). Approximately 4.1% (6/147), 16.3% (24/147), 70/147 (47.6%), 29.9% (44/147) and 2.0% (3/147) of patients were American Joint Committee on Cancer (AJCC) stage I, II, III, IV and unknown, respectively. The mean (standard deviation) age of the patients was 47.5 (16.2) years. Approximately 53.1% (78/147) of the cohort were male. As expected, men were on average taller (p<0.001) than women. All baseline areal muscle measurements were on average larger in men than women. The average PMA (p<0.001) and TMA (p<0.001) were significantly larger in men than women (Table I). Approximately 47.6% (70/147) of patients progressed and 29.9% (44/147) died of their disease. Older age was negatively associated with lower PMT (r=– 0.27, p=0.001), lower TMT (r=–0.51, p<0.001), and lower T12 HU (r=–0.60, p<0.001).

View this table:
Table I.

Demographic and clinical characteristics of study cohort.

Among males, PMI was positively correlated with TMI (r=0.74, p<0.001). PMT and TMT were also correlated (r=0.83, p<0.001). Among males, T12HU was strongly correlated with PMT (r=0.25, p=0.027) and TMT (r=0.43, p<0.001) (Table II). Among females, PMI was also positively correlated with TMI (r=0.86, p<0.001). T12 HU was also strongly correlated with PMT (r=0.29, p=0.017) and TMT (r=0.50, p<0.001). We also found that PMT and TMT were positively correlated within females (r=0.75, p<0.001).

View this table:
Table II.

Correlations between bone and muscle CT measurements at the time of diagnosis.

Univariate Cox proportional hazards analyses results for PFS and OS are shown in Table III. Kaplan–Meier curves evaluating sarcoma survival are shown for PMT (Figure 3A and B) and PMI (Figure 4A and B). Multivariable Cox-proportional hazards models adjusting for age, gender, tumor grade and chemotherapy treatment showed that higher baseline PMT (HR=0.97, 95%CI=0.95-0.99) and higher baseline PMI (HR=0.99, 95%CI=0.9987-0.9996) were associated with increased OS (Table IV).

View this table:
Table III.

Univariate Cox-proportional hazards analysis predicting progression free survival (PFS) and overall survival (OS) by gender.

Figure 3.
Figure 3.

Association between pectoralis muscle computed tomography attenuation and overall survival. A) Kaplan–Meier Curves for sarcoma survival by pectoralis muscle computed tomography attenuation (PMT) for men. p-Value was obtained using the Log-rank test. B) Kaplan–Meier Curves for sarcoma survival by PMT for women. p-Value was obtained using the Log-rank test.

Figure 4.
Figure 4.

Association between pectoralis muscle index and overall survival. A) Kaplan–Meier Curves for sarcoma survival by pectoralis muscle index (PMI) for men. p-Value was obtained using the Log-rank test. B) Kaplan–Meier Curves for sarcoma survival by PMI for women. p-Value was obtained using the Log-rank test.

View this table:
Table IV.

Multivariable Cox-proportional hazards analyses predicting progression-free survival (PFS) and overall survival (OS) after adjusting for age, gender, grade and history of prior chemotherapy.

Discussion

The results of this study show that sarcoma patients with higher baseline PMT and PMI had increased OS. This suggests that the amount of baseline cross sectional area and fatty infiltration of the pectoralis musculature were associated with increased OS independent of tumor grade and chemotherapy. The data also show that the CT attenuation of the T12 vertebral body was positively correlated with PMI, TMT and PMT in both males and females.

Muscle loss is known to be an independent predictor of survival in patients with hepatocellular carcinoma after hepatectomy (12), stage III melanoma (15), pancreatic adenocarcinoma after resection (13, 14), lung adenocarcinoma (9-11), prostate cancer (29), ovarian cancer (30), breast cancer (22, 31), esophageal cancer (20, 21), and colorectal cancer (16). Therefore, other studies support our findings, and suggest that surveillance CT studies may have imaging biomarkers that can be used to predict patient prognosis, and show that muscle loss is associated with poor prognosis and decreased overall survival.

One prior study investigating muscle loss in patients with sarcoma found no association between muscle loss assessed by evaluating the height-adjusted psoas CSA at L3 and overall survival (16). However, there are key differences between our study and this prior study. We adjusted for gender, height, and grade rather than just height. We were not interested in estimating sarcopenia – instead we were interested in identifying a CT imaging biomarker that could be used for sarcoma prognosis. Patients with both bone and soft tissue sarcomas were included in our study, whereas in the prior study, only patients with soft tissue sarcoma were evaluated. In addition, we analyzed CT measures of muscle and bone density as continuous variables rather than binary variables – which gives our study more power to detect an association (32).

Muscle loss is a key component of cancer cachexia, and thought to be multifactorial. Environmental causes of muscle loss may include decrease in physical activity and decrease in nutritional intake (33). Patients with progressing sarcoma, like other cancers, may be less active due to fatigue and pain and may suffer from anorexia (33). Muscle loss may be related to decreases in hormones that are important for preservation of muscle mass such as testosterone, dehydroepiandrosterone sulfate (DHEAS), insulin-like growth factor -1 and estrogen (33-38). It is unclear whether decreases in these hormones contribute to muscle loss in patients with sarcoma. Future research is required to assess how all of these factors contribute to muscle loss in patients with sarcoma. Another interesting finding was that PMI was strongly correlated with the CT measure of bone mineral density in both men and women. One possible explanation for this finding is that individuals that are more active have larger PMI and develop increased BMD, and suggests that bone density and muscle mass are correlated.

This study has a few limitations. This study is based on patients treated at a single tertiary care academic center. The retrospective nature of the study makes it susceptible to ascertainment biases due to referral patterns. Sarcomas are a heterogeneous group of tumors of mesenchymal origin and the optimal treatment depends on the tumor histology. Some tumor types such as osteosarcomas, Ewing sarcoma and myxoid round cell tumors, and metastatic disease are treated with chemotherapy and corticosteroids. Patients with these sarcoma subtypes and metastatic disease may be more susceptible to increased muscle loss because of their treatment, however our analysis adjusted for chemotherapy treatment, which should have mitigated this problem. In conclusion, increased baseline PMI and PMT are associated with better OS after adjusting for patient age, height, tumor grade and chemotherapy in patients with sarcoma.

Acknowledgements

RS was supported by R21 NIH/NIMH MH093415.

Footnotes

  • Authors’ Contributions

    SJ: Data curation, manuscript editing, review and approval of final manuscript. RS: Conceptualization, writing – original draft, manuscript review and editing, formal statistical analysis, methodology, review and approval of final manuscript

  • ↵* Both Authors contributed equally to this work.

  • This article is freely accessible online.

  • Conflicts of Interest

    The Authors’ declare no financial conflicts of interest in relation to this study.

  • Received February 2, 2021.
  • Revision received February 17, 2021.
  • Accepted February 18, 2021.

This is an open access article distributed under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

References

  1. ↵
    1. Siegel RL,
    2. Miller KD and
    3. Jemal A
    : Cancer statistics, 2019. CA Cancer J Clin 69(1): 7-34, 2019. PMID: 30620402. DOI: 10.3322/caac.21551
    OpenUrlCrossRefPubMed
  2. Bone and Joint Cancer - Cancer Stat Facts. SEER. Available at: https://seer.cancer.gov/statfacts/html/bones.html [Last accessed on October 1, 2019]
  3. ↵
    Soft Tissue Cancer - Cancer Stat Facts. SEER. Available at: https://seer.cancer.gov/statfacts/html/soft.html [Last accessed on March 27, 2019]
  4. ↵
    1. Cormier JN and
    2. Pollock RE
    : Soft tissue sarcomas. CA Cancer J Clin 54(2): 94-109, 2004. PMID: 15061599. DOI: 10.3322/canjclin.54.2.94
    OpenUrlCrossRefPubMed
    1. Skubitz KM and
    2. D’Adamo DR
    : Sarcoma. Mayo Clin Proc 82(11): 1409-1432, 2007. PMID: 17976362. DOI: 10.4065/82.11.1409
    OpenUrlCrossRefPubMed
  6. ↵
    1. Chao C and
    2. Goldberg M
    : Surgical treatment of metastatic pulmonary soft-tissue sarcoma. Oncology (Williston Park) 14(6): 835-841; discussion 842-4, 847, 2000. PMID: 10887634
    OpenUrl
  7. ↵
    1. Digesu CS,
    2. Wiesel O,
    3. Vaporciyan AA and
    4. Colson YL
    : Management of sarcoma metastases to the lung. Surg Oncol Clin N Am 25(4): 721-733, 2016. PMID: 27591495. DOI: 10.1016/j.soc.2016.05.005
    OpenUrlCrossRef
  8. ↵
    1. Harneshaug M,
    2. Benth JS,
    3. Kirkhus L,
    4. Gronberg BH,
    5. Bergh S,
    6. Rostoft S and
    7. Slaaen M
    : CT derived muscle measures, inflammation, and frailty in a cohort of older cancer patients. In Vivo 34(6): 3565-3572, 2020. PMID: 33144469. DOI: 10.21873/invivo.12200
    OpenUrlAbstract/FREE Full Text
  9. ↵
    1. Kim EY,
    2. Kim YS,
    3. Park I,
    4. Ahn HK,
    5. Cho EK,
    6. Jeong YM and
    7. Kim JH
    : Evaluation of sarcopenia in small-cell lung cancer patients by routine chest CT. Support Care Cancer 24(11): 4721-4726, 2016. PMID: 27364150. DOI: 10.1007/s00520-016-3321-0
    OpenUrlCrossRef
    1. Kim EY,
    2. Kim YS,
    3. Park I,
    4. Ahn HK,
    5. Cho EK and
    6. Jeong YM
    : Prognostic Significance of CT-Determined Sarcopenia in Patients with Small-Cell Lung Cancer. J Thorac Oncol 10(12): 1795-1799, 2015. PMID: 26484630. DOI: 10.1097/JTO.0000000000000690
    OpenUrlCrossRefPubMed
  11. ↵
    1. Kinsey CM,
    2. San José Estépar R,
    3. van der Velden J,
    4. Cole BF,
    5. Christiani DC and
    6. Washko GR
    : Lower pectoralis muscle area is associated with a worse overall survival in non-small cell lung cancer. Cancer Epidemiol Biomarkers Prev 26(1): 38-43, 2017. PMID: 27197281. DOI: 10.1158/1055-9965.EPI-15-1067
    OpenUrlAbstract/FREE Full Text
  12. ↵
    1. Harimoto N,
    2. Shirabe K,
    3. Yamashita YI,
    4. Ikegami T,
    5. Yoshizumi T,
    6. Soejima Y,
    7. Ikeda T,
    8. Maehara Y,
    9. Nishie A and
    10. Yamanaka T
    : Sarcopenia as a predictor of prognosis in patients following hepatectomy for hepatocellular carcinoma. Br J Surg 100(11): 1523-1530, 2013. PMID: 24037576. DOI: 10.1002/bjs.9258
    OpenUrlCrossRefPubMed
  13. ↵
    1. Peng P,
    2. Hyder O,
    3. Firoozmand A,
    4. Kneuertz P,
    5. Schulick RD,
    6. Huang D,
    7. Makary M,
    8. Hirose K,
    9. Edil B,
    10. Choti MA,
    11. Herman J,
    12. Cameron JL,
    13. Wolfgang CL and
    14. Pawlik TM
    : Impact of sarcopenia on outcomes following resection of pancreatic adenocarcinoma. J Gastrointest Surg 16(8): 1478-1486, 2012. PMID: 22692586. DOI: 10.1007/s11605-012-1923-5
    OpenUrlCrossRefPubMed
  14. ↵
    1. Amini N,
    2. Spolverato G,
    3. Gupta R,
    4. Margonis GA,
    5. Kim Y,
    6. Wagner D,
    7. Rezaee N,
    8. Weiss MJ,
    9. Wolfgang CL,
    10. Makary MM,
    11. Kamel IR and
    12. Pawlik TM
    : Impact total psoas volume on short- and long-term outcomes in patients undergoing curative resection for pancreatic adenocarcinoma: A new tool to assess sarcopenia. J Gastrointest Surg 19(9): 1593-1602, 2015. PMID: 25925237. DOI: 10.1007/s11605-015-2835-y
    OpenUrlCrossRef
  15. ↵
    1. Sabel MS,
    2. Lee J,
    3. Cai S,
    4. Englesbe MJ,
    5. Holcombe S and
    6. Wang S
    : Sarcopenia as a prognostic factor among patients with stage III melanoma. Ann Surg Oncol 18(13): 3579-3585, 2011. PMID: 21822551. DOI: 10.1245/s10434-011-1976-9
    OpenUrlCrossRefPubMed
  16. ↵
    1. Wilson RJ,
    2. Alamanda VK,
    3. Hartley KG,
    4. Mesko NW,
    5. Halpern JL,
    6. Schwartz HS and
    7. Holt GE
    : Sarcopenia does not affect survival or outcomes in soft-tissue sarcoma. Sarcoma 2015: 146481, 2015. PMID: 26696772. DOI: 10.1155/2015/146481
    OpenUrlCrossRef
    1. Nemec U,
    2. Heidinger B,
    3. Sokas C,
    4. Chu L and
    5. Eisenberg RL
    : Diagnosing sarcopenia on thoracic computed tomography: Quantitative assessment of skeletal muscle mass in patients undergoing transcatheter aortic valve replacement. Acad Radiol 24(9): 1154-1161, 2017. PMID: 28365235. DOI: 10.1016/j.acra.2017.02.008
    OpenUrlCrossRef
    1. Murray TÉ,
    2. Williams D and
    3. Lee MJ
    : Osteoporosis, obesity, and sarcopenia on abdominal CT: a review of epidemiology, diagnostic criteria, and management strategies for the reporting radiologist. Abdom Radiol (NY) 42(9): 2376-2386, 2017. PMID: 28386693. DOI: 10.1007/s00261-017-1124-5
    OpenUrlCrossRef
    1. Mourtzakis M,
    2. Prado CM,
    3. Lieffers JR,
    4. Reiman T,
    5. McCargar LJ and
    6. Baracos VE
    : A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care. Appl Physiol Nutr Metab 33(5): 997-1006, 2008. PMID: 18923576. DOI: 10.1139/H08-075
    OpenUrlCrossRefPubMed
  20. ↵
    1. Prado CM,
    2. Lieffers JR,
    3. McCargar LJ,
    4. Reiman T,
    5. Sawyer MB,
    6. Martin L and
    7. Baracos VE
    : Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: A population-based study. Lancet Oncol 9(7): 629-635, 2008. PMID: 18539529. DOI: 10.1016/S1470-2045(08)70153-0
    OpenUrlCrossRefPubMed
  21. ↵
    1. Boshier PR,
    2. Heneghan R,
    3. Markar SR,
    4. Baracos VE and
    5. Low DE
    : Assessment of body composition and sarcopenia in patients with esophageal cancer: a systematic review and meta-analysis. Dis Esophagus 31(8): 2018. PMID: 29846548. DOI: 10.1093/dote/doy047
    OpenUrlCrossRef
  22. ↵
    1. Caan BJ,
    2. Cespedes Feliciano EM,
    3. Prado CM,
    4. Alexeeff S,
    5. Kroenke CH,
    6. Bradshaw P,
    7. Quesenberry CP,
    8. Weltzien EK,
    9. Castillo AL,
    10. Olobatuyi TA and
    11. Chen WY
    : Association of muscle and adiposity measured by computed tomography with survival in patients with nonmetastatic breast cancer. JAMA Oncol 4(6): 798-804, 2018. PMID: 29621380. DOI: 10.1001/jamaoncol.2018.0137
    OpenUrlCrossRefPubMed
    1. Caan BJ,
    2. Meyerhardt JA,
    3. Kroenke CH,
    4. Alexeeff S,
    5. Xiao J,
    6. Weltzien E,
    7. Feliciano EC,
    8. Castillo AL,
    9. Quesenberry CP,
    10. Kwan ML and
    11. Prado CM
    : Explaining the obesity paradox: The association between body composition and colorectal cancer survival (C-SCANS Study). Cancer Epidemiol Biomarkers Prev 26(7): 1008-1015, 2017. PMID: 28506965. DOI: 10.1158/1055-9965.EPI-17-0200
    OpenUrlAbstract/FREE Full Text
    1. Jacobs AJ,
    2. Michels R,
    3. Stein J and
    4. Levin AS
    : Improvement in overall survival from extremity soft tissue sarcoma over twenty years. Sarcoma 2015: 279601, 2015. PMID: 25821397. DOI: 10.1155/2015/279601
    OpenUrlCrossRef
    1. Rubbieri G,
    2. Mossello E and
    3. Di Bari M
    : Techniques for the diagnosis of sarcopenia. Clin Cases Miner Bone Metab 11(3): 181-184, 2014. PMID: 25568650
    OpenUrl
  26. ↵
    1. Sebro R
    : Obesity, hepatic steatosis, and their impact on fat infiltration of the trunk musculature using unenhanced computed tomography. J Comput Assist Tomogr 41(2): 298-301, 2017. PMID: 28230568. DOI: 10.1097/RCT.0000000000000507
    OpenUrlCrossRef
  27. ↵
    1. Romme EA,
    2. Murchison JT,
    3. Phang KF,
    4. Jansen FH,
    5. Rutten EP,
    6. Wouters EF,
    7. Smeenk FW,
    8. Van Beek EJ and
    9. Macnee W
    : Bone attenuation on routine chest CT correlates with bone mineral density on DXA in patients with COPD. J Bone Miner Res 27(11): 2338-2343, 2012. PMID: 22692725. DOI: 10.1002/jbmr.1678
    OpenUrlCrossRefPubMed
  28. ↵
    1. Emohare O,
    2. Cagan A,
    3. Morgan R,
    4. Davis R,
    5. Asis M,
    6. Switzer J and
    7. Polly DW Jr.
    : The use of computed tomography attenuation to evaluate osteoporosis following acute fractures of the thoracic and lumbar vertebra. Geriatr Orthop Surg Rehabil 5(2): 50-55, 2014. PMID: 25360331. DOI: 10.1177/2151458514525042
    OpenUrlCrossRefPubMed
  29. ↵
    1. McDonald AM,
    2. Swain TA,
    3. Mayhew DL,
    4. Cardan RA,
    5. Baker CB,
    6. Harris DM,
    7. Yang ES and
    8. Fiveash JB
    : CT measures of bone mineral density and muscle mass can be used to predict noncancer death in men with prostate cancer. Radiology 282(2): 475-483, 2017. PMID: 27598538. DOI: 10.1148/radiol.2016160626
    OpenUrlCrossRef
  30. ↵
    1. Gadducci A and
    2. Cosio S
    : The prognostic relevance of computed tomography-assessed skeletal muscle index and skeletal muscle radiation attenuation in patients with gynecological cancer. Anticancer Res 41(1): 9-20, 2021. PMID: 33419795. DOI: 10.21873/anticanres.14747
    OpenUrlAbstract/FREE Full Text
  31. ↵
    1. Villaseñor A,
    2. Ballard-Barbash R,
    3. Baumgartner K,
    4. Baumgartner R,
    5. Bernstein L,
    6. McTiernan A and
    7. Neuhouser ML
    : Prevalence and prognostic effect of sarcopenia in breast cancer survivors: the HEAL Study. J Cancer Surviv 6(4): 398-406, 2012. PMID: 23054848. DOI: 10.1007/s11764-012-0234-x
    OpenUrlCrossRefPubMed
  32. ↵
    1. Altman DG and
    2. Royston P
    : The cost of dichotomising continuous variables. BMJ 332(7549): 1080, 2006. PMID: 16675816. DOI: 10.1136/bmj.332.7549.1080
    OpenUrlFREE Full Text
  33. ↵
    1. Walston JD
    : Sarcopenia in older adults. Curr Opin Rheumatol 24(6): 623-627, 2012. PMID: 22955023. DOI: 10.1097/BOR.0b013e328358d59b
    OpenUrlCrossRefPubMed
    1. McIntire KL and
    2. Hoffman AR
    : The endocrine system and sarcopenia: potential therapeutic benefits. Curr Aging Sci 4(3): 298-305, 2011. PMID: 21529322. DOI: 10.2174/1874609811104030298
    OpenUrlCrossRefPubMed
    1. Horstman AM,
    2. Dillon EL,
    3. Urban RJ and
    4. Sheffield-Moore M
    : The role of androgens and estrogens on healthy aging and longevity. J Gerontol A Biol Sci Med Sci 67(11): 1140-1152, 2012. PMID: 22451474. DOI: 10.1093/gerona/gls068
    OpenUrlCrossRefPubMed
    1. Jo E,
    2. Lee SR,
    3. Park BS and
    4. Kim JS
    : Potential mechanisms underlying the role of chronic inflammation in age-related muscle wasting. Aging Clin Exp Res 24(5): 412-422, 2012. PMID: 22717404. DOI: 10.3275/8464
    OpenUrlCrossRefPubMed
    1. McFarlane C,
    2. Plummer E,
    3. Thomas M,
    4. Hennebry A,
    5. Ashby M,
    6. Ling N,
    7. Smith H,
    8. Sharma M and
    9. Kambadur R
    : Myostatin induces cachexia by activating the ubiquitin proteolytic system through an NF-kappaB-independent, FoxO1-dependent mechanism. J Cell Physiol 209(2): 501-514, 2006. PMID: 16883577. DOI: 10.1002/jcp.20757
    OpenUrlCrossRefPubMed
  38. ↵
    1. Baracos VE
    : Psoas as a sentinel muscle for sarcopenia: a flawed premise. J Cachexia Sarcopenia Muscle 8(4): 527-528, 2017. PMID: 28675689. DOI: 10.1002/jcsm.12221
    OpenUrlCrossRef
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