Joon-Kee Yoon1, Jeon Yeob Jang2, Young-Sil An1, Su Jin Lee1. 1. Department of Nuclear Medicine and Molecular Imaging, Ajou University School of Medicine, Suwon, Republic of Korea. 2. Department of Otolaryngology, Ajou University School of Medicine, Suwon, Republic of Korea.
Abstract
PURPOSE: To evaluate the feasibility of using skeletal muscle mass (SMM) at C3 (C3 SMM) as a diagnostic marker for sarcopenia in head and neck cancer (HNC) patients. METHODS: We evaluated 165 HNC patients and 42 healthy adults who underwent 18F-fluorodeoxyglucose positron emission tomography/computed tomography scans. The paravertebral muscle area at C3 and skeletal muscle area at L3 were measured by CT. Pearson's correlation was used to assess the relationship between L3 and C3 SMMs. The prediction model for L3 SMM was developed by multiple linear regression. Then the correlation and the agreement between actual and predicted L3 SMMs were assessed. To evaluate the diagnostic value of C3 SMM for sarcopenia, the receiver operating characteristics (ROC) curves were analyzed. RESULTS: Of the 165 HNC patients, 61 (37.0%) were sarcopenic and 104 (63.0%) were non-sarcopenic. A very strong correlation was found between L3 SMM and C3 SMM in both healthy adults (r = 0.864) and non-sarcopenic patients (r = 0.876), while a fair association was found in sarcopenic patients (r = 0.381). Prediction model showed a very strong correlation between actual SMM and predicted L3 SMM in both non-sarcopenic patients and healthy adults (r > 0.9), whereas the relationship was moderate in sarcopenic patients (r = 0.7633). The agreement between two measurements was good for healthy subjects and non-sarcopenic patients, while it was poor for sarcopenic patients. On ROC analysis, predicted L3 SMM showed poor diagnostic accuracy for sarcopenia. CONCLUSIONS: A correlation between L3 and C3 SMMs was weak in sarcopenic patients. A prediction model also showed a poor diagnostic accuracy. Therefore, C3 SMM may not be a strong predictor for L3 SMM in sarcopenic patients with HNC.
PURPOSE: To evaluate the feasibility of using skeletal muscle mass (SMM) at C3 (C3 SMM) as a diagnostic marker for sarcopenia in head and neck cancer (HNC) patients. METHODS: We evaluated 165 HNC patients and 42 healthy adults who underwent 18F-fluorodeoxyglucose positron emission tomography/computed tomography scans. The paravertebral muscle area at C3 and skeletal muscle area at L3 were measured by CT. Pearson's correlation was used to assess the relationship between L3 and C3 SMMs. The prediction model for L3 SMM was developed by multiple linear regression. Then the correlation and the agreement between actual and predicted L3 SMMs were assessed. To evaluate the diagnostic value of C3 SMM for sarcopenia, the receiver operating characteristics (ROC) curves were analyzed. RESULTS: Of the 165 HNC patients, 61 (37.0%) were sarcopenic and 104 (63.0%) were non-sarcopenic. A very strong correlation was found between L3 SMM and C3 SMM in both healthy adults (r = 0.864) and non-sarcopenic patients (r = 0.876), while a fair association was found in sarcopenic patients (r = 0.381). Prediction model showed a very strong correlation between actual SMM and predicted L3 SMM in both non-sarcopenic patients and healthy adults (r > 0.9), whereas the relationship was moderate in sarcopenic patients (r = 0.7633). The agreement between two measurements was good for healthy subjects and non-sarcopenic patients, while it was poor for sarcopenic patients. On ROC analysis, predicted L3 SMM showed poor diagnostic accuracy for sarcopenia. CONCLUSIONS: A correlation between L3 and C3 SMMs was weak in sarcopenic patients. A prediction model also showed a poor diagnostic accuracy. Therefore, C3 SMM may not be a strong predictor for L3 SMM in sarcopenic patients with HNC.
Authors: Lucas Stone; Brennan Olson; Alia Mowery; Stephanie Krasnow; Angie Jiang; Ryan Li; Joshua Schindler; Mark K Wax; Peter Andersen; Daniel Marks; Virginie Achim; Daniel Clayburgh Journal: JAMA Otolaryngol Head Neck Surg Date: 2019-07-01 Impact factor: 6.223
Authors: Kenneth Fearon; Florian Strasser; Stefan D Anker; Ingvar Bosaeus; Eduardo Bruera; Robin L Fainsinger; Aminah Jatoi; Charles Loprinzi; Neil MacDonald; Giovanni Mantovani; Mellar Davis; Maurizio Muscaritoli; Faith Ottery; Lukas Radbruch; Paula Ravasco; Declan Walsh; Andrew Wilcock; Stein Kaasa; Vickie E Baracos Journal: Lancet Oncol Date: 2011-02-04 Impact factor: 41.316
Authors: Justin E Swartz; Ajit J Pothen; Inge Wegner; Ernst J Smid; Karin M A Swart; Remco de Bree; Loek P H Leenen; Wilko Grolman Journal: Oral Oncol Date: 2016-10-03 Impact factor: 5.337
Authors: Marina Mourtzakis; Carla M M Prado; Jessica R Lieffers; Tony Reiman; Linda J McCargar; Vickie E Baracos Journal: Appl Physiol Nutr Metab Date: 2008-10 Impact factor: 2.665
Authors: Aaron J Grossberg; Sasikarn Chamchod; Clifton D Fuller; Abdallah S R Mohamed; Jolien Heukelom; Hillary Eichelberger; Michael E Kantor; Katherine A Hutcheson; G Brandon Gunn; Adam S Garden; Steven Frank; Jack Phan; Beth Beadle; Heath D Skinner; William H Morrison; David I Rosenthal Journal: JAMA Oncol Date: 2016-06-01 Impact factor: 31.777
Authors: Koeun Lee; Yongbin Shin; Jimi Huh; Yu Sub Sung; In Seob Lee; Kwon Ha Yoon; Kyung Won Kim Journal: Korean J Radiol Date: 2019-02 Impact factor: 3.500
Authors: Remco de Bree; Christiaan D A Meerkerk; Gyorgy B Halmos; Antti A Mäkitie; Akihiro Homma; Juan P Rodrigo; Fernando López; Robert P Takes; Jan B Vermorken; Alfio Ferlito Journal: Front Oncol Date: 2022-05-12 Impact factor: 5.738