Skeletal muscle mass at C3 may not be a strong predictor for skeletal muscle mass at L3 in sarcopenic patients with head and neck cancer

Joon-Kee Yoon, Jeon Yeob Jang, Young-Sil An and Su Jin Lee

PLOS ONE, 2021, vol. 16, issue 7, 1-13

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.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0254844

DOI: 10.1371/journal.pone.0254844

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