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Temporalis muscle thickness as an indicator of sarcopenia predicts progression-free survival in head and neck squamous cell carcinoma
- Source :
- Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
- Publication Year :
- 2021
- Publisher :
- Nature Portfolio, 2021.
-
Abstract
- Abstract Temporalis muscle thickness (TMT) on brain magnetic resonance imaging (MRI) is correlated with sarcopenia and can be a predictive marker for survival in patients with brain tumors, but the association of TMT on head and neck computed tomography (CT) with survival in head and neck squamous cell carcinoma (HNSCC) remains unclear. We investigated whether TMT on CT could predict progression-free survival (PFS) in patients with HNSCC. A total of 106 patients with newly diagnosed HNSCC were included in this retrospective study. The patients underwent baseline head and neck CT and/or MRI between July, 2008 and August, 2018. The correlation between TMT on CT and MRI was tested using intraclass correlation coefficient (ICC). The cut-off value of TMT on CT for determining tumor progression was identified using receiver-operating characteristic curve analysis. Uni- and consecutive multi-variable Cox regression models were used to verify the association between TMT and PFS. TMT on CT and MRI showed excellent correlation (ICC, 0.894). After a mean follow-up of 37 months, 49 out of 106 patients showed locoregional recurrence and/or distant metastasis. The cut-off TMT of 6.47 mm showed good performance in predicting tumor progression (area under the curve, 0.779). The Cox regression model showed that TMT ≤ 6.24 mm (median value in study population) was a significant contributing factor for predicting shorter PFS (hazard ratio 0.399; 95% confidence interval 0.209–0.763; P = .005). TMT may be used as a surrogate parameter for pre-treatment sarcopenia and could help predict PFS in patients with HNSCC.
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 11
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Scientific Reports
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.358c51d1413248beb31f5564c2eddf15
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41598-021-99201-3