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Sarcopenia accompanied by systemic inflammation can predict clinical outcomes in patients with head and neck cancer
Ken Kasahara1,2, Takeyuki Kono1, Yoichiro Sato2
1Department of Otolaryngology and Head and Neck Surgery, Keio University School of Medicine, Shinjuku-ku, Tokyo, Japan.
Objectives:
Evaluation of sarcopenia accompanied by systemic inflammation status is a more beneficial prognostic marker than sarcopenia alone in various cancers. However, few studies have focused on this combination in patients with head and neck squamous cell cancer (HNSCC). In this study, we investigated how the combination of sarcopenia and systemic inflammation could affect survival in patients with HNSCC. Moreover, we explored which systemic inflammation markers could be better prognostic indicators when accompanied by sarcopenia.
Materials And Methods:
We retrospectively reviewed the medical records of patients with HNSCC treated between 2012 and 2016. Sarcopenia was defined by the skeletal muscle area measured on a computed tomography image slice at the level of the third cervical vertebra. The neutrophil/lymphocyte, platelet/lymphocyte, and lymphocyte/monocyte ratios (NLR, PLR, and LMR, respectively) were used as systemic inflammation markers that were combined with sarcopenia to evaluate prognosis.
Results:
A total of 100 patients were enrolled, and 71 patients were considered sarcopenia. Patients with sarcopenia had significantly lower LMR and higher NLR and PLR. They also showed worse overall survival (OS) and progression-free survival (PFS). The comparative assessment of multiple combination patterns of sarcopenia and systemic inflammation indices proved that sarcopenia plus LMR considered as most reliable indicator for prognosis in HNSCC patients. Sarcopenia plus low LMR was a significantly poor prognostic factor both for OS and PFS with greater HR values than sarcopenia alone.
Conclusions:
The combination of sarcopenia and LMR was considered the most sensitive prognostic factor in patients with HNSCC, suggesting it might be beneficial for identifying poor outcome risks.
