The pretreatment erythrocyte sedimentation rate predicts survival outcomes after surgery and adjuvant radiotherapy for extremity soft tissue sarcoma

Autor: Geumju Park, Si Yeol Song, Jin-Hee Ahn, Wan-lim Kim, Jong-seok Lee, Seong-Yun Jeong, Jae Won Park, Eun Kyung Choi, Wonsik Choi, In-Hye Jung
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Radiation Oncology, Vol 14, Iss 1, Pp 1-8 (2019)
Druh dokumentu: article
ISSN: 1748-717X
DOI: 10.1186/s13014-019-1331-z
Popis: Abstract Background Systemic inflammation plays a critical role in cancer progression and oncologic outcomes in cancer patients. We investigated whether preoperative inflammatory biomarkers, including C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and neutrophil to lymphocyte ratio (NLR), could be surrogate biomarkers for predicting overall survival (OS) in soft tissue sarcoma (STS) patients treated with surgery and postoperative radiotherapy. Methods A series of 99 patients who presented with localized extremity STS were retrospectively reviewed. The preoperative CRP levels, ESR, and NLR were evaluated for associations with OS, disease-free survival (DFS), local recurrence-free survival (LRFS), and distant metastasis-free survival (DMFS). Cutoff values for CRP, ESR, and NLR were derived from receiver-operating characteristic curve analysis. Results Elevated CRP (> 0.14 mg/dL), ESR (> 15 mm/h), and NLR (> 1.95) levels were seen in 33, 44, and 45 patients, respectively. Of these three inflammatory biomarkers, elevated CRP and ESR were associated with a poorer OS (CRP: P = 0.050; ESR: P = 0.001), DFS (CRP: P = 0.023; ESR: P = 0.003), and DMFS (CRP: P = 0.015; ESR: P = 0.001). By multivariate analysis, an elevated ESR was found to be an independent prognostic factor for OS (HR 3.580, P = 0.025) and DMFS (HR 3.850, P = 0.036) after adjustment for other established prognostic factors. Conclusions The preoperative ESR level is a simple and useful surrogate biomarker for predicting survival outcomes in STS patients and might improve the identification of high-risk patients of tumor relapse in clinical practice.
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