Prognostic Value of Inflammatory and Nutritional Indicators in Non-Metastatic Soft Tissue Sarcomas

炎症和营养指标在非转移性软组织肉瘤中的预后价值

阅读:1

Abstract

BACKGROUND: Soft tissue sarcoma (STS) has lacked reliable prognostic indicators. This study evaluates blood-based inflammatory and nutritional indexes to identify good predictors for STS outcomes. These indicators included neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic inflammation response index (SIRI), lymphocyte-to-monocyte ratio (PNI), albumin-to-globulin ratio (AGR), and platelet-to-albumin ratio (PAR). METHODS: A total of 93 were included, and blood indexes were measured preoperatively. Univariate and multivariate regression analyses identified significant predictors, and model performance was assessed using the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Concordance Index (C-index), and Likelihood Ratio Chi-Square (LR_χ2). RESULTS: Univariate analysis indicated that NLR, PLR, LMR, SIRI, AGR, and PAR show potentially significant differences (P<0.01), except for PNI. Further analysis showed that SIRI and AGR have a high C-index, LR_χ2, and -2 log-likelihood, lower AIC and BIC, indicating a better model fit for overall survival (OS) and disease-free survival (DFS). The combination index of the SIRI+AGR+Enneking stage achieved the best accuracy (C-index: 0.751 for DFS; C-index: 0.755 for OS). Multivariate regression showed higher Enneking staging (HR=2.720, P=0.038), lower AGR (HR=2.091, P=0.014), and higher SIRI (HR=2.078, P=0.034) as independent prognostic factors for DFS. Meanwhile, low AGR (HR=3.729, P=0.034), and high SIRI (HR=3.729, P=0.016) remained independent prognostic factors for OS. CONCLUSION: Preoperative SIRI is a better predictive index compared to NLR, PLR, and LMR. Preoperative SIRI and AGR are independent risk factors for both DFS and OS. The combination index of the SIRI+AGR+Enneking stage provides a more robust prediction of clinical prognosis in STS patients.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。