Neutrophil-to-lymphocyte ratio after pazopanib treatment predicts response in patients with advanced soft-tissue sarcoma

2017 ◽  
Vol 23 (2) ◽  
pp. 368-374 ◽  
Author(s):  
Hiroshi Kobayashi ◽  
Tomotake Okuma ◽  
Hiroyuki Oka ◽  
Toshihide Hirai ◽  
Takahiro Ohki ◽  
...  
2021 ◽  
Vol 41 (1) ◽  
pp. 527-532
Author(s):  
YASUYOSHI SATO ◽  
KENJI NAKANO ◽  
NAOKI FUKUDA ◽  
XIAOFEI WANG ◽  
TETSUYA URASAKI ◽  
...  

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 11049-11049
Author(s):  
Jason Yongsheng Chan ◽  
Zewen Zhang ◽  
Winston Chew ◽  
Grace Fangmin Tan ◽  
Chloe Liwen Lim ◽  
...  

11049 Background: Recent studies suggest that markers of systemic inflammation such as blood neutrophil-to-lymphocyte ratio (NLR) may be prognostic for various cancers, though its clinical utility has not been widely accepted. This study aims to investigate its clinical relevance in patients (pts) with soft tissue sarcoma (STS). Methods: Five hundred and twenty-nine pts with localized STS who had available pre-operative blood counts at the time of diagnosis were retrospectively examined. An optimal cutoff for high NLR ( > 2.5) in predicting overall survival (OS) and relapse-free survival (RFS) in pts who underwent curative surgery (n = 473) was determined using receiver operating curve analyses. Cutoffs for platelet-lymphocyte ratios (PLR, > 180) and lymphocyte-monocyte ratios (LMR, < 3.6) were similarly obtained. Survival analysis was performed using the Kaplan-Meier method and multivariate Cox proportional models. Median follow-up was 40 months. Results: A high NLR was present in 311 (58.8%) pts, which was significantly associated with tumor grade ( p< 0.0001), depth ( p= 0.003) and size > 5 cm ( p= 0.0242), but not with age at diagnosis, sex or ethnicity. High NLR was associated with both worse OS (HR 1.78; 95%CI 1.28-2.47; p= 0.0005) and RFS (HR 1.54; 95%CI 1.17-2.03; p= 0.0019), as were age at diagnosis, tumor grade, size, PLR and LMR. In multivariate models adjusted for clinicopathological predictors of survival, only NLR, in addition to tumor grade and size, were independently associated with worse OS (HR 1.52; 95%CI 1.09-2.11; p= 0.0131) and RFS (HR 1.42; 95%CI 1.08-1.85; p= 0.0114). Analysis of survival according to American Joint Committee on Cancer (AJCC) stages subdivided as NLR-high and NLR-low revealed a significant worse prognosis for NLR-high subgroups ( p< 0.0001), with a 2.2-fold and 1.5-fold higher risk of death within stages II (HR 2.20; 95%CI 1.20-4.01; p= 0.0103) and III (HR 1.55; 95%CI 1.01-2.37; p= 0.0459), respectively. Conclusions: High NLR is an independent marker of poor prognosis among pts with localized STS. Inclusion of NLR as a classifier into the AJCC staging of STS may improve estimation of survival.


Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6266
Author(s):  
Yasuyoshi Sato ◽  
Kenji Nakano ◽  
Xiaofei Wang ◽  
Naoki Fukuda ◽  
Tetsuya Urasaki ◽  
...  

Pazopanib with trabectedin and eribulin is widely used to treat soft-tissue sarcoma (STS). We have shown that baseline neutrophil-to-lymphocyte ratio (NLR) may predict the efficacy and patient prognosis of eribulin. Changes in NLR, but not baseline NLR, can predict patient prognosis of trabectedin. However, prognostic factors of pazopanib for STS have not been identified. We present a retrospective analysis of 141 patients treated with pazopanib for recurrent or metastatic non-round cell STS. Univariate and multivariate analyses were performed to determine the predictive factors of durable clinical benefit (DCB), overall survival (OS), and progression-free survival. L-sarcoma histology (odds ratio [OR] = 0.31, 95% CI = 0.12–0.79; p = 0.014) and pre-treatment NLR < 3.0 (OR = 2.03, 95% CI = 1.02–6.67; p = 0.045) were independent predictive factors of DCB. Pre-treatment NLR < 3.0 (hazard ratio [HR] = 0.55, 95% CI = 0.36–0.84; p = 0.0057), liposarcoma histology (HR = 1.78, 95% CI = 1.09–2.91; p = 0.022), primary extremity site (HR = 0.48, 95% CI = 0.31–0.75; p = 0.0010), ECOG PS ≥ 1 (HR = 1.62, 95% CI = 1.08–2.42; p = 0.019), and CRP < 0.3 (HR = 0.52, 95% CI = 0.33–0.82; p = 0.0050) were independent predictive factors of OS. These findings indicate that baseline NLR predicts the efficacy and patient prognosis of pazopanib for STS.


2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e23537-e23537
Author(s):  
Se Jun Park ◽  
Jinsoo Lee ◽  
Kabsoo Shin ◽  
Hyunho Kim ◽  
In-Ho Kim ◽  
...  

e23537 Background: Recent studies suggest that the neutrophil-to-lymphocyte ratio (NLR) may be associated with prognosis in several cancers. However, it has not been widely accepted in a clinical situation. In this study, we investigated the clinical significance of NLR as prognostic marker in patients with soft tissue sarcoma. Methods: Between January 2008 to December 2018, 168 patients with STS who had available blood counts at the time of diagnosis were retrospectively evaluated. Receiver operator characteristic (ROC) curve analysis was used to identify the optimal cut-off value for NLR in predicting overall survival. The association between NLR and overall survival (OS) and disease-free survival (DFS) was analyzed with Kaplan-meier method and multivariate Cox proportional models. Results: A total of 168 patients were analyzed, 116 (69.0%) patients were initially resectable disease. Based on the results of ROC curve analysis, patients were classified into two groups as; high-NLR ( > 1.8) and low-NLR (≤1.8). High-NLR was presented in 107 (63.7%) patients which was significantly associated initial disease status (HR 3.30; 95% CI 1.51-7.20, p= 0.002), but not with age at diagnosis ( p= 0.167). High-NLR was significantly correlated with worse OS (HR 3.14; 95% CI 1.62-6.10, p < 0.001). 3-year DFS was 26.2% for high-NLR group versus 37.3% for low-NLR group. DFS tended to be better in low-NLR group, though not statistically significant (HR 1.65; 95% CI 0.95-2.87, p= 0.078). Conclusions: Pre-treatment NLR is a useful predictive factor for prognosis in patients with soft tissue sarcoma. Further studies are needed to evaluate the association between factors representing of host inflammatory status and cancer prognosis.


Biomarkers ◽  
2012 ◽  
Vol 17 (6) ◽  
pp. 539-544 ◽  
Author(s):  
O. K. Idowu ◽  
Q. Ding ◽  
A. F. G. Taktak ◽  
C. R. Chandrasekar ◽  
Q. Yin

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