scholarly journals Neutrophil to Lymphocyte Ratio as Prognostic Indicator for Patients with Esophageal Squamous Cell Cancer

2017 ◽  
Vol 32 (4) ◽  
pp. 409-414 ◽  
Author(s):  
Guo-Dong Gao ◽  
Bo Sun ◽  
Xian-Bin Wang ◽  
Shi-Meng Wang
Keyword(s):  
Overall Survival ◽  
Squamous Cell ◽  
Cox Regression ◽  
Cell Cancer ◽  
Prognostic Indicator ◽  
Neutrophil To Lymphocyte Ratio ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Leukocyte Counts ◽  
Clinical Records

Background This study aimed to evaluate the correlation between neutrophil to lymphocyte ratio (NLR) with overall survival (OS) of esophageal squamous cell carcinoma (ESCC) patients. Method Records of patients with diagnosed ESCC were reviewed. Leukocyte counts and patients' characteristics were extracted from their clinical records to calculate NLR. Correlation between NLR and baseline characteristics with overall survival (OS) was then analyzed using Cox regression. The patients were then separated into higher and lower NLR groups according to median NLR. OS was further compared between the 2 groups. Results A total of 1281 patients were included in the study. Cox regression analysis showed a significant correlation of NLR with OS of ESCC patients. The median pretreatment NLR was identified as 2.86. Higher NLR was associated with worse prognosis in terms of OS. Conclusions Pretreatment NLR is independently associated with OS of ESCC patients. Therefore, NLR may be used as a predictive indicator for pretreatment evaluation and adjustment of treatment regimen.

scholarly journals Prognostic Association between Common Laboratory Tests and Overall Survival in Elderly Men with De Novo Metastatic Castration Sensitive Prostate Cancer: A Population-Based Study in Canada

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2844
Author(s):  
Christopher J. D. Wallis ◽  
Bobby Shayegan ◽  
Scott C. Morgan ◽  
Robert J. Hamilton ◽  
Ilias Cagiannos ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Overall Survival ◽  
Clinical Decision Making ◽  
Cox Regression ◽  
De Novo ◽  
Population Based ◽  
Population Based Study ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Laboratory Markers

De novo cases of metastatic prostate cancer (mCSPC) are associated with poorer prognosis. To assist in clinical decision-making, we aimed to determine the prognostic utility of commonly available laboratory-based markers with overall survival (OS). In a retrospective population-based study, a cohort of 3556 men aged ≥66 years diagnosed with de novo mCSPC between 2014 and 2019 was identified in Ontario (Canada) administrative database. OS was assessed by using the Kaplan–Meier method. Multivariate Cox regression analysis was performed to evaluate the association between laboratory markers and OS adjusting for patient and disease characteristics. Laboratory markers that were assessed include neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), albumin, hemoglobin, serum testosterone and PSA kinetics. Among the 3556 older men with de novo mCSPC, their median age was 77 years (IQR: 71–83). The median survival was 18 months (IQR: 10–31). In multivariate analysis, a statistically significant association with OS was observed with all the markers (NLR, PLR, albumin, hemoglobin, PSA decrease, reaching PSA nadir and a 50% PSA decline), except for testosterone levels. Our findings support the use of markers of systemic inflammation (NLR, PLR and albumin), hemoglobin and PSA metrics as prognostic indicators for OS in de novo mCSPC.

scholarly journals Low cardiac dose and neutrophil-to-lymphocyte ratio predict overall survival in inoperable esophageal squamous cell cancer patients after chemoradiotherapy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yu-Chieh Ho ◽  
Yuan-Chun Lai ◽  
Hsuan-Yu Lin ◽  
Ming-Hui Ko ◽  
Sheng-Hung Wang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Cancer Patients ◽  
Squamous Cell ◽  
Squamous Cell Cancer ◽  
Performance Status ◽  
Cell Cancer ◽  
Esophageal Squamous Cell Cancer ◽  
Lymphocyte Ratio ◽  
Cardiac Dose

AbstractWe aimed to determine the prognostic significance of cardiac dose and hematological immunity parameters in esophageal cancer patients after concurrent chemoradiotherapy (CCRT). During 2010–2015, we identified 101 newly diagnosed esophageal squamous cell cancer patients who had completed definitive CCRT. Patients' clinical, dosimetric, and hematological data, including absolute neutrophil count, absolute lymphocyte count, and neutrophil-to-lymphocyte ratio (NLR), at baseline, during, and post-CCRT were analyzed. Cox proportional hazards were calculated to identify potential risk factors for overall survival (OS). Median OS was 13 months (95% confidence interval [CI]: 10.38–15.63). Univariate analysis revealed that male sex, poor performance status, advanced nodal stage, higher percentage of heart receiving 10 Gy (heart V10), and higher NLR (baseline and follow-up) were significantly associated with worse OS. In multivariate analysis, performance status (ECOG 0 & 1 vs. 2; hazard ratio [HR] 3.12, 95% CI 1.30–7.48), heart V10 (> 84% vs. ≤ 84%; HR 2.24, 95% CI 1.26–3.95), baseline NLR (> 3.56 vs. ≤ 3.56; HR 2.36, 95% CI 1.39–4.00), and follow-up NLR (> 7.4 vs. ≤ 7.4; HR 1.95, 95% CI 1.12–3.41) correlated with worse OS. Volume of low cardiac dose and NLR (baseline and follow-up) were associated with worse patient survival.

scholarly journals Combination of Tertiary Lymphoid Structure and Neutrophil-to-Lymphocyte Ratio Predicts Survival in Patients With Hepatocellular Carcinoma

2022 ◽  
Vol 12 ◽  
Author(s):  
Shaodi Wen ◽  
Yuzhong Chen ◽  
Chupeng Hu ◽  
Xiaoyue Du ◽  
Jingwei Xia ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Systemic Inflammation ◽  
Cox Regression ◽  
Primary Liver Cancer ◽  
Paraffin Section ◽  
Neutrophil To Lymphocyte Ratio ◽  
Survival Prediction ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Inflammation Parameters

BackgroundHepatocellular carcinoma (HCC) is the most common pathological type of primary liver cancer. The lack of prognosis indicators is one of the challenges in HCC. In this study, we investigated the combination of tertiary lymphoid structure (TLS) and several systemic inflammation parameters as a prognosis indicator for HCC.Materials and MethodsWe retrospectively recruited 126 postoperative patients with primary HCC. The paraffin section was collected for TLS density assessment. In addition, we collected the systemic inflammation parameters from peripheral blood samples. We evaluated the prognostic values of those parameters on overall survival (OS) using Kaplan-Meier curves, univariate and multivariate Cox regression. Last, we plotted a nomogram to predict the survival of HCC patients.ResultsWe first found TLS density was positively correlated with HCC patients’ survival (HR=0.16, 95% CI: 0.06 − 0.39, p < 0.0001), but the power of TLS density for survival prediction was found to be limited (AUC=0.776, 95% CI:0.772 − 0.806). Thus, we further introduced several systemic inflammation parameters for survival analysis, we found neutrophil-to-lymphocyte ratio (NLR) was positively associated with OS in univariate Cox regression analysis. However, the combination of TLS density and NLR better predicts patient’s survival (AUC=0.800, 95% CI: 0.698-0.902, p < 0.001) compared with using any single indicator alone. Last, we incorporated TLS density, NLR, and other parameters into the nomogram to provide a reproducible approach for survival prediction in HCC clinical practice.ConclusionThe combination of TLS density and NLR was shown to be a good predictor of HCC patient survival. It also provides a novel direction for the evaluation of immunotherapies in HCC.

Real world outcomes in advanced urothelial cancer and the role of neutrophil to lymphocyte ratio.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e16020-e16020
Author(s):  
Steven Yip ◽  
Jeenan Kaiser ◽  
Haocheng Li ◽  
Scott A. North ◽  
Daniel Yick Chin Heng ◽  
...  
Keyword(s):  
Real World ◽  
Cox Regression ◽  
Response Rates ◽  
Neutrophil To Lymphocyte Ratio ◽  
Second Line ◽  
First Line ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Line Setting

e16020 Background: Advanced urothelial carcinoma (UC) patients have a poor prognosis. In the first and second line UC treatment setting, we investigated real world outcomes and evaluated the prognostic role of the neutrophil to lymphocyte ratio (NLR). Methods: A retrospective analysis was performed on advanced UC patients treated with systemic therapy. Overall response rates (ORR), time to treatment failure (TTF) and overall survival (OS) were calculated. Cox regression analysis was performed to examine the association between baseline NLR (low NLR<3 vs high NLR≥3) and TTF and OS. Results: We evaluated 233 advanced UC patients. In the first line setting, the ORR was 25%. Median TTF and OS were 6.9 mo and 9 mo, respectively. Low baseline NLR was significantly associated with improved 8.3 mo median TTF, versus 5.8 mo for high NLR patients (p=0.05). Low NLR was significantly correlated with a longer median OS of 13.1 mo, in comparison to 8.2 mo in patients with high NLR (p=0.007). In the second line, an ORR of 22%, a median TTF of 4.1 mo and a median OS of 8 mo were observed. Low NLR in the second line was significantly associated with improved median TTF at 7.9 mo, versus 3.6 mo for patients with high NLR (p=0.03). Second line low NLR was also significantly associated with a longer median OS of 12.2 mo, in comparison to 6.8 mo in patients with high NLR (p=0.003). Conclusions: In this real world analysis of advanced UC patients, first line outcomes were lower than expected, while response rates in the second line compared favorably to the literature, suggesting a highly selected patient population actually receives second line treatment. A low baseline NLR in the first and second line is associated with improved TTF and OS and warrants further prospective evaluation. [Table: see text]

scholarly journals Development and validation of a radiomics-based model to predict local progression-free survival after chemo-radiotherapy in patients with esophageal squamous cell cancer

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
He-San Luo ◽  
Ying-Ying Chen ◽  
Wei-Zhen Huang ◽  
Sheng-Xi Wu ◽  
Shao-Fu Huang ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Local Recurrence ◽  
Squamous Cell ◽  
Cox Regression ◽  
Validation Cohort ◽  
Cell Cancer ◽  
Clinical Factors ◽  
Free Survival ◽  
Training Cohort ◽  
Cox Regression Analysis

Abstract Purpose To develop a nomogram model for predicting local progress-free survival (LPFS) in esophageal squamous cell carcinoma (ESCC) patients treated with concurrent chemo-radiotherapy (CCRT). Methods We collected the clinical data of ESCC patients treated with CCRT in our hospital. Eligible patients were randomly divided into training cohort and validation cohort. The least absolute shrinkage and selection operator (LASSO) with COX regression was performed to select optimal radiomic features to calculate Rad-score for predicting LPFS in the training cohort. The univariate and multivariate analyses were performed to identify the predictive clinical factors for developing a nomogram model. The C-index was used to assess the performance of the predictive model and calibration curve was used to evaluate the accuracy. Results A total of 221 ESCC patients were included in our study, with 155 patients in training cohort and 66 patients in validation cohort. Seventeen radiomic features were selected by LASSO COX regression analysis to calculate Rad-score for predicting LPFS. The patients with a Rad-score ≥ 0.1411 had high risk of local recurrence, and those with a Rad-score < 0.1411 had low risk of local recurrence. Multivariate analysis showed that N stage, CR status and Rad-score were independent predictive factors for LPFS. A nomogram model was built based on the result of multivariate analysis. The C-index of the nomogram was 0.745 (95% CI 0.7700–0.790) in training cohort and 0.723(95% CI 0.654–0.791) in validation cohort. The 3-year LPFS rate predicted by the nomogram model was highly consistent with the actual 3-year LPFS rate both in the training cohort and the validation cohort. Conclusion We developed and validated a prediction model based on radiomic features and clinical factors, which can be used to predict LPFS of patients after CCRT. This model is conducive to identifying the patients with ESCC benefited more from CCRT.

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