Prognostic nomogram for patients with Nasopharyngeal Carcinoma incorporating hematological biomarkers and clinical characteristics

The relationship between LDH and GLIM criteria for cancer cachexia: Systematic review and meta-analysis

INTRODUCTION

Cancer cachexia is a clinical condition characterized by recognizable "sickness behaviors" accompanied by loss of lean body tissue. The Global Leadership on Malnutrition (GLIM) has proposed phenotypic (unintentional weight loss, low body mass index and low muscle mass) and aetiologic (reduced food intake and inflammation or disease burden) diagnostic criteria. Recent work has suggested serum lactate dehydrogenase (LDH) might represent a 3rd aetiologic criteria. Little is known of its relationship with GLIM. A systematic review and meta-analysis of their comparative prognostic value and association was performed.

METHODS

A search of electronic databases (PubMed, Medline, Ovid, Cochrane) up to February 2023 was used to identify studies that compared the prognostic value of LDH and components of the GLIM criteria in cancer. An analysis of the relationship between LDH and the components of GLIM was undertaken where this data was available. RevMan 5.4.1 was used to perform a meta-analysis for each diagnostic criteria that had 3 or more studies which reported hazard ratios with a 95 per cent confidence interval for overall survival (OS).

RESULTS

A total of 119 studies were reviewed. Advanced lung cancer was the most studied population. Included in the meta-analysis were 6 studies (n=2165) on LDH and weight loss, 17 studies (n=7540) on LDH and low BMI, 5 studies (n=758) on LDH and low muscle mass, 0 studies on LDH and food intake and 93 studies (n=32,190) on LDH and inflammation. There was a significant association between elevated serum LDH and each of low BMI (OR 1.39, 1.09 - 1.77; p=0.008), elevated NLR (OR 2.04, 1.57 - 2.65; p<0.00001) and elevated CRP (OR 2.58, 1.81 - 3.67; p<0.00001). There was no association between elevated serum LDH and low muscle mass. Only one study presented data on the association between LDH and unintentional weight loss. Elevated LDH showed a comparative OS (HR 1.86, 1.57 - 2.07; p<0.00001) to unintentional weight loss (HR 1.57, 1.23 - 1.99; p=0.0002) and had a similar OS (HR 2.00, 1.70 - 2.34; p<0.00001) to low BMI (HR 1.57, 1.29-2.90; p<0.0001). LDH also showed an OS (HR 2.25, 1.76 - 2.87; p<0.00001) congruous with low muscle mass (HR 1.93, 1.14 - 3.27; p=0.01) and again, LDH conferred as poor an OS (HR 1.77, 1.64-1.90; p<0.00001) as elevated NLR (HR 1.61, 1.48 - 1.77; p<0.00001) or CRP (HR 1.55, 1.43 - 1.69; p<0.00001).

CONCLUSION

Current literature suggests elevated serum LDH is associated with inflammation in cancer (an aetiologic GLIM criterion), however more work is required to establish the relationship between LDH and the phenotypic components of GLIM. Additionally, elevated serum LDH appears to be a comparative prognosticator of overall survival in cancer when compared to the GLIM criteria.

Clinical significance of serum lactate dehydrogenase combined with a multivariate model for predicting the near-term outcome of primary nasopharyngeal carcinoma

BACKGROUND AND OBJECTIVES

This investigation explores the clinical significance of integrating serum lactate dehydrogenase (LDH) with a multivariate model for assessing the short-term prognosis of primary nasopharyngeal carcinoma (NPC). Epstein-Barr virus (EBV) quantification is a crucial prognostic indicator in NPC cases, but not all patients with NPC test positive for EBV. Furthermore, widespread adoption of EBV-DNA quantification remains challenging due to its high cost. Consequently, it is imperative to incorporate additional convenient and cost-effective prognostic markers to comprehensively evaluate patient outcomes.

METHODS

This retrospective analysis included 203 newly diagnosed NPC cases treated at the Affiliated Qingyuan Hospital of Guangzhou Medical University between January 2018 and March 2022. The dataset included personal information and clinical data, and the treatment protocols followed the CSCO guidelines. Efficacy assessments were based on the RECIST 1.1 criteria and were conducted after induction chemotherapy and one week and three months after radiotherapy.

RESULTS

A noteworthy correlation emerged between baseline serum LDH levels and treatment efficacy at one week after radiotherapy (P = 0.03) and at three months after radiotherapy (P < 0.01). Additionally, a prognostic model that incorporates age (P = 0.010), LDH (P < 0.001), C-reactive protein (P = 0.010), and alkaline phosphatase (P = 0.005) demonstrated robust predictive accuracy and clinical applicability.

CONCLUSION

This investigation substantiates the significant correlation between baseline serum LDH levels and NPC outcomes. Furthermore, we introduce a refined prognostic model that holds promise for informing personalized treatment strategies, thereby contributing to the advancement of the diagnosis of NPC.

Enhancing Nasopharyngeal Carcinoma Survival Prediction: Integrating Pre- and Post-Treatment MRI Radiomics with Clinical Data

Recurrences are frequent in nasopharyngeal carcinoma (NPC) despite high remission rates with treatment, leading to considerable morbidity. This study aimed to develop a prediction model for NPC survival by harnessing both pre- and post-treatment magnetic resonance imaging (MRI) radiomics in conjunction with clinical data, focusing on 3-year progression-free survival (PFS) as the primary outcome. Our comprehensive approach involved retrospective clinical and MRI data collection of 276 eligible NPC patients from three independent hospitals (180 in the training cohort, 46 in the validation cohort, and 50 in the external cohort) who underwent MRI scans twice, once within 2 months prior to treatment and once within 10 months after treatment. From the contrast-enhanced T1-weighted images before and after treatment, 3404 radiomics features were extracted. These features were not only derived from the primary lesion but also from the adjacent lymph nodes surrounding the tumor. We conducted appropriate feature selection pipelines, followed by Cox proportional hazards models for survival analysis. Model evaluation was performed using receiver operating characteristic (ROC) analysis, the Kaplan-Meier method, and nomogram construction. Our study unveiled several crucial predictors of NPC survival, notably highlighting the synergistic combination of pre- and post-treatment data in both clinical and radiomics assessments. Our prediction model demonstrated robust performance, with an accuracy of AUCs of 0.66 (95% CI: 0.536-0.779) in the training cohort, 0.717 (95% CI: 0.536-0.883) in the testing cohort, and 0.827 (95% CI: 0.684-0.948) in validation cohort in prognosticating patient outcomes. Our study presented a novel and effective prediction model for NPC survival, leveraging both pre- and post-treatment clinical data in conjunction with MRI features. Its constructed nomogram provides potentially significant implications for NPC research, offering clinicians a valuable tool for individualized treatment planning and patient counseling.

Predicting the overall survival and progression-free survival of nasopharyngeal carcinoma patients based on hemoglobin, albumin, and globulin ratio and classical clinicopathological parameters

BACKGROUND

Serum biomarkers have a significant impact on the prediction of treatment outcomes in patients diagnosed with nasopharyngeal carcinoma (NPC). The primary aim of this study was to develop and validate a nomogram that incorporates hemoglobin, albumin, and globulin ratio (HAGR) and clinical data to accurately forecast treatment outcomes in patients with NPC.

METHODS

A total of 796 patients diagnosed with NPC were included in the study.

RESULTS

The results of the multivariate Cox analysis revealed that TNM stage and HAGR were found to be significant independent prognostic factors for OS and PFS. Furthermore, the utilization of the nomogram demonstrated a significant improvement in the evaluation of OS, PFS compared with the eighth TNM staging system. Additionally, the implementation of Kaplan-Meier curves and decision curve analysis curves further confirmed the discriminability and clinical effectiveness of the nomogram.

CONCLUSIONS

The HAGR, an innovative prognostic factor grounded in the realm of immunonutrition, has emerged as a promising prognostic marker for both OS and PFS in individuals afflicted with NPC.

Plasma IL-1 and IL-6 Family Cytokines with Soluble Receptor Levels at Diagnosis in Head and Neck Squamous Cell Carcinoma: High Levels Predict Decreased Five-Year Disease-Specific and Overall Survival

Activation of the acute-phase cascade (APC) has been correlated with outcomes in various cancers, including head and neck squamous cell carcinoma (HNSCC). Primary drivers of the APC are the cytokines within the interleukin-6 (IL-6) and IL-1 families. Plasma levels of IL-6 family cytokines/soluble receptors (IL-6, IL-27, IL-31, OSM, CNTF, soluble (s-)gp130, s-IL-6Rα) and IL-1 family members (IL-1RA, s-IL-33Rα) were determined at diagnosis for 87 human papillomavirus (HPV)-negative (-) HNSCC patients. We then studied the 5-year Disease-Specific Survival (DSS) and Overall Survival (OS). Increased plasma levels of IL-6 (p < 0.001/p < 0.001) (DSS/OS), IL-31 (p = 0.044/p = 0.07), IL-1RA (p = 0.004/p = 0.035), soluble (s)-IL-6Rα p = 0.022/p = 0.035), and s-gp130 (p = 0.007/p = 0.003) at diagnosis were predictors of both OS and DSS from HPV(-) HNSCC patients. The cytokine DSS/OS predictions were associated with TNM stage and smoking history, whereas the soluble receptors IL-6Rα, gp130, and IL33Rα more uniquely predicted DSS/OS. Clinically, IL-6 levels above 2.5 pg/mL yielded 75% specificity and 70% sensitivity for DSS. In conclusion, high plasma levels of IL-6, IL-31, and IL-1RA, as well as the soluble receptors IL-6Rα, gp130, and IL33Rα, predicted clinical outcome. This shows their potential as candidates for both general therapy and immune therapy stratification, as well as being future platforms for the development of new immunotherapy.

Pretreatment multiparametric MRI radiomics-integrated clinical hematological biomarkers can predict early rapid metastasis in patients with nasopharyngeal carcinoma

BACKGROUND

To establish and validate a predictive model combining pretreatment multiparametric MRI-based radiomic signatures and clinical characteristics for the risk evaluation of early rapid metastasis in nasopharyngeal carcinoma (NPC) patients.

METHODS

The cutoff time was used to randomly assign 219 consecutive patients who underwent chemoradiation treatment to the training group (n = 154) or the validation group (n = 65). Pretreatment multiparametric magnetic resonance (MR) images of individuals with NPC were employed to extract 428 radiomic features. LASSO regression analysis was used to select radiomic features related to early rapid metastasis and develop the Rad-score. Blood indicators were collected within 1 week of pretreatment. To identify independent risk variables for early rapid metastasis, univariate and multivariate logistic regression analyses were employed. Finally, multivariate logistic regression analysis was applied to construct a radiomics and clinical prediction nomogram that integrated radiomic features and clinical and blood inflammatory predictors.

RESULTS

The NLR, T classification and N classification were found to be independent risk indicators for early rapid metastasis by multivariate logistic regression analysis. Twelve features associated with early rapid metastasis were selected by LASSO regression analysis, and the Rad-score was calculated. The AUC of the Rad-score was 0.773. Finally, we constructed and validated a prediction model in combination with the NLR, T classification, N classification and Rad-score. The area under the curve (AUC) was 0.936 (95% confidence interval (95% CI): 0.901-0.971), and in the validation cohort, the AUC was 0.796 (95% CI: 0.686-0.905).

CONCLUSIONS

A predictive model that integrates the NLR, T classification, N classification and MR-based radiomics for distinguishing early rapid metastasis may serve as a clinical risk stratification tool for effectively guiding individual management.

A Nomogram Model Based on the Inflammation-Immunity-Nutrition Score (IINS) and Classic Clinical Indicators for Predicting Prognosis in Extranodal Natural Killer/T-Cell Lymphoma

Background

Systemic inflammation, immunity, and nutritional status are closely related to patients' outcomes in several kinds of cancers. This study aimed to establish a new nomogram based on inflammation-immunity-nutrition score (IINS) to predict the prognosis of extranodal natural killer/T-cell lymphoma (ENKTL) patients.

Methods

The clinical data of 435 patients with ENTKL were retrospectively reviewed and randomly assigned to training cohort (n=305) and validation cohort (n=131) at a ratio of 7:3. Cox regression analysis was employed to identify independent prognostic factors and develop a nomogram in the training cohort. Harrell's concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) curve were employed to assess the performance of the nomogram and compare it with traditional prognostic systems (PINK, IPI, KPI). Internal validation was performed using 1000 bootstrap resamples in the validation cohort. Kaplan-Meier survival analyses were conducted to compare the overall survival (OS) of patients in different risk groups.

Results

In the training cohort, in addition to several classic parameters, IINS was identified as an independent prognostic factor significantly associated with the OS of patients. The nomogram established based on the independent prognostic indicators showed superior survival prediction efficacy, with C-index of 0.733 in the training cohort and 0.759 in the validation cohort compared to the PINK (0.636 and 0.737), IPI (0.81 and 0.707), and KPI (0.693 and 0.639) systems. Furthermore, compared with PINK, IPI, and IPI systems, the nomogram showed relatively superior calibration curves and more powerful prognostic discrimination ability in predicting the OS of patients. DCA curves revealed some advantages in terms of clinical applicability of the nomogram compared to the PINK, IPI, and IPI systems.

Conclusion

Compared with traditional prognostic systems, the nomogram showed promising prospects for risk stratification in ENKTL patient prognosis, providing new insights into the personalized treatment.

Fusing Diverse Decision Rules in 3D-Radiomics for Assisting Diagnosis of Lung Adenocarcinoma

This study aimed to develop an interpretable diagnostic model for subtyping of pulmonary adenocarcinoma, including minimally invasive adenocarcinoma (MIA), adenocarcinoma in situ (AIS), and invasive adenocarcinoma (IAC), by integrating 3D-radiomic features and clinical data. Data from multiple hospitals were collected, and 10 key features were selected from 1600 3D radiomic signatures and 11 radiological features. Diverse decision rules were extracted using ensemble learning methods (gradient boosting, random forest, and AdaBoost), fused, ranked, and selected via RuleFit and SHAP to construct a rule-based diagnostic model. The model's performance was evaluated using AUC, precision, accuracy, recall, and F1-score and compared with other models. The rule-based diagnostic model exhibited excellent performance in the training, testing, and validation cohorts, with AUC values of 0.9621, 0.9529, and 0.8953, respectively. This model outperformed counterparts relying solely on selected features and previous research models. Specifically, the AUC values for the previous research models in the three cohorts were 0.851, 0.893, and 0.836. It is noteworthy that individual models employing GBDT, random forest, and AdaBoost demonstrated AUC values of 0.9391, 0.8681, and 0.9449 in the training cohort, 0.9093, 0.8722, and 0.9363 in the testing cohort, and 0.8440, 0.8640, and 0.8750 in the validation cohort, respectively. These results highlight the superiority of the rule-based diagnostic model in the assessment of lung adenocarcinoma subtypes, while also providing insights into the performance of individual models. Integrating diverse decision rules enhanced the accuracy and interpretability of the diagnostic model for lung adenocarcinoma subtypes. This approach bridges the gap between complex predictive models and clinical utility, offering valuable support to healthcare professionals and patients.

Development and internal validation of a nomogram based on peripheral blood inflammatory markers for predicting prognosis in nasopharyngeal carcinoma

BACKGROUND

Inflammatory markers, including the product of neutrophil count, platelet count, and monocyte count divided by lymphocyte count (PIV) and the platelet-to-white blood cell ratio (PWR), have not been previously reported as prognostic factors in nasopharyngeal carcinoma (NPC) patients. In order to predict overall survival (OS) in NPC patients, our goal was to create and internally evaluate a nomogram based on inflammatory markers (PIV, PWR).

METHODS

A retrospective study was done on patients who received an NPC diagnosis between January 2015 and December 2018. After identifying independent prognostic indicators linked to OS using Cox proportional hazards regression analysis, we created a nomogram with the factors we had chosen.

RESULTS

A total of 630 NPC patients in all were split into training (n = 441) and validation sets (n = 189) after being enrolled in a population-based study in 2015-2018 and monitored for a median of 5.9 years. In the training set, the age, PIV, and PWR, selected as independent predictors for OS via multivariate Cox's regression model, were chosen to develop a nomogram. Both training and validation cohorts had C-indices of 0.850 (95% confidence interval [CI]: 0.768-0.849) and 0.851 (95% CI: 0.765-0.877). Furthermore, compared with traditional TNM staging, our nomogram demonstrated greater accuracy in predicting patient outcomes. The risk stratification model derived from our prediction model may facilitate personalized treatment strategies for NPC patients.

CONCLUSION

Our findings confirmed the prognostic significance of the PWR and PIV in NPC. High PIV levels (>363.47) and low PWR (≤36.42) values are associated with worse OS in NPC patients.

Epidemiology of nasopharyngeal carcinoma: current insights and future outlook

Nasopharyngeal carcinoma (NPC) is characterised by its remarkable geographical and ethnic distribution. The interplay between genetic susceptibility, environmental exposures, and Epstein-Barr virus (EBV) infections is indicated in the development of NPC. Exposure to tobacco smoking, dietary factors, and inhalants has been associated with the risk of NPC. Genetic association studies have revealed NPC-associated susceptibility loci, including genes involved in immune responses, xenobiotic metabolism, genome maintenance, and cell cycle regulation. EBV exposure timing and strain variation might play a role in its carcinogenicity, although further investigations are required. Other factors including medical history and oral hygiene have been implicated in NPC. Prevention strategies, including primary prevention and secondary prevention through early detection, are vital in reducing mortality and morbidity of NPC. The current review discusses the global and regional distribution of NPC incidences, the risk factors associated with NPC, and the public health implications of these insights. Future investigations should consider international, large-scale prospective studies to elucidate the mechanisms underlying NPC pathogenesis and develop individualized interventions for NPC.

Significance of radiologic extranodal extension in locoregionally advanced nasopharyngeal carcinoma with lymph node metastasis: a comprehensive nomogram

OBJECTIVE

We aimed to assess the significance of rENE and creat a predictive tool (nomogram) for estimating Overall Survival (OS) in locoregionally advanced Nasopharyngeal Carcinoma (NPC) patients with Lymph Node Metastasis (LNM) based on their clinical characteristics and Radiologic Extranodal Extension (rENE).

METHODS

Five hundred and sixty-nine NPC patients with LNM were randomly divided into training and validation groups. Significant factors were identified using univariate and multivariate analyses in the training cohort. Then, the nomogram based on the screening results was established to predict the Overall Survival (OS). Calibration curves and the Concordance index (C-index) gauged predictive accuracy and discrimination. Receiver Operating Characteristic (ROC) analysis assessed risk stratification, and clinical utility was measured using Decision Curve Analysis (DCA). The nomogram's performance was validated for discrimination and calibration in an independent validation cohort.

RESULTS

A total of 360 (63.2%) patients were present with radiologic extranodal extension at initial diagnosis. Patients with rENE had significantly lower OS than other patients. Multivariate analysis identified the five factors, including rENE, for the nomogram model. The C-index was 0.75 (0.71-0.78) in the training cohort and 0.76 (0.69-0.83) in the validation cohort. Notably, the nomogram outperformed the 8th TNM staging system, as evident from the higher AUC values (0.77 vs. 0.60 for 2year and 0.75 vs. 0.65 for 3year) and well-calibrated calibration curves. Decision curve analysis indicated improved Net Benefit (NB) with the nomogram for predicting OS. The log-rank test confirmed significant survival distinctions between risk groups in both training and validation cohorts.

CONCLUSIONS

We demonstrated the prognostic value of rENE in nasopharyngeal carcinoma and developed a nomogram based on rENE and other factors to provide individual prediction of OS for locoregionally advanced nasopharyngeal carcinoma with lymph node metastasis.

LEVEL OF EVIDENCE

III.

Outcome of Atezolizumab Plus Bevacizumab Combination Therapy in High-Risk Patients with Advanced Hepatocellular Carcinoma

Real-world data regarding treatment with atezolizumab plus bevacizumab in high-risk patients with advanced HCC are lacking. In this multicenter retrospective cohort study, a total of 215 patients with advanced HCC received atezolizumab plus bevacizumab treatment at four tertiary hospitals. High-risk patients were those with grade Vp4 portal vein thrombus, bile duct invasion, or more than 50% liver infiltration. In total, 98 (45.6%) were the high-risk population, 186 (86.5%) were considered to be Child-Pugh class A, and 128 (59.5%) had previously received neoadjuvant or concomitant radiation treatment. Median overall survival (OS) was 11.25 months (95% CI, 9.50-13.10), and the median progression-free survival (PFS) was 8.00 months (95% CI, 6.82-9.18). In the high-risk population, the median OS was 10 months (95% CI, 8.19-11.82) and the median PFS was 6.50 months (95% CI, 3.93-9.08). In the high-risk population, multivariate analysis indicated that radiation therapy and lower ALBI grade were associated with better OS and PFS. A total of 177 (82.3%) patients experienced adverse events of any grade, the most common being proteinuria (23.7%). Atezolizumab plus bevacizumab treatment showed consistent efficacy and tolerability in both the total and high-risk population. Radiation therapy combined with atezolizumab plus bevacizumab treatment might be helpful to improve PFS and OS in high-risk populations.

Optimized Nomogram for Nasopharyngeal Carcinoma Prognosis Prediction in Younger Patients (Aged 18-59): Development and Validation

PURPOSE

To develop a nomogram model for the predicted overall survival (OS) in patients aged 18 to 59 years with nasopharyngeal carcinoma (NPC) and assess the value of the clinical application.

METHODS

In total, 1334 registers of NPC patients from 2010 to 2015 were retrieved from the Surveillance, Epidemiology, and End Results database. Univariate and multivariate Cox analysis were used to screen out independent risk factors affecting patients. Cox analysis predicted OS for patients with NPC at 3, 5, and 8 years. Nomogram performance was validated using the concordance index (C-index), receiver operating characteristic, calibration curve, and decision curve analysis (DCA).

RESULTS

Age, sex, race, marital, histological type, tumor size, AJCC stage, and radiotherapy were independent risk factors. The C-index of the nomogram was 0.69 [95% confidence interval (CI): 0.68-0.71] for the training set, and the C-index of the AJCC stage was 0.63 (95% CI: 0.62-0.65), both statistically significant (P < .01). The area under the curve for the nomogram at these intervals (0.755, 0.729, and 0.729, respectively) was higher than that of the AJCC stage (0.667, 0.646, and 0.646, respectively), indicating better predictive accuracy. The calibration curves revealed a high degree of agreement between the observation and the prediction. Compared to the American Joint Committee on Cancer (AJCC) stage, DCA showed better clinical utility.

CONCLUSION

The nomogram as novel predictor for nasopharyngeal carcinoma patients' survival.

Clinical observational study on the efficacy of induction chemotherapy sequential concurrent radiotherapy combined with targeted therapy in patients with locally advanced EGFR-positive nasopharyngeal carcinoma: prediction model construction and efficacy testing

OBJECTIVE

To establish a nomogram for prediction of prognosis in EGFR-positive advanced nasopharyngeal carcinoma (NPC) patients who were treated with induction chemotherapy (IC) and concurrent chemoradiotherapy (CCRT). The clinical data of 124 NPC patients who received IC sequential CCRT combined with targeted therapy at the Department of Oncology of the Affiliated Hospital of North Sichuan Medical College between June 2017 and September 2022 were retrospectively reviewed. Logistic regression analysis was used to identify the prognostic factors for building the nomogram.

RESULTS

Multifactorial regression analysis showed that the use of targeted drugs and T stage were independent factors of prognosis (p < 0.05) and the equation Y = 0.476 + 2.733X1 + - 0.758 × 2 (Y = efficacy, X1 = targeted drug therapy, X2 = T stage) was obtained. Then, a prognostic nomogram prediction model was constructed. The prediction model was validated internally for 1000 times using the Bootstrap resampling method with an accuracy of 79.29%. The calibration curve suggests that the predicted values fit well with the true values. The clinical decision curve (DCA) shows that the model has good clinical predictive value.

CONCLUSION

The use of targeted therapy significantly improved the prognosis of patients with EGFR-positive advanced NPC. For advanced NPC patients with T1 and T2 stages, IC sequenced with CCRT is more effective, and the addition of targeted therapy can further improve patients' prognosis. For advanced NPC patients with T3 and T4 stages, IC sequenced with CCRT is ineffective, and the addition of targeted therapy can significantly improve patient prognosis.

A Novel Prognostic Model Predicts Outcomes in Non-Metastatic Nasopharyngeal Carcinoma Based on Inflammation, Nutrition, and Coagulation Signature

Purpose

This study aimed to assess the prognostic and predictive value of a circulating hematological signature (CHS) and to develop a CHS-based nomogram for predicting prognosis and guiding individualized chemotherapy in non-metastatic nasopharyngeal carcinoma (NPC) patients.

Patients and Methods

NPC patients were recruited between January 2014 and December 2017 at the Jiangxi Cancer Hospital. The CHS was constructed based on a series of hematological indicators. The nomogram was developed by CHS and clinical factors.

Results

A total of 779 patients were included. Three biomarkers were selected by least absolute shrinkage and selection operator regression, including prognostic nutritional index, albumin-to-fibrinogen ratio, and prealbumin-to-fibrinogen ratio, were used to construct the CHS. The patients in the low-CHS group had better 5-year DMFS and OS than those in the high-CHS group in the training (DMFS: 85.0% vs 56.6%, p<0.001; OS: 90.3% vs 65.4%, p<0.001) and validation cohorts (DMFS: 92.3% vs 43.6%, p<0.001; OS: 92.1% vs 65.5%, p<0.001). The nomogram_CHS showed better performance than clinical stage in predicting distant metastasis (concordance index: 0.728 vs 0.646). In the low-TRS (total risk scores) group, the patients received RT alone, CCRT and IC plus CCRT had similar 5-year DMFS and OS (p>0.05). In the middle-TRS group, the patients received RT alone had worse 5-year DMFS (58.7% vs 80.8% vs 90.8%, p=0.002) and OS (75.0% vs 94.1% vs 95.0%, p=0.001) than those received CCRT or IC plus CCRT. In the high-TRS group, the patients received RT alone and CCRT had worse 5-year DMFS (18.6% vs 31.3% vs 81.5%, p<0.001) and OS (26.9% vs 53.2% vs 88.8%, p<0.001) than those received IC plus CCRT.

Conclusion

The developed nomogram_CHS had satisfactory prognostic accuracy in NPC patients and may individualize risk estimation to facilitate the identification of suitable IC candidates.

Outcome prediction models incorporating clinical variables for Head and Neck Squamous cell Carcinoma: A systematic review of methodological conduct and risk of bias

Multiple outcome prediction models have been developed for Head and Neck Squamous Cell Carcinoma (HNSCC). This systematic review aimed to identify HNSCC outcome prediction model studies, assess their methodological quality and identify those with potential utility for clinical practice. Inclusion criteria were mucosal HNSCC prognostic prediction model studies (development or validation) incorporating clinically available variables accessible at time of treatment decision making and predicting tumour-related outcomes. Eligible publications were identified from PubMed and Embase. Methodological quality and risk of bias were assessed using the checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies (CHARMS) and prediction model risk of bias assessment tool (PROBAST). Eligible publications were categorised by study type for reporting. 64 eligible publications were identified; 55 reported model development, 37 external validations, with 28 reporting both. CHARMS checklist items relating to participants, predictors, outcomes, handling of missing data, and some model development and evaluation procedures were generally well-reported. Less well-reported were measures accounting for model overfitting and model performance measures, especially model calibration. Full model information was poorly reported (3/55 model developments), specifically model intercept, baseline survival or full model code. Most publications (54/55 model developments, 28/37 external validations) were found to have high risk of bias, predominantly due to methodological issues in the PROBAST analysis domain. The identified methodological issues may affect prediction model accuracy in heterogeneous populations. Independent external validation studies in the local population and demonstration of clinical impact are essential for the clinical implementation of outcome prediction models.

An Individualized Prognostic Model in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma Based on Serum Metabolomic Profiling

PURPOSE

This study aims to evaluate the value of a serum metabolomics-based metabolic signature for locoregionally advanced nasopharyngeal carcinoma (LA-NPC) patients, thereby assisting clinical decisions.

METHODS

In this retrospective study, a total of 320 LA-NPC patients were randomly divided into a training set (ca. 70%; n = 224) and a validation set (ca. 30%; n = 96). Serum samples were analyzed using widely targeted metabolomics. Univariate and multivariate Cox regression analyses were used to identify candidate metabolites related to progression-free survival (PFS). Patients were categorized into high-risk and low-risk groups based on the median metabolic risk score (Met score), and the PFS difference between the two groups was compared using Kaplan-Meier curves. The predictive performance of the metabolic signature was evaluated using the concordance index (C-index) and the time-dependent receiver operating characteristic (ROC), and a comprehensive nomogram was constructed using the Met score and other clinical factors.

RESULTS

Nine metabolites were screened to build the metabolic signature and generate the Met score, which effectively separated patients into low- and high-risk groups. The C-index in the training and validation sets was 0.71 and 0.73, respectively. The 5-year PFS was 53.7% (95% CI, 45.12-63.86) in the high-risk group and 83.0% (95%CI, 76.31-90.26) in the low-risk group. During the construction of the nomogram, Met score, clinical stage, pre-treatment EBV DNA level, and gender were identified as independent prognostic factors for PFS. The predictive performance of the comprehensive model was better than that of the traditional model.

CONCLUSION

The metabolic signature developed through serum metabolomics is a reliable prognostic indicator of PFS in LA-NPC patients and has important clinical significance.

Epidemiological, Clinicopathological and Prognosis Features of Moroccan Patients with Nasopharyngeal Carcinoma

PROPOSAL

A distinct epidemiology, etiology, clinical characteristics, and therapeutic outcomes characterize nasopharyngeal carcinoma (NPC) from other head and neck cancers. An actualized analysis of NPC patients' features enables a global view of NPC management. Accordingly, the current study investigated the epidemiological and clinical characteristics of Moroccan patients with NPC, as well as their 4-years survival outcomes and influencing prognostic factors.

METHODS

We prospectively analyzed data of 142 histologically confirmed Moroccan patients with NPC between October 2016 and February 2019. Kaplan-Meier and Cox regression analyses were used to assess predictive prognostic factors related to NPC. All analyses were conducted using SPSS version 21 statistical software.

RESULTS

In the present study, a net male predominance was found, with a mean age of 44±16.3 years old. Advanced stages of NPC were observed in 64.1% of patients, and 32.4% of patients presented with distant metastasis at diagnosis. The 4-years overall survival, locoregional relapse-free survival, distant metastasis-free survival and progression-free survival were 68.0%, 63.0%, 53.9%, and 39.9%, respectively. Age, N category and distant metastasis were identified as the most important independent prognosis factors for NPC in this cohort (p<0.05).

CONCLUSION

In conclusion, NPC affects young adults and is frequently diagnosed at advanced disease stages, impacting therefore negatively patients survival; which is in line with data from endemic areas for NPC. The current study clearly highlights that a greater attention should be directed to improving the management of this aggressive malignancy.

Nasopharyngeal necrosis contributes to overall survival in nasopharyngeal carcinoma without distant metastasis: a comprehensive nomogram model

OBJECTIVES

This study focused on developing and validating a nomogram to predict the overall survival (OS) of patients with nasopharyngeal carcinoma (NPC) without distant metastasis based on their clinical characteristics, serum biomarkers, and presence of nasopharyngeal (NP) necrosis.

METHODS

This study included 9298 patients with NPC. Patients from January 2009 to December 2014 were randomly categorized into the training cohort and validation cohort A. Validation cohort B, whose data were collected from January 2015 to December 2017, was also included. OS was the primary endpoint of this study. Cox regression analysis was used to detect independent risk variables. Decision curve analysis, calibration curve, time-dependent receiver operating characteristic (ROC) curve, and concordance index (C-index) were used to evaluate the performance of the nomogram model.

RESULTS

A total of 267 patients developed NP necrosis after the first routine radiotherapy. After radiotherapy, patients with NP necrosis had significantly lower OS than other patients in all three cohorts (p < 0.001). Eleven factors, including NP necrosis, were involved in the nomogram, which had favorable discrimination and calibration with a C-index of 0.768 in the training cohort, 0.749 in validation cohort A, and 0.739 in validation cohort B. The nomogram exhibited a significantly larger area under the ROC curve for predicting OS than the TNM stage and Epstein-Barr virus (EBV) DNA (p < 0.001).

CONCLUSION

Compared with the TNM system and EBV DNA, we established a nomogram model with an accurate prognostic prediction for patients with NPC, which might help with patient management in NPC.

KEY POINTS

• This study included 9298 patients with NPC, and 11 factors were involved in the final model. • The nomogram had a significantly higher C-index and area under the ROC curve than the TNM stage and EBV DNA. • We established the first nomogram model for NPC involving the occurrence of NP necrosis, which was valuable for providing individual counseling and clinical assessments.

Pretreatment Serum Lactate Dehydrogenase and Metastases Numbers as Potential Determinants of Anti-PD-1 Therapy Outcome in Nasopharyngeal Carcinoma

BACKGROUND

We aimed to investigate the determinant factors of anti-PD-1 therapy outcome in nasopharyngeal carcinoma (NPC).

METHODS

In this retrospective study, we included 64 patients with recurrent/metastatic NPC. The association of patients' characteristics, C-reactive protein (CRP), neutrophil to lymphocyte ratio (NLR), and lactate dehydrogenase (LDH) with survival benefit of anti-PD-1 therapy were analyzed using Cox regression models and Kaplan-Meier analyses. Patients were divided based on the median value of CRP, NLR or LDH into different subgroups.

RESULTS

At a median follow-up time of 11.4 months (range: 1-28 months), median progression-free survival (PFS) and overall survival (OS) were 1.9 months (95% CI, .18-3.6) and 15 months (95% CI, 10.9-19.1) months, respectively. Pretreatment metastases numbers was significant predictor of PFS (HR = 1.99; 95% CI 1.10-3.63; P = .024) and OS (HR = 2.77; 95% CI 1.36-5.61; P = .005). Baseline LDH level was independent predictor of OS (HR = 7.01; 95% CI 3.09-15.88; P < .001). Patients with LDH level >435 U/L at the baseline had significantly shorter PFS and OS compared to patients with LDH level ≤435 U/L (median PFS: 1.7 vs 3.5 months, P = .040; median OS: 3.7 vs 18.5 months, P < .001). Patients with non-durable clinical benefit (NDB) had significantly higher LDH level at the baseline compared to patients who achieved durable clinical benefit (DCB) (P = .025). Post-treatment levels of CRP, LDH, and NLR were decreased compared to baseline in patients with DCB (P = .030, P = .088, and P = .066, respectively), whereas, there was a significant increase in post-treatment level of LDH compared with baseline in patients with NDB (P = .024).

CONCLUSIONS

LDH level at the baseline was an independent predictor of OS and pretreatment metastases numbers was a significant predictor of PFS and OS.

Concurrent chemoradiotherapy combined with nimotuzumab in stage III–IVa nasopharyngeal carcinoma: a retrospective analysis

PURPOSE

The efficacy and safety of nimotuzumab (NTZ) added to concurrent chemoradiotherapy (CCRT) were investigated in patients with stage III-IVa nasopharyngeal carcinoma (NPC).

METHODS

Patients with stage III-IVa NPC treated with CCRT, with or without NTZ, were screened between January 2015 and December 2017. We compared patients' overall survival (OS), progression-free survival (PFS), locoregional recurrence-free survival (LRFS), and distant metastasis-free survival (DMFS) between different therapeutic regimens. Propensity score matching (PSM) was applied to reduce the selection bias. Nomogram models were developed to predict the survival of CCRT with or without NTZ.

RESULTS

Four hundred and twenty-six patients were included after PSM, with 213 patients in each regimen. Compared with NPC patients receiving CCRT alone, patients who received NTZ plus CCRT treatment had significantly better OS (5 year OS, 76.1 vs. 72.3%, P = 0.004), PFS (5 year PFS, 73.2 vs. 69.0%, P = 0.002), and LRFS (5 year LRFS, 73.2 vs. 69.0%, P = 0.028). A multivariate Cox regression analysis demonstrated that, compared with receiving CCRT alone, NTZ plus CCRT was an independently positive factor for OS, PFS, and LRFS. No significant difference was observed in the major toxicities between the two treatments (all P > 0.05). In addition, the nomogram presented good accuracy for predicting the prognosis of NPC patients.

CONCLUSION

CCRT combined with NTZ presented favorable clinical outcomes for stage III-IVa NPC patients with good tolerance and similar toxicity compared to CCRT alone. A prospective, randomized clinical trial is essential to validate the current findings.

Prediction of 5-year progression-free survival in advanced nasopharyngeal carcinoma with pretreatment PET/CT using multi-modality deep learning-based radiomics

Objective

Deep learning-based radiomics (DLR) has achieved great success in medical image analysis and has been considered a replacement for conventional radiomics that relies on handcrafted features. In this study, we aimed to explore the capability of DLR for the prediction of 5-year progression-free survival (PFS) in advanced nasopharyngeal carcinoma (NPC) using pretreatment PET/CT images.

Methods

A total of 257 patients (170/87 patients in internal/external cohorts) with advanced NPC (TNM stage III or IVa) were enrolled. We developed an end-to-end multi-modality DLR model, in which a 3D convolutional neural network was optimized to extract deep features from pretreatment PET/CT images and predict the probability of 5-year PFS. The TNM stage, as a high-level clinical feature, could be integrated into our DLR model to further improve the prognostic performance. For a comparison between conventional radiomics and DLR, 1,456 handcrafted features were extracted, and optimal conventional radiomics methods were selected from 54 cross-combinations of six feature selection methods and nine classification methods. In addition, risk group stratification was performed with clinical signature, conventional radiomics signature, and DLR signature.

Results

Our multi-modality DLR model using both PET and CT achieved higher prognostic performance (area under the receiver operating characteristic curve (AUC) = 0.842 ± 0.034 and 0.823 ± 0.012 for the internal and external cohorts) than the optimal conventional radiomics method (AUC = 0.796 ± 0.033 and 0.782 ± 0.012). Furthermore, the multi-modality DLR model outperformed single-modality DLR models using only PET (AUC = 0.818 ± 0.029 and 0.796 ± 0.009) or only CT (AUC = 0.657 ± 0.055 and 0.645 ± 0.021). For risk group stratification, the conventional radiomics signature and DLR signature enabled significant difference between the high- and low-risk patient groups in both the internal and external cohorts (p < 0.001), while the clinical signature failed in the external cohort (p = 0.177).

Conclusion

Our study identified potential prognostic tools for survival prediction in advanced NPC, which suggests that DLR could provide complementary values to the current TNM staging.

An Exploratory Study of Refining TNM-8 M1 Categories and Prognostic Subgroups Using Plasma EBV DNA for Previously Untreated De Novo Metastatic Nasopharyngeal Carcinoma

(1) Background: NPC patients with de novo distant metastasis appears to be a heterogeneous group who demonstrate a wide range of survival, as suggested by growing evidence. Nevertheless, the current 8th edition of TNM staging (TNM-8) grouping all these patients into the M1 category is not able to identify their survival differences. We sought to identify any anatomic and non-anatomic subgroups in this study. (2) Methods: Sixty-nine patients with treatment-naive de novo M1 NPC (training cohort) were prospectively recruited from 2007 to 2018. We performed univariable and multivariable analyses (UVA and MVA) to explore anatomic distant metastasis factors, which were significantly prognostic of overall survival (OS). Recursive partitioning analysis (RPA) with the incorporation of significant factors from MVA was then performed to derive a new set of RPA stage groups with OS segregation (Set 1 Anatomic-RPA stage groups); another run of MVA was performed with the addition of pre-treatment plasma EBV DNA. A second-round RPA with significant prognostic factors of OS identified in this round of MVA was performed again to derive another set of stage groups (Set 2 Prognostic-RPA stage groups). Both sets were then validated externally with an independent validation cohort of 67 patients with distant relapses of their initially non-metastatic NPC (rM1) after radical treatment. The performance of models in survival segregation was evaluated by the Akaike information criterion (AIC) and concordance index (C-index) under 1000 bootstrapping samples for the validation cohort; (3) Results: The 3-year OS and median follow-up in the training cohort were 36.0% and 17.8 months, respectively. Co-existence of liver-bone metastases was the only significant prognostic factor of OS in the first round UVA and MVA. Set 1 RPA based on anatomic factors that subdivide the M1 category into two groups: M1a (absence of co-existing liver-bone metastases; median OS 28.1 months) and M1b (co-existing liver-bone metastases; median OS 19.2 months, p = 0.023). When pre-treatment plasma EBV DNA was also added, it became the only significant prognostic factor in UVA (p = 0.001) and MVA (p = 0.015), while co-existing liver-bone metastases was only significant in UVA. Set 2 RPA with the incorporation of pre-treatment plasma EBV DNA yielded good segregation (M1a: EBV DNA ≤ 2500 copies/mL and M1b: EBV DNA > 2500 copies/mL; median OS 44.2 and 19.7 months, respectively, p < 0.001). Set 2 Prognostic-RPA groups (AIC: 228.1 [95% CI: 194.8−251.8] is superior to Set 1 Anatomic-RPA groups (AIC: 278.5 [254.6−301.2]) in the OS prediction (p < 0.001). Set 2 RPA groups (C-index 0.59 [95% CI: 0.54−0.67]) also performed better prediction agreement in the validation cohort (vs. Set 1: C-index 0.47 [95% CI: 0.41−0.53]) (p < 0.001); (4) Conclusions: Our Anatomic-RPA stage groups yielded good segregation for de novo M1 NPC, and prognostication was further improved by incorporating plasma EBV DNA. These new RPA stage groups for M1 NPC can be applied to countries/regions regardless of whether reliable and sensitive plasma EBV DNA assays are available or not.

Nomogram for distant metastasis-free survival in patients with locoregionally advanced nasopharyngeal carcinoma

OBJECTIVE

To develop and validate a nomogram to predict distant metastasis-free survival of patients with locoregionally advanced nasopharyngeal carcinoma.

METHODS

We collected the total clinical data of 820 nasopharyngeal carcinoma (NPC) patients, of whom 482 formed the training cohort from one hospital and 328 made up the validation cohort from another hospital. By analyzing the prognosis of all patients after intensity-modulated radiotherapy by univariate and multivariate Cox regression models, a nomogram related to DMFS was created in the training cohort. The discriminatory and calibration power of the nomogram was successively assessed in the training and validation cohorts by the C‑index and calibration curve. The predictive ability for 3‑year DMFS was compared between the nomogram and TNM stage using ROC curves. Patients were divided into different risk groups based on scores calculated from the nomogram.

RESULTS

Age, lymph node gross tumor volume (GTVnd), and gross tumor volume of the nasopharynx (GTVnx) were the factors included in the nomogram. The C‑index of the nomogram was 0.721 in the training cohort and 0.750 in the validation cohort. The calibration curves were satisfactory. Patients in the high-risk group were more likely to develop metastases.

CONCLUSION

A nomogram incorporating age, GTVnd, and GTVnx showed good performance for predicting DMFS in patients with locoregionally advanced NPC.

Refining TNM-8 M1 categories with anatomic subgroups for previously untreated de novo metastatic nasopharyngeal carcinoma

PURPOSE

To propose a refined M1 classification in de novo metastatic nasopharyngeal carcinoma (NPC) based on pooled data from two academic institutions.

METHODS

Previously untreated de novo M1 NPC patients prospectively treated at The University of Hong Kong (N = 69) and Fujian Cancer Hospital (N = 114) between 2007 and 2016 were recruited and randomized in a 2:1 ratio to generate training (N = 120) and validation (N = 63) cohorts, respectively. Multivariable analysis (MVA) was performed for the training and validation cohorts to identify anatomic prognostic factors for overall survival (OS). Recursive partitioning analysis (RPA) was performed which incorporated the anatomic prognostic factors identified in the MVA to derive Anatomic-RPA groups which stratified OS in the training cohort, and were then validated in the validation cohort.

RESULTS

Median follow-up for the training and validation cohorts was 27.2 and 30.2 months with 3-year OS of 51.6% and 51.1%, respectively. MVA revealed that co-existing liver-bone metastases was the only factor prognostic for OS in both the training and validation cohorts. Anatomic-RPA separated M1 disease into M1a (no co-existing liver-bone metastases) and M1b (co-existing liver-bone metastases) with median OS 39.5 and 23.7 months, respectively (p = 0.004) in the training cohort. RPA for the validation cohort also confirmed good segregation with co-existing liver-bone metastases with median OS 47.7 and 16.0 months, respectively (p = 0.008).

CONCLUSION

Our proposal to subdivide de novo M1 NPC into M1a (no co-existing liver-bone metastases) vs. M1b (co-existing liver-bone metastases) provides better OS segregation.

Prognostic and clinicopathological significance of lymphocyte-to-monocyte ratio in patients with nasopharyngeal carcinoma: A meta-analysis

BACKGROUND

This study aimed to evaluate the prognostic effect of LMR in NPC through meta-analysis.

METHODS

The prognostic value of LMR for overall survival (OS) and disease-free survival (DFS)/progression-free survival (PFS) was evaluated by pooling hazard ratios (HRs) and 95% confidence intervals (CIs). The association between LMR and clinicopathological characteristics was estimated by using odds ratios (ORs) and 95% CIs.

RESULTS

A total of 7 studies with 3773 patients were included in this meta-analysis. The results showed that a low LMR was associated with poor OS (HR = 1.94, 95%CI = 1.71-2.20, p < 0.001) and reduced DFS/PFS (HR = 1.51, 95%CI = 1.23-1.85, p < 0.001) in NPC. Furthermore, a low LMR was significantly associated with male sex (OR = 1.34, 95%CI = 1.12-1.59, p = 0.001), T3-T4 stage (OR = 1.58, 95%CI = 1.02-2.45, p = 0.040), and tumor stage III-IV (OR = 1.54, 95%CI = 1.22-1.95, p < 0.001).

CONCLUSIONS

Our study indicated that a low LMR was correlated with poor survival and advanced tumor stage in patients with NPC.

Adjunctive PD-1 inhibitor versus standard chemotherapy in recurrent or metastatic nasopharyngeal carcinoma: a systematic review and meta-analysis

Objective:

To investigate whether Adjunctive PD-1 inhibitors have improved clinical outcomes compared to chemotherapy alone in platinum-pretreated and platinum-naive recurrent or metastatic nasopharyngeal carcinoma (R/M NPCA).

Methods:

The study involved a literature search from PubMed, Cochrane CENTRAL, and Google Scholar for randomized clinical trials (RCTs) on the use of PD-1 inhibitors versus chemotherapy alone in patients with R/M NPCA. Bias was assessed using Cochrane collaboration’s risk of bias tool. Overall Survival (OS) was examined as the primary endpoint. Secondary endpoints were Progression-Free Survival (PFS), Objective Response Rate, Disease Control Rate (DCR), Duration of Response, and Serious/Grade ⩾3 Adverse Events. Outcomes were measured with either Mean Difference, Risk ratio (RR), or Hazard ratios (HRs) at 95% confidence interval.

Results:

Four RCTs were included in the meta-analysis and systematic review. OS for the monotherapy subgroup was a HR of 0.87 [0.67, 1.13] ( p = 0.30) while the combination subgroup had 0.64 [0.45, 0.90] ( p = 0.01). The monotherapy subgroup exhibited significantly worse outcomes in PFS (HR 1.31 [1.01, 1.68]) ( p = 0.04) and DCR (RR 1.52 [1.12, 2.05]) ( p = 0.007) but no significant difference in other outcomes. For combination therapy, a statistically significant benefit can be seen in all outcomes except DCR (RR 0.62 [0.38, 1.01]) ( p = 0.06) which was a non-significant benefit favoring PD-1 inhibitors.

Conclusion:

Combination PD-1 inhibitor + chemotherapy followed by maintenance PD-1 inhibitor therapy is superior to chemotherapy alone in the first-line treatment of R/M NPCA, implying a potential benefit with the use of PD-1 inhibitors + chemotherapy with maintenance PD-1 inhibitors as first-line in R/M NPCA compared to standard chemotherapy alone.

RuleFit-Based Nomogram Using Inflammatory Indicators for Predicting Survival in Nasopharyngeal Carcinoma, a Bi-Center Study

PURPOSE

Traditional prognostic studies utilized different cut-off values, without evaluating potential information contained in inflammation-related hematological indicators. Using the interpretable machine-learning algorithm RuleFit, this study aimed to explore valuable inflammatory rules reflecting prognosis in nasopharyngeal carcinoma (NPC) patients.

PATIENTS AND METHODS

In total, 1706 biopsy-proven NPC patients treated in two independent hospitals (1320 and 386) between January 2010 and March 2014 were included. RuleFit was used to develop risk-predictive rules using hematological indicators with no distributive difference between the two centers. Time-event-dependent hematological rules were further selected by stepwise multivariate Cox analysis. Combining high-efficiency hematological rules and clinical predictors, a final model was established. Models based on other algorithms (AutoML, Lasso) and clinical predictors were built for comparison, as well as a reported nomogram. Area under the receiver operating characteristic curve (AUROC) and concordance index (C-index) were used to verify the predictive precision of different models. A site-based app was established for convenience.

RESULTS

RuleFit identified 22 combined baseline hematological rules, achieving AUROCs of 0.69 and 0.64 in the training and validation cohorts, respectively. By contrast, the AUROCs of the optimal contrast model based on AutoML were 1.00 and 0.58. For overall survival, the final model had a much higher C-index than the base model using TN staging in two cohorts (0.769 vs 0.717, P<0.001; 0.752 vs 0.688, P<0.001), and showing great generalizability in training and validation cohorts. The two models based on RuleFit rules performed best, compared with other models. As for other endpoints, the final model showed a similar trend. Kaplan-Meier curve exhibited 22.9% (390/1706) patients were "misclassified" by AJCC staging, but the final model could assess risk classification accurately.

CONCLUSION

The proposed final models based on inflammation-related rules based on RuleFit showed significantly elevated predictive performance.

Nomogram Predicting Cancer-Specific Death in Parotid Carcinoma: a Competing Risk Analysis

Purpose

Multiple factors have been shown to be tied to the prognosis of individuals with parotid cancer (PC); however, there are limited numbers of reliable as well as straightforward tools available for clinical estimation of individualized mortality. Here, a competing risk nomogram was established to assess the risk of cancer-specific deaths (CSD) in individuals with PC.

Methods

Data of PC patients analyzed in this work were retrieved from the Surveillance, Epidemiology, and End Results (SEER) data repository and the First Affiliated Hospital of Nanchang University (China). Univariate Lasso regression coupled with multivariate Cox assessments were adopted to explore the predictive factors influencing CSD. The cumulative incidence function (CIF) coupled with the Fine-Gray proportional hazards model was employed to determine the risk indicators tied to CSD as per the univariate, as well as multivariate analyses conducted in the R software. Finally, we created and validated a nomogram to forecast the 3- and 5-year CSD likelihood.

Results

Overall, 1,467 PC patients were identified from the SEER data repository, with the 3- and 5-year CSD CIF after diagnosis being 21.4% and 24.1%, respectively. The univariate along with the Lasso regression data revealed that nine independent risk factors were tied to CSD in the test dataset (n = 1,035) retrieved from the SEER data repository. Additionally, multivariate data of Fine-Gray proportional subdistribution hazards model illustrated that N stage, Age, T stage, Histologic, M stage, grade, surgery, and radiation were independent risk factors influencing CSD in an individual with PC in the test dataset (p < 0.05). Based on optimization performed using the Bayesian information criterion (BIC), six variables were incorporated in the prognostic nomogram. In the internal SEER data repository verification dataset (n = 432) and the external medical center verification dataset (n = 473), our nomogram was well calibrated and exhibited considerable estimation efficiency.

Conclusion

The competing risk nomogram presented here can be used for assessing cancer-specific mortality in PC patients.

Prognostic Value of Plasma Epstein-Barr Virus DNA Levels Pre- and Post-Neoadjuvant Chemotherapy in Patients With Nasopharyngeal Carcinoma

Background

In this study, we evaluated the prognostic value of the plasma levels of Epstein-Barr virus (EBV) DNA in patients with nasopharyngeal carcinoma (NPC) at different treatment stages.

Methods

We retrospectively analyzed the Data of 206 patients with NPC. Pre-neoadjuvant chemotherapy (pre-NACT), post-NACT, post-radiotherapy, and post-treatment plasma EBV DNA levels were used to establish prognostic nomograms. The concordance index (C-index) and calibration curves were used to compare the prognostic accuracy of the nomograms. The results were confirmed in a validation cohort consisting of patients who were tested for EBV DNA levels at all four stages of treatment. The Kaplan-Meier method was used to calculate the progression-free survival (PFS) and overall survival (OS). Survival differences were calculated using the log-rank test.

Results

EBV DNA-positive patients had worse 3-year PFS and 5-year OS than EBV DNA-negative patients; this was true for pre-NACT (PFS: 82.7% vs. 57.3%, P < 0.001; OS: 90.9% vs. 68.7%, P = 0.08) and post-NACT (PFS: 85.0% vs. 50.6%, P < 0.001; OS: 91.7% vs. 65.7%; P = 0.001) EBV DNA levels but not for post-radiotherapy (PFS: 72.2% vs. 60.9%, P = 0.192; OS: 73.1% vs. 77.2%, P = 0.472) or post-treatment (PFS: 77.3% vs. 59.2%, P = 0.063; OS: 77.5% vs. 79.7%, P = 0.644) levels. Nomograms combining pre-NACT and post-NACT EBV DNA levels had a superior prognostic ability than those of post-radiotherapy and post-treatment EBV DNA levels.

Conclusion

Pre-NACT EBV DNA levels combined with post-NACT EBV DNA levels can more reliably predict survival outcomes in patients with NPC.

Prognostic Value of Inflammatory Markers in Nasopharyngeal Carcinoma Patients in the Intensity-Modulated Radiotherapy Era

Purpose

Inflammatory markers have been widely used in various cancers, but rarely in nasopharyngeal carcinoma (NPC). Here, we evaluated the prognostic value of pretreatment neutrophil-to-lymphocyte ratio (NLR), platelet-lymphocyte-ratio (PLR), systemic immune index (SII), and systemic inflammation response index (SIRI) on NPC in the intensity-modulated radiotherapy (IMRT) era.

Methods

We retrospectively analyzed data from NPC patients from the Renmin Hospital of Wuhan University, between January 2012 and July 2020. We used Chi-square test or Fisher’s exact test to compare the baseline characteristics, then applied Kaplan–Meier (K-M) survival analysis to compare the overall survival (OS) and progression-free survival (PFS) rates. Multivariate Cox proportional risk models were applied to identify independent prognostic factors.

Results

We enrolled a total of 342 NPC patients and found optimal cut-off values of 2.65, 184.91, 804.08, and 1.34 for NLR, PLR, SII, and SIRI, respectively. K-M survival analysis revealed that high NLR, PLR, SII, and SIRI were significantly associated with worse OS and PFS relative to those in the low groups. Results from univariate Cox analysis showed that clinical, T, and M stages, as well as NLR, PLR, SII, and SIRI were associated with OS, whereas age, alongside the aforementioned parameters, was associated with PFS. Moreover, multivariate Cox analysis showed that age ≥49 years (HR=2.48, 95% CI=1.21–5.05, P=0.013) and M1 stage (HR=3.84, 95% CI=1.52–9.73, P=0.013) were independent prognostic factors for OS, whereas SIRI ≥1.34 (HR=1.91, 95% CI=1.05–3.47, P=0.034) and M1 stage (HR=2.91, 95% CI=1.44–5.86, P=0.003) were independent prognostic factors for PFS.

Conclusion

Overall, our findings indicated that high NLR, PLR, SII, and SIRI were significantly associated with poor OS and PFS in NPC patients. High SIRI may be an independent risk factor for PFS of NPC patients in the IMRT era.

A systematic review and recommendations on the use of plasma EBV DNA for nasopharyngeal carcinoma

INTRODUCTION

Nasopharyngeal carcinoma (NPC) is an endemic malignancy in Southeast Asia, particularly Southern China. The classical non-keratinising cell type is almost unanimously associated with latent Epstein-Barr virus (EBV) infection. Circulating plasma EBV DNA can be a useful biomarker in various clinical aspects, but comprehensive recommendations and international guidelines are still lacking. We conducted a systematic review of all original articles on the clinical application of plasma EBV DNA for NPC; we further evaluated its strengths and limitations for consideration as standard recommendations.

METHODS

The search terms 'nasopharyngeal OR nasopharynx', and 'plasma EBV DNA OR cell-free EBV OR cfEBV' were used to identify full-length articles published up to December 2020 in the English literature. Three authors independently reviewed the article titles, removed duplicates and reviewed the remaining articles for eligibility.

RESULTS

A total of 81 articles met the eligibility criteria. Based on the levels of evidence and grades of recommendation assessed, it is worth considering the inclusion of plasma EBV DNA in screening, pre-treatment work-up for enhancing prognostication and tailoring of treatment strategy, monitoring during radical treatment, post-treatment surveillance for early detection of relapse, and monitoring during salvage treatment for recurrent or metastatic NPC. One major limitation is the methodology of measurement requiring harmonisation for consistent comparability.

CONCLUSIONS

The current comprehensive review supports the inclusion of plasma EBV DNA in international guidelines in the clinical aspects listed, but methodological issues must be resolved before global application.

Establishment of a Prognostic Nomogram for Patients With Locoregionally Advanced Nasopharyngeal Carcinoma Incorporating TNM Stage, Post-Induction Chemotherapy Tumor Volume and Epstein-Barr Virus DNA Load

Objectives

To establish and validate an effective nomogram to predict clinical outcomes for patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC).

Materials and Methods

The clinicopathological parameters and follow-up information of 402 locoregionally advanced NPC patients (training cohort, n = 302; validation cohort, n = 100) were retrospectively enrolled. The nomogram was built with the important prognostic variables identified by Cox regression analysis. Overall survival (OS) and progression-free survival (PFS) were the primary and secondary endpoints, respectively. The predictive power and clinical utility of the nomogram were assessed using the Harrell concordance index (C-index), calibration curve, and decision curve analysis. We compared the eighth staging system model with the nomogram to analyze whether the model could improve the accuracy of prognosis

Results

Epstein–Barr virus (EBV) DNA load, the gross tumor volume (GTVnx), and cervical lymph node tumor volume (GTVnd) after induction chemotherapy were the independent predictors of OS and PFS. The calibration curves indicated superb agreement between the nomogram-predicted probabilities and observed actual probabilities of survival. The C-index and area under the receiver operator characteristic curve (AUC) of the nomogram integrating these significant factors and N stage, and TNM stage were higher than those of the eighth TNM system alone. In addition, the decision curve analyses demonstrated the clinical value and higher overall net benefit of the nomogram. High-risk groups identified by the nomogram had significantly poorer OS and PFS than the low-risk group (p < 0.05).

Conclusions

The multidimensional nomogram incorporating TNM stage, EBV DNA load, and tumor volume after induction chemotherapy led to a more precise prognostic prediction and could be helpful for stratifying risk and guiding treatment decisions in locoregionally advanced NPC patients who have undergone induction chemotherapy and concurrent chemoradiation.

Human/eukaryotic ribosomal protein L14 (RPL14/eL14) overexpression represses proliferation, migration, invasion and EMT process in nasopharyngeal carcinoma

Although human/eukaryotic ribosomal protein L14 (RPL14/eL14) is known to be associated with a variety of cancers, its role in nasopharyngeal carcinoma (NPC) remains unclear. The aim of this study was to explore the impact of RPL14(eL14) in NPC. The results of quantitative real-time polymerase chain reaction (qRT-PCR), western blot, and immunohistochemical staining revealed that the expression of RPL14(eL14) significantly reduced in NPC tissues and cells. Furthermore, the protein expression of RPL14(eL14) was linked to NPC-related clinical pathological features, including the T and N classification of Tumor Node Metastasis (TNM) staging (all p < 0.05). Cell counting kit-8 (CCK-8) assay and colony formation assay revealed that RPL14(eL14) overexpression repressed NPC cell proliferation. In cell cycle assay, RPL14(eL14) overexpression significantly blocked NPC cells in S phase. Overexpression of RPL14(eL14) repressed cell migration and invasion in NPC as shown by transwell assay and cell scratch healing assay. In addition, RPL14(eL14) was closely correlated with the expression of epithelial–mesenchymal transition (EMT) biomarkers, including E-cadherin, N-cadherin, and vimentin as detected by western blot. In conclusion, our results revealed that RPL14(eL14) may be considered as an antioncogene in NPC, which greatly suppresses cancer progression.

Prognostic and Predictive Value of Circulating Inflammation Signature in Non-Metastatic Nasopharyngeal Carcinoma: Potential Role for Individualized Induction Chemotherapy

Purpose

We sought to assess the prognostic and predictive value of a circulating inflammation signature (CISIG) and develop CISIG-based tools for predicting prognosis and guiding individualized induction chemotherapy (ICT) in non-metastatic nasopharyngeal carcinoma (NPC).

Patients and Methods

We retrospectively collected a candidate inflammatory biomarker panel from patients with NPC treated with definitive radiotherapy between 2012 and 2017. We developed the CISIG using candidate biomarkers identified by a least absolute shrinkage and selection operator (LASSO) Cox regression model. The Cox regression analyses were used to evaluate the CISIG prognostic value. A CISIG-based prediction model was constructed, validated, and assessed. Potential stratified ICT treatment effects were examined.

Results

A total of 1149 patients were analyzed. Nine biomarkers selected by LASSO regression in the training cohort were used to construct the CISIG, including hyaluronidase, laminin, procollagen III, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, high-density lipoprotein, lactate dehydrogenase, and C-reactive protein-to-albumin ratio. CISIG was an independent prognostic factor for disease-free survival (DFS; hazard ratio: 2.65, 95% confidence interval: 1.93–3.64; P < 0.001). High CISIG group (>−0.2) was associated with worse 3-year DFS than low CISIG group in both the training (67.5% vs 88.3%, P < 0.001) and validation cohorts (72.3% vs 85.1%, P < 0.001). We constructed and validated a CISIG-based nomogram, which showed better performance than the clinical stage and Epstein–Barr virus DNA classification methods. A significant interaction between CISIG and the ICT treatment effect was observed (P for interaction = 0.036). Patients with high CISIG values did not benefit from ICT, whereas patients with low CISIG values significantly benefited from ICT.

Conclusion

The developed CISIG, based on a circulating inflammatory biomarker panel, adds prognostic information for patients with NPC. The proposed CISIG-based tools offer individualized risk estimation to facilitate suitable ICT candidate identification.

A novel prognostic model predicts overall survival in patients with nasopharyngeal carcinoma based on clinical features and blood biomarkers

This study aims to develop and validate a novel prognostic model to estimate overall survival (OS) in nasopharyngeal carcinoma (NPC) patients based on clinical features and blood biomarkers. We assessed the model's incremental value to the TNM staging system, clinical treatment, and Epstein‐Barr virus (EBV) DNA copy number for individual OS estimation. We retrospectively analyzed 519 consecutive patients with NPC. A prognostic model was generated using the Lasso regression model in the training cohort. Then we compared the predictive accuracy of the novel prognostic model with TNM staging, clinical treatment, and EBV DNA copy number using concordance index (C‐index), time‐dependent ROC (tdROC), and decision curve analysis (DCA). Subsequently, we built a nomogram for OS incorporating the prognostic model, TNM staging, and clinical treatment. Finally, we stratified patients into high‐risk and low‐risk groups according to the model risk score, and we analyzed the survival time of these two groups using Kaplan–Meier survival plots. All results were validated in the independent validation cohort. Using the Lasso regression, we established a prognostic model consisting of 13 variables with respect to patient prognosis. The C‐index, tdROC, and DCA showed that the prognostic model had good predictive accuracy and discriminatory power in the training cohort than did TNM staging, clinical treatment, and EBV DNA copy number. Nomogram consisting of the prognostic model, TNM staging, clinical treatment, and EBV DNA copy number showed some superior net benefit. Based on the model risk score, we split the patients into two subgroups: low‐risk (risk score ≤ −1.423) and high‐risk (risk score > −1.423). There were significant differences in OS between the two subgroups of patients. Similar results were observed in the validation cohort. The proposed novel prognostic model based on clinical features and serological markers may represent a promising tool for estimating OS in NPC patients.

Nomogram based on nutritional and inflammatory indicators for survival prediction of small cell carcinoma of the esophagus

OBJECTIVES

Small cell carcinoma of the esophagus (SCCE) is a rare type of esophageal cancer, and the parameters for prediction of SCCE outcome are unclear. This study aimed to construct a nomogram to predict the outcome of SCCE.

METHODS

Patients who underwent treatments at the Sun Yat-Sen University Cancer Center were recruited and divided randomly into training and validation cohorts (61 and 32 patients, respectively). A Cox regression analysis was utilized to identify independent prognostic factors to establish a nomogram and predict overall survival (OS) and disease-free survival (DFS).

RESULTS

Information on pretreatment nutritional candidate hemoglobin and inflammation-related neutrophil-to-lymphocyte ratio and platelet count were entered into the nomogram. In the training cohort, the concordance index of the nomogram for OS was 0.728, higher than that obtained by tumor/node/metastasis staging (0.614; P = 0.014). A significant difference was observed in the nomogram for DFS (0.668 vs tumor/node/metastasis stage: 0.616; P = 0.014). Similar results were found in the validation group. The decision curve analysis, net reclassification improvement, and integrated discrimination improvement showed moderate improvement of the nomogram in predicting survival. Based on the cut point calculated according to the constructed nomogram, the high-risk group had poorer OS and DFS than the low-risk group in both cohorts (all P < 0.05). Moreover, the DFS of patients receiving surgery in the high-risk group was better than that of patients receiving single radiation therapy or chemotherapy (P = 0.0111).

CONCLUSIONS

A nomogram based on nutrition- and inflammation-related indicators was developed to predict the survival of patients with SCCE.

Characteristics of Early Death in Patients With Localized Nasopharyngeal Cancer: A Population-Based SEER Analysis

Localized nasopharyngeal cancer (NPC) is a highly curable disease, but the prognosis of certain cases is still poor. Distinguishing patients with a poor outcome is necessary when developing therapeutic strategies. The aim of this study was to investigate the characteristics of early death (ED) among patients with localized NPC, and to identify independent predictors of ED. Patients diagnosed with localized NPC were included from the Surveillance, Epidemiology, and End Results dataset, and univariate and multivariate logistic regression analyses were performed to identify ED predictors. A total of 752 patients with localized NPC were enrolled, including 198 cases of ED and 480 long-term survivors. Older age, unmarried status, and white race were risk factors for ED, whereas diagnosis in the recent period and undifferentiated non-keratinizing histology type were protective factors. In addition, for older patients, women and those without radiation treatment, there was less ED for married patients than unmarried patients. In conclusion, this population-based study provides an overview of the characteristics of ED patients with localized NPC. Age, race, marital status, year of diagnosis and histology type are risk factors for ED. Moreover, married patients are at a significantly lower risk of ED. This protective effect is especially pronounced in older people, women and those without radiation treatment.

Comparison of Prognostic Value of Red Cell-Related Parameters of Biliary Tract Cancer After Surgical Resection and Integration of a Prognostic Nomogram: A Retrospective Study

INTRODUCTION

Biliary tract cancer (BTC) comprises infrequently occurring neoplasms with poor prognoses. Red blood cell-related parameters are commonly reported prognostic factors. We aimed to compare and evaluate the clinical value of red blood cell-related parameters and develop a prognostic nomogram.

METHODS

The analysis involved 418 patients with BTC who underwent surgery from December 2003 to April 2017. Patients were divided into training and validation cohorts. Red blood cell-related parameters were compared using Kaplan-Meier analysis, the area under receiver-operating characteristic curve (AUC), and C-index. Predictive abilities were evaluated using Cox regression. We developed a nomogram incorporating superior parameters verified using calibration curves, internal validation, and subgroup analysis. The nomogram was compared with the tumour-node-metastasis staging system through ROC, C-index, and Kaplan-Meier analysis.

RESULTS

A combined parameter comprising haemoglobin, albumin, lymphocytes, and platelets (HALP), which was superior to other red blood cell-related parameters, indicated a high risk of worse overall survival when low. Univariate analysis revealed that HALP together with other clinical characteristics was associated with overall survival. Multivariate analysis revealed that HALP, tumour-node-metastasis staging, and operative outcome were independent predictors of poor overall survival. Internal validation proved the predictive value of the nomogram. Additional statistical analyses established the advantages of the nomogram vs. tumour-node-metastasis staging.

CONCLUSION

HALP was a superior red blood cell-related parameter and an independent predictor of prognosis. Our nomogram based on HALP, tumour-node-metastasis staging, and operative outcome is a promising model for predicting overall survival.

Eugenol-piperine loaded polyhydroxy butyrate/polyethylene glycol nanocomposite-induced apoptosis and cell death in nasopharyngeal cancer (C666-1) cells through the inhibition of the PI3K/AKT/mTOR signaling pathway

Nasopharyngeal cancer is a malignancy developing from the nasopharynx epithelium due to smoking and nitrosamine-containing foods. Nasopharyngeal cancer is highly endemic to Southeast Asia. Eugenol and piperine have shown many anticancer activities on numerous cancer types, like colon, lung, liver, and breast cancer. In this study, we amalgamated eugenol and piperine loaded with a polyhydroxy butyrate/polyethylene glycol nanocomposite (Eu-Pi/PHB-PEG-NC) for better anticancer results against nasopharyngeal cancer (C666-1) cells. In the current study, nasopharyngeal cancer cell lines C666-1 were utilized to appraise the cytotoxic potential of Eug-Pip-PEG-NC on cell propagation, programmed cell death, and relocation. Eu-Pi/PHB-PEG-NC inhibits cellular proliferation on C666-1 cells in a dose-dependent manner, and when compared with 20 µg/ml, 15 µg/ml of loaded mixture evidently restrained the passage aptitude of C666-1 cells, this was attended with a downregulated expression of mitochondrial membrane potential. Treatment with 15 µg/ml Eu-Pi/PHB-PEG-NC suggestively amplified cell apoptosis in the C666-1 cells. Furthermore, its cleaved caspase-3, 8, and 9 and Bax gene expression was augmented and Bcl-2 gene expression was diminished after Eu-Pi/PHB-PEG-NC treatment. Additionally, our data established that the collective effect of Eu-Pi/PHB-PEG-NC loaded micelles inhibited the expansion of C666-1 cells augmented apoptosis connected with the intrusion of PI3K/Akt/mTOR signaling pathway.

Development and Validation of Prognostic Nomograms Based on Gross Tumor Volume and Cervical Nodal Volume for Nasopharyngeal Carcinoma Patients With Concurrent Chemoradiotherapy

PURPOSE

Our study aimed to establish and validate prognostic nomograms based on gross tumor volume (GTV) and cervical nodal volume (CNV) for nasopharyngeal carcinoma (NPC) patients treated with two cycles of concurrent chemoradiotherapy (CCRT).

METHODS

From 2012 to 2015, 620 eligible patients who received radical treatment at the Cancer Hospital of Shantou University Medical College were recruited for a nomogram study. Variables were determined in a training set of 463 patients from 2012 to 2014 by X-tile analysis, univariate and multivariate Cox proportional hazard analyses, and the least absolute shrinkage and selection operator (LASSO). Another cohort of 157 patients in 2015 was validated with bootstrap resampling. The concordance index (C-index) and calibration curves were applied to assess its predictive discriminative and accuracy ability, while decision curve analysis (DCA), X-tile analysis and Kaplan-Meier curve for clinical application.

RESULTS

Independent prognostic variables for overall survival (OS) were age, GTV, CNV, cranial nerve, positive cervical lymph node laterality below the caudal border of cricoid cartilage (LNBC), and were selected for the nomogram. Optimal prognostic factors including Karnofsky performance status (KPS), age, GTV, CNV, LNBC were incorporated in the nomogram for progression-free survival (PFS). In the training set, the C-index of our nomograms for OS and PFS were 0.755 (95% CI, 0.704 to 0.807) and 0.698 (95% CI, 0.652 to 0.744). The calibration curve showed good agreement between nomogram-predicted and actual survival. DCA indicated that our nomograms were of clinical benefit.

CONCLUSION

Our nomograms are capable of effective prognostic prediction for patients with NPC.

Pretreatment hemoglobin level as a predictor to evaluate the efficacy of immune checkpoint inhibitors in patients with advanced non-small cell lung cancer

Background:

Targeting immune checkpoints represents an immense breakthrough in cancer therapeutics. The prognostic value of hemoglobin (Hb) has been investigated in many malignancies including non-small cell lung cancer (NSCLC). However, the prognostic impact of pretreatment Hb count for immune checkpoint inhibitors (ICIs) in advanced NSCLC patients remains unclear.

Methods:

A total of 310 late-stage NSCLC patients who received ICI therapies between January 2015 and March 2019 were prospectively enrolled. We used a propensity score-matched cohort analysis for this study. Patients’ clinicopathological characteristics and pretreatment Hb concentration were assessed against the progression-free survival (PFS) and overall survival (OS) using the Kaplan–Meier method and Cox proportional hazards regression.

Results:

A propensity score (PS)-matched cohort analysis was applied to adjust for potential bias and to create two comparable groups according to patients’ clinicopathological characteristics. The patients with normal baseline Hb levels (⩾110 g/L) had significantly longer PFS [median: 10.0 versus 4.0 months, hazard ratio (HR): 0.63, 95% confidence interval (CI): 0.46−0.86; p = 0.001] and OS [median: 17.6 versus 10.5 months, HR (95% CI): 0.56 (0.40−0.79); p < 0.001] than those with decreased Hb count (<110 g/L) in a PS-matched cohort (n = 255). For patients with normal pretreatment Hb levels, ICI combination therapy was significantly associated with better PFS [median: 11.1 versus 8.0 months, HR (95% CI): 0.74 (0.50−1.06); p = 0.09] and OS [median: 26.0 versus 12.9 months, HR (95% CI): 0.56 (0.37−0.86); p = 0.008] than monotherapy, but there was no such trend for patients with decreased baseline Hb levels.

Conclusion:

Our findings showed that normal pretreatment Hb count served as a favorable prognostic marker in advanced NSCLC patients treated with ICIs, representing an economical biomarker with readily measuring performance among all reported ones.

Pretreatment Photopenia on 18F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography Scans Predicts Poor Prognosis in Nasopharyngeal Cancer Patients Undergoing Concurrent Chemoradiotherapy

OBJECTIVES

To investigate the influence of pretreatment primary tumor or nodal photopenia (PP) on 18F-fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET-CT), an indicator of tumor ischemia, on survival results of nasopharyngeal cancers (NPCs) treated with concurrent chemoradiotherapy (C-CRT).

METHODS

The pre-C-CRT FDG PET-CT scans of 104 patients with NPC (cT1-4 N0-3 M0) were retrospectively examined to determine the presence of PP (PP+). Our primary endpoint was the influence of PP+ on overall survival (OS), while the progression-free survival (PFS) and locoregional PFS (LRPFS) constituted the secondary endpoints.

RESULTS

The PP+ was detected in 29 (27.9%): nine (8.7%), seven (6.7%), and 13 (12.5%) in the primary tumor alone, primary tumor plus neck nodes, and neck nodes alone, respectively. Because the PP+ cases were small by count per location, all comparative analyses were performed according to overall PP+/ PP- status instead of per detected site. At a median follow-up of 67.8 months (range, 9 to 130 months), the median survival times were not reached (NR) for the entire population, while 5-year OS, LRPFS, and PFS rates were 73.3%, 68.2%, and 63.4%, respectively. Comparatively the PP+ patients exhibited significantly poorer median OS (49.8 months vs. NR, P<0.001), LRPFS (40.7 months vs. NR, P=0.001), and PFS (31.8 months vs. NR, P=0.002) durations than their PP- counterparts. Furthermore, the PP+ retained its independent prognostic significance in multivariate analysis (P<0.001).

CONCLUSION

Present results uncovered the pre-C-CRT PP as an independent predictor of poor prognosis for NPC patients, which underscore the requirement for the fortification of the local and systemic treatments in hypoxic NPCs.

The Acute Phase Reaction and Its Prognostic Impact in Patients with Head and Neck Squamous Cell Carcinoma: Single Biomarkers Including C-Reactive Protein Versus Biomarker Profiles

C-reactive protein (CRP) has a prognostic impact in head and neck squamous cell carcinoma (HNSCC). However, the acute phase reaction involves many other proteins depending on its inducing events, including various cytokines that can function as reaction inducers. In the present study, we compared the pretreatment acute phase cytokine profile for 144 patients with potentially curative HNSCC. We investigated the systemic levels of interleukin (IL)6 family mediators (glycoprotein (gp130), IL6 receptor (R)α, IL6, IL27, IL31, oncostatin M (OSM), ciliary neurotrophic factor (CNTF)), IL1 subfamily members (IL1R antagonist (A), IL33Rα), and tumor necrosis factor (TNF)α. Patient subsets identified from this 10-mediator profile did not differ with regard to disease stage, human papilloma virus (HPV) status, CRP levels, or death cause. Increased CRP, IL6, and IL1RA levels were independent markers for HNSCC-related death in the whole patient population. Furthermore, gp130, IL6Rα, and IL31 were suggested to predict prognosis among tumor HPV-negative patients. Only IL6 predicted survival in HPV-positive patients. Finally, we did a clustering analysis of HPV-negative patients based on six acute phase mediators that showed significant or borderline association with prognosis in Kaplan–Meier analyses; three subsets could then be identified, and they differed in survival (p < 0.001). To conclude, (i) HPV-negative and HPV-positive HNSCC patients show similar variations of their systemic acute phase profiles; (ii) the prognostic impact of single mediators differs between these two patient subsets; and (iii) for HPV-negative patients, acute phase profiling identifies three patient subsets that differ significantly in survival.

Construction of a nomogram to predict the prognosis of non-small-cell lung cancer with brain metastases

Patients with non-small-cell lung cancer (NSCLC) often have a poor prognosis when brain metastases (BM) occur. This study aimed to evaluate the prognostic factors of BM in newly diagnosed NSCLC patients and construct a nomogram to predict the overall survival (OS).We included NSCLC patients with BM newly diagnosed from 2010 to 2015 in Surveillance, Epidemiology, and End Results database. The independent prognostic factors for NSCLC with BM were determined by Cox proportional hazards regression analysis. We then constructed and validated a nomogram to predict the OS of NSCLC with BM.We finally included 4129 NSCLC patients with BM for analysis. Age, race, sex, liver metastasis, primary site, histologic type, grade, bone metastasis, T stage, N stage, surgery, chemotherapy, and lung metastasis were identified as the prognostic factors for NSCLC with BM and integrated to establish the nomogram. The calibration, receiver operating characteristic curve, and decision curve analyses also showed that the clinical prediction model performed satisfactorily in predicting prognosis.A clinical prediction model was constructed and validated to predict individual OS for NSCLC with BM. The establishment of this clinical prediction model has great significance for clinicians and individuals.

Squalene epoxidase-induced cholesteryl ester accumulation promotes nasopharyngeal carcinoma development by activating PI3K/AKT signaling

Nasopharyngeal carcinoma (NPC) is a common malignant tumor and a major cause of mortality and morbidity in southern China. However, the mechanism is still elusive. Here, we focused on studying the role of squalene epoxidase (SQLE), a key enzyme of cholesterol biosynthesis, in the progression of NPC. Clinical study revealed that SQLE expression was significantly upregulated in NPC tissues compared to normal tissues from mRNA level and patients with high expression of SQLE showed a poor prognosis. In vitro experiments showed that SQLE overexpression led to a significant proliferation of cells whereas SQLE knockdown showed an opposite result. In vivo studies also showed that SQLE promoted tumor growth in nude mice. Further study revealed that SQLE promoted NPC proliferation by cholesteryl ester accumulation instead of cholesterol. Mechanism studies indicated that cholesteryl ester promoted NPC cell proliferation by activating the PI3K/AKT pathway and inhibition of this pathway in SQLE-overexpressed or cholesteryl ester-treated cells resulted in a significant reduction of NPC cell proliferation. These results indicate that the oncogenic effect of SQLE in NPC mainly resulted from cholesteryl ester accumulation and PI3K/AKT is a promising target for NPC with SQLE overexpression.

Prognostic Nomogram for Patients with Radical Surgery for Non-Metastatic Colorectal Cancer Incorporating Hematological Biomarkers and Clinical Characteristics

BACKGROUND

There is a large difference in postoperative survival in patients with non-metastatic colorectal cancer. We aimed to develop nomograms incorporating both hematological biomarkers and clinical characteristics to predict overall survival (OS) in patients with radical surgery for non-metastatic colorectal cancer.

METHODS

A retrospective analysis was performed on date from 508 patients who underwent radical resection of colorectal cancer at the Affiliated Tumor Hospital of Guangxi Medical University from December 2011 to December 2015. Simple random sampling was performed by dividing these patients into a training set (n=355) and validation set(n=153), which yielded a 7:3 ratio in the sample sizes between these groups. Based on COX regression analysis of the results from the training cohort, a nomogram was developed to predict the three-year and five-year overall survival rate, and internal verification was also performed. The nomogram prediction accuracy and discriminating ability were evaluated by Harrell's C-index (C-index), calibration curves and were compared with the colorectal cancer TNM staging system.

RESULTS

We found that age, degree of differentiation, T stage, N stage, neurological invasion, neutrophils, monocytes, HGB, and LDH were independent risk factors for predicting OS in patients with colorectal cancer. In the training cohort, the C index was 0.796 (95% CI: 0.761-0.831). In the validation cohort, the C index was 0.671 (95% CI: 0.656-0.686).The nomogram showed a stronger predictive ability than did TNM staging. Decision curve analysis showed that the nomogram had value in terms of clinical application.

CONCLUSION

Our nomogram combined hematological biomarkers and clinical characteristics and was highly effective in predicting OS in patients with non-metastatic colorectal cancer. Hence, our nomogram may provide a reference tool for clinicians to guide individualized treatment and follow-ups for patients with colorectal cancer.

Prognostic nomogram integrated baseline serum lipids for patients with non-esophageal squamous cell carcinoma

Background

Serum lipids have been documented as prognostic biomarkers in several types of cancer, however the prognostic value of serum lipids in non-esophageal squamous cell carcinoma (non-ESCC) is not clear. The purpose of this study was to investigate the prognostic roles of serum lipids in non-ESCC and to establish a novel effective nomogram for overall survival (OS) and disease-free survival (DFS) in patients with non-ESCC.

Methods

We retrospectively analyzed the prognostic values of pretreatment serum lipids, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoproteinA-I (ApoAI), and apolipoprotein B (ApoB) and three lipid derivatives: atherogenic index [AI: (TC-HDL-C)/HDL-C], THR (TG/HDL-C) and LHR (LDL-C/HDL-C) in non-ESCC patients. Prognostic factors predictive of OS and DFS were determined by univariate and cox hazards analysis, and prognostic nomograms were established. The predictive power of independent prognostic factors was compared adopting time-dependent ROC. Comparisons between the nomograms and traditional TNM staging systems were evaluated using the C-index and decision curve analysis.

Results

A total of 180 non-ESCC patients were recruited in this prospective study between January 2006 and December 2016. Four (cancer type, TNM stage, TC, and TG) and five (cancer type, TNM stage, TC, TG, and LDL-C) independent prognostic factors were chosen to generate the nomogram for OS and DFS, respectively. Our results showed that the area under curves (AUCs) of cancer type and TG were higher than TNM stage for OS. For DFS, however, AUCs of cancer type, TG and LDL-C were higher than the TNM stage. The C-index of the nomogram for predicting the OS was 0.69, which was significantly higher than that of TNM stage (0.58, P=0.005). In addition, for DFS, the C-index of the nomogram was significantly higher than that of the TNM stage (0.70 vs. 0.60, P=0.001). Furthermore, decision curve analysis showed that the predictive accuracy of the prognostic nomogram for OS and DFS were both higher than the TNM stage.

Conclusions

Our study demonstrated that pretreatment of serum lipids based on the prognostic nomogram could be applied to predict the OS and DFS in non-ESCC patients.

Comparison between the seventh and eighth edition of the AJCC/UICC staging system for nasopharyngeal cancer integrated with pretreatment plasma Epstein–Barr virus DNA level in a non-Chinese population: secondary analysis from a prospective randomized trial

The eighth AJCC/UICC staging for nasopharyngeal cancer had higher prognostic values than the previous edition. Pretreatment plasma EBV DNA integrated into the next edition could further improve the outcome prediction.