Nomogram Based on Inflammatory Biomarkers and Nutritional Indicators for Predicting Overall Survival in Locoregionally Advanced Nasopharyngeal Carcinoma

Effect of Preoperative Serum Lactate Dehydrogenase-to-Albumin Ratio on the Survival of Oral Cancer: A Retrospective Study

Background

Several studies have investigated the relationship between serum lactate dehydrogenase-to-albumin ratio (LAR) and the prognosis of cancers. However, no studies have explored the association between serum LAR and the survival of oral cancer (OC). This study was aimed to determine the association of serum LAR with the overall survival (OS) of OC.

Methods

One hundred and ninety patients with OC were included in this study between January 2018 and December 2019. Log rank test and Kaplan-Meier method were used to compare the survival rate of OC between the low LAR group and the high LAR group. The association between serum LAR and the survival of OC patients was determined via univariate and multivariate Cox regression analyses.

Results

Kaplan-Meier analysis and Log rank test indicated that the OS rate in low LAR group was significantly higher than that in high LAR group (P < 0.05). Univariate cox analysis showed that TNM III-IV stage, serum LDH > 162 U/L, and serum LAR > 3.79 were significantly associated with the OS of OC patients. Multivariate Cox analysis suggested that the TNM III-IV stage (HR, 2.317; 95% CI, 1.423-3.774, P = 0.001) and serum LAR > 3.79 (HR, 5.138; 95% CI, 2.245-11.756, P = 0.000) were independently related with poor OS of OC patients.

Conclusion

High serum LAR (>3.79) is an independent predictor of adverse prognosis in OC patients. LAR could be used as a promising marker for predicting the OS of OC patients.

A novel nomogram integrated with preablation stimulated thyroglobulin and thyroglobulin/thyroid-stimulating hormone ratio to predict the therapeutic response of intermediate‑ and high‑risk differentiated thyroid cancer patients: a bi-center retrospective study

PURPOSE

To investigate the factors influencing the outcome of radioactive iodine (RAI) treatment in intermediate- to high-risk patients with differentiated thyroid carcinoma (DTC).

METHODS

We enrolled 553 DTC patients who underwent total thyroidectomy and categorized them into two groups according to their response to RAI therapy: excellent response (ER) and non-ER groups. Clinical and pathological characteristics of the patients were collected and retrospectively analyzed using univariate and multivariate binary logistic regression. Receiver operating characteristic (ROC) curves and diagnostic cutoff values were analyzed to assess the predictive value of important quantitative influences on 131I treatment outcomes. A new nomogram model was developed based on the above independent risk factors. R software was used to develop nomograms with all the independent prognostic factors included.

RESULTS

The multivariate analysis showed that lymph node metastasis (LNM), stimulated thyroglobulin (sTg), thyroglobulin antibodies (TgAb), and sTg/thyroid-stimulating hormone (TSH) were significantly associated with non-ER of DTC patients. In the training set, the consistency index (C-index) of the new column line graph was 0.868 (95% CI 0.865-0.871).

CONCLUSION

We proposed a new nomogram to predict non-ER for DTC with excellent discrimination and calibration.

A nomogram based on nutritional and inflammatory parameters to predict DMFS and identify beneficiaries of adjuvant chemotherapy in IVA-stage nasopharyngeal carcinoma

OBJECTIVE

This study aims to develop a nomogram integrating inflammation (NLR), Prognostic Nutritional Index (PNI), and EBV DNA (tumor burden) to achieve personalized treatment and prediction for stage IVA NPC. Furthermore, it endeavors to pinpoint specific subgroups that may derive significant benefits from S-1 adjuvant chemotherapy.

METHODS

A total of 834 patients diagnosed with stage IVA NPC were enrolled in this study and randomly allocated into training and validation cohorts. Multivariate Cox analyses were conducted to identify independent prognostic factors for constructing the nomogram. The predictive and clinical utility of the nomogram was assessed through measures including the AUC, calibration curve, DCA, and C-indexes. IPTW was employed to balance baseline characteristics across the population. Kaplan-Meier analysis and log-rank tests were utilized to evaluate the prognostic value.

RESULTS

In our study, we examined the clinical features of 557 individuals from the training cohort and 277 from the validation cohort. The median follow-up period was 50.1 and 49.7 months, respectively. For the overall cohort, the median follow-up duration was 53.8 months. The training and validation sets showed 3-year OS rates of 87.7% and 82.5%, respectively. Meanwhile, the 3-year DMFS rates were 95.9% and 84.3%, respectively. We created a nomogram that combined PNI, NRI, and EBV DNA, resulting in high prediction accuracy. Risk stratification demonstrated substantial variations in DMFS and OS between the high and low risk groups. Patients in the high-risk group benefited significantly from the IC + CCRT + S-1 treatment. In contrast, IC + CCRT demonstrated non-inferior 3-year DMFS and OS compared to IC + CCRT + S-1 in the low-risk population, indicating the possibility of reducing treatment intensity.

CONCLUSIONS

In conclusion, our nomogram integrating NLR, PNI, and EBV DNA offers precise prognostication for stage IVA NPC. S-1 adjuvant chemotherapy provides notable benefits for high-risk patients, while treatment intensity reduction may be feasible for low-risk individuals.

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.

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.

Nomograms based on the lymphocyte-albumin-neutrophil ratio (LANR) for predicting the prognosis of nasopharyngeal carcinoma patients after definitive radiotherapy

Much evidence has accumulated to show that inflammation and nutritional status are associated with the prognosis of patients with various cancers. The present study was designed to explore the prognostic role of the LANR in NPC patients receiving definitive radiotherapy and to construct a nomogram for predicting patient survival. This study retrospectively reviewed 805 NPC patients (604 in the training cohort and 201 in the validation cohort) who received definitive radiotherapy between January 2013 and December 2019. The clinical data and pretreatment laboratory test data, including lymphocyte count, neutrophil count, and serum ALB concentration, were collected for all patients. The LANR was calculated as the albumin × lymphocyte/neutrophil ratio. Patients in the training cohort and validation cohort were categorized into high-LANR and low-LANR groups according to the corresponding cutoff values. The independent prognostic factors for overall survival (OS), progression-free survival (PFS), relapse-free survival (RFS), and metastasis-free survival (MFS) were evaluated by univariate and multivariate Cox regression analyses, and a nomogram was subsequently constructed. The performance of the nomogram was evaluated by the concordance index (C-index) and calibration curve. A low LANR (< 14.3) was independently associated with worse OS, PFS and MFS in NPC patients. A prognostic prediction nomogram was established based on T stage, N stage, Eastern Cooperative Oncology Group (ECOG) score, treatment modality, and LANR and was validated. The C-indices of the nomograms for OS and PFS in the training cohort were 0.729 and 0.72, respectively. The C-indices of the nomograms for OS and PFS in the validation cohort were 0.694 and 0.695, respectively. The calibration curve revealed good consistency between the actual survival and the nomogram prediction. Patients with NPC with low pretreatment LANR had a poor prognosis. The nomogram established on the basis of the LANR was efficient and clinically useful for predicting survival in NPC patients who underwent definitive radiotherapy.

Risk stratification of stage II rectal mucinous adenocarcinoma to predict the benefit of adjuvant chemotherapy following neoadjuvant chemoradiation and surgery

Background

The treatment strategy for stage II rectal mucinous adenocarcinoma (RMA) recommends neoadjuvant chemoradiotherapy (NCR) followed by total mesorectal excision (TME). However, the necessity of adjuvant chemotherapy (AC) remains controversial.

Materials and methods

Chi-square test was used to assess the relationship between pathological classification, AC and clinicopathological characteristics. Kaplan-Meier (KM) curves and the log-rank test were utilized to analyze differences in overall survival (OS) and cancer-specific survival (CSS) among different groups. Cox regression identified prognostic factors. Nomogram was established utilizing the independent prognostic factors. X-tile divided patients into three risk subgroups.

Results

Compared to RMA, rectal adenocarcinoma (RA) demonstrates longer OS and CSS in all and non-AC stage II patients, with no difference in OS and CSS for AC stage II patients. Propensity score matching analyses yielded similar results. Stratified analysis found that AC both improve OS of RA and RMA patients. Age, gender, pathologic T stage, regional nodes examined, and tumor size were identified as independent prognostic factors for RMA patients without AC. A nomogram was constructed to generate risk scores and categorize RMA patients into three subgroups based on these scores. KM curves revealed AC benefits for moderate and high-risk groups but not for the low-risk group. The external validation cohort yielded similar results.

Conclusions

In summary, our study suggests that, compared to stage II RA patients, stage II RMA patients benefit more from AC after NCR. AC is recommended for moderate and high-risk stage II RMA patients after NCR, whereas low-risk patients do not require AC.

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.

Nomograms containing body dose parameters for predicting survival in patients with nasopharyngeal carcinoma

PURPOSE

To assess the impact of body dose on survival outcomes in nasopharyngeal carcinoma (NPC) patients and to create novel nomograms incorporating body dose parameters for predicting survival.

METHODS

594 of non-metastasis NPC patients (training group, 396; validation group, 198) received intensity-modulated radiation therapy at our institution from January 2012 to December 2016. Patient characteristics, body dose parameters in dose-volume histogram (DVH) and hematology profiles were collected for predicting overall survival (OS) and progression-free survival (PFS). Nomograms for OS and PFS were developed using the selected predictors. Each nomogram was evaluated based on its C-index and calibration curve.

RESULTS

Body dose-based risk score for OS (RSOS), N stage, age, and induction chemotherapy were independent predictors for OS, with a C-index of 0.784 (95% CI 0.749-0.819) in the training group and 0.763 (95% CI 0.715-0.810) in the validation group for the nomogram. As for PFS, the most important predictors were the body dose-based risk score for PFS (RSPFS), N stage, and induction chemotherapy. C-index of PFS nomogram was 0.706 (95% CI 0.681-0.720) in the training group and 0.691 (95% CI 0.662-0.711) in the validation group. The two models outperformed the TNM staging system in predicting outcomes.

CONCLUSIONS

Body dose coverage is a useful predictor of prognosis in clinical routine patients. The novel nomograms integrating body dose parameters can precisely predict OS and PFS in NPC patients.

Radiomics-clinical nomogram based on pretreatment 18F-FDG PET-CT radiomics features for individualized prediction of local failure in nasopharyngeal carcinoma

To explore the prognostic significance of PET/CT-based radiomics signatures and clinical features for local recurrence-free survival (LRFS) in nasopharyngeal carcinoma (NPC). We retrospectively reviewed 726 patients who underwent pretreatment PET/CT at our center. Least absolute shrinkage and selection operator (LASSO) regression and the Cox proportional hazards model were applied to construct Rad-score, which represented the radiomics features of PET-CT images. Univariate and multivariate analyses were used to establish a nomogram model. The concordance index (C-index) and calibration curve were used to evaluate the predictive accuracy and discriminative ability. Receiver operating characteristic analysis was performed to stratify the local recurrence risk of patients. The nomogram was validated by evaluating its discrimination ability and calibration in the validation cohort. A total of eight features were selected to construct Rad-score. A radiomics-clinical nomogram was built after the selection of univariate and multivariable Cox regression analyses, including the Rad-score and maximum standardized uptake value (SUVmax). The C-index was 0.71 (0.67-0.74) in the training cohort and 0.70 (0.64-0.76) in the validation cohort. The nomogram also performed far better than the 8th T-staging system with an area under the receiver operating characteristic curve (AUC) of 0.75 vs. 0.60 for 2 years and 0.71 vs. 0.60 for 3 years. The calibration curves show that the nomogram indicated accurate predictions. Decision curve analysis (DCA) revealed significantly better net benefits with this nomogram model. The log-rank test results revealed a distinct difference in prognosis between the two risk groups. The PET/CT-based radiomics nomogram showed good performance in predicting LRFS and showed potential to identify patients at high-risk of developing NPC.

Developing a nomogram model and prognostic analysis of nasopharyngeal squamous cell carcinoma patients: a population-based study

BACKGROUND

Nasopharyngeal squamous cell carcinoma (NPSCC) is a common histo-logical subtype of nasopharyngeal cancer with a generally poor prognosis. The aim of this study is to identify factors affecting the survival prognosis of NPSCC patients and develop a specialized nomogram model.

METHODS

We extracted clinical data of 1235 diagnosed cases of NPSCC from the SEER database using SEER*Stat software. Univariate and multivariate Cox proportional hazards regression analyses were conducted to explore clinical factors that impact the prognosis of NPSCC patients. Based on significant independent factors, we developed a nomogram to predict the 1, 3, and 5 years overall survival rates. The discriminative and predictive abilities of the nomogram were evaluated using C-index, calibration curve, area under the curve (AUC), and receiver operating characteristic curve. We evaluated the clinical value of the nomogram using decision curve analysis (DCA) and clinical impact curve (CIC).

RESULTS

We performed a cohort analysis on 846 patients with nasopharyngeal cancer in the training cohort. Multivariate Cox regression analysis revealed age, race, marital status, primary tumor, radiation therapy, chemotherapy, SJCC stage, primary tumor size, Lung metastasis and brain metastasis as independent prognostic factors for NPSCC patients, which we used to construct the nomogram prediction model. The C-index of the training cohort was 0.737. The ROC curve analysis indicated that the AUC of the OS rate at 1, 3, and 5 years in the training cohort was > 0.75. The calibration curves of the two cohorts showed good consistency between the predicted and observed results. DCA and CIC demonstrated that the nomogram prediction model had good clinical benefits.

CONCLUSIONS

The nomogram risk prediction model for NPSCC patient survival prognosis, constructed in this study, has exhibited excellent predictive capability. This model can be employed for swift and precise assessment of individualized survival prognosis. It can offer valuable guidance to clinical physicians in diagnosing and treating NPSCC patients.

Development of Prognostic Nomogram Based on Lipid Metabolic Markers and Lactate Dehydrogenase in Non-Metastatic Nasopharyngeal Carcinoma

Purpose

To establish and verify a comprehensive prognostic nomogram for predicting survival outcomes and improving the prognosis for non-metastatic nasopharyngeal carcinoma (NPC).

Patients and Methods

Our retrospective study screened 613 cases of non-metastatic NPC who received radiotherapy from July 2012 to December 2016. A reliable nomogram was formulated for predicting overall survival (OS) and progression-free survival (PFS) using all independent predictors selected by Cox regression analysis. A comparison is conducted between the current staging and the predictive performance of the nomogram. Internal validation was performed in a single center using the validation cohort to assess predictive accuracy and discrimination.

Results

High-density lipoprotein cholesterol, Epstein-Barr virus DNA and lactate dehydrogenase were determined to be valuable predictive indicators for predicting OS and PFS. Triglycerides were a valuable predictive indicator for predicting OS. Calibration curves demonstrated that the nomogram had remarkable correspondence between the prediction outcomes and the actual observations. Receiver operating characteristic curves showed that the nomogram had greater area under the curve and more satisfactory discrimination capability than the current TNM staging. Decision curve analysis revealed that the nomogram had high net clinical benefits. Significant differences were observed when low- and high-risk groups were stratified via Kaplan-Meier curves.

Conclusion

Our proposed nomogram combining lipid metabolic markers and lactate dehydrogenase could assist clinicians in the accurate prognostic prediction of non-metastatic NPC patients and provide personalized treatment recommendations.

A promising predictive biomarker combined EBV NDA with PNI for nasopharyngeal carcinoma in nonendemic area of China

In endemic areas, EBV DNA is used to guide diagnosis, detect recurrence and distant metastasis of NPC. Until now, the importance of EBV DNA in the prediction of NPC has received little attention in non-endemic regions. To explore the prognostic value of EBV DNA alone or in combination with PNI in NPC patients from a non-endemic area of China. In this retrospective study, 493 NPC patients were enrolled. Clinical pathologic data, pre-treatment plasma EBV DNA, and laboratory tests were all performed. A standard anticancer treatment was prescribed, and follow up data were collected. EBV DNA was found to be positively related to clinical stage (r = 0.357, P < 0.001), T stage (r = 0.193, P < 0.001), N stage (r = 0.281, P < 0.001), and M stage (r = 0.215, P < 0.001). The difference in EBV DNA loads between clinical stage, T, N and M stage was statistically significant (P < 0.001). In this study, the best cutoff value for EBV-DNA to distinguish the prognosis of NPC was 262.7 copies/ml. The 5-year OS of patients in the EBV-DNA ≤ 262.7 copies/ml group and EBV-DNA > 262.7 copies/ml group was 88% and 65.3%, respectively (P < 0.001). EBV-DNA and PNI were found to be independent prognostic factors for OS in multivariate analysis (P < 0.05). EBV-DNA was independent prognostic factors for PFS. In predicting NPC patients OS, the novel combination marker of EBV DNA and PNI outperformed TNM staging (AUC: 0.709 vs. 0.675). In addition, the difference between EBV + PNI and EBV + TNM was not statistically significant for OS or PFS (P > 0.05). This novel combination biomarker was a promising biomarker for predicting NPC survival and may one day guide treatment option.

An overall survival predictive nomogram to identify high-risk patients among locoregionally advanced nasopharyngeal carcinoma: Developed based on the SEER database and validated institutionally

Objective

Locoregionally advanced nasopharyngeal carcinoma (LA-NPC) patients, even at the same stage, have different prognoses. We aim to construct a prognostic nomogram for predicting the overall survival (OS) to identify the high-risk LA-NPC patients.

Materials and methods

Histologically diagnosed WHO type II and type III LA-NPC patients in the Surveillance, Epidemiology, and End Results (SEER) database were enrolled as the training cohort (n= 421), and LA-NPC patients from Shantou University Medical College Cancer Hospital (SUMCCH) served as the external validation cohort (n= 763). Variables were determined in the training cohort through Cox regression to form a prognostic OS nomogram, which was verified in the validation cohort, and compared with traditional clinical staging using the concordance index (C-index), Kaplan–Meier curves, calibration curves and decision curve analysis (DCA). Patients with scores higher than the specific cut-off value determined by the nomogram were defined as high-risk patients. Subgroup analyses and high-risk group determinants were explored.

Results

Our nomogram had a higher C-index than the traditional clinical staging method (0.67 vs. 0.60, p&lt;0.001). Good agreement between the nomogram-predicted and actual survival were shown in the calibration curves and DCA, indicating a clinical benefit of the nomogram. High-risk patients identified by our nomogram had worse prognosis than the other groups, with a 5-year overall survival (OS) of 60.4%. Elderly patients at advanced stage and without chemotherapy had a tendency for high risk than the other patients.

Conclusions

Our OS predictive nomogram for LA-NPC patients is reliable to identify high-risk patients.

The prognostic nutritional index represents a novel inflammation-nutrition-based prognostic factor for nasopharyngeal carcinoma

Purpose

This study explored the relationship between the prognostic nutritional index (PNI) and overall survival rate (OS) in patients with nasopharyngeal carcinoma (NPC), and established and validated an effective nomogram to predict clinical outcomes.

Methods

This study included 618 patients newly diagnosed with locoregionally advanced NPC. They were divided into training and validation cohorts at a ratio of 2:1 based on random numbers. The primary endpoint of this study was OS, progression-free survival (PFS) was the second endpoint. A nomogram was drawn from the results of multivariate analyses. Harrell's concordance index (C-index), area under the receiver operator characteristic curve (AUC), and decision curve analysis (DCA) were used to evaluate the clinical usefulness and predictive ability of the nomogram and were compared to the current 8th edition of the International Union Against Cancer/American Joint Committee (UICC/AJCC) staging system.

Results

The PNI cutoff value was 48.1. Univariate analysis revealed that age (p < 0.001), T stage (p < 0.001), N stage (p = 0.036), tumor stage (p < 0.001), PNI (p = 0.001), lymphocyte-neutrophil ratio (NLR, p = 0.002), and lactate dehydrogenase (LDH, p = 0.009) were significantly associated with OS, age (p = 0.001), T-stage (p < 0.001), tumor stage (p < 0.001), N-stage (p = 0.011), PNI (p = 0.003), NLR (p = 0.051), and LDH (p = 0.03) were significantly associated with PFS. Multivariate analysis showed that age (p < 0.001), T-stage (p < 0.001), N-stage(p = 0.02), LDH (p = 0.032), and PNI (p = 0.006) were significantly associated with OS, age (p = 0.004), T-stage (<0.001), N-stage (<0.001), PNI (p = 0.022) were significantly associated with PFS. The C-index of the nomogram was 0.702 (95% confidence interval [CI]: 0.653-0.751). The Akaike information criterion (AIC) value of the nomogram for OS was 1142.538. The C-index of the TNM staging system was 0.647 (95% CI, 0.594-0.70) and the AIC was 1163.698. The C-index, DCA, and AUC of the nomogram demonstrated its clinical value and higher overall net benefit compared to the 8th edition of the TNM staging system.

Conclusion

The PNI represents a new inflammation-nutrition-based prognostic factor for patients with NPC. In the proposed nomogram, PNI and LDH were present, which led to a more accurate prognostic prediction than the current staging system for patients with NPC.

Utilizing the Lactate Dehydrogenase-to-Albumin Ratio for Survival Prediction in Patients with Bladder Cancer After Radical Cystectomy

Purpose

Previous studies have suggested that the preoperative lactate dehydrogenase-to-albumin ratio (LAR) is correlated with survival in several cancers except bladder cancer (BCa). This study aimed to determine the prognostic value of the LAR in patients with urothelial carcinoma of the bladder (UCB) after radical cystectomy (RC).

Patients and Methods

A total of 595 UCB patients with RC in West China Hospital from December 2010 to May 2020 were enrolled. A receiver operating characteristic (ROC) curve was used to determine the optimal cutoff value of the LAR. Kaplan-Meier curves and Cox regression analyses were applied to evaluate the association of the LAR with overall survival (OS) and recurrence-free survival. Independent factors in multivariate analyses were selected to construct nomograms. Calibration curves, ROC curves, concordance index (C-index) and decision curve analyses were used to evaluate the performance of the nomograms.

Results

The optimal cutoff value of the LAR was determined to be 3.8. Preoperative low LAR was associated with decreased OS (P < 0.001) and RFS (P < 0.001), especially in patients with ≥ pT2 disease. LAR was an independent factor for OS (hazard ratio [HR]: 1.719; P <0.001) and RFS (HR: 1.429; P = 0.012). The addition of the LAR into nomograms could result in better prediction performance. The areas under the curves of the nomograms were 0.821 and 0.801 for the prediction of 3-year OS and RFS, respectively. The C-indexes of the nomograms were 0.760 and 0.741 for the prediction of OS and RFS, respectively.

Conclusion

The preoperative LAR is a novel and reliable independent prognostic biomarker for survival in UCB after RC.

Development and validation of a risk prediction model for overall survival in patients with nasopharyngeal carcinoma: a prospective cohort study in China

Objective

Nasopharyngeal carcinoma (NPC) is prevailing in Southern China, characterized by distinct geographical distribution. Aimed to predict the overall survival (OS) of patients with nasopharyngeal carcinoma, this study developed and validated nomograms considering demographic variables, hematological biomarkers, and oncogenic pathogens in China.

Methods

The clinicopathological and follow-up data of the nasopharyngeal carcinoma patients obtained from a prospective longitudinal cohort study in the Chongqing University Cancer Hospital between Jan 1, 2017 and Dec 31, 2019 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{n}=1635$$\end{document}n=1635). Cox regression model was used to tested the significance of all available variables as prognostic factors of OS. And independent prognostic factors were identified based on multivariable analysis to model nomogram. Concordance index (C-index), area under the receiver operating characteristic (AUC), calibration curve, and decision curve analysis (DCA) were measured to assess the model performance of nomogram.

Results

Data was randomly divided into a training cohort (1227 observers, about 70% of data) and a validation group (408 observers, about 30% of data). At multivariable analysis, the following were independent predictors of OS in NPC patients and entered into the nomogram: age (hazard ratio [HR]: 1.03), stage (stage IV vs. stage I–II, HR: 4.54), radiotherapy (Yes vs. No, HR: 0.43), EBV (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\ge 1000$$\end{document}≥1000 vs.\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<1000$$\end{document}<1000, HR: 1.92), LAR (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$>6.15$$\end{document}>6.15 vs.\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\le 6.15$$\end{document}≤6.15, HR: 2.05), NLR (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$>4.84$$\end{document}>4.84 vs. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\le 4.84$$\end{document}≤4.84 HR: 1.54), and PLR (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$>206.33$$\end{document}>206.33 vs.\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\le 206.33$$\end{document}≤206.33, HR: 1.79). The C-indexes for training cohort at 1-, 3- and 5-year were 0.73, 0.83, 0.80, respectively, in the validation cohort, the C-indexes were 0.74 (95% CI 0.63–0.86), 0.80 (95% CI 0.73–0.87), and 0.77 (95% CI 0.67–0.86), respectively. The calibration curve demonstrated that favorable agreement between the predictions of the nomograms and the actual observations in the training and validation cohorts. In addition, the decision curve analysis proved that the nomogram model had the highest overall net benefit.

Conclusion

A new prognostic model to predict OS of patients with NPC was developed. This can offer clinicians treatment making and patient counseling. Furthermore, the nomogram was deployed into a website server for use.