Prognostic Nomogram for Patients with Nasopharyngeal Carcinoma after Intensity-Modulated Radiotherapy

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.

Intraductal papillary carcinoma of breast with invasion: A nomogram and survival from the analysis of the SEER database

BACKGROUND

Intraductal papillary carcinoma (IPC) with invasion is a rare type of breast cancer. There have been few studies on its prognosis, and a nomogram that predicts the prognosis of the disease has not been described to date.

METHODS

Patients who were diagnosed with invasive IPC were screened from the Surveillance, Epidemiology, and End Results (SEER) database. The screened patients were randomly divided into a training cohort and a verification cohort at 7:3. A Cox proportional hazard regression model was performed to analyze the effects of different variables on the risk of death in invasive IPC. A nomogram was constructed to quantify the possibility of death. The concordance index (C-index), calibration plots, receiver operating characteristic (ROC) curves, and decision curves analysis (DCA) were used to verify the proposed model.

RESULTS

We included a total of 803 patients diagnosed with invasive IPC, including 563 patients in the training cohort and 240 patients in the validation cohort. The median follow-up times in the training cohort and validation cohort were 63 months (range, 2-155 months) and 61 months (range, 1-154 months), respectively. For all patients, the probability of death with invasive IPC was 1.4% within 5 years and 5.4% within 10 years. In multivariate analysis, sex, race, tumor size, lymph node status, type of treatment, and chemotherapy were related to the prognosis of invasive IPC. We constructed a nomogram to predict the possibility of death in patients with invasive IPC.

CONCLUSION

Patients with invasive IPC had a high survival rate. The proven nomogram was helpful to both patients and clinical decision makers.

A Radiomics Nomogram for Non-Invasive Prediction of Progression-Free Survival in Esophageal Squamous Cell Carcinoma

To construct a prognostic model for preoperative prediction on computed tomography (CT) images of esophageal squamous cell carcinoma (ESCC), we created radiomics signature with high throughput radiomics features extracted from CT images of 272 patients (204 in training and 68 in validation cohort). Multivariable logistic regression was applied to build the radiomics signature and the predictive nomogram model, which was composed of radiomics signature, traditional TNM stage, and clinical features. A total of 21 radiomics features were selected from 954 to build a radiomics signature which was significantly associated with progression-free survival (p &lt; 0.001). The area under the curve of performance was 0.878 (95% CI: 0.831–0.924) for the training cohort and 0.857 (95% CI: 0.767–0.947) for the validation cohort. The radscore of signatures' combination showed significant discrimination for survival status. Radiomics nomogram combined radscore with TNM staging and showed considerable improvement over TNM staging alone in the training cohort (C-index, 0.770 vs. 0.603; p &lt; 0.05), and it is the same with clinical data (C-index, 0.792 vs. 0.680; p &lt; 0.05), which were confirmed in the validation cohort. Decision curve analysis showed that the model would receive a benefit when the threshold probability was between 0 and 0.9. Collectively, multiparametric CT-based radiomics nomograms provided improved prognostic ability in ESCC.

The prognostic significance of race in nasopharyngeal carcinoma by histological subtype

BACKGROUND

Race has been shown to have variable prognostic importance in nasopharyngeal carcinoma (NPC). However, previous studies are limited by a lack of comprehensive treatment, epidemiologic, and comorbidity data.

METHODS

This was a retrospective cohort study utilizing the National Cancer Database from 2004 to 2016. Multivariable Cox proportional hazards regressions were used to calculate adjusted hazard ratios (aHR) for overall survival.

RESULTS

A cohort of 9995 patients met inclusion and exclusion criteria. Race, insurance, comorbidity, treatment, stage, age, and histology were independent prognosticators. Among patients with keratinizing NPC, Asians and Hispanics had superior survival (aHR 0.58 [95% confidence interval (CI) 0.48-0.69], aHR 0.76 [95% CI 0.61-0.96]) compared to white patients. Among patients with non-keratinizing differentiated NPC, Asians and black patients had improved survival (aHR 0.71 [95% CI 0.56-0.91], aHR 0.72 [95% CI 0.54-0.95]) compared to white patients. Race was not prognostic in non-keratinizing undifferentiated NPC.

CONCLUSION

The prognostic significance of race varies across histological subtypes of NPC.

A Model Combining Skeletal Muscle Mass and a Hematological Biomarker to Predict Survival in Patients With Nasopharyngeal Carcinoma Undergoing Concurrent Chemoradiotherapy

Background

Using the current tumor lymph node metastasis (TNM) staging system to make treatment decisions and predict survival in patients with nasopharyngeal carcinoma (NPC) lacks sufficient accuracy. Patients at the same stage often have different survival prognoses.

Methods

In the current study 802 NPC patients who underwent concurrent radiotherapy and chemotherapy from January 2010 to December 2014 at Sun Yat-sen University Cancer Center in China were retrospectively assessed. The optimal cut-off points for skeletal muscle index (SMI) and monocyte-to-lymphocyte ratio (MLR) were determined via receiver operating characteristic curves. SMI-MLR (S-M) grade and a nomogram were developed and used as clinical indicators in NPC patients. The consistency index (C-index) and a calibration curve were used to measure the accuracy and discriminative capacity of prediction.

Results

The predictive performance of S-M grade was better than that of TNM staging (C-index 0.639, range 0.578–0.701 vs. 0.605, range 0.545–0.665; p = 0.037). In multivariate analysis S-M grade, T stage, and N stage were independent prognostic factors. These three factors were then combined, yielding a nomogram with a C-index of 0.71 (range 0.64–0.77), indicating good predictive capacity.

Conclusion

We developed and validated a prognostic parameter, S-M grade, which increased prediction accuracy significantly and can be combined with TNM staging to predict survival in patients with NPC undergoing concurrent chemoradiotherapy.

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.

Loss of AKR1C1 is a good prognostic factor in advanced NPC cases and increases chemosensitivity to cisplatin in NPC cells

Cisplatin resistance is one of the main obstacles in the treatment of advanced nasopharyngeal carcinoma (NPC). AKR1C1 is a member of the Aldo-keto reductase superfamily (AKRs), which converts aldehydes and ketones to their corresponding alcohols and has been reported to be involved in chemotherapeutic resistance of multiple drugs. The expression and function of AKR1C1 in NPC have not been reported until now. The aim of this research was to investigate the expression of AKR1C1 and it is role in cisplatin resistance in NPC. AKR1C1 protein expression was detected by immunohistochemistry in human NPC tissues and by Western blot assays in NPC and immortalized nasopharyngeal epithelial cells. The effects of AKR1C1 knock-down by siRNA on proliferation, migration and invasion in NPC cells were evaluated by CCK8, wound healing and transwell assays. To evaluate the effects of AKR1C1 silencing on cisplatin sensitivity in NPC cells, CCK8 assays were used to detect cell proliferation, flow cytometry was used to detect cell cycle distribution, and flow cytometry and DAPI staining were used to detect cell apoptosis. AKR1C1 down-regulation was associated with advanced clinicopathological characters such as larger tumor size, more lymphatic nodes involvement, with metastasis and later clinical stages, while AKR1C1 down-regulation was a good prognostic factor for overall survival (OS) in NPC patients. In vitro study showed that AKR1C1 was not directly involved in the malignant biological behaviours such as proliferation, cell cycle progression and migration of NPC cells, whereas AKR1C1 knock-down could enhance cisplatin sensitivity of NPC cells. These results suggest that AKR1C1 is a potential marker for predicting cisplatin response and could serve as a molecular target to increase cisplatin sensitivity in NPC.

Machine Learning Analysis of Image Data Based on Detailed MR Image Reports for Nasopharyngeal Carcinoma Prognosis

We aimed to assess the use of automatic machine learning (AutoML) algorithm based on magnetic resonance (MR) image data to assign prediction scores to patients with nasopharyngeal carcinoma (NPC). We also aimed to develop a 4-group classification system for NPC, superior to the current clinical staging system. Between January 2010 and January 2013, 792 patients with recent diagnosis of NPC, who had MR image data, were enrolled in the study. The AutoML algorithm was used and all statistical analyses were based on the 10-fold test. Primary endpoints included the probabilities of overall survival (OS), distant metastasis-free survival (DMFS), and local-region relapse-free survival (LRFS), and their sum was recorded as the final voting score, representative of progression-free survival (PFS) for each patient. The area under the receiver operating characteristic (ROC) curve generated from the MR image data-based model compared with the tumor, node, and metastasis (TNM) system-based model was 0.796 (P=0.008) for OS, 0.752 (P=0.053) for DMFS, and 0.721 (P=0.025) for LRFS. The Kaplan-Meier (KM) test values for II/I, III/II, IV/III groups in our new machine learning-based scoring system were 0.011, 0.010, and <0.001, respectively, whereas those for II/I, III/II, IV/III groups in the TNM/American Joint Committee on Cancer (AJCC) system were 0.118, 0.121, and <0.001, respectively. Significant differences were observed in the new machine learning-based scoring system analysis of each curve (P < 0.05), whereas the P values of curves obtained from the TNM/AJCC system, between II/I and III/II, were 0.118 and 0.121, respectively, without a significant difference. In conclusion, the AutoML algorithm demonstrated better prognostic performance than the TNM/AJCC system for NPC. The algorithm showed a good potential for clinical application and may aid in improving counseling and facilitate the personalized management of patients with NPC. The clinical application of our new scoring and staging system may significantly improve precision medicine.

Prognostic Nomogram For Locoregionally Advanced Nasopharyngeal Carcinoma

The TNM staging system of NPC is the most important model for survival prediction. However, this model does not consider the biological variability of the tumor itself. This study aimed to develop a nomogram for predicting the overall survival of loco-regionally advanced nasopharyngeal carcinoma. 487 Patients with confimed nasopharyngeal carcinoma who underwent IMRT and chemotherapy were included in this study. We established prognostic nomogram for overall survival (OS) based on the Cox proportional hazards model. The predictive accuracy and discriminative ability were measured using the concordance index (C-index) and calibration curve. Nomogram was validated externally by assessing discrimination and calibration using an independent data set. Continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to analyze whether nomogram improve the prediction of survival than TNM stage system. Recursive partitioning analysis (RPA) was performed to stratifying risk of patients. Age, T-stage, N-stage, NLR, LDH were included in the nomogram for OS. The C-index of the nomogram for OS were 0.726 (95% CI, 0.690 to 0.762); The calibration curve showed the nomogram was able to predict 5-year OS accurately. The nomogram had a higher C-index than the TNM stage system (0.726 VS 0.632, P-value < 0.001). The NRI was 0.235 (95% CI: 0.129 to 0.396, P < 0.001), the IDI was 0.079 (95% CI: 0.034 to 0.396, p < 0.001). RPA was performed to stratify patients into three risk group, OS was significantly different between all three risk groups. High risk groups can be benefited survival from adjuvant chemotherapy. The nomogram outperformed the TNM staging system in predicting the OS of loco-regionally advanced nasopharyngeal carcinoma underwent intensity modulated radiation therapy and chemotherapy.

Development and validation of a nomogram for predicting long-term overall survival in nasopharyngeal carcinoma: A population-based study

We aimed to develop a nomogram based on a population-based cohort to estimate the individualized overall survival (OS) for patients with nasopharyngeal carcinoma (NPC) and compare its predictive value with that of the traditional staging system.Data for 3693 patients with NPC were extracted from the Surveillance, Epidemiology, and End Results dataset and randomly divided into two sets: training (n = 2585) and validation (n = 1108). On the basis of multivariate Cox regression analysis, a nomogram was constructed to predict the 3-, 5-, and 10-year survival probability for a patient. The performance of the nomogram was quantified with respect to discrimination, calibration, and clinical utility.In the training set, age, sex, race, marital status, histological type, T stage, N stage, M stage, radiotherapy, and chemotherapy were selected to develop a nomogram for predicting the OS probability based on the multivariate Cox regression model. The nomogram was generally more discriminative compared with the American Joint Committee on Cancer 7th staging system. Calibration plots exhibited an excellent consistency between the observed probability and the nomogram's prediction. Categorical net classification improvement and integrated discrimination improvement suggested that the predictive accuracy of the nomogram exceeded that of the classic staging system. With respect to decision curve analyses, the nomogram exhibited preferable net benefit gains than the staging system across a wide range of threshold probabilities.This proposed nomogram exhibits an excellent performance with regard to its predictive accuracy, discrimination capability, and clinical utility, and thus can be used as a convenient and reliable tool for prognosis prediction in patients with NPC.

Contrast-enhanced Ultrasound in evaluating of angiogenesis and tumor staging of nasopharyngeal carcinoma in nude mice

OBJECTIVE

To explore the use of Contrast-enhanced Ultrasound (CEUS) in evaluating angiogenesis in a xenograft nasopharyngeal carcinoma (NPC) model in nude mice and the evolution of CEUS parameters according to the growth of NPC.

METHODS

Nude mice were divided into three groups according to experiments conducted at various times from tumor implantation (8 mice/group; group A: 4 weeks from implantation; group B:6 weeks from implantation; group C:8 weeks from implantation). CNE-2 cells were transplanted in 24 nude mice and CEUS evaluations of the tumors were performed at 4, 6 or 8 weeks from implantation. CEUS parametric perfusion images and pathological findings were recorded. R version 3.4.4 software was used to analyze the CEUS parameters and pathological findings.

RESULTS

One-way anova analysis indicated statistically significant differences among the three groups with the parameters of peak intensity (PI) (p<0.001), area wash in (AWI) (p<0.001), area wash out (AWO) (p<0.001) and tumor volumes (p<0.001).Pearson correlation coefficient analysis indicated that microvessel density (MVD) was correlated with tumor volume (r = 0.644, p = 0.001), PI (r = 0.904, p<0.0001), AWI (r = 0.547, p = 0.008) and AWO (r = 0.744, P<0.0001). Tumor volume was correlated with MVD (r = 0.644, p = 0.001), PI (r = 0.625, p = 0.002), AWI (r = 0.528, p = 0.012) and AWO (r = 0.784, p<0.001). The percentage of necrosis in histological sections was correlated with the percentage of CEUS unperfused area (r = 0.446,p = 0.038). Spearman rank correlation coefficient analysis indicated that vascular endothelial growth factor (VEGF) was correlated with PI (r = 0.462, P = 0.032). Welch t test indicated PI, AWI and AWO parameters were significantly lower than that of kidneys (p<0.001, p = 0.009, p = 0.005).

CONCLUSIONS

The CEUS parameters PI, AWI and AWO indirectly reflect the MVD and the tumor volume in our model of subcutaneous transplanted NPC in nude mice, providing precious information on angiogenesis and tumor growth. VEGF may play a role in promoting angiogenesis of NPC.

Third Epidemiological Analysis of Nasopharyngeal Carcinoma in the Central Region of Japan from 2006 to 2015

The present study aimed to clarify the incidence and clinical outcomes of nasopharyngeal carcinoma (NPC) in the Chubu region of Japan from 2006 to 2015, compared with previous reports. A retrospective analysis was conducted based on medical records from 40 hospitals located in the Chubu region in the central Japanese main island, with a population of around 22.66 million individuals. This study was designed in line with to two previous clinical studies into NPC conducted in the same area of Japan. We recruited NPC patients diagnosed in hospitals across this area over a 10-year period (2006–2015) using a questionnaire about sex, age, primary site, clinical symptoms, pathology, Union for International Cancer Control (UICC) staging, serological exam, treatment, and survival. A total of 620 NPC patients were identified. The age-standardized incidence of NPC from 2006 to 2015 was 0.27 per 100,000 individuals per year. There were no significant differences between this study and the previous two studies conducted in the same area of Japan. The five-year overall survival rate for all patients was 75.9%, while those for patients with stages I, II, III, and IVA were 97%, 91%, 79%, and 68%, respectively. The age-standardized annual incidence of NPC in the present study was 0.27 per 100,000 individuals per year, which was relatively low and stable. The five-year overall survival rate for all NPC patients was significantly improved in this decade compared with previous studies. The smoking rates in male and female NPC patients were 64.5% and 18.8%, respectively, thereby suggesting the involvement of smoking in the incidence of NPC.

Personalized prognostication in head and neck cancer: A systematic review of nomograms according to the AJCC precision medicine core (PMC) criteria

BACKGROUND

The American Joint Committee on Cancer (AJCC) Precision Medicine Core (PMC) has recognized the need for more personalized probabilistic predictions above the "TNM" staging system and has recently released a checklist of inclusion and exclusion criteria for evaluating prognostic models.

METHODS

A systematic review of articles in which nomograms were created for head and neck cancer (HNC) was carried out according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The AJCC PMC criteria were used to score the individual studies.

RESULTS

Forty-four studies were included in the final qualitative analysis. The mean number of inclusion criteria met was 9.3 out of 13, and the mean number of exclusion criteria met was 2.1 out of 3. Studies were generally of high quality, but no single study fulfilled all of the AJCC PMC criteria.

CONCLUSION

This is the first study to utilize the AJCC checklist to comprehensively evaluate the published prognostic nomograms in HNC. Future studies should attempt to adhere to the AJCC PMC criteria. Recommendations for future research are given.

SUMMARY

The AJCC recently released a set of criteria to grade the quality of prognostic cancer models. In this study, we grade all published nomograms for head and neck cancer according to the new guidelines.

A nomogram for predicting the risk of neck node metastasis in pathologically node-negative oral cavity carcinoma

OBJECTIVE

To generate a nomogram for predicting the risk of neck node metastasis in pathologically node-negative patients using a combination of variables comprising of protein expression, ultrastructural alterations and clinicopathological parameters.

MATERIALS AND METHODS

Surgically removed oral tumours (n = 103) were analysed for the expression of desmosomal and hemidesmosomal assembly proteins by immunohistochemistry and ultrastructural alterations by transmission electron microscopy (TEM). Protein expression, ultrastructural alterations and clinicopathological variables were used to construct nomogram from the training set in 75 patients. Clinical utility of the nomogram was validated in a discrete set of 28 patients.

RESULTS

Univariate and multivariate analyses were performed on the training set, and obtained significant variables comprising of integrin β4 expression (p = .027), number of hemidesmosomes (p = .027)/desmosomes (p = .046), tumour differentiation grade (p = .033) and tumour thickness (p = .024) were used for construction of the nomogram. The area under the curve was calculated for both training 0.821 (95% CI 0.725-0.918) and validation sets 0.880 (95% CI 0.743-1.000). The nomogram demonstrated a predictive accuracy of 73.3% and 78.6% with the sensitivity of 81.4% and 83.3% in the training and validation sets, respectively.

CONCLUSIONS

The nomogram constructed on postsurgical tumour samples will be a value addition to histopathology for the detection of neck node metastasis in pathologically node-negative patients.

Prognostic nomogram for refining the prognostication of the proposed 8th edition of the AJCC/UICC staging system for nasopharyngeal cancer in the era of intensity-modulated radiotherapy

BACKGROUND

The objective of this study was to develop a nomogram for refining prognostication for patients with nondisseminated nasopharyngeal cancer (NPC) staged with the proposed 8th edition of the American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) staging system.

METHODS

Consecutive patients who had been investigated with magnetic resonance imaging, staged with the proposed 8th edition of the AJCC/UICC staging system, and irradiated with intensity-modulated radiotherapy from June 2005 to December 2010 were analyzed. A cohort of 1197 patients treated at Fujian Provincial Cancer Hospital was used as the training set, and the results were validated with 412 patients from Pamela Youde Nethersole Eastern Hospital. Cox regression analyses were performed to identify significant prognostic factors for developing a nomogram to predict overall survival (OS). The discriminative ability was assessed with the concordance index (c-index). A recursive partitioning algorithm was applied to the survival scores of the combined set to categorize the patients into 3 risk groups.

RESULTS

A multivariate analysis showed that age, gross primary tumor volume, and lactate dehydrogenase were independent prognostic factors for OS in addition to the stage group. The OS nomogram based on all these factors had a statistically higher bias-corrected c-index than prognostication based on the stage group alone (0.712 vs 0.622, P <.01). These results were consistent for both the training cohort and the validation cohort. Patients with <135 points were categorized as low-risk, patients with 135 to <160 points were categorized as intermediate-risk, and patients with ≥160 points were categorized as high-risk. Their 5-year OS rates were 92%, 84%, and 58%, respectively.

CONCLUSIONS

The proposed nomogram could improve prognostication in comparison with the TNM stage group. This could aid in risk stratification for individual NPC patients. Cancer 2016;122:3307-3315. © 2016 American Cancer Society.