Dataset Information

Nomograms Forecasting Long-Term Overall and Cancer Specific Survival of Patients With Head and Neck Neuroendocrine Carcinoma.

ABSTRACT:

Background

The purpose of this retrospective analysis was to build and validate nomograms to predict the cancer-specific survival (CSS) and overall survival (OS) of head and neck neuroendocrine carcinoma (HNNEC) patients.

Methods

A total of 493 HNNEC patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015, and 74 HNNEC patients were collected from the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital (HCH) between 2008 and 2020. Patients from SEER were randomly assigned into training (N=345) and internal validation (N=148) groups, and the independent data group (N=74) from HCH was used for external validation. Independent prognostic factors were collected using an input method in a Cox regression model, and they were then included in nomograms to predict 3-, 5-, and 10-year CSS and OS rates of HNNEC patients. Finally, we evaluated the internal and external validity of the nomograms using the consistency index, while assessing their prediction accuracy using calibration curves. A receiver operating curve (ROC) was also used to measure the performance of the survival models.

Results

The 3-, 5-, and 10-year nomograms of this analysis demonstrated that M classification had the largest influence on CSS and OS of HNNEC, followed by the AJCC stage, N stage, age at diagnosis, sex/gender, radiation therapy, and marital status. The training validation C-indexes for the CSS and OS models were 0.739 and 0.713, respectively. Those for the internal validation group were 0.726 and 0.703, respectively, and for the external validation group were 0.765 and 0.709, respectively. The area under the ROC curve (AUC) of 3-, 5-, and 10-year CSS and OS models were 0.81, 0.82, 0.82, and 0.78, 0.81, and 0.82, respectively. The C-indexes were all higher than 0.7, indicating the high accuracy ability of our model's survival prediction.

Conclusions

In this study, prognosis nomograms in HNNEC patients were constructed to predict CSS and OS for the first time. Clinicians can identify patients' survival risk better and help patients understand their survival prognosis for the next 3, 5, and 10 years more clearly by using these nomograms.

SUBMITTER: Yan O

PROVIDER: S-EPMC7917297 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Nomograms Forecasting Long-Term Overall and Cancer Specific Survival of Patients With Head and Neck Neuroendocrine Carcinoma.

Yan Ouying O Xie Wenji W Teng Haibo H Fu Shengnan S Chen Yanzhu Y Liu Feng F

Frontiers in oncology 20210215

<h4>Background</h4>The purpose of this retrospective analysis was to build and validate nomograms to predict the cancer-specific survival (CSS) and overall survival (OS) of head and neck neuroendocrine carcinoma (HNNEC) patients.<h4>Methods</h4>A total of 493 HNNEC patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015, and 74 HNNEC patients were collected from the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South U ...[more]

PMID: 33659217

Similar Datasets

Project description:ImportanceData are limited on the prognostic value of human papillomavirus (HPV) status for head and neck carcinoma subsites.ObjectiveTo determine whether HPV positivity at each head and neck subsite is associated with improved overall survival.Design, setting, and participantsThis retrospective population-based cohort study used the National Cancer Database to identify patients diagnosed with head and neck squamous cell carcinomas from January 1, 2010, to December 31, 2014. Patients were classified according to the location of their primary malignancy into 1 of the 6 main subsites of the upper aerodigestive tract: oral cavity, oropharynx, nasopharynx, hypopharynx, larynx, and sinonasal tract. Patients were also classified by their HPV status. Data collection for this study took place from January 1, 2010, to December 31, 2014. Data analysis was conducted from August 1, 2017, to September 30, 2017.Main outcomes and measuresThe difference in 5-year overall survival between patients with HPV-positive status and those with HPV-negative status in various head and neck carcinoma subsites; the role of HPV status in an unadjusted Cox multivariate regression model.ResultsOf the 175 223 total number of patients identified (129 634 [74.0%] male; 45 589 [26.0%] female; mean [SD] age, 63.1 [11.9] years), 133 273 (76.1%) were ineligible and 41 950 (23.9%) were included in the sample. This sample included 16 644 patients (39.7%) with HPV-positive tumors and 25 306 (60.3%) with HPV-negative tumors. Patients with an HPV-positive status were more likely to be younger, be white, be male, present with local T category tumors, and have poor differentiation on histologic examination. HPV-positive status was associated with survival at 4 tumor subsites: oral cavity (hazard ratio [HR], 0.76; 95% CI, 0.66-0.87), oropharynx (HR, 0.44; 95% CI, 0.41-0.47), hypopharynx (HR, 0.59; 95% CI, 0.45-0.77), and larynx (HR, 0.71; 95% CI, 0.59-0.85). The HPV status was the greatest factor in survival outcome between the HPV-positive and -negative cohorts at the oropharynx subsite (77.6% vs 50.7%; survival difference, 26.9%; 95% CI, 25.6%-28.2%) and hypopharynx subsites (52.2% vs 28.8%; survival difference, 23.4%; 95% CI, 17.5%-29.3%). For the nasopharynx (HR, 1.03; 95% CI, 0.75-1.42) and sinonasal tract (HR, 0.63; 95% CI, 0.39-1.01) subsites, HPV-positive status was not an independent prognostic factor.Conclusions and relevanceHuman papillomavirus positivity was associated with improved survival in 4 subsites (oropharynx, hypopharynx, oral cavity, and larynx), and the largest survival difference was noted in the oropharynx and hypopharynx subsites. In the nasopharynx and sinonasal tract subsites, HPV positivity had no association with overall survival. Given these results, routine testing for HPV at the oropharynx, hypopharynx, oral cavity, and larynx subsites may be warranted.

Project description:BackgroundEstimated life expectancy is one of the most important factors in determining treatment options for prostate cancer (PCa) patients. However, clinicians have few effective prognostic tools to individually assess survival in patients with PCa.MethodsWe screened 283,252 patients diagnosed with PCa from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015, and randomly divided them into the training and validation groups. We used univariate and multivariate Cox analyses to identify independent prognostic factors and further established nomograms to predict 1-, 3-, 5-, and 10-year overall survival (OS) and cancer-specific survival (CSS) for PCa patients. The prediction performance of nomograms was tested and externally validated by Concordance index (C-index) and receiver operating characteristic (ROC) curve. Calibration curve and decision curve analysis (DCA) were used for internal validation. We further developed PCa prognostic scoring system based on the impact of available variables on survival.ResultsThe variables age, race, marital status, TNM stage, surgery method, radiotherapy, chemotherapy, PSA value, and Gleason score identified as independent prognostic factors were included in the survival nomograms. The results of training (C-index: OS = 0.776, CSS = 0.889; AUC value: OS = 0.772-0.802, CSS = 0.892-0.936) and external validation (C-index: OS = 0.759, CSS = 0.875) indicated our nomograms had good performance in predicting 1-, 3-, 5-, and 10-year OS and CSS prediction. Internal validation using the calibration curves and DCA curves demonstrated the effectiveness of the prediction models. The prognostic scoring system was more effective than the AJCC staging system in predicting the survival of PCa patients, especially for OS.ConclusionThe prognostic nomograms and prognostic scoring system have favorable performance in predicting OS and CSS of PCa patients. These individualized survival prediction tools may contribute to clinical decisions.

Project description:BackgroundFew studies have focused on the prognosis of patients with hepatocellular carcinoma (HCC) of Barcelona Clinic Liver Cancer (BCLC) stage 0‒C in terms of early recurrence and 5-years overall survival (OS). We sought to develop nomograms for predicting 5-year OS and early recurrence after curative resection of HCC, based on a clinicopathological‒radiological model. We also investigated whether different treatment methods influenced the OS of patients with early recurrence.MethodsRetrospective data, including clinical pathology, radiology, and follow-up data, were collected for 494 patients with HCC who underwent hepatectomy. Nomograms estimating OS and early recurrence were constructed using multivariate Cox regression analysis, based on the random survival forest (RSF) model. We evaluated the discrimination and calibration abilities of the nomograms using concordance indices (C-index), calibration curves, and Kaplan‒Meier curves. OS curves of different treatments for patients who had recurrence within 2 years after curative surgery were depicted and compared using the Kaplan-Meier method and the log-rank test.ResultsMultivariate Cox regression revealed that BCLC stage, non-smooth margin, maximum tumor diameter, age, aspartate aminotransferase levels, microvascular invasion, and differentiation were prognostic factors for OS and were incorporated into the nomogram with good predictive performance in the training (C-index: 0.787) and testing cohorts (C-index: 0.711). A nomogram for recurrence-free survival was also developed based on four prognostic factors (BCLC stage, non-smooth margin, maximum tumor diameter, and microvascular invasion) with good predictive performance in the training (C-index: 0.717) and testing cohorts (C-index: 0.701). In comparison to the BCLC staging system, the C-index (training cohort: 0.787 vs. 0.678, 0.717 vs. 0.675; external cohort 2: 0.748 vs. 0.624, 0.729 vs. 0.587 respectively, for OS and RFS; external cohort1:0.716 vs. 0.627 for RFS, all p value<0.05), and model calibration curves all showed improved performance. Patients who underwent surgery after tumor recurrence had a higher reOS than those who underwent comprehensive treatments and supportive care.ConclusionsThe nomogram, based on clinical, pathological, and radiological factors, demonstrated good accuracy in estimating OS and recurrence, which can guide follow-up and treatment of individual patients. Reoperation may be the best option for patients with recurrence in good condition.

Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is a common malignancy that emanates from the lips, mouth, paranasal sinuses, oropharynx, larynx, nasopharynx, and from other pharyngeal cancers. The availability of high-throughput expression data has made it possible to use global gene expression data to analyze the relationship between metabolic-related gene expression and clinical outcomes in HNSCC patients.MethodIn this study, we used RNA sequencing (RNA-seq) data from the cancer genome atlas (TCGA), with validation in the GEO dataset to profile the metabolic microenvironment and define potential biomarkers for metabolic therapy.ResultsWe extracted data for 529 patients and 327 metabolic genes (198 upregulated and 129 downregulated genes) in the TCGA database. Carbonic anhydrase 9 (CA9) and CA6 had the largest logFCs in the upregulated and downregulated genes, respectively. Our Cox regression model data showed 51 prognostic-related genes with lysocardiolipin acyltransferase 1 (LCLAT1) and choline dehydrogenase (CHDH) being associated with the highest risk (HR = 1.144, 95% CI = 1.044 ~ 1.251) and the lowest risk (HR = 0.580, 95% CI = 0.400 ~ 0.839) in HNSCC, respectively. We next used the ROC curve to evaluate whether the differentially expressed metabolic-related genes could serve as early predictors of HNSCC. The findings showed an AUC of 0.745 and 0.618 in the TCGA and GEO analysis, respectively. Besides, the ability for the genes to predict clinicopathological HNSCC status was analyzed and the data showed that the AUC for age, gender, grade, stage, T, M, and N was 0.520, 0.495, 0.568, 0.606, 0.577, 0.476, and 0.673, respectively, in the TCGA dataset. On the other hand, the AUC for age, gender, stage, T, M, N, smoking, and HPV16-pos was 0.599, 0.531, 0.622, 0.606, 0.616, 0.550, 0.614, 0.519, and 0.397, respectively, in the GEO dataset.ConclusionTaken together, our study unearths a novel metabolic gene signature for the prediction of HNSCC prognosis based on the TCGA dataset. Our signature might point out the metabolic microenvironment disorders and provides potential treatment targets and prognostic biomarkers.

Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is a common cancer characterized by late diagnosis and poor prognosis. The aim of this study was to identify a novel ferroptosis-related DNA methylation signature as an alternative diagnosis index for patients with HNSCC.MethodsMethylome and transcriptome data of 499 HNSCC patients, including 275 oral squamous cell carcinoma (OSCC) samples, were obtained from The Cancer Genome Atlas (TCGA). An additional independent methylation dataset of 50 OSCC patients from the NCBI Gene Expression Omnibus (GEO) database was used for validation. As an index of ferroptosis activity, the ferroptosis score (FS) of each patient was inferred from the transcriptome data using single-sample gene set enrichment analysis. Univariate, multivariate, and LASSO Cox regression analyses were used to select CpG sites for the construction of a ferroptosis-related DNA methylation signature for diagnosis of patients.ResultsWe initially inferred the FS of each TCGA HNSCC patient and divided the samples into high- and low-FS subgroups. Results showed that the high-FS subgroup displayed poor overall survival. Moreover, 378 differentially methylated CpG sites (DMCs) were identified between the two HNSCC subgroups, with 16 selected to construct a 16-DNA methylation signature for risk prediction in HNSCC patients using the LASSO and multivariate Cox regression models. Relative operating characteristic (ROC) curve analysis showed great predictive efficiency for 1-, 3-, and 5-year HNSCC survival using the 16-DNA methylation signature. Its predictive efficiency was also observed in OSCC patients from the TCGA and GEO databases. In addition, we found that the signature was associated with the fractions of immune types in the tumor immune microenvironment (TIME), suggesting potential interactions between ferroptosis and TIME in HNSCC progression.ConclusionsWe established a novel ferroptosis-related 16-DNA methylation signature that could be applied as an alternative tool to predict prognosis outcome in patients with HNSCC, including OSCC.

Dataset Information

Nomograms Forecasting Long-Term Overall and Cancer Specific Survival of Patients With Head and Neck Neuroendocrine Carcinoma.

Background

Methods

Results

Conclusions

Publications

Nomograms Forecasting Long-Term Overall and Cancer Specific Survival of Patients With Head and Neck Neuroendocrine Carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets