scholarly journals A Population-Based Systematic Clinical Analysis With a Single-Center Case Series of Patients With Pulmonary Large Cell Neuroendocrine Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Xu Sun ◽  
Yijun Wu ◽  
Jing Shen ◽  
Chang Han ◽  
Kai Kang ◽  
...  
Keyword(s):  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Case Series ◽  
Large Cell ◽  
Mortality Rates ◽  
Population Based ◽  
Large Cell Neuroendocrine Carcinoma ◽  
Rank Test ◽  
Seer Database ◽  
Incidence And Mortality

Background and ObjectivesThis study aims to conduct an updated systematic analysis of patients with pulmonary large cell neuroendocrine carcinoma (PLCNC) in recent decades, concerning incidence and mortality trends, demographics, treatments, survival and death causes.MethodsPatients who were diagnosed with PLCNC at the Peking Union Medical College Hospital (PUMCH) between 2000 to 2020 were retrospectively analyzed. The population-based Surveillance, Epidemiology, and End Results (SEER) database were also retrieved. Frequencies and average annual age-adjusted rates (AAR) of PLCNC patients were calculated and analyzed by Joint-point regression. Univariate and multivariate Cox regression were used for identifying prognostic factors. Predictive nomograms for overall survival (OS) and cancer-specific survival (CSS) were developed and then validated by calculating C-index values and drawing calibration curves. Survival curves were plotted using the Kaplan-Meier method and compared by log-rank test. Causes of death were also analyzed by time latency.ResultsA total of 56 PLCNC patients of the PUMCH cohort were included. Additionally, the PLCNC patients in the SEER database were also identified from different subsets. The AAR from 2001 to 2017 were 3.21 (95%CI: 3.12-3.30) per million. Its incidence and mortality rates in PLCNC patients increased at first but seemed to decline in recent years. Besides TNM stage and treatments, older age and male gender were independently associated with poorer survival, while marital status only affected CSS other than OS. The nomograms for OS and CSS presented great predictive ability and calibration performance. Surgery gave significantly more survival benefits to PLCNC patients, and chemotherapy might add survival benefits to stage II-IV. However, radiation therapy seemed to only improve stage III patients’ survival.ConclusionsThis study supported some previous studies in terms of incidence, survival, and treatment options. The mortality rates seemed to decline recently, after an earlier increase. Among PLCNC patients, most of the deaths occurred within the first five years, while other non-PLCNC diseases increased after that. Thus, careful management and follow-up of other comorbidities are of equal importance. Our study may partly solve the dilemma caused by PLCNC’s rarity and inspire more insights in future researches.

scholarly journals Construction of a nomogram to predict overall survival for patients with lung large cell neuroendocrine carcinoma: analysis of the SEER database

2020 ◽  
Author(s):  
Dong Han ◽  
Fei Gao ◽  
Nan Li ◽  
Hao Wang ◽  
Qi Fu
Keyword(s):  
Overall Survival ◽  
Survival Rate ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Risk Group ◽  
Multivariable Analysis ◽  
Large Cell ◽  
Large Cell Neuroendocrine Carcinoma ◽  
Seer Database ◽  
Cox Regression Analysis

Abstract Background Lung large cell neuroendocrine carcinoma (L-LCNEC) has a poor prognosis with lower survival rate than other NSCLC patients. The estimation of an individual survival rate is puzzling. The main purpose of this study was to establish a more accurate model to predict the prognosis of L-LCNEC.Methods Patients aged 18 years or older with L-LCNEC were identified from the Surveillance, Epidemiology and End Results (SEER) database from 2004 to 2015. Cox regression analysis was used to identify factors associated with survival time. The results were used to construct a nomogram to predict 1-year, and 3-year survival probability in L-LCNEC patients. Overall survival (OS) were compared between low risk group and high risk group by the Kaplan–Meier analysis.Results A total of 3216 patients were included in the study. We randomly divided all included patients into 7:3 training and validating groups. In multivariable analysis of training cohort, age at diagnosis, sex, stage of tumor, surgical treatment, radiotherapy and chemotherapy were independent prognostic factors for OS. All these factors were incorporated to construct a nomogram, which was tested in the validating cohort.Conclusions we constructed a visual nomogram prognosis model, which had the potential to predict the 1-year and 3-year survival rate of L-LCNEC patients, and could be used as an assistant prediction tool in clinical practice.

scholarly journals Construction of a Nomogram to Predict Overall Survival for Patients With Lung Large Cell Neuroendocrine Carcinoma: Analysis of the SEER Database

2021 ◽  
Author(s):  
Dong Han ◽  
Fei Gao ◽  
Nan Li ◽  
Hao Wang ◽  
Qi Fu
Keyword(s):  
Overall Survival ◽  
Survival Rate ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Risk Group ◽  
Multivariable Analysis ◽  
Large Cell ◽  
Large Cell Neuroendocrine Carcinoma ◽  
Seer Database ◽  
Cox Regression Analysis

Abstract Background: Lung large cell neuroendocrine carcinoma (L-LCNEC) has a poor prognosis with lower survival rate than other NSCLC patients. The estimation of an individual survival rate is puzzling. The main purpose of this study was to establish a more accurate model to predict the prognosis of L-LCNEC. Methods: Patients aged 18 years or older with L-LCNEC were identified from the Surveillance, Epidemiology and End Results (SEER) database from 2004 to 2015. Cox regression analysis was used to identify factors associated with survival time. The results were used to construct a nomogram to predict 1-year, and 3-year survival probability in L-LCNEC patients. Overall survival (OS) were compared between low risk group and high risk group by the Kaplan–Meier analysis. Results: A total of 3216 patients were included in the study. We randomly divided all included patients into 7:3 training and validating groups. In multivariable analysis of training cohort, age at diagnosis, sex, stage of tumor, surgical treatment, radiotherapy and chemotherapy were independent prognostic factors for OS. All these factors were incorporated to construct a nomogram, which was tested in the validating cohort.Conclusions: we constructed a visual nomogram prognosis model, which had the potential to predict the 1-year and 3-year survival rate of L-LCNEC patients, and could be used as an assistant prediction tool in clinical practice.

scholarly journals CDX2 Expression and Prognostic Factors of Resectable Pulmonary Large Cell Neuroendocrine Carcinoma

2020 ◽  
Vol 14 ◽  
pp. 117955492096731
Author(s):  
Ryo Mori ◽  
Shin-ichi Yamashita ◽  
Kensuke Midorikawa ◽  
Sosei Abe ◽  
Kazuo Inada ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Adjuvant Chemotherapy ◽  
Prognostic Factor ◽  
Neuroendocrine Carcinoma ◽  
Vascular Invasion ◽  
Cox Regression ◽  
Large Cell ◽  
Large Cell Neuroendocrine Carcinoma ◽  
Clinicopathological Factors ◽  
Cdx2 Expression

Background and Aim: Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rare neoplasm, and its clinical features and management are still limited. We evaluated the clinicopathological factors, including CDX2 immunohistochemical expression, to predict survival in patients with LCNEC. Patients and Methods: In all, 50 patients with LCNEC who underwent surgery at 4 institutes between 2001 and 2017 were included. Clinicopathological characteristics were evaluated for prognostic factors and statistically analyzed by Kaplan-Meier curve with a log-rank test or Cox regression models. We used immunohistochemical (IHC) analysis to determine the expressions of CDX2 and compared them with clinicopathological factors and survival. Results: Sixteen of the 50 cases (32%) were CDX2 positive. No correlation was found between the CDX2 expression by IHC and clinicopathological factors. Multivariate analysis identified adjuvant chemotherapy (hazard ratio [HR] =2.86, 95% confidence interval [CI] = 1.04-8.16, P = .04) and vascular invasion (HR = 4.35, 95% CI = 1.21-15.63, P = .03) as being associated with a significantly worse rate of recurrence-free survival. Conclusion: CDX2 was expressed in 1/3 of LCNEC but not associated with prognostic factor. Adjuvant chemotherapy and vascular invasion were associated with a negative prognostic factor of LCNEC.

scholarly journals Survival and prognostic factor analyses in malignant giant cell tumour of bone

2020 ◽  
Author(s):  
Jin Zhang ◽  
Xin Wang ◽  
Feng Lin ◽  
Guijun Xu ◽  
Haixiao Wu ◽  
...  
Keyword(s):  
Giant Cell ◽  
Cox Regression ◽  
Giant Cell Tumour ◽  
Large Population ◽  
Survival Rates ◽  
Population Based ◽  
Cell Tumour ◽  
Rank Test ◽  
Seer Database ◽  
Increased Risk

Abstract Background: The characteristics and survival of patients with malignant giant cell tumour of bone (GCTB) have not been investigated thoroughly due to the rarity of the disease. We evaluated these factors in a large cohort in the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database.Methods: Data from patients who were diagnosed with malignant GCTB from 1975 to 2016 were extracted from the SEER database. The overall survival (OS) was calculated by Kaplan–Meier analysis, and intergroup differences were tested by the log-rank test. Univariate and multivariate Cox proportional hazard regression analyses were conducted to identify the independent survival factors.Results: A total of 325 patients with malignant GCTB were included. The overall 1-, 5-, and 10-year survival rates were 94.3% (95% CI: 91.7-96.8), 82.3% (95% CI: 77.9-86.6), and 80.1% (95% CI: 75.4-84.7), respectively. A potential non-linear J-shaped dose–response relationship between the age or diagnosis year and survival were found. Multivariate Cox regression showed poor survival in patients with age from 35 to 60 years (hazard ratio (HR) =9.99, 95% CI: 1.34-74.80, P=0.025), age older than 60 years (HR=62.03, 95% CI: 7.94-484.38, P<0.001), with stage T2 disease (HR=4.85, 95% CI: 1.52-15.47, P=0.008), with stage T3 disease (HR=6.09, 95% CI: 1.03-36.23, P=0.047), and with distant tumours (HR=2.76, 95% CI: 1.14-6.65, P=0.024), and extraskeletal sites (HR=3.33, 95% CI: 1.02-10.85, P=0.046).Conclusions: This large population-based series described the clinical characteristics of malignant GCTB. Patients with stage T2/3disease, distant disease and extra-skeletal sites had more odds to be with worse survival. The elder age than 34 years had a gradually increased risk for survival.

Nomogram to predict survival of pulmonary large-cell neuroendocrine carcinoma after surgery

2020 ◽  
Author(s):  
Qian Huang ◽  
Jie Liu ◽  
Huifang Cai ◽  
Qi Zhang ◽  
Lina Wang
Keyword(s):  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Factors ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Predictive Performance ◽  
Large Cell ◽  
Large Cell Neuroendocrine Carcinoma ◽  
Operating Characteristics ◽  
Cox Regression Analysis

Abstract Background Pulmonary large-cell neuroendocrine carcinoma (LCNEC) is a rare primary malignant tumor with a poor prognosis, and surgery is the main treatment. However, there are no effective predictive tools to assess the prognosis of postoperative patients. Our aim is to identify prognostic factors and construct nomogram to accurately assess prognosis. Methods Patients were identified in the Surveillance, Epidemiology, and End Results (SEER) database. Based on the results of Cox regression analysis, construct nomogram for predicting 1-, 3-, and 5-year survival. The predictive performance of nomogram was evaluated using the consistency index (C-index), the area under the receiver operating characteristics curve (AUC), and calibration plots. Results We finally screened 903 patients with pulmonary LCNEC who underwent surgery. The Cox regression analysis showed that age, SEER stage, T stage, N stage, M stage, tumor size, and chemotherapy were independent prognostic factors for overall survival (P<0.05). The C-index of the nomogram is 0.681 on the training cohort and 0.675 on the validation cohort. The AUC and calibration plots show that the nomogram has good performance. Conclusion We constructed and validated nomogram for predicting 1-, 3-, and 5-year survival of patients with pulmonary LCNEC after surgery. Our nomogram provides reference information for assessing the overall survival of these patients.

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