A nomogram predicting overall survival in patients with non-metastatic pancreatic head adenocarcinoma after surgery: a population-based study

Abstract Background Pancreatic head adenocarcinoma (PHAC), a malignant tumour, has a very poor prognosis, and the existing prognostic tools lack good predictive power. This study aimed to develop a better nomogram to predict overall survival after resection of non-metastatic PHAC. Methods Patients with non-metastatic PHAC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and divided randomly into training and validation cohorts at a ratio of 7:3. Cox regression analysis was used to screen prognostic factors and construct the nomogram. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the performance of the model. The predictive accuracy and clinical benefits of the nomogram were validated using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Results From 2010 to 2016, 6419 patients with non-metastatic PHAC who underwent surgery were collected from the SEER database. A model including T stage, N stage, grade, radiotherapy, and chemotherapy was constructed. The concordance index of the nomogram was 0.676, and the AUCs of the model assessing survival at multiple timepoints within 60 months were significantly higher than those of the American Joint Committee on Cancer (AJCC) 8th staging system in the training cohort. Calibration curves showed that the nomogram had ability to predict the actual survival. The NRI, IDI, and DCA curves also indicated that our nomogram had higher predictive capability and clinical utility than the AJCC staging system. Conclusions Our nomogram has an ability to predict overall survival after resection of non-metastatic PHAC and includes prognostic factors that are easy to obtain in clinical practice. It would help assist clinicians to conduct personalized medicine.

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A nomogram for predicting overall survival in patients with Merkel cell carcinoma: A population-based analysis

10.21203/rs.3.rs-1052951/v1 ◽

2021 ◽

Author(s):

Miao Wang ◽

Ye Qiu ◽

Fang Tang ◽

Yi-Xin Liu ◽

Yi Li ◽

...

Keyword(s):

Overall Survival ◽

Prognostic Factors ◽

Cell Carcinoma ◽

Merkel Cell Carcinoma ◽

Cox Regression ◽

Predictive Accuracy ◽

Characteristic Curve ◽

Staging System ◽

Merkel Cell ◽

Cox Regression Analysis

Abstract Background: Merkel cell carcinoma (MCC) is a rare neuroendocrine skin cancer with increasing incidence and poor prognosis. We sought to develop and validate a nomogram to estimate overall survival (OS) of MCC patients. Methods: 1863 MCC patients between 2010-2015 from the Surveillance, Epidemiology and End Results (SEER) database were randomly divided into the training and validation cohort. Independent prognostic factors determined by Cox regression analysis in the training cohort were used to establish a nomogram. We evaluated prognostic performance using the concordance index (C-index), area under receiver operating characteristic curve (AUC) and calibration curves. Decision curve analysis (DCA), net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to compared the the nomogram’s clinical utility with that of the staging system.Results: eight independent prognostic factors were incorporated in the nomogram. The C-index of the nomogram was 0.744, which was superior to the C-index of AJCC TNM Stage (0.659). The AUC was greater than 0.75 and the calibration plots of this model exhibited good performance. Additionally, the positive NRI and IDI of nomogram versus the staging system illustrated that the nomogram had better predictive accuracy than the staging system (P<0.001) and the DCA showed great clinical usefulness of the nomogram. MCC patients were perfectly classified into three risk groups by the nomogram, showing better discrimination than the staging system.Conclusions: We developed and validated a nomogram to assist clinicians in evaluating prognosis of MCC patients.

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Prognostic nomogram to predict overall survival for patients with perihilar cholangiocarcinoma: A population-based study of SEER database (Preprint)

10.2196/preprints.26118 ◽

2020 ◽

Author(s):

Chendong Wang

Keyword(s):

Overall Survival ◽

Prognostic Factors ◽

Staging System ◽

Tnm Staging ◽

Survival Outcome ◽

Perihilar Cholangiocarcinoma ◽

Cox Regression Analysis ◽

Calibration Curves ◽

Tnm Staging System ◽

Net Benefits

BACKGROUND Perihilar cholangiocarcinoma (pCCA) is a highly aggressive malignancy with poor prognosis. Accurate prediction is of great significance for patients’ survival outcome. OBJECTIVE The present study aimed to propose a prognostic nomogram for predicting the overall survival (OS) for patients with pCCA. METHODS We conducted a retrospective analysis in a total of 940 patients enrolled from the Surveillance, Epidemiology, and End Results (SEER) program and developed a nomogram based on the prognostic factors identified from the cox regression analysis. Concordance index (C-index), risk group stratification and calibration curves were adopted to test the discrimination and calibration ability of the nomogram with bootstrap method. Decision curves were also plotted to evaluate net benefits in clinical use against TNM staging system. RESULTS On the basis of multivariate analysis, five independent prognostic factors including age, summary stage, surgery, chemotherapy, together with radiation were selected and entered into the nomogram model. The C-index of the model was significantly higher than TNM system in the training set (0.703 vs 0.572, P<0.001), which was also proved in the validation set (0.718 vs 0.588, P<0.001). The calibration curves for 1-, 2-, and 3-year OS probabilities exhibited good agreements between the nomogram-predicted and the actual observation. Decision curves displayed that the nomogram obtained more net benefits than TNM staging system in clinical context. The OS curves of two distinct risk groups stratified by nomogram-predicted survival outcome illustrated statistical difference. CONCLUSIONS We established and validated an easy-to-use prognostic nomogram, which can provide more accurate individualized prediction and assistance in decision making for pCCA patients.

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Development and Validation of Nomograms to Predict Prognosis of Oral and Oropharyngeal Mucoepidermoid Carcinoma: A SEER-Based Study

10.21203/rs.3.rs-125136/v1 ◽

2020 ◽

Author(s):

muyuan liu ◽

Litian Tong ◽

Manbin Xu ◽

Xiang Xu ◽

Bin Liang ◽

...

Keyword(s):

Overall Survival ◽

Prognostic Factors ◽

Mucoepidermoid Carcinoma ◽

Cox Regression ◽

Seer Database ◽

Disease Specific Survival ◽

Cox Regression Analysis ◽

T Stage ◽

N Stage ◽

Disease Specific

Abstract Background: Due to the low incidence of mucoepidermoid carcinoma, there lacks sufficient studies for determining optimal treatment and predicting prognosis. The purpose of this study was to develop prognostic nomograms, to predict overall survival and disease-specific survival (DSS) of oral and oropharyngeal mucoepidermoid carcinoma patients, using the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database. Methods: Clinicopathological and follow-up data of patients diagnosed with oral and oropharyngeal mucoepidermoid carcinoma between 2004 and 2017 were collected from the SEER database. The Kaplan-Meier method with the log-rank test was employed to identify single prognostic factors. Multivariate Cox regression was utilized to identify independent prognostic factors. C-index, area under the ROC curve (AUC) and calibration curves were used to assess performance of the prognostic nomograms. Results: A total of 1230 patients with oral and oropharyngeal mucoepidermoid carcinoma were enrolled in the present study. After multivariate Cox regression analysis, age, sex, tumor subsite, T stage, N stage, M stage, grade and surgery were identified as independent prognostic factors for overall survival. T stage, N stage, M stage, grade and surgery were identified as independent prognostic factors for disease-specific survival. Nomograms were constructed to predict the overall survival and disease-specific survival based on the independent prognostic factors. The fitted nomograms possessed excellent prediction accuracy, with a C-index of 0.899 for OS prediction and 0.893 for DSS prediction. Internal validation by computing the bootstrap calibration plots, using the validation set, indicated excellent performance by the nomograms. Conclusion: The prognostic nomograms developed, based on individual clinicopathological characteristics, in the present study, accurately predicted the overall survival and disease-specific survival of patients with oral and oropharyngeal mucoepidermoid carcinoma.

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Prognostic nomogram to predict overall survival for patients with perihilar cholangiocarcinoma: A population-based study of SEER database

10.21203/rs.3.rs-40400/v1 ◽

2020 ◽

Author(s):

Chendong Wang ◽

Huanyu Gong ◽

Zhiyuan Zhang ◽

Danzhou Fang ◽

Huiqun Wu

Keyword(s):

Overall Survival ◽

Prognostic Factors ◽

Staging System ◽

Tnm Staging ◽

Survival Outcome ◽

Perihilar Cholangiocarcinoma ◽

Cox Regression Analysis ◽

Calibration Curves ◽

Tnm Staging System ◽

Net Benefits

Abstract Background Perihilar cholangiocarcinoma (pCCA) is a highly aggressive malignancy with poor prognosis. Accurate prediction is of great significance for patients’ survival outcome. The present study aimed to propose a prognostic nomogram for predicting the overall survival (OS) for patients with pCCA. Methods We conducted a retrospective analysis in a total of 940 patients enrolled from the Surveillance, Epidemiology, and End Results (SEER) program and developed a nomogram based on the prognostic factors identified from the cox regression analysis. Concordance index (C-index), risk group stratification and calibration curves were adopted to test the discrimination and calibration ability of the nomogram with bootstrap method. Decision curves were also plotted to evaluate net benefits in clinical use against TNM staging system. Results On the basis of multivariate analysis, five independent prognostic factors including age, summary stage, surgery, chemotherapy, together with radiation were selected and entered into the nomogram model. The C-index of the model was significantly higher than TNM system in the training set (0.703 vs 0.572, P<0.001), which was also proved in the validation set (0.718 vs 0.588, p<0.001). The calibration curves for 1-, 2-, and 3-year OS probabilities exhibited good agreements between the nomogram-predicted and the actual observation. Decision curves displayed that the nomogram obtained more net benefits than TNM staging system in clinical context. The OS curves of two distinct risk groups stratified by nomogram-predicted survival outcome illustrated statistical difference. Conclusions We established and validated an easy-to-use prognostic nomogram, which can provide more accurate individualized prediction and assistance in decision making for pCCA patients.

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A novel model with nutrition-related parameters for predicting overall survival of cancer patients

10.21203/rs.3.rs-333040/v1 ◽

2021 ◽

Author(s):

Qi Zhang ◽

Kangping Zhang ◽

Xiangrui Li ◽

Xi Zhang ◽

Mengmeng Song ◽

...

Keyword(s):

Overall Survival ◽

Prognostic Factors ◽

Nutritional Status ◽

Cancer Patients ◽

Cox Regression ◽

Validation Cohort ◽

Staging System ◽

Tnm Staging ◽

Cox Regression Analysis ◽

Tnm Staging System

Abstract Background Increasing evidence indicates that nutritional status could influence the survival of cancer patients. This study aims to develop and validate a nomogram with nutrition-related parameters for predicting the overall survival of cancer patients.Patients and Methods 8,749 patients from the multicentre cohort study in China were included as the primary cohort to develop the nomogram, and 696 of these patients were recruited as a validation cohort. Patients nutritional status were assessed using the PG-SGA. LASSO regression models and Cox regression analysis were used for factor selection and nomogram development. The nomogram was then evaluated for its effectiveness in discrimination, calibration, and clinical usefulness by the C-index, calibration curves, and Decision Curve Analysis. Kaplan-Meier survival curves were used to compare the survival rate.Results Seven independent prognostic factors were identified and integrated into the nomogram. The C-index was 0.73 (95% CI, 0.72 to 0.74) and 0.77 (95% CI, 0.74 to 0.81) for the primary cohort and validation cohort, which were both higher than 0.59 (95% CI, 0.58 to 0.61) of the TNM staging system. DCA demonstrated that the nomogram was higher than the TNM staging system and the TNM staging system combined with PG-SGA. Significantly median overall survival differences were found by stratifying patients into different risk groups (score <18.5 and ≥18.5) for each TNM category (all Ps < 0.001).Conclusion Our study screened out seven independent prognostic factors and successfully generated an easy-to-use nomogram, validated and shown a better predictive validity for the overall survival of cancer patients.

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Overall survival in patients with metastatic pancreatic cancer after surgically primary tumor resected: a SEER-based nomogram analysis

10.21203/rs.2.23955/v1 ◽

2020 ◽

Author(s):

Maoen Pan ◽

Yuanyuan Yang ◽

Xiaoting Wu ◽

Heguang Huang

Keyword(s):

Pancreatic Cancer ◽

Overall Survival ◽

Prognostic Factors ◽

Primary Tumor ◽

Cox Regression ◽

Predictive Accuracy ◽

Tumor Resection ◽

Training Group ◽

Metastatic Pancreatic Cancer ◽

Cox Regression Analysis

Abstract Background This study aimed to establish and validate a nomogram to predict overall survival in patients with metastatic pancreatic cancer (mPC) after surgically primary tumor resected. Methods All mPC patients who underwent primary tumor resection at SEER database between 2004 and 2016 were identified. We randomly assigned two-thirds of the patients to the training group and one third to the validation group. In the training group, the Kaplan–Meier survival analysis was used to analyze survival outcomes. A univariate and multivariate cox regression analysis was used to identify significant prognostic factors for establishing a nomogram. The predictive accuracy and discriminative ability were measured by the concordance index (C-index) and risk group stratification. Results A total of 742 patients were included for analysis. Four significant prognostic factors were obtained and included in the nomogram. The nomogram showed an acceptable discrimination ability (C- index:0.711) and good calibration and was further validated in the validation cohort (C- index: 0.727). The nomogram total points (NTP) had the potential to stratify patients into 2-risk groups with a median OS of 11 and 4.5 months (P < 0.001), respectively. Conclusions The nomogram can provide considerable accuracy individual prediction OS outcomes in patients with metastatic pancreatic cancer undergone primary tumor surgery and it can guide clinicians to make decisions in the clinical therapies.

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Incidence, Survival, and Associated Factors Estimation in Osteosarcoma Patients with Lung Metastasis: A Single-center Experience of 11 Years in Tianjin, China

10.21203/rs.3.rs-1071152/v1 ◽

2021 ◽

Author(s):

Chao Zhang ◽

Haixiao Wu ◽

Guijun Xu ◽

Wenjuan Ma ◽

Lisha Qi ◽

...

Keyword(s):

Risk Factors ◽

Overall Survival ◽

Regression Analysis ◽

Prognostic Factors ◽

Lung Metastasis ◽

Associated Factors ◽

Cox Regression ◽

Cancer Center ◽

Single Center ◽

Cox Regression Analysis

Abstract Background: Osteosarcoma is the most common primary malignant bone tumor. The current study was conducted to describe the general condition of patients with primary osteosarcoma in a single cancer center in Tianjin, China and to investigate the associated factors in osteosarcoma patients with lung metastasis. Methods: From February 2009 to October 2020, patients from Tianjin Medical University Cancer Institute and Hospital, China were retrospectively analyzed. The Kaplan–Meier method was used to evaluate the overall survival of osteosarcoma patients. Prognostic factors of patients with osteosarcoma were identified by the Cox proportional hazard regression analysis. Risk factor of lung metastasis in osteosarcoma were investigated by the logistic regression model. Results: A total of 203 patients were involved and 150 patients were successfully followed up for survival status. The 5-year survival rate of osteo-sarcoma patients was 70.0%. Surgery, bone and lung metastasis were the significant prognostic factors in multivariable Cox regression analysis. Twenty-one (10.3%) patients showed lung metastasis at the diagnosis of osteosarcoma and 67 (33%) lung metastases during the later course. T3 stage (OR=11.415, 95%CI 1.362-95.677, P=0.025) and synchronous bone metastasis (OR=6.437, 95%CI 1.69-24.51, P=0.006) were risk factors of synchronous lung metastasis occurrence. Good necrosis (≥90%, OR=0.097, 95%CI 0.028-0.332, P=0.000) and elevated Ki-67 (≥50%, OR=4.529, 95%CI 1.241-16.524, P=0.022) were proved to be significantly associated with metachronous lung metastasis occurrence. Conclusion: The overall survival, prognostic factors and risk factors for lung metastasis in this single center provided insight about osteosarcoma management.

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Ampullary neuroendocrine tumors: A window into a rare tumor using a national database.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.3_suppl.373 ◽

2021 ◽

Vol 39 (3_suppl) ◽

pp. 373-373

Author(s):

Samantha M Ruff ◽

Gary B Deutsch ◽

Matthew John Weiss ◽

Danielle Deperalta

Keyword(s):

Overall Survival ◽

Neuroendocrine Tumors ◽

Cox Regression ◽

Case Series ◽

Pancreatic Head ◽

National Database ◽

Rare Tumor ◽

Cox Regression Analysis ◽

Significant Difference ◽

Poorly Differentiated

373 Background: Ampullary neuroendocrine tumors (NET) make up < 1% of all gastrointestinal NETs. Information about their behavior and prognosis is reliant on small case series. This study set out to describe the population of patients who are diagnosed with ampullary NETs and compare them to patients with duodenal and pancreatic head NETs. Methods: The National Cancer Database (2004 – 2016) was queried for patients with ampullary, duodenal, and pancreatic head NETs. Clinicopathologic and treatment characteristics were compared. Subset analysis was performed on patients who underwent surgery. Kaplan Meier (KM) analysis and Cox regression were used to analyze the survival of patients with ampullary NETs. Results: Overall, 872 patients were identified with ampullary NET, 9692 with duodenal NET, and 6562 with pancreatic head NET. Patients with ampullary NET had an average age of 60.9 +/- 14.5 years, were evenly split among men and women (N = 437, 50.1% vs N = 435, 49.9%, respectively), and primarily Caucasian (N = 663, 76.0%). 72.1% underwent local tumor destruction or surgery (N = 629). Most did not receive radiation (N = 832, 95.4%), chemotherapy (N = 627, 71.9%), or hormone therapy (N = 788, 90.4%). Patients with ampullary NETs had more poorly differentiated tumors (N = 119, 13.6%) than patients with duodenal (N = 159, 1.6%) or pancreatic head (N = 602, 9.2%) NETs. Patients with ampullary NETs had more positive lymph nodes (N = 288, 33%) than patients with duodenal (N = 915, 9.4%) or pancreatic head (N = 1381, 21%) NETs. At five years, the overall survival for patients with ampullary, duodenal, and pancreatic head NETs was 57%, 68%, and 46%, respectively. Within the surgical population, five-year survival for patients with ampullary (N = 367), duodenal (N = 991), and pancreatic head (N = 1961) NETs was 60%, 74%, and 72%, respectively. When compared, there was a statistically significant difference between the mean overall survival of patients with ampullary (98 +/- 4.7 months), duodenal (112 +/- 2.5 months), and pancreatic head (108 +/- 1.7 months) NETs (p < 0.001). In the cox regression analysis, sex, Charlson-Deyo score, lymph node positivity, lymph-vascular invasion, mitotic rate, chromogranin A level, 5-HIAA level, and tumor size did not correlate with survival. Increasing age (HR 1.04, CI 1.01 – 1.07, p = 0.008) and worse tumor differentiation (poorly differentiated HR 3.33, CI 1.38 – 8.04, p = 0.008 and undifferentiated HR 8.31, CI 2.77 – 24.92, p < 0.001 compared to well differentiated) were associated with increased mortality. Conclusions: This study sheds light on a rare tumor histology. When compared to patients who underwent surgical resection for duodenal or pancreatic head NETs, patients with ampullary NETs had a significantly worse prognosis. Identifying prognostic factors allows us to create more concrete treatment recommendations and provide patients with improved prognostic information.

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Overall Survival Rate Analysis For Risk Factors In Women With Neuroendocrine Carcinoma of The Cervix Using Surveillance, Epidemiology, And End Results (SEER) Database

10.21203/rs.3.rs-1131793/v1 ◽

2021 ◽

Author(s):

Ziran Yin ◽

Xiumin Huang

Keyword(s):

Overall Survival ◽

Lymph Nodes ◽

Neuroendocrine Carcinoma ◽

Cox Regression ◽

Analysis Data ◽

Seer Database ◽

Regional Lymph Nodes ◽

Data Set ◽

Cox Models ◽

Cox Regression Analysis

Abstract Background: Neuroendocrine carcinoma of the cervix is rare and aggressive disease, of which prognosis information and the effectiveness of the therapies is unclear.Methods: A retrospective study using data from the SEER database for the first diagnosed Neuroendocrine carcinoma of the cervix patients was conducted. We performed univariate and multivariate Cox models to screen for independent prognostic factors for overall survival. Subgroup analysis and sensitive analysis were performed for further study, then again univariate and multivariate analyses of Cox regression analysis were performed based on the sensitivity analysis data set.Results: A total of 250 Neuroendocrine carcinoma of the cervix cases was included, tumor subtype, age, marriage, race, number of regional lymph nodes, number of positive lymph nodes, radiotherapy, surgery, and FIGO stage were all factors affecting OS, and multivariate analysis identified FIGO staging (HR, 2.4; 95% CI, 1.505-3.828, P < 0.001) and surgery (HR, 0.467; 95% CI, 0.358-0.609, P < 0.001) treatment as independent indicators. With respect to the factors associated with treatments, we found that patients who underwent surgery (yes vs. no vs. unknown) or radiation (yes vs. no) experienced prolonged survival, both P < 0.001Conclusions: Our investigation shows that for patients with NECC surgery seems to be the effective treatment. Chemotherapy cannot improve the prognosis of NECC patients, and the effectiveness of radiation should be further verified.

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Development and validation of a prognostic nomogram for predicting overall survival in patients with primary bladder sarcoma: a SEER-based retrospective study

BMC Urology ◽

10.1186/s12894-021-00929-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Shijie Li ◽

Xuefeng Liu ◽

Xiaonan Chen

Keyword(s):

Overall Survival ◽

Risk Stratification ◽

Cox Regression ◽

Staging System ◽

Tnm Staging ◽

Calibration Curves ◽

Tnm Staging System ◽

Primary Bladder ◽

Stratification System ◽

Risk Stratification System

Abstract Background Primary bladder sarcoma (PBS) is a rare malignant tumor of the bladder with a poor prognosis, and its disease course is inadequately understood. Therefore, our study aimed to establish a prognostic model to determine individualized prognosis of patients with PBS. Patients and Methods Data of 866 patients with PBS, registered from 1973 to 2015, were extracted from the surveillance, epidemiology, and end result (SEER) database. The patients included were randomly split into a training (n = 608) and a validation set (n = 258). Univariate and multivariate Cox regression analyses were employed to identify the important independent prognostic factors. A nomogram was then established to predict overall survival (OS). Using calibration curves, receiver operating characteristic curves, concordance index (C-index), decision curve analysis (DCA), net reclassification improvement (NRI) and integrated discrimination improvement (IDI), the performance of the nomogram was internally validated. We compared the nomogram with the TNM staging system. The application of the risk stratification system was tested using Kaplan–Meier survival analysis. Results Age at diagnosis, T-stage, N-stage, M-stage, and tumor size were identified as independent predictors of OS. C-index of the training cohort were 0.675, 0.670, 0.671 for 1-, 3- and 5-year OS, respectively. And that in the validation cohort were 0.701, 0.684, 0.679, respectively. Calibration curves also showed great prediction accuracy. In comparison with TNM staging system, improved net benefits in DCA, evaluated NRI and IDI were obtained. The risk stratification system can significantly distinguish the patients with different survival risk. Conclusion A prognostic nomogram was developed and validated in the present study to predict the prognosis of the PBS patients. It may assist clinicians in evaluating the risk factors of patients and formulating an optimal individualized treatment strategy.

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