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

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.

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

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.

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

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.

scholarly journals Prognostic nomogram to predict the overall survival of patients with early-onset colorectal cancer: a population-based analysis

2021 ◽  
Author(s):  
Junxian Wu ◽  
Linbin Lu ◽  
Hong Chen ◽  
Yihong Lin ◽  
Huanlin Zhang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Early Onset ◽  
Clinical Decision Making ◽  
Staging System ◽  
Tnm Staging ◽  
Discriminative Ability ◽  
Tnm Staging System ◽  
Early Onset Colorectal Cancer

Abstract Purpose The present study aimed to identify independent clinicopathological and socio-economic prognostic factors associated with overall survival of early-onset colorectal cancer (EO-CRC) patients and then establish and validate a prognostic nomogram for patients with EO-CRC. Methods Eligible patients with EO-CRC diagnosed from 2010 to 2017 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly divided into a training cohort and a testing cohort. Independent prognostic factors were obtained using univariate and multivariate Cox analyses and were used to establish a nomogram for predicting 3- and 5-year overall survival (OS). The discriminative ability and calibration of the nomogram were assessed using C-index values, AUC values, and calibration plots. Results In total, 5585 patients with EO-CRC were involved in the study. Based on the univariate and multivariate analyses, 15 independent prognostic factors were assembled into the nomogram to predict 3- and 5-year OS. The nomogram showed favorable discriminatory ability as indicated by the C-index (0.840, 95% CI 0.827–0.850), and the 3- and 5-year AUC values (0.868 and 0.84869 respectively). Calibration plots indicated optimal agreement between the nomogram-predicted survival and the actual observed survival. The results remained reproducible in the testing cohort. The C-index of the nomogram was higher than that of the TNM staging system (0.840 vs 0.804, P < 0.001). Conclusion A novel prognostic nomogram for EO-CRC patients based on independent clinicopathological and socio-economic factors was developed, which was superior to the TNM staging system. The nomogram could facilitate postoperative individual prognosis prediction and clinical decision-making.

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

BMC Urology ◽  
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.

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

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenbo Zou ◽  
Zizheng Wang ◽  
Fei Wang ◽  
Gong Zhang ◽  
Rong Liu
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Pancreatic Head ◽  
Staging System ◽  
Seer Database ◽  
Cox Regression Analysis ◽  
Net Reclassification Improvement ◽  
Calibration Curves

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.

scholarly journals Construction and Validation of a Novel Immunosignature for Overall Survival in Uveal Melanoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Chufeng Gu ◽  
Xin Gu ◽  
Yujie Wang ◽  
Zhixian Yao ◽  
Chuandi Zhou
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Immune Cell ◽  
Risk Group ◽  
Staging System ◽  
Risk Groups ◽  
Tnm Staging ◽  
High Risk Group ◽  
Immune Cell Infiltration ◽  
Tnm Staging System

ObjectivesUveal melanoma (UM) is the most common primary intraocular malignancy in adults, and immune infiltration plays a crucial role in the prognosis of UM. This study aimed to generate an immunological marker-based predictive signature for the overall survival (OS) of UM patients.MethodsSingle-sample gene-set enrichment analysis (ssGSEA) was used to profile immune cell infiltration in 79 patients with UM from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate least absolute shrinkage and selection operator (LASSO) Cox regressions were used to determine the prognostic factors for UM and construct the predictive immunosignature. Receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves were performed to evaluate the clinical ability and accuracy of the model. In addition, the predictive accuracy was compared between the immunosignature and the Tumor, Node, Metastasis (TNM) staging system of American Joint Committee on Cancer (AJCC). We further analyzed the differences in clinical characteristics, immune infiltrates, immune checkpoints, and therapy sensitivity between high- and low-risk groups characterized by the prognostic model.ResultsHigher levels of immune cell infiltration in UM were related to a lower survival rate. Matrix metallopeptidase 12 (MMP12), TCDD inducible poly (ADP-ribose) polymerase (TIPARP), and leucine rich repeat neuronal 3 (LRRN3) were identified as prognostic signatures, and an immunological marker-based prognostic signature was constructed with good clinical ability and accuracy. The immunosignature was developed with a concordance index (C-index) of 0.881, which is significantly better than that of the TNM staging system (p &lt; 0.001). We further identified 1,762 genes with upregulated expression and 798 genes with downregulated expression in the high-risk group, and the differences between the high- and low-risk groups were mainly in immune-related processes. In addition, the expression of most of the immune checkpoint-relevant and immune activity-relevant genes was significantly higher in the high-risk group, which was more sensitive to therapy.ConclusionWe developed a novel immunosignature constructed by MMP12, TIPARP, and LRRN3 that could effectively predict the OS of UM.

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