scholarly journals Derivation and Validation of a Prognostic Scoring Model Based on Clinical and Pathological Features for Risk Stratification in Oral Squamous Cell Carcinoma Patients: A Retrospective Multicenter Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Jiaying Zhou ◽  
Huan Li ◽  
Bin Cheng ◽  
Ruoyan Cao ◽  
Fengyuan Zou ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Validation Cohort ◽  
External Validation ◽  
Staging System ◽  
Tnm Staging ◽  
Pathological Features ◽  
Scoring Model ◽  
Tnm Staging System ◽  
Pathological Model ◽  
Clinical And Pathological Features

ObjectiveTo develop and validate a simple-to-use prognostic scoring model based on clinical and pathological features which can predict overall survival (OS) of patients with oral squamous cell carcinoma (OSCC) and facilitate personalized treatment planning.Materials and MethodsOSCC patients (n = 404) from a public hospital were divided into a training cohort (n = 282) and an internal validation cohort (n = 122). A total of 12 clinical and pathological features were included in Kaplan–Meier analysis to identify the factors associated with OS. Multivariable Cox proportional hazards regression analysis was performed to further identify important variables and establish prognostic models. Nomogram was generated to predict the individual’s 1-, 3- and 5-year OS rates. The performance of the prognostic scoring model was compared with that of the pathological one and the AJCC TNM staging system by the receiver operating characteristic curve (ROC), concordance index (C-index), calibration curve, and decision curve analysis (DCA). Patients were classified into high- and low-risk groups according to the risk scores of the nomogram. The nomogram-illustrated model was independently tested in an external validation cohort of 95 patients.ResultsFour significant variables (physical examination-tumor size, imaging examination-tumor size, pathological nodal involvement stage, and histologic grade) were included into the nomogram-illustrated model (clinical–pathological model). The area under the ROC curve (AUC) of the clinical–pathological model was 0.687, 0.719, and 0.722 for 1-, 3- and 5-year survival, respectively, which was superior to that of the pathological model (AUC = 0.649, 0.707, 0.717, respectively) and AJCC TNM staging system (AUC = 0.628, 0.668, 0.677, respectively). The clinical–pathological model exhibited improved discriminative power compared with pathological model and AJCC TNM staging system (C-index = 0.755, 0.702, 0.642, respectively) in the external validation cohort. The calibration curves and DCA also displayed excellent predictive performances.ConclusionThis clinical and pathological feature based prognostic scoring model showed better predictive ability compared with the pathological one, which would be a useful tool of personalized accurate risk stratification and precision therapy planning for OSCC patients.

Establishment of a Nomogram by Integrating Molecular Markers and Tumor-Node-Metastasis Staging System for Predicting the Prognosis of Hepatocellular Carcinoma

2018 ◽  
Vol 36 (5) ◽  
pp. 426-432 ◽  
Author(s):  
Xi-Tai Huang ◽  
Liu-Hua Chen ◽  
Chen-Song Huang ◽  
Jian-Hui Li ◽  
Jian-Peng Cai ◽  
...  
Keyword(s):  
Molecular Markers ◽  
Validation Cohort ◽  
External Validation ◽  
Staging System ◽  
Tnm Staging ◽  
Hazard Ratio ◽  
Tumor Node Metastasis ◽  
Training Cohort ◽  
Tnm Staging System

Aims: This study aimed to develop a valuable nomogram by integrating molecular markers and tumor-node-metastasis (TNM) staging system for predicting the long-term outcome of patients with hepatocellular carcinoma (HCC). Methods: The gene expression profiles of HCC patients undergoing liver resection were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. One hundred and ninety-nine patients from TCGA and 94 patients from GEO were selected to be part of the training cohort and validation cohort respectively. Univariate and multivariate cox analyses were performed to identify genes with independent prognostic values for overall survival (OS) of HCC patients in training cohort. Risk score was calculated based on the coefficients and Z-score of 3 genes for each patient. The nomogram was developed based on the risk score and TNM staging system. Discrimination and predictive accuracy of the nomogram were measured by using the concordance index (C-index) and calibration curve. The efficacy of the nomogram was tested in the external validation cohort. Results: Univariate and multivariate cox analyses revealed that EXT2 (p = 0.035, hazard ratio 13.412), ETV5 (p = 0.010, hazard ratio 4.325), and CHODL (p < 0.001, hazard ratio 6.286) were independent prognostic factors and chosen for further nomogram establishment. The C-index of the nomogram for predicting the OS in the training cohort was superior to that of the TNM staging system (0.77 vs. 0.64, p < 0.01). The calibration curve of predicted 1-, 3-, and 5-year OS showed satisfactory accuracy. The external validation cohort showed good performance of comprehensive nomogram as well. Conclusion: The novel nomogram by integrating the molecular markers and TNM staging system has better performance in predicting long-term prognosis in HCC patients than the TNM staging system alone.

scholarly journals Predicting Survival for Nasopharyngeal Carcinoma: Development and Validation of Nomograms With Routine Hematological Biomarkers Based on the 8th Edition of AJCC/UICC Staging System

2020 ◽  
Author(s):  
Yu Liang ◽  
Kaihua Chen ◽  
Jie Yang ◽  
Jing Zhang ◽  
Rurong Peng ◽  
...  
Keyword(s):  
Validation Cohort ◽  
External Validation ◽  
Progression Free Survival ◽  
Staging System ◽  
Tnm Staging ◽  
Prognostic Role ◽  
Tnm System ◽  
Ebv Dna ◽  
8Th Edition

Abstract BackgroundThe 8th edition of AJCC/UICC TNM staging system (TNM system) and the previous nomograms have limitations, therefore we aimed to develop and validate nomograms incorporating routine hematological biomarkers with or without EBV DNA for overall survival (OS) and progression-free survival (PFS). We also evaluated the prognostic role of EBV DNA.Material and Methods1203 patients at our hospital from 2013 to 2016 were retrospectively reviewed and divided into two parts (922 patients for primary cohort and 281 for validation cohort). Nomograms (nomogram with or without EBV DNA) were developed and compared with other models (TNM system alone, TNM system with EBV DNA), via comparison the prognostic role of EBV DNA was evaluated. Internal and external validation were performed. Risk stratification were conducted with recursive partitioning analysis.ResultsThe nomograms with EBV DNA for OS and PFS included sex, age, T category, N category, EBV DNA, albumin, neutrophil to lymphocyte ratio and lactate dehydrogenase. The nomograms without EBV DNA for OS and PFS included the same variables but without EBV DNA. The C-index for nomogram with EBV DNA was 0.715 for OS and 0.705 for PFS. For nomogram without EBV DNA, it was 0.709 and 0.700, respectively. It was 0.639 and 0.636 for TNM system alone and 0.648, 0.646 respectively for TNM system with EBV DNA. The nomograms with or without EBV DNA had better performance than both the TNM system alone and TNM system with EBV DNA, while the TNM system with EBV DNA were better than TNM system alone. The validation cohort indicates great applicability of nomograms. The patients were stratified into 4 risk groups.ConclusionThe nomograms with or without EBV DNA provide better prognostication than the TNM system and also the TNM system with EBV DNA. EBV DNA is valuable in predicting survival, but it is not suggested to incorporate EBV DNA alone to TNM system.

scholarly journals Predicting Death in Patients with Squamous Cell Carcinoma of the Tongue

Proceedings ◽  
2019 ◽  
Vol 35 (1) ◽  
pp. 18
Author(s):  
Caponio ◽  
Troiano ◽  
Mascitti ◽  
Santarelli ◽  
Mauceri ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Cavity ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Gold Standard ◽  
Staging System ◽  
Tnm Staging ◽  
Mucosal Surface ◽  
Tnm Staging System ◽  
Carcinoma Of The Tongue

Tongue squamous cell carcinoma (TSCC) accounts for 40% of all squamous cell carcinoma involving the mucosal surface of the oral cavity. TSCC is highly invasive and aggressive and, nowadays, TNM staging system is considered the gold standard in predicting patients’ outcomes. [...]

scholarly journals Identification of a 4-lncRNA Signature Predicting Prognosis of Patients with Non-Small Cell Lung Cancer: a Multicenter Study in China

2020 ◽  
Author(s):  
Rui-Qi Wang ◽  
Xiao-Ran Long ◽  
Chun-Lei Ge ◽  
Mei-Yin Zhang ◽  
Long Huang ◽  
...  
Keyword(s):  
Risk Score ◽  
Validation Cohort ◽  
Staging System ◽  
Tnm Staging ◽  
Tnm Stage ◽  
Differentially Expressed ◽  
Prognostic Signature ◽  
Discovery Cohort ◽  
Tnm Staging System ◽  
Independent Cohort

Abstract Background: Previous findings have indicated that the tumor, nodes, and metastases (TNM) staging system is sub-optimal in terms of predicting survival outcomes in patients with non-small lung carcinoma (NSCLC).Thus, the aims to identify a long non-coding RNA (lncRNA) signature for predicting survival in patients with NSCLC and to provide additional prognostic information in combination with the TNM system.Methods: Patients with NSCLC were recruited from a hospital and divided into a discovery cohort (n=194) and validation cohort (n=172), and detected using a custom lncRNA microarray. Lung tissues obtained from patients at a different hospital (n = 73, independent validation cohort) were examined via qRT-PCR. Differentially expressed lncRNAs were determined with the Significance Analysis of Microarrays program and used to identify those associated with survival in the discovery cohort. These prognostic lncRNAs were employed to construct a prognostic signature with a risk-score method. Then, the utility of the prognostic signature was confirmed using the validation cohort and the independent cohort. Results: In the discovery cohort, we identified 305 lncRNAs that were differentially expressed between the NSCLC tissues and matched, adjacent normal lung tissues, of which 15 are associated with survival; a 4-lncRNA prognostic signature was identified from the 15 survival lncRNAs, which was significantly correlated with survivals of NSCLC patients. This signature was further validated in the validation cohort and independent cohort. Moreover, multivariate Cox analysis demonstrates that the 4-LncRNA signature is an independent survival predictor. Then we established a new risk-score model by combining 4-lncRNA signature and TNM stage. The receiver operating characteristics (ROC) curve indicates that the prognostic value of the combined model is significantly higher than that of the TNM stage alone, in all the cohorts. Conclusions: In this study, we identified a 4-lncRNA signature that can potentially serve as a powerful prognosis biomarker and can provide additional survival information to the traditional TNM staging system.

scholarly journals Development and validation of nomogram combining serum biomarker for predicting survival in patients with resected rectal cancer

2019 ◽  
Vol 39 (11) ◽  
Author(s):  
Shaonan Fan ◽  
Ting Li ◽  
Ping Zhou ◽  
Qiliang Peng ◽  
Yaqun Zhu
Keyword(s):  
Rectal Cancer ◽  
Clinical Decision Making ◽  
Validation Cohort ◽  
External Validation ◽  
Staging System ◽  
Clinical Decision ◽  
Tnm Staging ◽  
P Value ◽  
Training Cohort ◽  
American Joint Committee

Abstract Purpose: Nomogram is a widely used tool that precisely predicts individualized cancer prognoses. We aimed to develop and validate a reliable nomogram including serum tumor biomarkers to predict individual overall survival (OS) for patients with resected rectal cancer (RC) and compare the predictive value with the American Joint Committee on Cancer (AJCC) stages. Patients and methods: We analyzed 520 patients who were diagnosed with non-metastatic rectal cancer as training cohort. External validation was performed in a cohort of 11851 patients from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were identified and integrated to build a nomogram using the Cox proportional hazard regression model. The nomogram was evaluated by Harrell’s concordance index (C-index) and calibration plots in both training and validation cohort. Results: The calibration curves for probability of 1-, 3-, and 5-year OS in both cohorts showed favorable accordance between the nomogram prediction and the actual observation. The C-indices of the nomograms to predict OS were 0.71 in training cohort and 0.69 in the SEER cohort, which were higher than that of the seventh edition American Joint Committee on Cancer TNM staging system for predicting OS (training cohort, 0.71 vs. 0.58, respectively; P-value &lt; 0.001; validation cohort, 0.69 vs. 0.57, respectively; P-value &lt; 0.001). Conclusion: We developed and validated a novel nomogram based on CEA and other factors for predicting OS in patients with resected RC, which could assist clinical decision making and improvement of prognosis prediction for individual RC patients after surgery.

scholarly journals Construction and External Validation of a Nomogram for Predicting Survival of Intrahepatic Cholangiocarcinoma Patients Without Lymph Node and Distant Metastasis

2021 ◽  
Author(s):  
Chuang Jiang ◽  
Fei Teng ◽  
Yunyou Tang ◽  
Ziqi Zhang ◽  
Yimin Chen ◽  
...  
Keyword(s):  
Lymph Node ◽  
Intrahepatic Cholangiocarcinoma ◽  
Validation Cohort ◽  
External Validation ◽  
Staging System ◽  
Tnm Staging ◽  
Internal Validation ◽  
West China Hospital ◽  
Training Cohort ◽  
West China

Abstract BackgroundThe purpose of this study was to construct and external validate a nomogram for predicting overall survival(OS) in intrahepatic cholangiocarcinoma (ICC) patients classified as N0M0 according to the 7th edition of American Joint Committee on Cancer (AJCC) TNM staging system.Methods:812 ICC patients without distant and lymph node metastasis between 2011 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database, then randomly assigned to the training cohort(n=648) or internal validation cohort(n=164), external validation cohort consisted of 136 ICC patients with N0M0 stage treated in West China Hospital of Sichuan University from 2013 to 2015. The precision of the nomogram was validated internally using SEER validation cohort and externally using the patients’ data of West China Hospital. Results :The nomogram was established to predict 1-year, 3-year and 5-year OS and the calibration curve showed nomogram prediction performance was in good agreement with the actual results. The C‑index of the nomogram was 0.750(95% CI:0.731-0.769) in the training cohort, and the internal and external validated C-indexes were 0.803(95% CI:0.783-0.823) and 0.681(95% CI:0.524-0.838), respectively. In the training, internal and external validation cohort, the 1-year, 3‑year and 5‑year AUCs were (0.772,0.809,0.798),(0.896,0.868,0.896) and (0.673,0.786,0.886), respectively.Conclusions This nomogram has an excellent predictive effect on the 1- ,3-, 5-year OS of ICC patients with stage N0M0 and guide the optimal treatment for these type of patients.

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