Predictive potential of preoperative Naples prognostic score-based nomogram model for the prognosis in surgical resected thoracic esophageal squamous cell carcinoma patients: A retrospective cohort study.

The present study aimed to establish an effective prognostic nomogram model based on the Naples prognostic score (NPS) for resectable thoracic esophageal squamous cell carcinoma (ESCC). A total of 277 patients with ESCC, who underwent standard curative esophagectomy and designated as study cohort, were retrospectively analyzed. The patients were divided into different groups, including NPS 0, NPS 1, NPS 2, and NPS 3 or 4 groups, for further analysis, and the results were validated in an external cohort of 122 ESCC patients, who underwent surgery at another cancer center. In our multivariate analysis of the study cohort showed that the tumor-node-metastasis (TNM) stage, systemic inflammation score, and NPS were the independent prognostic factors for the overall survival (OS) and progression-free survival (PFS) durations. In addition, the differential grade was also an independent prognostic factor for the OS in the patients with ESCC after surgery (all P < .05). The area under the curve of receiver operator characteristics for the PFS and OS prediction with systemic inflammation score and NPS were 0.735 (95% confidence interval [CI] 0.676-0.795, P < .001) and 0.835 (95% CI 0.786-0.884, P < .001), and 0.734 (95% CI 0.675-0.793, P < .001) and 0.851 (95% CI 0.805-0.896, P < .001), respectively. The above independent predictors for OS or PFS were all selected in the nomogram model. The concordance indices (C-indices) of the nomogram models for predicting OS and PFS were 0.718 (95% CI 0.681-0.755) and 0.669 (95% CI 0.633-0.705), respectively, which were higher than that of the 7th edition of American Joint Committee on Cancer TNM staging system [C-index 0.598 (95% CI 0.558-0.638) for OS and 0.586 (95% CI 0.546-0.626) for PFS]. The calibration curves for predicting the 5-year OS or PFS showed a good agreement between the prediction by nomogram and actual observation. In the external validation cohort, the nomogram discrimination for OS was better than that of the 7th edition of TNM staging systems [C-index: 0.697 (95% CI 0.639-0.755) vs 0.644 (95% CI 0.589-0.699)]. The calibration curves showed good consistency in predicting the 5-year survival between the actual observation and nomogram predictions. The decision curve also showed a higher potential of the clinical application of predicting the 5-years OS of the proposed nomogram model as compared to that of the 7th edition of TNM staging systems. The preoperative NPS-based nomogram model had a certain potential role for predicting the prognosis of ESCC patients.

Guo XW ，Ji L ，Xi XX ，Zhao WW ，Liu YC ，Zhou SB ，Ji SJ ... -  《-》

Prognostic nomogram integrated systemic inflammation score for patients with esophageal squamous cell carcinoma undergoing radical esophagectomy.

Shao Y ，Ning Z ，Chen J ，Geng Y ，Gu W ，Huang J ，Pei H ，Shen Y ，Jiang J ... -  《Scientific Reports》

Predicting prognosis in resected esophageal squamous cell carcinoma using a clinical nomogram and recursive partitioning analysis.

Development demand of precise medicine in resectable esophageal squamous cell carcinoma (ESCC) require to recognize patients at high risk treated by surgery alone. Thus, our aim was to construct a clinical nomogram and recursive partitioning analysis (RPA) to predict long-term survival in ESCC treated by surgery alone. Based on the patients with ESCC who treated by three-incisional esophagectomy and two-field lymphadenectomy alone, we identified and integrated significant prognostic factors for survival to build a nomogram. The nomogram was calibrated for overall survival (OS) and the predictive accuracy and discriminative ability was measured by concordance index (c-index) and Akaike information criterion (AIC). Based on the nomogram, the RPA was performed for risk stratification. A total of 747 patients were included for analysis. Five independent prognostic factors were identified and entered into the nomogram. The calibration curves for probability of 1-, 3-, and 5-year OS showed optimal agreement between nomogram prediction and actual observation. The AIC value of the nomogram was lower than that of the 7th edition staging system, whereas the c-index of the nomogram was higher than that of the 7th edition staging system. The risk groups stratified by RPA allowed significant distinction between survival curves within respective TNM categories. The RPA based on a clinical nomogram appears to be suitable for risk stratification in OS for resected ESCC. This practical system may help clinicians in decision making and design of clinical studies.

Zheng Y ，Fu S ，He T ，Yan Q ，Di W ，Wang J ... -  《-》

Nomogram to Predict Overall Survival for Thoracic Esophageal Squamous Cell Carcinoma Patients After Radical Esophagectomy.

Deng W ，Zhang W ，Yang J ，Ni W ，Yu S ，Li C ，Chang X ，Zhou Z ，Chen D ，Feng Q ，Chen X ，Lin Y ，Zhu K ，Zheng X ，He J ，Gao S ，Xue Q ，Mao Y ，Cheng G ，Sun K ，Liu X ，Fang D ，Chen J ，Xiao Z ... -  《-》

Development of a Survival Nomogram for Esophageal Squamous Cell Carcinoma Patients: a Population-Based Analysis.

In this study, we developed a prognostic nomogram for esophageal squamous cell carcinoma (ESCC) patients. Patients diagnosed with ESCC from the Surveillance, Epidemiology, and End Results (SEER) database (1975-2017) and a local hospital were enrolled in this retrospective cohort study. Prognoses were analyzed using the R language software, and the predictive power of the model was then assessed by the Harrell concordance index (C-index) and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. In total, 2915 ESCC patients from SEER database were divided into training and validation cohorts. Multivariate analysis revealed that sex, marital status, tumor-node-metastasis (TNM) stage, surgery, chemotherapy, and radiation all showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (also with tumor grade). These characteristics were employed to build a nomogram. The C-index of the nomogram for OS and CSS prediction was 0.743 and 0.748 for the training cohort, which were superior to the predictive power of the 7th TNM staging system. The AUCs of the nomogram for predicting 2- and 5-year OS were 0.805 and 0.812, respectively, and the AUCs for CSS were 0.811 and 0.821, respectively. ROC and calibration curves of data from the SEER internal validation set and of data from our hospital showed that this model had good accuracy for predicting the prognosis of ESCC patient. The nomogram developed in this study provides a useful tool for accurately estimating OS and CSS for ESCC patients.

Lu G ，Fang W ，Lin Y ，Huang H ... -  《-》