Competing risk nomogram to predict cancer‑specific survival in esophageal cancer during the intensity‑modulated radiation therapy era: A single institute analysis

Abstract

The present study aimed to investigate the probability of cancer-associated mortality of patients with esophageal cancer undergoing intensity-modulated radiation therapy (IMRT), and to establish a competing risk nomogram to predict the esophageal cancer-specific survival (EC-SS) of these patients. A total of 213 patients with EC who underwent IMRT between January 2014 and May 2017 were selected to establish nomograms according to Fine and Gray's competing risk analysis. Predictive accuracy and discriminative ability of the model were determined using the concordance index (C-index), calibration curves and the area under receiver operating characteristic curves. Decision tree analysis was also constructed for patient grouping. With a median follow-up of 19 months (range, 3-50), the 2-year EC-specific mortality (EC-SM) and the non-esophageal cancer specific mortality (NEC-SM) of the cohort were 35.4 and 3.51%, respectively. Furthermore, an elevated 2-year EC-SM was observed in patients with tumor length ≥4.5 cm compared with patients with tumor length <4.5 cm (45.8% vs. 21.4%; P<0.001), patients with non-squamous cell carcinoma compared with patients with squamous cell carcinoma (49.9 vs. 33.7%; P=0.025) and patients with N3 stage (43.2%; P=0.005). The 2-year NEC-SM of patients with tumor length ≥4.5 cm was 6% vs. 0% in patients with tumor length <4.5 cm (P=0.016). Three independent risk factors for survival, including tumor length, histological type and N stage, were integrated to build competing nomograms for the EC-SS model (C-index= 0.72; 95% confidence interval, 0.66-0.77). In addition, the nomograms displayed better discrimination power than the 7th edition of the Tumor-Node-Metastasis staging system for predicting EC-SS (area under the curve=0.707 vs. 0.634). Furthermore, the results from the classification tree analysis demonstrated that N stage was the initial node and that primary tumor length was a determinant for EC-SM in these patients. In conclusion, NEC-SM represented a competing event for patients with EC with a tumor length ≥4.5 cm. The competing risk nomograms may therefore be considered as convenient individualized predictive tools for cancer-specific survival in patients with EC undergoing IMRT treatment.

Development and Validation of a Contrast-Enhanced CT-Based Radiomics Nomogram for Prediction of Therapeutic Efficacy of Anti-PD-1 Antibodies in Advanced HCC Patients

“…Moreover, radiomics has recently been recognized as a newly emerging form of imaging technology in oncology using a series of statistical analysis tools or data-mining algorithms on high-throughput imaging features to obtain predictive or prognostic information (25). Its application has achieved successful prediction abilities in various tumors by building appropriate models with refined features and clinical data (26)(27)(28)(29)(30). For instance, radiomic features extracted from contrast-enhanced CT (CECT) have been proved to be useful in predicting microvascular invasion (MVI) and the long-term clinical outcomes in patients with HCC (31).…”

Modified Glasgow prognostic score predicts the prognosis of patients with advanced esophageal squamous cell carcinoma: A propensity score‐matched analysis

“…Over recent decades, a number of prognostic factors for esophageal cancers have been suggested, such as the pathological tumor-node-metastasis (TNM) stage, treatment strategies, and other miscellaneous factors, 16,17 but few studies regarding the mGPS in the esophageal cancer, especially SCC, are available. Esophageal SCC is more likely to localize near the tracheal bifurcation and has a proclivity for earlier lymphatic spread, 18 therefore compared with advanced esophageal adenocarcinoma, esophageal SCC is associated with a poorer prognosis.…”