Abstract
We aimed to evaluate the prognostic value of clinical and pathologic factors in rectal squamous cell carcinomas (SCC) and to construct a nomogram for their outcome prediction.The study cohort was selected from Surveillance, Epidemiology, and End Results (SEER) program between January 2004 and December 2013. Univariate and multivariate analyses were performed using Cox proportional hazards regression model to evaluate the prognostic value of involved variables. All prognostic factors were combined to construct a nomogram to predict the overall survival (OS), followed by discrimination as well as calibration plots and receiver operating characteristic (ROC) curves for assessing the predictive accuracy of the nomogram.We identified 806 patients with a median follow-up time of 35 months. Multivariate analyses revealed that marital status (P < .001), age (P < .001), T stage (P = .008), M stage (P < .001), surgery (P = .004), chemotherapy (P = .003) and radiotherapy (P = .016) were independent prognostic factors of OS. Finally, the 7 variables were combined to construct a 3-year and 5-year OS nomogram. The concordance indexes (C-indexes) of OS were 0.756 (95% CI, 0.726-0.786) for the internal validation and 0.729 (95% CI, 0.678-0.780) for the external validation. Additionally, there was superior discrimination power of the nomogram over the SEER stage or the 8th edition AJCC TNM staging classification (P < .001). Calibration plots further showed good consistency between the nomogram prediction and actual observation. The area under the curve (AUC) of ROC curves for 3-year OS was 0.811 (95% CI: 0.769-0.853) in the training cohort and 0.748 (95% CI: 0.681-0.815) in the validation cohort. The AUC for 5-year OS was 0.770 (95% CI: 0.721-0.819) in the training cohort and 0.797 (95% CI: 0.731-0.863) in the validation cohort. Finally, Kaplan-Meier analysis further validates the predictive potential of the nomogram.Marital status, age, T stage, M stage, surgery, chemotherapy and radiotherapy were significantly associated with OS of patients with rectal SCC. This predictive model has the potential to provide an individualized risk estimate of survival in patients with rectal SCC.