Construction and validation of a prognostic nomogram for anal squamous cell carcinoma. (1st December 2021) - Yang, Ningning; Xu, Lu; Wang, Qingqing; Chen, Fengxia; Zhou, Yunfeng
Abstract: Background: Anal squamous cell carcinoma (ASCC) is the main subtype of anal cancer and has great heterogeneity in prognosis. We aimed to construct a nomogram for predicting their 1‐, 3‐, and 5‐year overall survival (OS) rates. Methods: Patients with ASCC, enrolled between January 1, 2010 and December 31, 2017, were identified from the SEER database. They were divided into a training group and a validation group in a ratio of 7:3. Univariate and multivariate Cox analyses were used to identify the prognostic factors for OS. Then a prognostic nomogram was established and validated by Harrell consistency index (C‐index), area under the curve (AUC) of the receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Results: We identified 761 patients in training group and 326 patients in validation group. Four prognostic factors including age, sex, AJCC stage, and radiotherapy were identified and integrated to construct a prognostic nomogram. The C‐index and AUC values proved the model's effectiveness and calibration plots manifested its excellent discrimination. Furthermore, in comparison to the AJCC stage, the C‐index, AUC, and DCA proved the nomogram to be of good predictive value. Finally, we constructed a risk stratification model for dividing patients into low‐risk, medium‐risk, and high‐risk groups, and there were obvious differences in OS. Conclusions: A prognostic nomogram was firstly established for predicting the survival probability of ASCC patients and helping clinicians improve their risk management. Abstract : First, from the SEER database, we identified the prognostic factors for anal squamous cell carcinoma (ASCC) patients and develop a nomogram to better predict the prognosis of ASCC patients. Secondly, through comparison, our predictive model is a further improvement of traditional AJCC staging system based on patient's demographic and clinicopathological features not only in survival prediction, but also in clinical utility.