Open AccessConstruction and validation of a prognostic nomogram for anal squamous cell carcinoma
Author(s) -
Yang Ningning,
Xu Lu,
Wang Qingqing,
Chen Fengxia,
Zhou Yunfeng
Publication year - 2022
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.4458
Subject(s) - nomogram , medicine , oncology , univariate , ajcc staging system , receiver operating characteristic , multivariate analysis , area under the curve , stage (stratigraphy) , proportional hazards model , t stage , multivariate statistics , cancer , statistics , staging system , mathematics , paleontology , biology
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.