A competing risk nomogram for predicting cancer‐specific death of patients with buccal mucosa cancer. (1st October 2020)

• Record Type: Journal Article
• Authors: Jiang, Qingkun; Xue, Danfeng; Xin, Yuqi; Qiu, Jiaxuan
• Is Part Of: Oral diseases. Volume 27:Number 4(2021)
• Page Start: 900
• Page End: 910
• Publication Date: 2020-10-01
• Subjects: buccal mucosa cancer -- cancer‐specific death -- competing risk -- nomogram -- prediction model -- SEER; Mouth -- Diseases -- Research -- Periodicals; 617.522
• DOI: 10.1111/odi.13609
• Languages: English
• ISSNs: 1354-523X

Abstract

Abstract: Objectives: Our aim was to develop and validate a competing risk nomogram to determine the probability of cancer‐specific death in buccal mucosa cancer (BMC) patients. Materials and Methods: We examined the records of BMC patients in the Surveillance, Epidemiology, and End Results (SEER) Program and First Affiliated Hospital of Nanchang University (China). We adopted the cumulative incidence function and Fine–Gray proportional hazards model based on univariate and multivariate analyses by R‐software to identify the risk factors associated with cancer‐specific death. Subsequently, a nomogram was developed and validated to predict the 3‐ and 5‐year probability of cancer‐specific death. Results: In 1, 286 BMC patients identified from SEER database, cumulative incidences of cancer‐specific death after diagnosis were 33.4% and 35.5% for 3 and 5 years, respectively. In the training cohort ( n = 902) from SEER database, the Fine–Gray model indicated that age, Tumor Node Metastasis (TNM) stages, grade, surgery, and histological type were independent risk factors associated with cancer‐specific death, based on which a prognostic nomogram was developed. In the internal validation cohort from SEER database ( n = 384) and the external validation cohort from our medical center ( n = 174), the nomogram was well calibrated and showed remarkable prediction performance. Conclusion: The nomogram created herein may prove to be a good assistant tool for assessing the prognosis of BMC patients.