Development and validation of a nomogram for prognosis of sinonasal adenocarcinoma (a nomogram for sinonasal adenocarcinoma)

Author:

Huang Hesen1ORCID,Chen Kaiqin2,Deng Lifeng3,Chen Yaling1,Zhao Dean1,Lin Wei4

Affiliation:

1. Department of Otolaryngology-Head and Neck Surgery , Xiang'an Hospital of Xiamen University, Xia Men, Fu Jian, China

2. Department of Neurosurgery , Xiang'an Hospital of Xiamen University, Xia Men, Fu Jian, China

3. Quanzhou Medical College , Quanzhou, Fujian, China

4. Department of Otorhinolaryngology , The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China

Abstract

Abstract Background The incidence of sinonasal adenocarcinoma is low, and there are few studies on survival and prognosis. Therefore, we aim to develop and validate a prognostic model for predicting the overall survival of sinonasal adenocarcinoma and provide guidance for clinical management. Methods Patients who were diagnosed as sinonasal adenocarcinoma through Surveillance, Epidemiology, and End Results database between 1975 and 2015 were randomly divided into a training group and validation group. Univariate, multivariate survival analysis was performed to screen independent survival factors. A nomogram was established to predict the overall survival rate of sinonasal adenocarcinoma. Receiver operating characteristic curve and calibration plot were performed to verify the discrimination and accuracy of the model. A decision curve analysis was performed to verify the clinical applicability of the model. Results A total of 423 patients with sinonasal adenocarcinoma were randomly divided into training group (n = 299) and verification group (n = 124). We established and verified the Nomo map including age, marriage, grade, surgery and tumour size. The c-index of Surveillance, Epidemiology, and End Results stage, T stage and this model are 0.635, 0.626 and 0.803, respectively. The survival rate of the high-risk group scored by this model was lower than that of the low-risk group (P < 0.001). Decision curve analysis shows that the model has advantages in predicting survival rates. Conclusion Our model is considered to be a useful tool for predicting the overall survival of sinonasal adenocarcinoma, with good discrimination and clinical applicability. We hope that this model will help rhinologists to make clinical decisions and manage patients diagnosed with sinonasal adenocarcinoma.

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology,General Medicine

Reference32 articles.

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