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Randomized Controlled Trial
. 2022 Aug 5;52(8):869-879.
doi: 10.1093/jjco/hyac083.

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

Hesen Huang  1 , Kaiqin Chen  2 , Lifeng Deng  3 , Yaling Chen  1 , Dean Zhao  1 , Wei Lin  4
Affiliations
Randomized Controlled Trial

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

Hesen Huang et al. Jpn J Clin Oncol. .

Erratum in

  • Correction.
    [No authors listed] [No authors listed] Jpn J Clin Oncol. 2022 Nov 3;52(11):1358. doi: 10.1093/jjco/hyac156. Jpn J Clin Oncol. 2022. PMID: 36124846 Free PMC article. No abstract available.

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.

Keywords: Epidemiology; Surveillance; and End Results (SEER) database; nomogram; prognosis; sinonasal adenocarcinoma (SNAC).

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