Cao Y, Liu W, Gu D. A nomogram for predicting overall survival of patients with squamous cell carcinoma of the floor of the mouth: a population-based study.
Eur Arch Otorhinolaryngol 2023:10.1007/s00405-023-07971-5. [PMID:
37071145 DOI:
10.1007/s00405-023-07971-5]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 04/06/2023] [Indexed: 04/19/2023]
Abstract
BACKGROUND
Floor of mouth squamous cell carcinoma (SCCFOM) is a rare but aggressive malignancy with 5-year overall survival (OS) rates below 40% in published studies. However, the clinicopathological predictors of the prognosis of SCCFOM remain undefined. We aimed to establish a model to predict the survival outcomes of SCCFOM.
METHODS
We searched the Surveillance, Epidemiology, and End Results (SEER) database for patients diagnosed with SCCFOM between 2000 and 2017. Data on patient demographics, treatment modalities, and survival outcomes were retrieved. Risk factors for OS were evaluated by survival and Cox regression analyses. A nomogram for OS was developed based on the multivariate model and split the patients into high- and low-risk cohorts based on cutoff values.
RESULTS
Overall, 2014 SCCFOM patients were included in this population-based study. Multivariate Cox regression showed that age, married status, grade, American Joint Committee on Cancer stage, radiotherapy, chemotherapy, and surgery were significant risk factors for survival. A nomogram was established using the regression model. The C-indices, areas under the receiver operating characteristic curves, and calibration plots demonstrated the reliable performance of the nomogram. Patients assigned to the high-risk group had a significantly lower survival rate.
CONCLUSIONS
The nomogram predicting survival outcomes of SCCFOM patients based on clinical information showed good discriminative ability and prognostic accuracy. Our nomogram could be used to predict the survival probabilities for SCCFOM patients at different timepoints.
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