Frontiers in Medicine (Feb 2023)
A nomogram for predicting survival in patients with skin non-keratinizing large cell squamous cell carcinoma: A study based on the Surveillance, Epidemiology, and End Results database
Abstract
IntroductionThis study aimed to develop and validate a nomogram for predicting cancer-specific survival (CSS) in patients with non-keratinized large cell squamous cell carcinoma (NKLCSCC) at 3, 5, and 8 years after diagnosis.MethodsData on SCC patients were collected from the Surveillance, Epidemiology, and End Results database. Training (70%) and validation (30%) cohorts were generated using random selection of patients. Independent prognostic factors were selected using the backward stepwise Cox regression model. To predict the CSS rates in patients with NKLCSCC at 3, 5, and 8 years after diagnosis, all of the factors were incorporated into the nomogram. Indicators such as the concordance index (C-index), area under the time-dependent receiver operating characteristic curve (AUC), net reclassification index (NRI), integrated discrimination improvement (IDI), calibration curve, and decision-curve analysis (DCA) were then used to validate the performance of the nomogram.ResultsThis study included 9,811 patients with NKLCSCC. Twelve prognostic factors were identified by Cox regression analysis in the training cohort, which were age, number of regional nodes examined, number of positive regional nodes, sex, race, marital status, American Joint Committee on Cancer (AJCC) stage, surgery status, chemotherapy status, radiotherapy status, summary stage, and income. The constructed nomogram was validated both internally and externally. The nomogram had good discrimination ability, as indicated by the comparatively high C-indices and AUC values. The nomogram was properly calibrated, as indicated by the calibration curves. Our nomogram was superior to the AJCC model, as illustrated by its superior NRI and IDI values. DCA curves indicated the clinical usability of the nomogram.ConclusionThe first nomogram for prognosis predictions of patients with NKLCSCC has been developed and verified. Its performance and usability demonstrated that the nomogram could be utilized in clinical settings. However, additional external verification is still required.
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