| الوصف: |
Abstract Purpose Eyelid sebaceous gland carcinoma (SGC) is a malignancy with fatal risk, high recurrence rate, and pagetoid spread. Thus, recurrence risk prediction and prompt treatment are extremely important. This study aimed to develop a nomogram to predict SGC recurrence based on potential risk factors. Methods We conducted a retrospective study to train and test a nomogram based on the clinical data of 391 patients across our hospital (304) and other grass‐roots hospitals (87). After Cox regression, predictors included in the nomogram were selected, and sensitivity, specificity, concordance index (C‐index), etc., were calculated to test their discrimination ability. Results After a median follow‐up period of 4.12 years, SGC recurred in 52 (17.11%) patients. The 1‐, 2‐, and 5‐year recurrence‐free survival rates were 88.3%, 85.4%, and 81.6%, respectively. We examined five risk factors, such as lymph node metastasis at initial diagnosis (hazard ratio [HR], 2.260; 95% confidence interval [CI], 1.021–5.007), Ki67 (HR, 1.036; 95% CI, 1.020–1.052), histology differentiation degree (HR, 2.274; 95% CI, 1.063–4.865), conjunctival pagetoid infiltration (HR, 2.100; 95% CI, 1.0058–4.167), and orbital involvement (HR, 4.764; 95% CI, 1.436–15.803). The model had good discrimination in both internal and external test sets. The model had good discrimination in both internal and external test sets. The sensitivity of the internal test and external test set were 0.722 and 0.806, respectively, and specificity of the internal test and external test set were 0.886 and 0.893, respectively. Conclusion We examined the potential risk factors for eyelid SGC recurrence and constructed a nomogram, which complements the TNM system in terms of prediction, indicating that our nomogram has the potential to reach clinical significance. This nomogram has the potential to assist healthcare practitioners in promptly detecting patients who are at an elevated risk and in tailoring clinical interventions to meet their individualized needs. |
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