Summary: | Importance: Orbital invasion occurs in some periocular squamous cell carcinoma (SCC), compromising surgical outcomes, and prognoses of patients. To date, however, there are no validation studies on the clinical features related to orbital invasion in patients with periocular SCC.Objective: To explore clinical features that may be associated with orbital invasion and build a model for predicting the risk of orbital invasion.Design, Setting, and Participants: In this retrospective mono-center case-control study, 90 patients with periocular SCC were treated at the Ninth People's Hospital Shanghai Jiao Tong University School of Medicine from January 2005 to August 2019. “Case” is defined as a SCC patient with orbit invasion prior to operation. “Exposure” is defined as the different sites of lesion.Main Outcomes and Measures: Clinical features, including “time to relapse after surgery,” were collected. Multivariate logistic regression analysis was applied to identify the independent risk clinical features associated with orbital invasion, which was then incorporated into a nomogram.Results: Of the 90 patients included in this study, 33 patients (36.7%) had orbital invasion. 14 of the 33 orbit-invasive patients had local recurrence, while 11 of 57 orbit non-invasive patients had local recurrence, suggesting that orbital invasion is a risk factor for local recurrence. The multivariate binary logistic regression indicated that the lesions at the medial canthus [odds ratio (OR), 5.024, 95% CI, 1.409–17.912, P = 0.013], the age at diagnosis (10-years intervals; OR, 0.590, 95% CI, 0.412–0.844, P = 0.004), and bleeding in the lesion (OR, 3.480, 95% CI, 1.254–9.660, P = 0.017) were three preoperative clinical features significantly associated with orbital invasion.Conclusion: For periocular SCC, lesions at the medial canthus, the younger age of the patients at diagnosis, and bleeding in the lesion were the three main clinical features associated with orbital invasion. The risk score model for orbital invasion can act as a supportive tool for optimized clinical evaluation and treatment decisions.
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