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. 2023 Jun 19:13:1118862.
doi: 10.3389/fonc.2023.1118862. eCollection 2023.

The clinicopathological analysis of ocular and orbit tumors in southeast of China

Yuan Lin  1   2 , Xiaodong Liu  1   2 , Yujie Zhang  1   2 , Zhiwen Xie  1   2 , Xie Fang  1   2 , Ke Shi  1   2 , Yanlin Zhong  1   2 , Shengqi Su  1   2   3 , Minqing Cai  1   2 , Huping Wu  1   2 , Shangkun Ou  1   2
Affiliations

The clinicopathological analysis of ocular and orbit tumors in southeast of China

Yuan Lin et al. Front Oncol. .

Abstract

Purpose: The purpose of this study is to describe the clinicopathologic characteristics of ocular surface and orbit tumors in the Southeast of China and explore the method to differentiate the benign and malignant masses.

Materials and methods: 3468 patients undergoing mass resection from January 2015 to December 2020 were selected as observation subjects and were classified into benign and malignant masses according to postoperative pathology. The clinicopathologic characteristics were collected, including gender, age, pathological tissue signs, and pathological signs. Multivariate Logistic regression analysis of independent risk factors of malignant mass was applied to establish a diagnostic model and the efficacy was evaluated by the subject working characteristics (ROC) curve.

Results: Benign tumors accounted for 91.5% of all cases, and malignant tumors accounted for 8.5%. The most common ocular benign tumors were nevi (24.2%), granuloma (17.1%), and cysts (16.4%). The most common ocular malignant tumors were malignant lymphoma (32.1%) and Basal cell carcinoma (20.2%). As for the histologic origin, melanocytic origin was on the list with 819 (23.6%), mesenchymal 661 (19.1%), epithelial 568 (16.3%), cystic 521 (15.0%), skin adnexal 110 (3.1%), lymphoid 94 (2.8%), and Neural 25(0.8%). Based on the gender, age, tumor location, and the pathological tissue image feature (including differentiation, structural atypia, covering epithelial, keratosis, nest structure/distribution, nuclear atypia, cytoplasmic change and nuclear division), the diagnostic model had predictive value to differentiate the benign and malignant masses.

Conclusion: Most ocular surface and orbit tumors are benign. Tumor diagnosis is relative to the patient's age, gender, tumor location, and pathologic characteristics. We generated a satisfactory diagnostic model to differential diagnosis of benign and malignant masses.

Keywords: Southeast of China; benign tumor; clinicopathologic characteristics; malignant tumor; ocular tumor.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The pathological tissue image feature of ocular benign and malignant tumor. (A) Differentiation (HE×200); (B) Structural atypia (HE×100); (C) Covering epithelium (HE×40); (D) Keratosis (HE×100); (E) Nest structure/distribution (HE×100); (F) nuclear atypia (HE×100); (G) Cytoplasmic change (HE×100); (H) nuclear division (HE×200).
Figure 2
Figure 2
The correlation heatmap of the histopathological characteristics. (*P<0.05, **P<0.01, ****P<0.0001).
Figure 3
Figure 3
Forest map of the results of binary logistic regression. The histopathological features include nuclear, nucleus plemorphism, covering epithelium, structual atypia, differentiation, the location of conjunctiva and eyelid, in addition to age and gender could be the independent diagnostic factors of the malignant tumors and tumor-like lesions. Red line: the variables with no independent predictive power (p > 0.05), blue line: the variables are showing significant independent predictive power (p < 0.01), black line: the variables are showing a specific independent predictive power (0.05 > p > 0.01).
Figure 4
Figure 4
Receiver operating characteristic (ROC) curve analysis. The ROC curve value was 0.884(0.860-0.907, P<0.001).
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