角膜移植手术是治疗角膜病变重要且有效的手段。但对眼表功能完全失代偿、多次角膜移植排斥等类型的患者，常规同种异体角膜移植手术成功率却非常低。对于这类患者，人工角膜植入术成为复明的新希望。随着人工角膜的设计和植入方式的不断改进，人工角膜的功效及优点已渐渐突显。目前，波士顿I型(领扣型)人工角膜在全球范围内应用最为广泛。现就波士顿I型人工角膜的基本特征、临床应用及未来发展等方面进行阐述。

The corneal transplantation is an effective option for visually impaired patients with keratopathy to restore vision function. However, the success rate of allograft keratoplasty is still very low for those patients with end-stage ocular surface or repeated corneal graft rejection. For those patients, artificial keratoplasty might be a promising alternative option. The efficacy and advantages of artificial keratoplasty have been gradually highlighted, after consistent improvement of the product design and implantation procedure. Nowadays, the Boston type I (collar button) corneal prosthesis is the most widely used product around the world. In this review, the history, indications, postoperative complications and future prospect of Boston type I corneal prosthesis will be summarized.

Purpose: To develop a survival prediction model for primary conjunctival malignant tumors.

Methods: Detailed information on cases diagnosed with primary conjunctival malignant tumors from 2000 to 2019 was collected from SEER database.Subsequently,  cases meeting the inclusion criteria were randomly assigned to either the development group (1,216 cases) or validation group (608 cases). Relevant risk factors affecting overall survival (OS) were identified using Cox proportional hazards regression analysis. A nomogram was constructed to predict the 1-year, 3-year, and 5-year survival rates. The concordance index (C index) was calculated to assess the predictive power of the model. Receiver operating characteristic curves (ROC curves) and calibration curves were plotted. The area under the curve (AUC) was measured. Decision curve analysis (DCA) was also applied.

Results: The overall survival rate was 77.8%. Statistically significant differences in the survival time distribution were observed among groups based on age (P < 0.001), histology (P < 0.001), and stage (P = 0.01). According to the multivariate analysis, patients with lymphoma, younger age, and localized lesions exhibited better survival outcomes. The C-index of the constructed model was 0.79. In the training group, the AUC values for predicting 1-year, 3-year, and 5-year mortality were 0.824, 0.796, and 0.815, respectively. In the validation group, tge corresponding AU values were 0.750, 0.820, and 0.838. The DCA results demonstrated a significant advantage of the model, while the calibration plots indicated that the predicted OS was in good agreement with the actual OS in both groups. 

Conclusions: This study presents a satisfying survival prediction model for malignant conjunctival tumors.

Purpose: To develop a survival prediction model for primary conjunctival malignant tumors.

Methods: Detailed information on cases diagnosed with primary conjunctival malignant tumors from 2000 to 2019 was collected from SEER database.Subsequently,  cases meeting the inclusion criteria were randomly assigned to either the development group (1,216 cases) or validation group (608 cases). Relevant risk factors affecting overall survival (OS) were identified using Cox proportional hazards regression analysis. A nomogram was constructed to predict the 1-year, 3-year, and 5-year survival rates. The concordance index (C index) was calculated to assess the predictive power of the model. Receiver operating characteristic curves (ROC curves) and calibration curves were plotted. The area under the curve (AUC) was measured. Decision curve analysis (DCA) was also applied.

Results: The overall survival rate was 77.8%. Statistically significant differences in the survival time distribution were observed among groups based on age (P < 0.001), histology (P < 0.001), and stage (P = 0.01). According to the multivariate analysis, patients with lymphoma, younger age, and localized lesions exhibited better survival outcomes. The C-index of the constructed model was 0.79. In the training group, the AUC values for predicting 1-year, 3-year, and 5-year mortality were 0.824, 0.796, and 0.815, respectively. In the validation group, tge corresponding AU values were 0.750, 0.820, and 0.838. The DCA results demonstrated a significant advantage of the model, while the calibration plots indicated that the predicted OS was in good agreement with the actual OS in both groups. 

Conclusions: This study presents a satisfying survival prediction model for malignant conjunctival tumors.