Construction and validation of a novel web-based nomogram for primary ocular adnexal lymphoma: a real-world analysis based on the Surveillance, Epidemiology, and End Results database.

Background: The occurrence rate of primary ocular adnexal lymphoma (POAL) is relatively low, and estimation of prognosis of these patients poses significant challenges. This study aims to investigate the independent prognostic factors of POAL patients and establish a predictive model to provide clinical data for the formulation of standardized treatment plans.

Methods: We conducted a retrospective analysis by extracting data of POAL patients diagnosed between 2000 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database. The enrolled patients were randomly divided into a training group and a testing group in a 7:3 ratio. To identify independent prognostic factors, we used both univariate and multivariate Cox regression analyses. Conditional survival (CS) pattern of these patients was analyzed. We formulated a nomogram model to forecast survival rates at intervals of 2, 5, 10, and 15 years. The reliability of the model's predictions was assessed through the concordance index (C-index) and the area under the receiver operating characteristic (ROC) curve (AUC). Moreover, we designed an online survival calculator using the nomogram model.

Results: The study ultimately analyzed 3,324 patients with POAL, of which 2,327 and 997 were respectively assigned to a training group and a testing group. Important prognostic factors including age, sex, tumor site, tumor histology, coexistence of other malignancy, surgery, radiotherapy (RT), and marital status were identified. Based on these predictors, a novel nomogram model was successfully developed with excellent predictive performance, which can also be accessed on the website: https://helloshinyweb.shinyapps.io/eye_dynamic_nomogram/. The calibration curves demonstrated good consistency between the predicted and actual survival rates. Additionally, the C-index and AUC demonstrated good discriminative ability.

Conclusions: This study has successfully developed and validated a prognostic nomogram model that accurately predicts the survival rate of patients with POAL. The model proves invaluable in enabling clinical doctors to assess patients' risk factors and formulate personalized treatment strategies, thereby enhancing survival assessment and clinical management for POAL patients.