A nomogram model for predicting ocular GVHD following allo-HSCT based on risk factors

Abstract

Objective To develop and validate a nomogram model for predicting chronic ocular graft-versus-host disease (coGVHD) in patients after allogenic haematopoietic stem cell transplantation (allo-HSCT). Methods This study included 61 patients who survived at least 100 days after allo-HSCT. Risk factors for coGVHD were screened using LASSO regression, then the variables selected were subjected to logistic regression. Nomogram was established to further confirm the risk factors for coGVHD. Receiver operating characteristic (ROC) curves were constructed to assess the performance of the predictive model with the training and test sets. Odds ratios and 95% confidence intervals (95% CIs) were calculated by using logistic regression analysis. Results Among the 61 patients, 38 were diagnosed with coGVHD. We selected five texture features: lymphocytes (LYM) (OR = 2.26), plasma thromboplastin antecedent (PTA) (OR = 1.19), CD3 + CD25 + cells (OR = 1.38), CD3 + HLA-DR + cells (OR = 0.95), and the ocular surface disease index (OSDI) (OR = 1.44). The areas under the ROC curve (AUCs) of the nomogram with the training and test sets were 0.979 (95% CI, 0.895–1.000) and 0.969 (95% CI, 0.846–1.000), respectively.And the Hosmer–Lemeshow test was nonsignificant with the training (p = 0.9949) and test sets (p = 0.9691). Conclusion We constructed a nomogram that can assess the risk of coGVHD in patients after allo-HSCT and help minimize the irreversible loss of vision caused by the disease in high-risk populations.