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

Area of Science:

• Hematology
• Ophthalmology
• Transplantation Medicine

Background:

• Chronic ocular graft-versus-host disease (coGVHD) is a significant complication following allogeneic haematopoietic stem cell transplantation (allo-HSCT).
• Early identification and risk stratification of patients developing coGVHD are crucial for timely intervention and preventing irreversible vision impairment.

Purpose of the Study:

• To develop and validate a predictive nomogram model for chronic ocular graft-versus-host disease (coGVHD) in patients undergoing allo-HSCT.
• To identify key risk factors associated with coGVHD development post-transplantation.

Main Methods:

• A cohort of 61 patients surviving at least 100 days post-allo-HSCT was analyzed.
• LASSO regression identified risk factors, followed by logistic regression and nomogram construction.
• Model performance was assessed using Receiver Operating Characteristic (ROC) curves and the Hosmer-Lemeshow test.

Main Results:

• The nomogram incorporated lymphocytes, plasma thromboplastin antecedent, CD3+CD25+ cells, CD3+HLA-DR+ cells, and the Ocular Surface Disease Index (OSDI).
• The model demonstrated high predictive accuracy with Area Under the Curve (AUC) values of 0.979 for the training set and 0.969 for the test set.
• The Hosmer-Lemeshow test indicated good model fit for both training (p=0.9949) and test sets (p=0.9691).

Conclusions:

• A validated nomogram effectively predicts the risk of coGVHD in patients post-allo-HSCT.
• This predictive tool can assist clinicians in managing high-risk individuals and mitigating vision loss.
• Further research may refine this model for broader clinical application in transplantation centers.