Predicting alloimmunization risk in transfusion patients: A multivariate model and simplified scoring system

Red blood cell (RBC) alloimmunization is a clinically important complication in transfusion-dependent patients, particularly those with hemoglobinopathies and hematologic malignancies. It increases the risk of hemolytic reactions and complicates transfusion support. Despite the high alloimmunization rate in tranfusion-dependent patients in Saudi Arabia, most existing studies remain observational and lack an actionable predictive framework.This study aimed to develop a multivariate predictive model and a simplified risk scoring system to forecast alloimmunization risk in transfusion recipients at King Abdulaziz University Hospital (KAUH), Jeddah.

A retrospective observational study was conducted using data from 3316 patients who received blood transfusions between September and November 2024. Clinical, demographic, and transfusion-related variables were analyzed. Logistic regression was used to identify independent predictors of alloimmunization. A point-based scoring system was derived from the model and validated.

The overall alloimmunization rate was 5.0 %. RhD negative status, female gender, hematological diagnosis, and cumulative transfusion exposure were significantly associated with increased alloimmunization risk. A simplified point-based scoring system stratified patients into low-, moderate-, and high-risk categories, with corresponding alloimmunization rates of 3.7 %, 11.4 %, and 35.7 %, respectively. The model demonstrated acceptable discriminative performance (AUC = 0.73).

This study identified key clinical predictors of RBC alloimmunization and introduced a practical risk scoring tool to support personalized transfusion strategies. Integration of this tool into routine clinical practice can facilitate early identification of high-risk patients and guide targeted mitigation strategies such as blood group genotyping and extended antigen matching.