Objective: To investigate the added value of questionnaire-based predictors to existing prediction models for low haemoglobin (Hb) deferral in whole blood donors.
Background: Prediction models for Hb deferral risk can be applied in the invitation process of donors for a blood donation. Existing prediction models are based on routinely collected data. The model performance might be improved by the addition of predictive factors.
Methods: The added value of food consumption, smoking, physical activity, ethnicity and menstruation in the prediction of Hb deferral was assessed by comparing the existing models with extended models using the following measures: model X2 , concordance (c)-statistic and net reclassification improvement (NRI).
Results: Addition of one candidate predictor to the models did not substantially improve the model performance. Addition of multiple new candidate predictors significantly increased the model X2 (from 137 to 159 for men, and from 157 to 199 for women) and resulted in a non-significant increase of the c-statistic (from 0.85 to 0.87 for men, and from 0.78 to 0.81 for women). The NRI for men was 11.4% and for women 1.5% after addition of multiple predictors.
Conclusion: Addition of lifestyle behaviours, ethnicity or menstruation to prediction models for low Hb deferral in whole blood donors improved the model performance, but not substantially. For easy use in practice, we do not recommend addition of the investigated predictors to the prediction models.
Keywords: donor deferral; haemoglobin; lifestyle behaviours; prediction model; whole blood donors.
© 2019 British Blood Transfusion Society.