Treatment of previously untreated patients (PUPs) with severe haemophilia A is complicated by the formation of inhibitors. Prediction of PUPs with high risk is important to allow altering treatment with the intention to reduce the occurrence of inhibitors. An unselected multicentre cohort of 825 PUPs with severe haemophilia A (FVIII<0.01 IU mL(-1) ) was used. Patients were followed until 50 exposure days (EDs) or inhibitor development. All predictors of the existing prediction model including three new potential predictors were studied using multivariable logistic regression. Model performance was quantified [area under the curve (AUC), calibration plot] and internal validation (bootstrapping) was performed. A nomogram for clinical application was developed. Of the 825 patients, 225 (28%) developed inhibitors. The predictors family history of inhibitors, F8 gene mutation and an interaction variable of dose and number of EDs of intensive treatment were independently associated with inhibitor development. Age and reason for first treatment were not associated with inhibitor development. The AUC was 0.69 (95% CI 0.65-0.72) and calibration was good. An improved prediction model for inhibitor development and a nomogram for clinical use were developed in a cohort of 825 PUPs with severe haemophilia A. Clinical applicability was improved by combining dose and duration of intensive treatment, allowing the assessment of the effects of treatment decisions on inhibitor risk and potentially modify treatment.
Keywords: antibody formation; clinical prediction model; haemophilia A; predictors; risk factors.
© 2014 John Wiley & Sons Ltd.