Methodological Issues in the Development of a Pharmacogenomic Algorithm for Warfarin Dosing: Comparison of Two Regression Approaches

AIM: To ascertain whether multiple polynomial regression (MPR) has any advantage over multiple linear regression (MLR) in developing pharmacogenomic algorithms. MATERIALS & METHODS: Two pharmacogenomic algorithms were developed based on MPR and MLR models from a warfarin pharmacogenomic data set (derivation cohort [n = 125] and validation cohort [n = 115]). RESULTS: The MPR model showed better correlation with therapeutic dose (r = 0.62 vs 0.52); better diagnostic utility in distinguishing the warfarin-sensitive and warfarin-resistant patients (area under the receiver operating characteristic curves: 0.89 vs 0.81); and lower rate of underestimation (13.9 vs 20%) compared with the MLR model. Rate of overestimation was higher in the MPR than the MLR (10 vs 6.7%) model. CONCLUSION: The MPR approach has advantages over the MLR approach in predicting accurate and safe dose.