Methodological issues in the development of a pharmacogenomic algorithm for warfarin dosing: comparison of two regression approaches

Pharmacogenomics. 2014 Jun;15(8):1125-32. doi: 10.2217/pgs.14.59.

Abstract

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.

Keywords: anticoagulation; multiple linear regression; multiple polynomial regression; pharmacogenomics; warfarin.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Algorithms*
  • Dose-Response Relationship, Drug
  • Female
  • Humans
  • Linear Models*
  • Male
  • Middle Aged
  • Models, Statistical
  • Pharmacogenetics*
  • Warfarin / therapeutic use*

Substances

  • Warfarin