The ability of genomics to match precise information about the molecular biology of a cancer with the available present and future therapeutics offers tremendous promise for cancer patients. Unfortunately, few genomic-based tests or treatments are available today to benefit these patients. Using a pharmacogenetic test adoption model, previously introduced to model the adoption of HLA-B*5701 testing for abacavir hypersensitivity, six oncology biomarkers, HER2, BCR-ABL quantitation, KRAS mutation, UGT1A1, CYP2D6 for tamoxifen and EGFR expression, test adoption patterns are explored. Developmental milestones and emerging scientific knowledge relating to each of the biomarkers are discussed in the context of their impact on test ordering patterns. Through analysis of the adoption patterns of multiple cancer biomarkers, a pharmacogenetic model emerges which appears to be applicable in five of the six biomarkers. This model may be useful in predicting adoption patterns of new markers and in providing guidance to drug and test developers introducing personalized medicine applications.
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Faruki et al. (2010) studied this question.
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