The use of pharmacogenomics for selection of therapy in XXXX .

@entity1 @entity11833 @entity1149 @entity136 @entity319 @entity983 @entity902
INTRODUCTION: Performance status (PS) is the only known clinical predictor of outcome in @entity1 with advanced @entity1149 ( @entity1149 ), although pharmacogenomic markers may also correlate with outcome. The aim of our study was to correlate clinical and pharmacogenomic measures with overall survival. METHODS: This was an IRB approved, retrospective study in which the medical records of 50 @entity1 with advanced @entity1149 from 1998-2008 were reviewed, and gender, race, PS, and chemotherapy regimens were documented. Stromal expression of pharmacogenomic markers ( @entity319 , @entity11833  , pAKT, and @entity983 ) was measured. Clinical factors and pharmacogenomics markers were compared to overall survival using a Cox proportional hazards model. RESULTS: Forty @entity1 received @entity902 -based therapy. Median age was 65 years. Improved PS, female gender, and @entity136 therapy were significantly associated with longer overall survival (P = 0.004, P = 0.04, and P = 0.003, respectively). Age was not associated with survival. Caucasians had better overall survival in comparison to African Americans with median survival of 14.8 months versus 10.4 months (P = 0.1). @entity1 treated with @entity902 -based therapy had better survival of 15 months versus 8 months for non- @entity902 based therapy (P = 0.01). There was no significant association between any of the pharmacogenomics markers and overall survival other than in @entity1 treated with @entity902 , in whom @entity11833 negativity was strongly associated with longer survival (P = 0.007). CONCLUSION: @entity11833 negativity with @entity902 therapy, @entity136 therapy, good PS, and female gender all correlated with improved overall survival in @entity1 with advanced @entity1149 .
