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Objectives  To evaluate the impact of a genomic classifier ( GC ) test for predicting metastasis risk after radical prostatectomy ( RP ) on urologists' decision‐making about adjuvant treatment of patients with high‐risk prostate cancer.    Subjects and Methods  Patient case history was extracted from the medical records of each of the 145 patients with  pT3  disease or positive surgical margins ( PSMs ) after  RP  treated by six high‐volume urologists, from five community practices.  GC  results were available for 122 (84%) of these patients.  US  board‐certified urologists ( n  = 107) were invited to provide adjuvant treatment recommendations for 10 cases randomly drawn from the pool of patient case histories. For each case, the study participants were asked to make an adjuvant therapy recommendation without (clinical variables only) and with knowledge of the  GC  test results. Recommendations were made without knowledge of other participants' responses and the presentation of case histories was randomised to minimise recall bias.    Results  A total of 110 patient case histories were available for review by the study participants. The median patient age was 62 years, 71% of patients had  pT3  disease and 63% had  PSMs . The median (range) 5‐year predicted probability of metastasis by the  GC  test for the cohort was 3.9 (1–33)% and the  GC  test classified 72% of patients as having low risk for metastasis. A total of 51 urologists consented to the study and provided 530 adjuvant treatment recommendations without, and 530 with knowledge of the  GC  test results. Study participants performed a mean of 130  RPs /year and 55% were from community‐based practices. Without  GC  test result knowledge, observation was recommended for 57% ( n  = 303), adjuvant radiation therapy ( ART ) for 36% ( n  = 193) and other treatments for 7% ( n  = 34) of patients. Overall, 31% (95%  CI : 27–35%) of treatment recommendations changed with knowledge of the  GC  test results. Of the  ART  recommendations without  GC  test result knowledge, 40% ( n  = 77) changed to observation (95%  CI : 33–47%) with this knowledge. Of patients recommended for observation, 13% ( n  = 38 [95%  CI : 9–17%]) were changed to  ART  with knowledge of the  GC  test result. Patients with low risk disease according to the  GC  test were recommended for observation 81% of the time ( n  = 276), while of those with high risk, 65% were recommended for treatment ( n  = 118;  P  < 0.001). Treatment intensity was strongly correlated with the  GC ‐predicted probability of metastasis ( P  < 0.001) and the  GC  test was the dominant risk factor driving decisions in multivariable analysis (odds ratio 8.6, 95%  CI : 5.3–14.3%;  P  < 0.001).    Conclusions  Knowledge of  GC  test results had a direct effect on treatment strategies after surgery. Recommendations for observation increased by 20% for patients assessed by the  GC  test to be at low risk of metastasis, whereas recommendations for treatment increased by 16% for patients at high risk of metastasis. These results suggest that the implementation of genomic testing in clinical practice may lead to significant changes in adjuvant therapy decision‐making for high‐risk prostate cancer.

Effect of a genomic classifier test on clinical practice decisions for patients with high‐risk prostate cancer after surgery