Renfro, Lindsay A.

3640 Background: Prior economic analysis of a 12-gene assay (Oncotype DX), compared with patterns of care reported in the NCCN database of patients with stage II, T3, DNA mismatch repair proficient (MMR-P) colon cancer, predicted that the assay would save medical costs and improve patient well-being (Hornberger et al. Value Health 2012). This study assessed the validity of those findings with actual adjuvant chemotherapy (aCT) recommendations. Methods: Outcomes and costs were estimated for patients with stage II, T3, MMR-P colon cancer using a Markov model. A study of 141 patients from 17 sites in the Mayo Clinic Cancer Research Consortium collected data on aCT recommended before and after knowledge of the 12-gene assay results (Srivastava et al. abstract). Quality-adjusted life years (QALY) and medical resource use after recurrence were computed using guideline-validated state-transition probability estimation methods. Risk of progression and incidence of adverse events with different aCT regimens were based on published literature. Drug and administration costs for aCT were obtained from 2012 Medicare fee schedules. One-way sensitivity analyses were conducted to evaluate parameter influence on economic impact. Results: After receiving the 12-gene assay results, physician recommendations in favor of aCT decreased 22% (95% CI 11%-32%; McNemar test p<0.001) from 73 (52%) to 42 (30%) patients. Oxaliplatin aCT and 5-FU monotherapy recommendations each declined 11%. Average aCT costs decreased $3,228 for drugs, $750 for administration, and $3,168 for adverse events management. Overall, average total direct medical costs decreased $1,683. The net effect on average patient well-being was a gain of 0.102 QALYs. Total change in medical costs is most influenced by the cost of death due to colon cancer, time-preference discount rate, and the change in aCT recommendations. Savings are expected to persist even if the cost of oxaliplatin dropped by >75% due to generic substitution. Conclusions: The 12-gene assayhas been shown to alter aCT recommendations for patients with stage II, T3, MMR-P colon cancer. This study provides real-world confirmation that these aCT changes reduce direct medical costs and improve patient well-being.

LBA1 The full, final text of this abstract will be available at abstracts.asco.org at 7:30 AM (EDT) on Sunday, June 4, 2017, and in the Annual Meeting Proceedings online supplement to the June 20, 2017, issue of the Journal of Clinical Oncology. Onsite at the Meeting, this abstract will be printed in the Sunday edition of ASCO Daily News.

Recently, several study designs incorporating treatment effect assessment in biomarker‐based subpopulations have been proposed. Most statistical methodologies for such designs focus on the control of type I error rate and power. In this paper, we have developed point estimators for clinical trials that use the two‐stage adaptive enrichment threshold design. The design consists of two stages, where in stage 1, patients are recruited in the full population. Stage 1 outcome data are then used to perform interim analysis to decide whether the trial continues to stage 2 with the full population or a subpopulation. The subpopulation is defined based on one of the candidate threshold values of a numerical predictive biomarker. To estimate treatment effect in the selected subpopulation, we have derived unbiased estimators, shrinkage estimators, and estimators that estimate bias and subtract it from the naive estimate. We have recommended one of the unbiased estimators. However, since none of the estimators dominated in all simulation scenarios based on both bias and mean squared error, an alternative strategy would be to use a hybrid estimator where the estimator used depends on the subpopulation selected. This would require a simulation study of plausible scenarios before the trial.