PCN170 - Estimating the Voi of Pivotal Studies Towards Predictive Biomarkers of High Dose Alkylating Chemotherapy in Triple Negative Breast Cancer

Abstract

Objectives: To estimate the expected benefits from a pivotal randomised controlled trial of predictive biomarkers for high dose alkylating chemotherapy (HDAC) in triple negative breast cancer (TNBC) and to inform decisions about the design and priority of further studies. Methods: A markov decision model compared treating 40- years old TNBC women with HDAC based on four predictive biomarker strategies: 1) BRCA1-like by MLPA testing; 2) BRCA1-like by aCGH testing, 3) strategy 1 followed by XIST and 53BP1 testing; and 4) strategy 2 followed by XIST and 53BP1 testing, versus treating all patients with standard chemotherapy. A Dutch societal perspective and a 20-year time horizon were used. Input data came from literature and expert opinions. We assessed four primary outcomes: the expected value of (partial) perfect information (EV (P) PI), the expected value of sample information (EVSI) and the expected net benefit of sampling (ENBS) for the ongoing pivotal TNM trial (NCT01057069) and/or potential future studies. Results: The population EVPI was €663 million (M). The EVPPI suggests prioritizing further research towards effectiveness parameters, specifically prevalence and positive predictive value of the biomarkers; response rates in biomarker negative patients and TNBC unclassified patients, which are estimated to collectively have a value of information of circa €630M. The value of further research on transition probabilities is estimated at € 41M, followed by utilities at €34M and costs at €34M. Further information on transition probabilities could be gathered from the TNM trial and that of effectiveness parameters and costs from accompanying studies to this trial, altogether estimated to have an ENBS of €657 M. Conclusions: Further research on predictive biomarkers for HDAC should focus on gathering transition probability data from the current TNM trial, and on accompanying studies to derive data on other effectiveness parameters and costs.