Correlating Surrogate Endpoints with Overall Survival at the Individual Patient Level in BRAFV600E-Mutated Metastatic Melanoma Patients Treated with Vemurafenib

Comparing the Efficacy of Cancer Therapies between Subgroups in Basket Trials

The need to test anticancer drugs in multiple indications has been addressed by basket trials, which are Phase I or II clinical trials involving multiple tumor subtypes and a single master protocol. Basket trials typically involve few patients per type, making it challenging to rigorously compare responses across types. We describe the use of permutation testing to test for differences among subgroups using empirical null distributions and the Benjamini-Hochberg procedure to control for false discovery. We apply the approach retrospectively to tumor-volume changes and progression-free survival in published basket trials for neratinib, larotrectinib, pembrolizumab, and imatinib and uncover examples of therapeutic benefit missed by conventional binomial testing. For example, we identify an overlooked opportunity for use of neratinib in lung cancers carrying ERBB2 Exon 20 mutations. Permutation testing can be used to design basket trials but is more conservatively introduced alongside established approaches to enrollment such as Simon’s two-stage design.

Basket clinical trials simultaneously test a single drug in multiple tumor subtypes, but statistical challenges limit the comparison of responses across subtypes. We describe a rigorous approach to permutation testing using empirical null distributions that can identify previously overlooked opportunities for use of targeted therapy in genetically defined cancer subtypes.

Impact of depth of response on survival in patients treated with cobimetinib ± vemurafenib: pooled analysis of BRIM-2, BRIM-3, BRIM-7 and coBRIM

BACKGROUND

This pooled analysis investigated the prognostic value of depth of response in two cohorts of patients with BRAF^V600-mutated metastatic melanoma treated with vemurafenib or cobimetinib plus vemurafenib.

METHODS

The data were pooled from BRIM-2, BRIM-3, BRIM-7 and coBRIM. Association of depth of response with survival was estimated by Cox proportional hazards regression, adjusted for clinically relevant covariates. Depth of response was analysed in previously identified prognostic subgroups based on disease characteristics and gene signatures.

RESULTS

Greater tumour reduction and longer time to maximal response were significantly associated with longer progression-free survival (PFS) and overall survival (OS) when evaluated as continuous variables. Patients with the deepest responses had long-lasting survival outcomes (median PFS: 14 months; OS: 32 months with vemurafenib; not estimable with cobimetinib plus vemurafenib). Cobimetinib plus vemurafenib improved depth of response versus vemurafenib monotherapy regardless of other prognostic factors, including gene signatures.

CONCLUSIONS

Greater depth of response was associated with improved survival, supporting its utility as a measure of treatment efficacy in melanoma and further evaluation of its incorporation into existing prognostic models. Cobimetinib plus vemurafenib improved outcomes across quartiles of response regardless of prognostic factors or gene signatures and provided durable survival benefits in patients with deep responses.

The Role of Neoadjuvant Trials in Drug Development for Solid Tumors

The relatively low success rate of phase II oncology trials in predicting success of novel drugs in phase III trials and in gaining regulatory approval may be due to reliance on the endpoint of response rate defined by the RECIST. The neoadjuvant treatment paradigm allows the antitumor activity of a novel therapy to be determined on a pathologic basis at the time of surgery instead of by RECIST, which was not developed to guide clinical decision making or correlate with long-term outcomes. Indeed, the FDA endorsed pathologic complete response (pCR) as a surrogate for overall survival (OS) in early-stage breast cancer and granted accelerated approval to pertuzumab based on this endpoint. We propose that pCR is a biologically rational method of determining treatment effect that may be more likely to predict OS. We discuss some advantages of the neoadjuvant trial design, review the use of neoadjuvant therapy as standards of care, and consider the neoadjuvant platform as a method for drug development. Clin Cancer Res; 22(10); 2323-8. ©2016 AACR.