Mandrekar, Sumithra J.

Key Points The addition of sorafenib to chemotherapy for older adults with FLT3-ITD mutated AML is safe and may improve overall survival.

Abstract Previous preclinical studies and a phase I clinical trial suggested that myo-inositol may be a safe and effective lung cancer chemopreventive agent. We conducted a randomized, double blind, placebo-controlled phase IIb study to determine the chemopreventive effects of myo-inositol in smokers with bronchial dysplasia. Smokers with ≥1 site of dysplasia identified by autofluorescence bronchoscopy-directed biopsy were randomly assigned to receive oral placebo or myo-inositol, 9 g once a day for 2 weeks, and then twice a day for 6 months. The primary endpoint was change in dysplasia rate after 6 months of intervention on a per-participant basis. Other trial endpoints reported herein include Ki-67 labeling index, blood and bronchoalveolar lavage fluid (BAL) levels of proinflammatory, oxidant/antioxidant biomarkers, and an airway epithelial gene expression signature for PI3K activity. Seventy-four (n = 38 myo-inositol and n = 36 placebo) participants with a baseline and 6-month bronchoscopy were included in all efficacy analyses. The complete response and the progressive disease rates were 26.3% versus 13.9% and 47.4% versus 33.3%, respectively, in the myo-inositol and placebo arms (P = 0.76). Compared with placebo, myo-inositol intervention significantly reduced IL6 levels in BAL over 6 months (P = 0.03). Among those with a complete response in the myo-inositol arm, there was a significant decrease in a gene expression signature reflective of PI3K activation within the cytologically normal bronchial airway epithelium (P = 0.002). The heterogeneous response to myo-inositol suggests a targeted therapy approach based on molecular alterations is needed in future clinical trials to determine the efficacy of myo-inositol as a chemopreventive agent. Cancer Prev Res; 9(12); 906–14. ©2016 AACR.

Phase I oncology trials are designed to identify a safe dose with an acceptable toxicity profile. The dose is typically determined based on the probability of severe toxicity observed during the first treatment cycle, although patients continue to receive treatment for multiple cycles. In addition, the toxicity data from multiple types and grades are typically summarized into a single binary outcome of dose‐limiting toxicity. A novel endpoint, the total toxicity profile, was previously developed to account for the multiple toxicity types and grades. In this work, we propose to account for longitudinal repeated measures of total toxicity profile over multiple treatment cycles, accounting for cumulative toxicity during dosing‐finding. A linear mixed model was utilized in the Bayesian framework, with addition of Bayesian risk functions for decision‐making in dose assignment. The performance of this design is evaluated using simulation studies and compared with the previously proposed quasi‐likelihood continual reassessment method (QLCRM) design. Twelve clinical scenarios incorporating four different locations of maximum tolerated dose and three different time trends (decreasing, increasing, and no effect) were investigated. The proposed repeated measures design was comparable with the QLCRM when only cycle 1 data were utilized in dose‐finding; however, it demonstrated an improvement over the QLCRM when data from multiple cycles were used across all scenarios. Copyright © 2016 John Wiley & Sons, Ltd.

Background: Futility (inefficacy) interim monitoring is an important component in the conduct of phase III clinical trials, especially in life-threatening diseases. Desirable futility monitoring guidelines allow timely stopping if the new therapy is harmful or if it is unlikely to demonstrate to be sufficiently effective if the trial were to continue to its final analysis. There are a number of analytical approaches that are used to construct futility monitoring boundaries. The most common approaches are based on conditional power, sequential testing of the alternative hypothesis, or sequential confidence intervals. The resulting futility boundaries vary considerably with respect to the level of evidence required for recommending stopping the study. Purpose: We evaluate the performance of commonly used methods using event histories from completed phase III clinical trials of the Radiation Therapy Oncology Group, Cancer and Leukemia Group B, and North Central Cancer Treatment Group. Methods: We considered published superiority phase III trials with survival endpoints initiated after 1990. There are 52 studies available for this analysis from different disease sites. Total sample size and maximum number of events (statistical information) for each study were calculated using protocol-specified effect size, type I and type II error rates. In addition to the common futility approaches, we considered a recently proposed linear inefficacy boundary approach with an early harm look followed by several lack-of-efficacy analyses. For each futility approach, interim test statistics were generated for three schedules with different analysis frequency, and early stopping was recommended if the interim result crossed a futility stopping boundary. For trials not demonstrating superiority, the impact of each rule is summarized as savings on sample size, study duration, and information time scales. Results: For negative studies, our results show that the futility approaches based on testing the alternative hypothesis and repeated confidence interval rules yielded less savings (compared to the other two rules). These boundaries are too conservative, especially during the first half of the study (<50% of information). The conditional power rules are too aggressive during the second half of the study (>50% of information) and may stop a trial even when there is a clinically meaningful treatment effect. The linear inefficacy boundary with three or more interim analyses provided the best results. For positive studies, we demonstrated that none of the futility rules would have stopped the trials. Conclusion: The linear inefficacy boundary futility approach is attractive from statistical, clinical, and logistical standpoints in clinical trials evaluating new anti-cancer agents.

Abstract The treatment of patients with metastatic non–small cell lung cancer (NSCLC) is slowly evolving from empirical cytotoxic chemotherapy to personalized treatment based on specific molecular alterations. Despite this 10-year evolution, targeted therapies have not been studied adequately in patients with resected NSCLC who have clearly defined actionable mutations. The advent of next-generation sequencing has now made it possible to characterize genomic alterations in unprecedented detail. The efforts begun by The Cancer Genome Atlas project to understand the complexities of the genomic landscape of lung cancer will be supplemented further by studying a large number of tumor specimens. The Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trial (ALCHEMIST) is an NCI-sponsored national clinical trials network (NCTN) initiative to address the needs to refine therapy for early-stage NSCLC. This program will screen several thousand patients with operable lung adenocarcinoma to determine whether their tumors contain specific molecular alterations [epidermal growth factor receptor mutation (EGFR) and anaplastic lymphoma kinase rearrangement (ALK)], making them eligible for treatment trials that target these alterations. Patients with EGFR mutation or ALK gene rearrangement in their tumor will be randomized to placebo versus erlotinib or crizotinib, respectively, after completion of their standard adjuvant therapy. ALCHEMIST will also contain a large discovery component that will provide an opportunity to incorporate genomic studies to fully understand the clonal architecture, clonal evolution, and mechanisms of resistance to therapy. In this review, we describe the concept, rationale, and outline of ALCHEMIST and the plan for genomic studies in patients with lung adenocarcinoma. Clin Cancer Res; 21(24); 5439–44. ©2015 AACR.