The clinical trials landscape for GBM is characterized by long development times, inadequate dissemination of information, suboptimal go/no-go decision making, and low patient participation.

Purpose: Deviations from proportional hazards (DPHs), which may be more prevalent in the era of precision medicine and immunotherapy, can lead to underpowered trials or misleading conclusions. We used a meta-analytic approach to estimate DPHs across cancer trials, investigate associated factors, and evaluate data-analysis approaches for future trials.Experimental Design: We searched PubMed for phase III trials in breast, lung, prostate, and colorectal cancer published in a preselected list of journals between 2014 and 2016 and extracted individual patient-level data (IPLD) from Kaplan-Meier curves. We re-analyzed IPLD to identify DPHs. Potential efficiency gains, when DPHs were present, of alternative statistical methods relative to standard log-rank based analysis were expressed as sample-size requirements for a fixed power level.Results: From 152 trials, we obtained IPLD on 129,401 patients. Among 304 Kaplan-Meier figures, 75 (24.7%) exhibited evidence of DPHs, including eight of 14 (57%) KM pairs from immunotherapy trials. Trial type [immunotherapy, odds ratio (OR), 4.29; 95% confidence interval (CI), 1.11-16.6], metastatic patient population (OR, 3.18; 95% CI, 1.26-8.05), and non-OS endpoints (OR, 3.23; 95% CI, 1.79-5.88) were associated with DPHs. In immunotherapy trials, alternative statistical approaches allowed for more efficient clinical trials with fewer patients (up to 74% reduction) relative to log-rank testing.Conclusions: DPHs were found in a notable proportion of time-to-event outcomes in published clinical trials in oncology and was more common for immunotherapy trials and non-OS endpoints. Alternative statistical methods, without proportional hazards assumptions, should be considered in the design and analysis of clinical trials when the likelihood of DPHs is high.

Background: Quantitative MRI (qMRI) metrics reflect microstructural skeletal muscle changes secondary to denervation and may correspond to conventional electromyography (EMG) assessments of motor unit recruitment (MUR) and denervation. Hypothesis: Differences in quantitative T 2 , diffusion-based apparent fiber diameter (AFD), and fat fraction (FF) exist between EMG grades, in patients with clinically suspected neuropathy of the brachial plexus. Study Type: Prospective. Population: A total of 30 subjects (age = 37.5 AE 17.5, 21M/9F) with suspected brachial plexopathy. Field Strength/Sequence: 3-Tesla; qMRI using fast spin echo (T 2 -mapping), multi-b-valued diffusion-weighted echo planar imaging (for AFD), and dual-echo Dixon gradient echo (FF-mapping) sequences. Assessment: qMRI values were compared against EMG grades (MUR and denervation). qMRI values (T 2 , AFD, and FF) were obtained for five regional shoulder muscles. A 4-point scale was used for MUR/denervation severity. Statistical Tests: Linear mixed models and least-squares pairwise comparisons were used to evaluate qMRI differences between EMG grades. Predictive accuracy of EMG grades from qMRI was quantified by 10-fold cross-validated logistic models. A P value < 0.05 was considered statistically significant. Results: Mean (95% confidence interval) qMRI for "full" MUR were T 2 = 39.40 msec (35.72-43.08 msec), AFD = 78.35 μm (72.52-84.19 μm), and FF = 4.54% (2.11-6.97%). Significant T 2 increases (+8.36 to +14.67 msec) and significant AFD decreases (À11.04 to À21.58 μm) were observed with all abnormal MUR grades as compared to "full" MUR. Significant changes in both T 2 and AFD were observed with increased denervation (+9.59 to +15.04 msec, À16.25 to À18.66 μm). There were significant differences in FF between some MUR grades (À1.45 to +2.96%), but no significant changes were observed with denervation (P = 0.089-0.662). qMRI prediction of abnormal MUR or denervation was strong (mean accuracy = 0.841 and 0.810, respectively) but moderate at predicting individual grades (accuracy = 0.492 and 0.508, respectively). Data Conclusion: Quantitative T 2 and AFD differences were observed between EMG grades in assessing muscle denervation. Level of Evidence: 2 Technical Efficacy: Stage 1

No abstract

Background Understanding the value of randomization is critical in designing clinical trials. Here, we introduce a simple and interpretable quantitative method to compare randomized designs versus single-arm designs using indication-specific parameters derived from the literature. We demonstrate the approach through application to phase II trials in newly diagnosed glioblastoma (ndGBM). Methods We abstracted data from prior ndGBM trials and derived relevant parameters to compare phase II randomized controlled trials (RCTs) and single-arm designs within a quantitative framework. Parameters included in our model were (i) the variability of the primary endpoint distributions across studies, (ii) potential for incorrectly specifying the single-arm trial’s benchmark, and (iii) the hypothesized effect size. Strengths and weaknesses of RCT and single-arm designs were quantified by various metrics, including power and false positive error rates. Results We applied our method to show that RCTs should be preferred to single-arm trials for evaluating overall survival in ndGBM patients based on parameters estimated from prior trials. More generally, for a given effect size, the utility of randomization compared with single-arm designs is highly dependent on (i) interstudy variability of the outcome distributions and (ii) potential errors in selecting standard of care efficacy estimates for single-arm studies. Conclusions A quantitative framework using historical data is useful in understanding the utility of randomization in designing prospective trials. For typical phase II ndGBM trials using overall survival as the primary endpoint, randomization should be preferred over single-arm designs.