Internal pilot designs involve conducting interim power analysis (without interim data analysis) to modify the final sample size. Recently developed techniques have been described to avoid the type I error rate inflation inherent to unadjusted hypothesis tests, while still providing the advantages of an internal pilot design. We present GLUMIP 2.0, the latest version of our free SAS/IML software for planning internal pilot studies in the general linear univariate model (GLUM) framework. The new analytic forms incorporated into the updated software solve many problems inherent to current internal pilot techniques for linear models with Gaussian errors. Hence, the GLUMIP 2.0 software makes it easy to perform exact power analysis for internal pilots under the GLUM framework with independent Gaussian errors and fixed predictors.

Purpose Addition of imatinib to intensive chemotherapy improved survival for children and young adults with Philadelphia chromosome-positive acute lymphoblastic leukemia. Compared with imatinib, dasatinib has increased potency, CNS penetration, and activity against imatinib-resistant clones. Patients and Methods Children's Oncology Group (COG) trial AALL0622 (Bristol Myers Squibb trial CA180-204) tested safety and feasibility of adding dasatinib to intensive chemotherapy starting at induction day 15 in patients with newly diagnosed Philadelphia chromosome-positive acute lymphoblastic leukemia age 1 to 30 years. Allogeneic hematopoietic stem-cell transplantation (HSCT) was recommended for patients at high risk based on slow response and for those with a matched family donor regardless of response after at least 11 weeks of therapy. Patients at standard risk based on rapid response received chemotherapy plus dasatinib for an additional 120 weeks. Patients with overt CNS leukemia received cranial irradiation. Results Sixty eligible patients were enrolled. Five-year overall (OS) and event-free survival rates (± standard deviations [SD]) were 86% ± 5% and 60% ± 7% overall, 87% ± 5% and 61% ± 7% for standard-risk patients (n = 48; 19% underwent HSCT), and 89% ± 13% and 67% ± 19% for high-risk patients (n = 9; 89% underwent HSCT), respectively. Five-year cumulative incidence (± SD) of CNS relapse was 15% ± 6%. Outcomes (± SDs) were similar to those in COG AALL0031, which used the same chemotherapy with continuous imatinib: 5-year OS of 81% ± 6% versus 86% ± 5% ( P = .63) and 5-year disease-free survival of 68% ± 7% versus 60% ± 7% ( P = 0.31) for AALL0031 versus AALL0622, respectively. IKZF1 deletions, present in 56% of tested patients, were associated with significantly inferior OS and event-free survival overall and in standard-risk patients. Conclusion Dasatinib was well tolerated with chemotherapy and provided outcomes similar to those with imatinib in COG AALL0031, where all patients received cranial irradiation. Our results support limiting HSCT to slow responders and suggest a potential role for transplantation in rapid responders with IKZF1 deletions.

Adaptive designs allow planned modifications based on data accumulating within a study. The promise of greater flexibility and efficiency stimulates increasing interest in adaptive designs from clinical, academic, and regulatory parties. When adaptive designs are used properly, efficiencies can include a smaller sample size, a more efficient treatment development process, and an increased chance of correctly answering the clinical question of interest. However, improper adaptations can lead to biased studies. A broad definition of adaptive designs allows for countless variations, which creates confusion as to the statistical validity and practical feasibility of many designs. Determining properties of a particular adaptive design requires careful consideration of the scientific context and statistical assumptions. We first review several adaptive designs that garner the most current interest. We focus on the design principles and research issues that lead to particular designs being appealing or unappealing in particular applications. We separately discuss exploratory and confirmatory stage designs in order to account for the differences in regulatory concerns. We include adaptive seamless designs, which combine stages in a unified approach. We also highlight a number of applied areas, such as comparative effectiveness research, that would benefit from the use of adaptive designs. Finally, we describe a number of current barriers and provide initial suggestions for overcoming them in order to promote wider use of appropriate adaptive designs. Given the breadth of the coverage all mathematical and most implementation details are omitted for the sake of brevity. However, the interested reader will find that we provide current references to focused reviews and original theoretical sources which lead to details of the current state of the art in theory and practice.