A two-stage group-sequential design for delayed treatment responses with the possibility of trial restart.

Common statistical theory applicable to confirmatory phase III trial designs usually assumes that patients are enrolled simultaneously and there is no time gap between enrollment and outcome observation. However, in practice, patients are enrolled successively and there is a lag between the enrollment of a patient and the measurement of the primary outcome. For single-stage designs, the difference between theory and practice only impacts on the trial duration but not on the statistical analysis and its interpretation. For designs with interim analyses, however, the number of patients already enrolled into the trial and the number of patients with available outcome measurements differ, which can cause issues regarding the statistical analyses of the data. The main issue is that current methodologies either imply that at the time of the interim analysis there are so-called pipeline patients whose data are not used to make a statistical decision (like stopping early for efficacy) or the enrollment into the trial needs to be at least paused for interim analysis to avoid pipeline patients. There are methods for delayed responses available that introduced error-spending stopping boundaries for the enrollment of patients followed by critical values to reject the null hypothesis in case the stopping boundaries have been crossed beforehand. Here, we will discuss other solutions, considering different boundary determination algorithms using conditional power and introducing a design allowing for recruitment restart while keeping the type I error rate controlled.

What Causes Cancer in Women with a gBRCA Pathogenic Variant? Counselees' Causal Attributions and Associations with Perceived Control.

Laypersons have a strong need to explain critical life events, such as the development of an illness. Expert explanations do not always match the beliefs of patients. We therefore assessed causal attributions made by women with a pathogenic germline variant in BRCA1/2 (gBRCA1/2-PV), both with and without a cancer diagnosis. We assumed that attributions would be associated with the control experience. We conducted a cross-sectional study of N = 101 women with a gBRCA1/2-PV (mean age 43.3 ± 10.9). Women answered self-report questionnaires on perceived causes and control. Most women (97%) named genes as a causal factor for the development of cancer. Surprisingly, the majority of women also named stress and health behavior (both 81%), environment (80%), and personality (61%). Women with a cancer diagnosis tended to endorse more causes. The attributions to personality (ρ = 0.39, p < 0.01) health behavior (ρ = 0.44, p < 0.01), and environment (ρ = 0.22, p < 0.05) were significantly associated with personal control, whereas attribution to genes showed a small, albeit significant association with treatment control (ρ = 0.20, p < 0.05). Discussing causal beliefs in clinical counseling may provide a "window of opportunity" in which risk factors and health behaviors could be better addressed and individually targeted.