A randomized double-blind controlled trial of everolimus in individuals with PTEN mutations: Study design and statistical considerations
Abstract
This randomized, double-blind controlled trial of everolimus in individuals with germline phosphatase and tensin homolog mutations (PTEN) was designed to evaluate the safety of everolimus compared with placebo and to evaluate the efficacy of everolimus on neurocognition and behavior compared to placebo as measured by standardized neurocognitive and motor measures as well as behavioral questionnaires. The safety profile of everolimus is characterized by manageable adverse events that are generally reversible and non-cumulative. The primary safety endpoint of this study was drop-out rate due to side effects, comparing everolimus versus placebo. We also sought to determine the frequency of adverse events by type and severity. The main efficacy endpoint was a neurocognitive composite computed in two ways: 1) an average for working memory, processing speed, and fine motor subtests; and 2) the same average as above except weighted 2/3, and an additional average based on all other available neurocognitive testing measures assessing the additional domains of nonverbal ability, visuomotor skills, verbal learning, and receptive and expressive language, weighted 1/3. Secondary efficacy endpoints examined the effect of everolimus on overall global clinical improvement, autism symptoms, behavioral problems, and adaptive abilities as measured by validated, standardized instruments. We predicted that the rate of adverse events would be no more than 10% higher in the everolimus group…
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design.
Read the paper
Related studies
- In silico toxicology protocols
- QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
- Quantum Informed Machine-Learning Potentials for Molecular Dynamics Simulations of CO2's Chemisorption and Diffusion in Mg-MOF-74
- In-silico strategies in nano-drug design: Bridging nanomaterials and pharmacological applications
- mRNA codon optimization with quantum computers
- The computational power of the human brain
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.