The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
Health professionals and policy makers want to make healthcare decisions based on the relevant research evidence. The questions in clinical research are typically studied more than once independently by different researchers. Literature review is used for summarizing the results of these studies and strengthening the evidence. Systematic review is a type of literature review that collects and critically analyzes multiple research studies or papers that answer the same question. If the results of these multiple studies are diverse and conflicting then the clinical decision-making becomes difficult. To overcome this problem meta-analysis is used. Meta-analysis is a statistical procedure for combining the results of studies that are included in systematic review. While meta-analysis is a powerful technique, it may give misleading results due to issues like improper selection of studies, publication bias, and heterogeneity among studies. In this blog, we will focus on the problem of heterogeneity.
As part of Cytel's new Trial Innovations Webinar Series, Pat Mitchell, Statistical Science Director at AstraZeneca presented the October webinar "Formal Go/No-Go decisions are a key component of risk management in early clinical development."
Robust go/no-go (GNG) decision-making is essential for effectively managing risk across a clinical portfolio. In early phase development, it is particularly important to have the correct tools in place to terminate ineffective compounds quickly, while accelerating promising ones through the process.