Episode 20: Missing Data in Clinical Trials

In this QCast episode, Jullia and Tom unpack missing data in clinical trials — why it biases effect estimates, how the estimand framework drives prevention and analysis choices, and what good sensitivity work and reporting look like for credible, inspection-ready results.Key Takeaways Define estimands and intercurrent-event strategies, then align follow-up and data collection.  Prevent over correct with simpler schedules, remote options, continued follow-up, and early action on gaps.  Use principled methods such as mixed models and multiple imputation, consider pattern-mixture approaches, avoid last observation carried forward.  Demonstrate robustness through targeted sensitivity analyses, tipping-point checks, and clear summaries of missingness and reasons. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast.🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode.About QuanticateFounded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in:Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.