Bayesian clinical trials: software and logistics
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This document discusses Bayesian clinical trial software developed by John D. Cook and colleagues at M. D. Anderson Cancer Center. It describes software tools for designing trials, such as for sample size calculation and dose finding, and for conducting trials, such as for safety monitoring and adaptive randomization. Challenges in clinical trial conduct software design are also outlined, such as handling changes during a trial. Resources for downloading or learning more about the software are provided.
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Bayesian clinical trials: software and logistics
- 1. Bayesian Clinical Trials: Software and Logistics John D. Cook, PhD Head of Software Development M. D. Anderson Cancer Center Division of Quantitative Sciences JSM 2007
- 2. Software developers • Hoang Nguyen • Kyle Wathen • Leiko Wooten • Clift Norris • Odis Wooten • John Cook
- 3. Outline • Software for designing trials • Software for running trials
- 4. Software for designing trials Basic utilities Safety monitoring Randomized trials Dose finding
- 5. Parameter Solver • Solve from quantiles or mean & variance • May also enter parameters • Self-validating • Graphics options
- 7. Inequality Calculator • Included inside several other applications • Supports common distributions • Allows a slippage term • Customizable plots of density function • Can specify parameters via ParameterSolver tool
- 9. Multc Lean • Original software Multc99, developed by Hsi-Guang Sun • Greatly simplified, added Windows UI • Well-tested • Added trial duration simulation
- 10. Multc Lean
- 11. TTEDesigner and TTEConduct • Safety monitoring for single-arm trials with time-to-event outcomes • Doesn’t artificially dichotomize data • Takes advantage of partial information • Very robust
- 14. Stop for futility: Predictive Probability • Supports binary and time-to-event outcomes • What is likely to happen given what has happened? Predictive probability • Three decisions: A, B, neither • If P(neither) is large, stop for futility • See PP tutorial on download site
- 16. Adaptive Randomization • Supports binary and TTE outcomes • Up to 10 arms • Support for covariates in development • Separate software for conduct
- 18. CRMSimulator • Emphasis on ease-of-use, not generality • Contains features commonly used at MDACC, and no more
- 19. CRMSimulator
- 20. EffTox dose-finding • Minimize toxicity, maximize efficacy • Investigator specifies trade-off • Uses twice as much data per patient • Uses dose values, not just dose order
- 23. Trial conduct software design • Store data on server, not on desktops • Maintain audit trail • Organize by protocol, not statistical method • Hide statistical detail from nurses • Expose statistical detail to statisticians • Label doses with dimensional units, not ordinal numbers • Design for sporadic use
- 24. Complications • Nurses can change jobs during a trial • Patients can withdraw from trial • Patients can be discovered to be ineligible after being treated • Trials may be redesigned mid-stream • Cohorts can be complicated • Nurses will forget to update data • Researchers may question software output
- 25. MDACC trial conduct software • Multc Lean requires no software • Simple TTE requires no software • TTE (Weibull with covariates) • CRM dose-finding • EffTox dose-finding to be added • Pocock-Simon • Adaptive Randomization (including covariates)
- 26. Resources • http://biostatistics.mdanderson.org/ SoftwareDownload/ • Watch RSS feed for news • http://www.johndcook.com