Statistical considerations for the Nipah virus treatment study Lori E Dodd, PhD Clinical Trials Research Section Division of Clinical Research/NIAID
Power for various sample sizes Statistical analysis Primary Endpoint: 28-day mortality Statistical test: test of lower mortality rate (using Boschloo’s test), two-sided type I error rate of 0.05 Sample size: 100 per arm Highly unlikely that one outbreak will provide sufficient statistical power for conclusive evidence Mortality rate Power for various sample sizes per arm SOC m102.4 50 75 100 80% 64% 40% 58% 71% 56% 72% 89% 96% 70% 49% 57% 75% 86% 50% 30% 53% 83% 20% 76% 87%
Draft statistical analysis plan: Action item Draft statistical analysis plan: who and what?
Randomization Stratified for statistical efficiency Limited to one stratification variable: Presence of neurologic symptoms (yes/no). Double-blinded design requires Process to ensure masking of treatment assignment Randomization via database with blinded treatment codes Pharmacist standardized operating procedure to preserve the blind Reporting of AEs to Data and Safety Monitoring Board who should be unblinded to treatment assignment
Action items Randomization SOP: list generation and database process SOP to ensure double-blinding SOP for reporting results to DSMB
Interim monitoring considerations Early data are unreliable but ethical considerations demand that a trial stops for Definitive early efficacy or Definitive early harm Monitoring too frequently increases chances of a false positive finding Study likely to continue across multiple outbreaks Solution: group sequential monitoring
Definitive early efficacy Truncated O’Brien-Fleming boundary with 5 interim looks: Number total 24 50 100 150 200 One-sided p-value boundary 0.0005 0.009 0.021 Mortality boundaries for first (n=24) interim analysis: Deaths in m102.4 Deaths in SOC 8+ 1 9+ 2 11+ 3 12 Flexibility to evaluate at the end of an outbreak
Definitive early harm Same frequency as for efficacy. Less evidence required to establish harm. p<0.05 for each look Mortality boundaries for first safety analysis (at n=24): Deaths in m102.4 Deaths in SOC 4+ 6+ 1 7+ 2 9+ 3
Conditional Power Method of calculating likelihood of concluding statistical significance given accumulated (but not complete) data Given the accumulated observed data (up to time of analysis), compute the probability of achieving statistical significance assuming the remaining data (up to total of 100/arm) follow assumed alternative: *e.g., 50% reduction in mortality Evaluated during interim analyses and/or accrual pauses (due to end of outbreak) —If conditional power < 20%, continuing study may be futile
Sample size reassessment After 100 participants have been accrued, sample size may be increased if: Conditional power is greater than 50%, or Pooled mortality rate is low
Continuing study across outbreaks Study continues (across outbreaks) without release of results until accrual completed or DSMB recommends early stopping. Procedures/agreements needed to ensure all sites/countries understand the importance of this. Early release of data without a definitive conclusion may make continued study of m102.4 impractical.
Prevail II example Randomized controlled trial comparing ZMappTM to standard-of-care during the 2013-16 Ebola outbreak Powered for a 50% reduction in mortality from 40% to 20% -200 subjects needed By January 2016, epidemic was clearly ending. Should study continue? West African Ebola outbreak was unprecedented. No pattern of regional outbreaks Unclear if and when another outbreak would occur
DSMB presented with the following data The PREVAIL II Writing Group. N Engl J Med 2016;375:1448-1456.
Recommendation DSMB recommended study closure and release of data Results published NEJM in 2016 ZMappTM was promising but results not definitive Ongoing debate about its efficacy Questions for thought: Should DSMB have kept study open? Suppose another outbreak was expected within a year, would DSMB have kept study going?
Action items DSMB charter DSMB approves protocol and monitoring plans Country-/site-wide agreement with monitoring plans Statistical analysis plan to describe interim analyses in detail