bio-clinical-biostatistics-bayesian-trials

What this skill does

## Version Compatibility

Reference examples tested with: R `RBesT` 1.7+ (Roche), `OncoBayes2` 0.8+ (Novartis), `BOIN` 2.7+, `dfcrm` 0.2-2+, `escalation` 0.1+, `trialr` 0.1.6+, `bayesDP`, `psborrow2` (FDA-supported), `rstan` / `cmdstanr`, `brms`. Legacy: `JAGS`, `WinBUGS`.

Before using code patterns, verify installed versions match. If versions differ:
- R: `packageVersion('<pkg>')` then `?function_name`
- Confirmatory regulatory work: validate against pinned package versions in submission

If code throws an error, introspect the installed package and adapt the example to match the actual API rather than retrying.

# Bayesian Clinical Trials

**"Design a Bayesian clinical trial"** -> Specify a prior, likelihood, and decision rule with frequentist operating characteristics demonstrated via simulation; for dose-finding use FDA-endorsed BOIN; for borrowing use robust MAP priors; for adaptive platforms use posterior probability of efficacy stopping with simulation-calibrated thresholds.

## Regulatory Status -- The 2024-2026 Bayesian Pivot

**FDA 2010 CDRH Bayesian Devices Guidance** (Feb 5 2010): the only Bayesian-specific FDA guidance until January 2026. Why devices were ahead: CDRH's PMA pathway permits one pivotal trial and accepts borrowing from prior/OUS data more readily than CDER. Example: Edwards SAPIEN (PARTNER B, PMA P100041, Nov 2011) approved using Bayesian propensity-matched comparison to registry of standard-of-care patients.

**FDA January 2026 CDER Bayesian Methodology Draft** (FDA-2025-D-3217; comment period closed March 13 2026): first-ever drug-side Bayesian guidance. Explicit that Bayesian primary inference in pivotals is acceptable provided:
- Prospective specification
- Simulation-based operating characteristics (including frequentist Type-I error under null scenarios — agency still wants calibration)
- Justified priors
- Code/data sufficient for FDA replication

**Project Optimus (FDA OCE, launched 2021; final dose-optimisation guidance Aug 2024):** rewrites Phase I/II oncology by requiring randomised dose comparison before registration. Has made multi-arm randomised dose-finding (BOIN-12, gBOIN-ET) much more important than classic MTD-finding.

**FDA BOIN Fit-for-Purpose qualification (December 2021):** first formal FDA endorsement of a specific dose-finding design under the Drug Development Tools program.

**ICH E20 (Step 2b/3 draft June 2025; NOT final)** treats Bayesian as a legitimate analytic framework but requires demonstration of acceptable frequentist operating characteristics (Type-I, power) over a pre-specified parameter space.

## Algorithmic Taxonomy

| Method | Use case | Software | Strength | Fails when |
|--------|----------|----------|----------|------------|
| BOIN | Phase I MTD | R `BOIN` (Yuan) | **FDA Fit-for-Purpose 2021**; pre-tabulated decisions; no bedside Bayesian software | Statistically less efficient than CRM under correct skeleton |
| mTPI-2 / Keyboard | Phase I MTD | R `escalation`; R `Keyboard` | Default replacement for mTPI; fixes Ockham bias | Tabulated; transparency |
| CRM | Phase I MTD | R `dfcrm`, `trialr` | Most efficient under correct skeleton | Skeleton mis-specification biases MTD |
| EWOC | Phase I MTD | R `ewoc`, `dfcrm` | Explicit overdose-control constraint (P(dose>MTD) <= 0.25) | More conservative than CRM in small trials |
| BOIN-12 / gBOIN-ET | Phase 1b dose-optimisation (Project Optimus) | R `BOIN` extensions | Multi-arm randomised dose comparison | Requires explicit efficacy + toxicity scoring |
| MAP prior | Borrowing from historical control arms | R `RBesT::gMAP` | Industry-standard borrowing | Sample-size of MAP prior must be calibrated (Schmidli 2014) |
| Robust MAP | Borrowing with prior-data conflict protection | R `RBesT::robustify` | Adds vague component (weight 0.1-0.3) to detach if conflict | Mixture weight choice affects borrowing |
| EXNEX | Basket trial across rare-disease strata | R `bhmbasket`; OncoBayes2 | Avoids HM catastrophic borrowing; mixture 0.5/0.5 default (Neuenschwander 2016) | Default weights may over-borrow |
| Dixon-Simon shrinkage | Subgroup analysis | Custom Stan/brms | Honest about no qualitative interaction prior | Prior on tau drives results |
| Berry-Berry 3-level hierarchical | AE multiplicity (AE within PT within SOC) | R `c212`; JMP Clinical | Tames safety multiplicity | Spike-and-slab tuning matters |
| Posterior probability stopping | Adaptive sequential | Custom; FACTS commercial | Bayesian likelihood-principle compatible | Threshold calibration via simulation |
| Predictive probability of success | End-of-Phase-2 go/no-go | Custom Stan | Decision-theoretic; integrates over posterior | Requires Phase 3 design specified |
| Spiegelhalter skeptical/enthusiastic prior | Sensitivity for regulatory pivotals | Custom | Frames regulator-vs-sponsor evidence | Prior elicitation effort |
| Power prior | Pediatric extrapolation borrowing from adults | R `bayesDP`, `psborrow2` | Partial borrowing with discount gamma | gamma choice (Jan 2026 FDA draft: 0.3-0.6) |

**Postdoc reading list:**

- FDA 2010 *Guidance for Industry: Use of Bayesian Statistics in Medical Device Clinical Trials* (Feb 5 2010)
- FDA 2026 Draft *Use of Bayesian Methodology in Clinical Trials* (FDA-2025-D-3217, Jan 2026)
- Berry SM, Carlin BP, Lee JJ, Müller P 2010 *Bayesian Adaptive Methods for Clinical Trials* (CRC)
- Schmidli H, Gsteiger S, Roychoudhury S, O'Hagan A, Spiegelhalter D, Neuenschwander B 2014 *Biometrics* 70:1023 (MAP + robust MAP)
- Weber S, Li Y, Seaman J, Kakizume T, Schmidli H 2021 *J Stat Softw* 100:19 (RBesT)
- Neuenschwander B, Wandel S, Roychoudhury S, Bailey S 2016 *Pharm Stat* 15:123 (EXNEX)
- Liu S, Yuan Y 2015 *J R Stat Soc C* 64:507 (BOIN)
- O'Quigley J, Pepe M, Fisher L 1990 *Biometrics* 46:33 (CRM)
- Babb J, Rogatko A, Zacks S 1998 *Stat Med* 17:1103 (EWOC)
- Ji Y, Liu P, Li Y, Bekele BN 2010 *Clin Trials* 7:653 (mTPI)
- Guo W, Wang SJ, Yang C, Ji Y 2017 *Contemp Clin Trials* 58:23 (mTPI-2 / Keyboard)
- Berry SM, Broglio KR, Groshen S, Berry DA 2013 *Clin Trials* 10:720 (basket trial hierarchical)
- Berry SM, Berry DA 2004 *Biometrics* 60:418 (three-level AE hierarchical)
- Spiegelhalter DJ, Freedman LS, Blackburn PR 1986 *Stat Med* 5:421 (skeptical prior framework)
- Park JW et al 2016 *NEJM* 375:11 (I-SPY 2 veliparib)
- Angus DC et al 2020 *JAMA* (REMAP-CAP COVID rationale)

## Decision Tree by Scenario

| Scenario | Recommended approach | Why |
|----------|---------------------|-----|
| Phase 1 oncology, single-agent MTD | BOIN with target DLT 30%; cohort size 3 | FDA Fit-for-Purpose 2021; tabulated escalation |
| Phase 1 oncology, combination (2 agents) | BLRM with EXNEX in OncoBayes2 | Multi-dimensional dose; industry standard at Novartis/Roche |
| Phase 1b/2 dose-optimisation (Project Optimus) | BOIN-12 or gBOIN-ET; randomised 2-dose comparison | Aug 2024 FDA dose-optimisation guidance |
| Phase 3 with historical control arms available | Robust MAP via RBesT; gMAP() + robustify() | Industry standard borrowing with prior-data conflict protection |
| Basket trial across rare-disease strata | EXNEX (0.5 EX / 0.5 NEX mixture) via OncoBayes2 | Avoids HM catastrophic borrowing |
| Pediatric extrapolation from adult data | Power prior with discount gamma 0.3-0.6 | working convention; the FDA Bayesian Jan 2026 draft does not prescribe a specific gamma range -- check the draft for the current language before quoting |
| Phase 3 trial with single arm + RWE comparator | Propensity-score-integrated power prior via psborrow2 | FDA-supported package for external controls |
| Adaptive trial wanting posterior-probability stopping | Custom Stan model + simulation-calibrated threshold | Bayesian likelihood-principle compatible; no penalty for repeated looks |
| End-of-Phase-2 go/no-go | Predictive probability of success in Phase 3 | Integrates posterior over Phase 3 design |
| Hypothesis-generating safety AE analysis (>100 PTs) | Berry-Berry 3-level hierarchical