Bayesian Methods for Subgroup Efficacy and Safety: Application to Japanese Patients in JAVELIN Renal 101

JAVELIN Renal 101 revealed that avelumab plus axitinib improved progression-free survival (PFS) compared with sunitinib in advanced renal cell carcinoma. However, Japanese subgroup estimates were imprecise. In this study, we evaluated how Bayesian borrowing assumptions translate into posterior probabilities for this subgroup.

Using published summary data from JAVELIN Renal 101, we modeled PFS on the log hazard-ratio scale with a normal-normal framework, comparing a weakly informative neutral prior with informative borrowing priors centered on the global final estimate (with sensitivity to the third interim estimate). Outputs were posterior HRs, 95% credible intervals (CrIs), P(hazard ratio [HR] <1), and P(HR < 0.8). Sensitivity analyses evaluated alternative borrowing specifications. Adverse events (AEs) were assessed with a no-borrowing beta-binomial framework using noninformative Jeffreys priors for Japanese and global data sets, reporting Japanese posterior means, 95% CrIs, and probabilities of enrichment for any grade and grade ≥3.

Under the neutral prior, evidence for PFS benefit in the Japanese subgroup was moderate (P[HR < 1] = .83; P[HR < 0.8] = .64), whereas informative borrowing priors yielded substantially higher probabilities. Borrowing in PD-L1⁺ Japanese patients narrowed CrIs while preserving the favorable direction of effect. Any-grade AEs in Japanese patients were most often enriched in hepatic/laboratory, thyroid, infusion-related, and hand-foot domains. For grade ≥3, enrichment mainly involved hepatic/laboratory abnormalities, while rare severe events yielded imprecise posteriors.

A paired Bayesian strategy, graded priors for efficacy and no-borrowing priors for safety, produced transparent posterior probability summaries for the Japanese subgroup. This framework illustrates how borrowing can narrow uncertainty when exchangeability is plausible, while clarifying toxicity domains that may warrant closer monitoring, using published trial data.