Immune-mediated adverse events and overall survival with tremelimumab plus durvalumab and durvalumab monotherapy in unresectable HCC: HIMALAYA phase III randomized clinical trial
Bibliographic record
Abstract
BACKGROUND AND AIMS: In the global phase III HIMALAYA study in unresectable HCC, STRIDE significantly improved overall survival (OS) versus sorafenib; durvalumab was noninferior to sorafenib. Immune checkpoint inhibitor studies have shown an association between the occurrence of immune-mediated adverse events (imAEs) and improved OS. We assessed potential associations between the occurrence of imAEs and OS, and temporal patterns of imAEs, in HIMALAYA. APPROACH AND RESULTS: OS in participants who did and did not experience imAEs and the frequency and timing of imAEs were assessed for STRIDE and durvalumab in the safety analysis set of HIMALAYA. imAEs occurred in 139/388 (35.8%) and 64/388 (16.5%) participants with STRIDE and durvalumab, respectively; most were low grade. OS HRs (95% CI) in participants who experienced imAEs versus those who did not were 0.73 (0.56-0.95) for STRIDE and 1.14 (0.82-1.57) for durvalumab. The 36-month OS rate (95% CI) for STRIDE was 36.2% (28.1-46.7) and 27.7% (22.4-34.2) in participants who did and did not experience imAEs, respectively. The most common imAE category with STRIDE was endocrine events (16.5%). Most imAEs occurred ≤3 months after treatment initiation. CONCLUSIONS: Participants who experienced imAEs with STRIDE had a numerical improvement in OS versus those who did not, which was not observed for durvalumab. Long-term OS with STRIDE was observed regardless of imAEs. Most imAEs were low grade, manageable, and occurred in the first 3 months after treatment initiation. Results continue to support the benefits of STRIDE in a diverse population that reflects unresectable HCC globally.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".