Pembrolizumab Monotherapy for Previously Untreated Advanced Hepatocellular Carcinoma: Data from the Open-Label, Phase II KEYNOTE-224 Trial
Bibliographic record
Abstract
PURPOSE: KEYNOTE-224 cohort 1 demonstrated that pembrolizumab was efficacious and tolerable in patients with advanced hepatocellular carcinoma (HCC) previously treated with sorafenib. We report results from KEYNOTE-224 (NCT02702414) cohort 2, which enrolled patients with advanced HCC and no prior systemic therapy. PATIENTS AND METHODS: KEYNOTE-224 was an open-label, multicountry phase II trial. Eligible patients in cohort 2 had advanced HCC not amenable or refractory to locoregional therapy and not previously treated with systemic therapy. Patients received pembrolizumab 200 mg intravenously every 3 weeks for ≤2 years. Primary endpoint was objective response rate (ORR) by central imaging review per RECIST v1.1. Secondary endpoints included duration of response (DOR), disease control rate (DCR), time to progression (TTP), progression-free survival (PFS), overall survival (OS), and safety/tolerability. RESULTS: Between September 4, 2018, and February 20, 2019, 51 patients were allocated in cohort 2. The median time from the first dose to data cutoff (January 19, 2021) was 27 months (range, 23-29). ORR was 16% [95% confidence interval (CI), 7-29] and was similar across key subgroups. Median DOR was 16 months (range, 3-24+), and DCR was 57%. The median PFS was 4 months (95% CI, 2-8), and median TTP was 4 months (95% CI, 3-9). Median OS was 17 months (95% CI, 8-23). Grade ≥3 treatment-related adverse events occurred in 16% of patients. CONCLUSIONS: In patients with advanced HCC with no prior systemic therapy, pembrolizumab provided durable antitumor activity, promising OS, and had a safety profile consistent with previous observations. These findings support further evaluation of pembrolizumab-based regimens for HCC.
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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 | 0.003 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".