Pembrolizumab and stereotactic body radiotherapy combined in advanced hepatocellular carcinoma post sorafenib – A phase II trial (PEMRAD)
Bibliographic record
Abstract
Background There is strong rationale for integrated approaches of immune-checkpoint inhibitors and locoregional therapies in hepatocellular carcinoma (HCC). Methods The PEMRAD phase II trial investigated the combination of pembrolizumab and stereotactic body radiation (SBRT) in patients with advanced HCC following progression on sorafenib. Patients received pembrolizumab on day 1 and SBRT commenced Day 2. Up to 10 hepatic lesions (<20cm) were treated with SBRT. Pembrolizumab was continued every 21 days until progression, unacceptable toxicity or withdrawal. The primary endpoint was objective response rate (ORR) as measured by RECIST v1.1, hypothesizing an increase to 40% with the combination. Tissue and liquid biopsies were collected for correlative analyses including immunohistochemistry, longitudinal blood Cytometry by Time-Of-Flight, and serum cytokines. Results Between March 2018 and March 2023, 18 patients of a planned 22 were enrolled,11 (61%) with macrovascular invasion (MVI) and 15 (83%) with extrahepatic metastases. Viral hepatitis was the underlying etiology in 50%. The ORR was 41%(95% CI 18-67%). The median progression free survival was 5.4 (2.8-9.9) months and median overall survival was 12.6 (5.7-25.8) months. Of 34 liver lesions treated with SBRT, only 3 progressed in 2 patients. Of the 11 patients with MVI, 5 (45%) had evidence of a response, including 1 complete response. Treatment related adverse events ≥ grade 3 were reported in 4 patients (22%). One death due to myocarditis was attributed to treatment. Peripheral immunophenotyping demonstrated a correlation with abundance of CD8+CD103+ T cells and improved survival. In contrast, abundance of natural killer cells associated with inferior outcomes. Conclusion The combination of SBRT and pembrolizumab demonstrated high response rates, as second-line treatment in advanced HCC and warrants continued evaluation in studies, particularly in patients with MVI. Impact and Implications The role of locoregional therapies including stereotactic body radiotherapy in combination with immune checkpoint inhibitors is unclear in advanced HCC. This study highlights the feasibility of this approach and high response rates in heavily pretreated patients, including patients with HCC and macrovascular invasion. The study should inform future clinical trial design in patients with advanced HCC .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".