Outcome and management of patients with hepatocellular carcinoma who achieved a complete response to immunotherapy-based systemic therapy
Bibliographic record
Abstract
BACKGROUND AND AIMS: The outcome of patients with HCC who achieved complete response (CR) to immune-checkpoint inhibitor (ICI)-based systemic therapies is unclear. APPROACH AND RESULTS: Retrospective study of patients with HCC who had CR according to modified Response Evaluation Criteria in Solid Tumors (CR-mRECIST) to ICI-based systemic therapies from 28 centers in Asia, Europe, and the United States. Of 3933 patients with HCC treated with ICI-based noncurative systemic therapies, 174 (4.4%) achieved CR-mRECIST, and 97 (2.5%) had CR according to RECISTv1.1 (CR-RECISTv1.1) as well. The mean age of the total cohort (male, 85%; Barcelona-Clinic Liver Cancer-C, 70%) was 65.9±9.8 years. The majority (83%) received ICI-based combination therapies. Median follow-up was 32.2 (95% CI: 29.9-34.4) months. One- and 3-year overall survival rates were 98% and 86%. One- and 3-year recurrence-free survival rates were excellent in patients with CR-mRECIST-only and CR-RECISTv1.1 (78% and 55%; 70% and 42%). Among patients who discontinued ICIs for reasons other than recurrence, those who received immunotherapy for ≥6 months after the first mRECIST CR had a longer recurrence-free survival than those who discontinued immunotherapy earlier ( p =0.008). Of 9 patients who underwent curative surgical conversion therapy, 8 (89%) had pathological CR (CR-RECISTv1.1, n= 2/2; CR-mRECIST-only, n= 6/7). CONCLUSIONS: Overall survival and recurrence-free survival of patients with CR-mRECIST-only and CR-RECISTv1.1 were excellent, and 6 of 7 patients with CR-mRECIST-only who underwent surgical conversion therapy had pathological CR. Despite potential limitations, these findings support the use of mRECIST in the context of immunotherapy for clinical decision-making. When considering ICI discontinuation, treatment for at least 6 months beyond CR seems advisable.
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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".