Outcome and management of patients with hepatocellular carcinoma who achieved complete response to immunotherapy-based systemic therapy
Bibliographic record
Abstract
Background: The management and natural history of patients with hepatocellular carcinoma (HCC) who achieve complete response (CR) to immune checkpoint inhibitor (ICI)-based systemic therapies is not well described. Materials and methods: We conducted a retrospective study of adult patients with HCC who had CR to systemic ICI-based therapies from 18 centers in Europe and Asia. Results: Of 2502 patients with HCC treated with ICI, 123 patients (4.9%) achieved CR according to mRECIST (CR-mRECIST) and 72 patients (2.9%) had CR according to RECISTv1.1 (CR-RECISTv1.1) as well. 103 patients were male (84%), and the majority had BCLC stage C (n=87;71%) and Child-Pugh class A (n=112;91%). Median follow-up was 32.1 (95%CI,30.5-33.6) months.Median duration of CR (mRECIST) was 35.5 (95%CI, not estimable) months. Overall, 41 patients (33%) experienced recurrence a median of 11.4 months (95%CI, 8.9-14.0) after mRECIST CR. Recurrence rate was similar in patients with CR-mRECIST only (26%) and CR-RECISTv1.1 (39%; p=0.120), as were recurrence-free survival rates at one and two years (77% and 61% for CR-mRECIST only vs. 74% and 58% for CR-RECISTv1.1; p=0.310). A total of 93 patients (75.6%) discontinued ICI during follow-up due to adverse events (n=11, 11.8%), recurrence (n=15, 16.1%), durable CR (n=41, 44.1%), or other reasons (n=26, 28.0%). Among those who discontinued treatment for reasons other than recurrence (n=76), recurrence rate was 23.7% (n=18); patients who received systemic treatment for>6 months after complete response had a numerically lower recurrence rate (15.8%, n=6/38) compared to those who discontinued treatment earlier (31.6%, n=12/38; p=0.105). One-/3-/5-year overall survival (OS) rates of the whole cohort were 98%/88%/77%. Conclusions: Only a small proportion of patients with advanced HCC achieves CR to palliative immunotherapy, but these patients have an excellent overall survival. When considering ICI discontinuation, treatment for>6 months beyond CR may be associated with a lower recurrence rate. Publication History Article published online: 05 June 2024 © 2024. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".