Lenvatinib for the Treatment of Hepatocellular Carcinoma After Liver Transplant
Bibliographic record
Abstract
What Is the Issue? Liver transplant is 1 of the main curative therapies for liver cancer; however, hepatocellular carcinoma (HCC) recurrence presents in 10% to 20% of patients after liver transplant. Lenvatinib, an oral multikinase inhibitor drug, was approved for use in Canada as a first-line standard therapy for unresectable HCC, based on a pivotal trial that excluded patients who underwent a prior liver transplant. Data were scarce on the efficacy and safety of lenvatinib for treatment of HCC recurrence in patients who received a liver transplant, and were limited to a few case series and case reports. What Did We Do? We identified and summarized the literature on the evidence of the clinical effectiveness and safety of lenvatinib for the first-line treatment of patients with unresectable HCC recurrence after liver transplant. We searched key resources, including journal citation databases and conducted a focused internet search for relevant evidence published since 2019. One reviewer screened citations for inclusion based on predefined criteria, critically appraised the included studies, and narratively summarized the findings. What Did We Find? We identified a multinational, multicentre, retrospective, single-arm chart review study evaluating the efficacy and safety of lenvatinib in patients with HCC recurrence after liver transplant. Lenvatinib was primarily used as a first-line treatment for most patients (n = 42; 93.3%) and as a second-line treatment for 3 patients (6.7%). The single-arm chart review study showed lenvatinib treatment had an overall response rate (ORR) of 20.0%, a median overall survival of 14.5 months, and a median progression-free survival (PFS) of 7.6 months. These findings were similar to those randomized to lenvatinib in the pivotal phase III REFLECT trial, which excluded patients who had a prior liver transplant. What Does This Mean? The findings of this report suggest that lenvatinib has a potential role as a first-line treatment of patients with HCC recurrence after liver transplant. As the current evidence is limited to a retrospective single-arm chart review study, which had several limitations (e.g., lack of sample size calculation, noncomparative, and retrospective design), further investigations are needed to establish the clinical efficacy and safety of lenvatinib as a first-line treatment for unresectable HCC recurrence after liver transplant.
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 | 0.015 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".