Sorafenib treatment in recurrent hepatocellular carcinoma post liver transplantation.
Bibliographic record
Abstract
e15613 Background: Liver transplantation (LT) is a potentially curative treatment for patients (pts) with selective hepatocellular carcinoma (HCC). HCC recurrence post LT is estimated to be 15-20%. Data on systemic therapy post-recurrence is scarce and limited case series suggest that sorafenib (SOR) may have benefit in this population. We reviewed a single center experience with SOR in recurrent HCC post LT Methods: A retrospective review was conducted on pts with recurrent HCC post LT at University Health Network (UHN) who were treated with SOR. Pt characteristics were collected including age, gender, comorbidities, background liver disease, type of LT, and time to recurrence after LT. Treatment information collected included: initial SOR dose (and adjustments), adverse events (AEs), duration of treatment and survival. Results: Between 2006 and 2016, 24 pts were identified. The average age was 60 years (range: 18-72), most pts were male (20/4), living/cadaveric transplant: 11/13. HCC etiology included hepatitis B (10), alcohol (4), NASH (3), hepatitis C (2), hemochromatosis (2), Budd-Chiari (2) and unknown (1). The average time to recurrence of HCC was 16.08 (range: 1.5-60) months post OLT. There was a bimodal time to recurrence with a median of 6 months. SOR starting doses were 200 mg BID in 18 pts, 300 mg BID in 1 and 400 mg BID in 4. 14 pts required dose adjustment due to AEs, mainly relating to fatigue and palmar-plantar syndrome. The median time on treatment was 2.5 (range: 0.25-37) months. The average time to progression on SOR and/or discontinuation due to AEs was 4.30 (+/- 7.2) months. Conclusions: SOR is reasonably tolerated in pts with recurrent HCC post LT, with expected AE profiles. In this small case series, the median time on SOR was short and estimated time to progression was shorter than that in non-transplant HCC population. Overall, SOR has limited activity in this population, but selected pts may derive extended benefit. Better understanding of responders and investigations of other therapies are needed for this population.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Case report | low |
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".