European Society of Organ Transplantation (ESOT) Consensus Report on Downstaging, Bridging and Immunotherapy in Liver Transplantation for Hepatocellular Carcinoma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Liver transplantation offers the best chance of cure for most patients with non-metastatic hepatocellular carcinoma (HCC). Although not all patients with HCC are eligible for liver transplantation at diagnosis, some can be downstaged using locoregional treatments such as ablation and transarterial chemoembolization. These aforementioned treatments are being applied as bridging therapies to keep patients within transplant criteria and to avoid them from dropping out of the waiting list while awaiting a liver transplant. Moreover, immunotherapy might have great potential to support downstaging and bridging therapies. To address the contemporary status of downstaging, bridging, and immunotherapy in liver transplantation for HCC, European Society of Organ Transplantation (ESOT) convened a dedicated working group comprised of experts in the treatment of HCC to review literature and to develop guidelines pertaining to this cause that were subsequently discussed and voted during the Transplant Learning Journey (TLJ) 3.0 Consensus Conference that took place in person in Prague. The findings and recommendations of the working group on Downstaging, Bridging and Immunotherapy in Liver Transplantation for Hepatocellular Carcinoma are presented in this article.
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.
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) | 0.000 | 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 it