Portal vein embolization effect on colorectal cancer liver metastasis progression: Lessons learned
Bibliographic record
Abstract
Colorectal liver metastasis (CRLM) is the major cause of death in patients diagnosed with colorectal cancer. The gold standard treatment of CRLM is surgical resection. Yet, in the past, more than half of these patients were deemed unresectable due to the inadequate future liver remnant (FLR). The introduction of efficient portal vein embolization (PVE) preoperatively allowed more resections of metastasis in CRLM patients by stimulating adequate liver hypertrophy. However, several experimental and clinical studies reported tumor progression after PVE which critically influences the subsequent management of these patients. The underlying pathophysiological mechanism of tumor progression post-PVE is still not fully understood. In spite of the adverse effects of PVE, it remains a potentially curative procedure in patients who would remain otherwise unresectable because of the insufficient FLR. Currently, the challenge is to halt tumor proliferation following PVE in patients who require this technique. This could potentially be achieved by either attempting to suppress the underlying oncologic stimulus or by inhibiting tumor growth once observed after PVE, without jeopardizing liver regeneration. More research is still required to better identify patients at risk of experiencing tumor growth post-PVE.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".