Liver resection for multifocal hepatocellular carcinoma.
Bibliographic record
Abstract
355 Background: Liver resection for multifocal hepatocellular carcinoma (HCC) is controversial. This study was conducted to outline our institution’s experience with liver resection for multifocal HCC. Methods: A retrospective review of patients who underwent liver resections from 1992 to 2011 for histologically confirmed hepatocellular carcinoma was performed. Multifocal disease was defined as more than 1 histologically proven HCC found in the liver resection specimens. Results: Of the 386 liver resections performed for HCC, 47 were performed for multifocal disease. Mean age was 60+11 years, and most patients (92%) had chronic liver disease. Hepatitis B was the most common etiology (60%), followed by hepatitis C (26%), and other etiologies (15%). Most patients were Child’s class A (89%). Most patients had intermediate Barcelona Clinic Liver Cancer (BCLC) stage (stage B) tumors (81%) and a minority of patients had early stage tumors (BCLC stage A, 19%). Major hepatectomy (>2 segments) was performed in 87% with an in hospital mortality of 6.4%. Major complications (Clavien-Dindo scale >3) occurred in 4 patients (9%). Median length of stay was 7 days and the rate of liver failure was 4.3%. Mean tumor number was 3+2 and the size of the largest lesion was 5+3 cm. Cirrhosis was present in 51% of patients. Majority of tumors were moderately differentiated (60%) and vascular invasion was present in 42%. The recurrence rate was 57% and the liver was the most common site of recurrence (81%). Treatment of recurrences occurred in 74% of patients: ablation (33%), chemotherapy (11%), transarterial chemoembolization (11%), resection (7.4%), sorafenib/radiation (7.4%) and transplantation (3.7%). Median disease free interval was 8 months and the overall survival was 18 months Conclusions: Liver resection for multifocal HCC can be performed safely in patients with chronic liver disease. Long term survival can be achieved in these patients and it should be considered as an option.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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, 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".