Extreme hepatic resections for the treatment of advanced hepatoblastoma: Are planned close margins an acceptable approach?
Bibliographic record
Abstract
BACKGROUND: Orthotopic liver transplantation (OLT) is considered the standard for children with hepatoblastoma (HB) in whom complete surgical resection is not possible. However, OLT is not always available or feasible. OBJECTIVE: To describe the outcome of children with HB who were initially deemed unresectable and underwent complex hepatectomy with planned close margins, and ultimately avoided OLT. METHODS: Demographic data, surgical and pathologic details, and survival information were collected from children treated for HB between January 2010 to December 2015. RESULTS: Among six children (median age 12 months (3-41 months)), PRETEXT classification was III (n = 2), III/IV (n = 1), and IV (n = 3). Patients received a median of six cycles (range 4-7) of platinum-based induction chemotherapy; five received doxorubicin. Experienced pediatric surgeons performed extended right and left hepatectomy in five and one patients, respectively, with assistance of an experienced liver transplant surgeon (n = 4). Microscopic margins were positive (n = 2) and negative but close (n = 4; 2-5 mm). Two patients required vascular reconstruction of the vena cava. At median follow-up of 3.3 years (1.7-4.6 years), there was no evidence of local recurrence. One patient had recurrence of pulmonary disease 3 months after surgery. CONCLUSIONS: Patients with advanced HB treated with complex surgical resections with positive or close negative margins had good outcomes without OLT. We suggest that planned positive or close microscopic margins in highly selected HB patients may spare the morbidity of OLT and offer an alternative for those ineligible for OLT. Our experience illustrates the importance of a multidisciplinary team specialized in the management of liver tumors.
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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".