18F-Fluorodeoxyglucose Positron-Emission Tomography Could Have a Prognostic Role in Patients with Advanced Hepatocellular Carcinoma
Bibliographic record
Abstract
INTRODUCTION: We set out to evaluate the prognostic value of (18)F-fluorodeoxyglucose positron-emission tomography (pet) in patients with advanced (non-transplant-eligible) hepatocellular carcinoma (hcc) and to evaluate the correlation between standardized uptake values (suvs) and survival outcomes. METHODS: We identified patients with hcc who, from 2005 to 2013, underwent pet imaging before any treatment. This retrospective study from our hcc database obtained complete follow-up data for the 63 identified patients. RESULTS: Of the 63 patients, 10 underwent surgical resection, and 59 underwent locoregional therapy. In this cohort, 28 patients were pet-positive (defined as any lesion with a suv ≥ 4.0) before any therapy was given, and 35 patients were pet negative (all lesions with a suv < 4.0). On survival analysis, median survival was greater for the pet-negative than for the pet-positive patients: 29 months (range: 16.3-41.1 months) versus 12 months (range: 4.0-22.1 months) respectively, p = 0.0241. The pet-positive patients more often had large tumours (≥5 cm), poor differentiation, and extrahepatic disease, reflecting more aggressive tumours. On multivariate analysis, only pet positivity was associated with poor survival (p = 0.049). CONCLUSIONS: Compared with pet-positive patients, pet-negative patients with hcc experienced longer survival. Imaging by pet can be of value in early prognostication for patients with hcc, especially patients receiving locoregional therapy for whom pathologic tumour differentiation is rarely available. This potential role for pet requires further validation in a prospective study.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".