Phase II Trial Evaluating the Clinical and Biologic Effects of Bevacizumab in Unresectable Hepatocellular Carcinoma
Bibliographic record
Abstract
PURPOSE: To determine the clinical and biologic effects of bevacizumab, an anti-vascular endothelial growth factor (VEGF) monoclonal antibody, in unresectable hepatocellular carcinoma (HCC). PATIENTS AND METHODS: Adults with organ-confined HCC, Eastern Cooperative Oncology Group performance status of 0 to 2, and compensated liver disease were eligible. Patients received bevacizumab 5 mg/kg (n = 12) or 10 mg/kg (n = 34) every 2 weeks until disease progression or treatment-limiting toxicity. The primary objective was to determine whether bevacizumab improved the 6-month progression-free survival (PFS) rate from 40% to 60%. Secondary end points included determining the effects of bevacizumab on arterial enhancement and on plasma cytokine levels and the capacity of patients' plasma to support angiogenesis via an in vitro assay. RESULTS: The study included 46 patients, of whom six had objective responses (13%; 95% CI, 3% to 23%), and 65% were progression free at 6 months. Median PFS time was 6.9 months (95% CI, 6.5 to 9.1 months); overall survival rate was 53% at 1 year, 28% at 2 years, and 23% at 3 years. Grade 3 to 4 adverse events included hypertension (15%) and thrombosis (6%, including 4% with arterial thrombosis). Grade 3 or higher hemorrhage occurred in 11% of patients, including one fatal variceal bleed. Bevacizumab was associated with significant reductions in tumor enhancement by dynamic contrast-enhanced magnetic resonance imaging and reductions in circulating VEGF-A and stromal-derived factor-1 levels. Functional angiogenic activity was associated with VEGF-A levels in patient plasma. CONCLUSION: We observed significant clinical and biologic activity for bevacizumab in nonmetastatic HCC and achieved the primary study end point. Serious bleeding complications occurred in 11% of patients. Further evaluation is warranted in carefully selected patients.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".