Hepatic decompensation is the major driver of mortality in patients with HCC treated with atezolizumab plus bevacizumab: The impact of successful antiviral treatment
Bibliographic record
Abstract
BACKGROUND AND AIMS: Unlike other malignancies, hepatic functional reserve competes with tumor progression in determining the risk of mortality from hepatocellular carcinoma (HCC). However, the relative contribution of hepatic decompensation over tumor progression in influencing overall survival (OS) has not been assessed in combination immunotherapy recipients. APPROACH AND RESULTS: From the AB-real observational study (n = 898), we accrued 571 patients with advanced/unresectable hepatocellular carcinoma, Child-Pugh A class treated with frontline atezolizumab + bevacizumab (AB). Hepatic decompensation and tumor progression during follow-up were studied in relationship to patients' OS using a time-dependent Cox model. Baseline characteristics were evaluated as predictors of decompensation in competing risks analysis. During a median follow-up of 11.0 months (95% CI: 5.1-19.7), 293 patients (51.3%) developed tumor progression without decompensation, and 94 (16.5%) developed decompensation. In multivariable time-dependent analysis, decompensation (HR: 19.04, 95% CI: 9.75-37.19), hepatocellular carcinoma progression (HR: 9.91, 95% CI: 5.85-16.78), albumin-bilirubin (ALBI) grade 2/3 (HR: 2.16, 95% CI: 1.69-2.77), and number of nodules >3(HR: 1.63, 95% CI: 1.28-2.08) were independently associated with OS. Pretreatment ALBI grade 2/3 (subdistribution hazard ratio [sHR]: 3.35, 95% CI: 1.98-5.67) was independently associated with decompensation, whereas viral etiology was protective (sHR: 0.55, 95% CI: 0.34-0.87). Among patients with viral etiology, effective antiviral treatment was significantly associated with a lower risk of decompensation (sHR: 0.48, 95% CI: 0.25-0.93). CONCLUSIONS: Hepatic decompensation identifies patients with the worst prognosis following AB and is more common in patients with baseline ALBI >1 and nonviral etiology. Effective antiviral treatment may protect from decompensation, highlighting the prognostic disadvantage of patients with nonviral etiologies and the importance of multidisciplinary management to maximize OS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".