Baseline Albumin-Bilirubin grade as a predictor of response and outcome of regorafenib therapy in patients with hepatocellular carcinoma: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background The use of regorafenib in the treatment of hepatocellular carcinoma (HCC) is widespread. Albumin-Bilirubin (ALBI) has been shown to be a potential prognostic marker for regorafenib treatment, but its prognostic value remains controversial. Therefore, we conducted a meta-analysis to investigate the value of the baseline ALBI grade in predicting the efficacy and survival outcomes of HCC patients after regorafenib treatment. Methods PubMed, Embase, Cochrane library, Web of Science, CNKI, Wan Fang Data, and Vip Database were searched from January 2010 to October 2022. Studies treating HCC patients with regorafenib and with ALBI as a categorical variable, overall survival (OS) and progression-free survival (PFS) as outcome indicators were included. After applying Newcastle–Ottawa Scale (NOS) to evaluate the quality of the included studies, Review Manager 5.4 was used to statistically analyze. Chi-square Q test and I2 statistics were used to detect heterogeneity. Funnel plot asymmetry, Egger’s and Begg’s test were used to evaluate publication bias. Results A total of 12 studies, comprising 1,918 patients, were included in the meta-analysis. The included studies were all evaluated as high quality. Compared to the high-grade baseline ALBI group, patients in the low-grade group had a longer survival time after receiving regorafenib and also more suitable for regorafenib treatment [odds ratio (OR) = 6.50, 95% confidence interval (CI): 2.22–18.96, P < 0.01]. The low-grade baseline ALBI group before sorafenib treatment was significantly correlated with better OS [hazard ratio (HR) = 2.36, 95% CI: 1.68–3.31, P < 0.00001] and PFS (HR = 1.56, 95% CI: 1.16–2.08, P = 0.003). Likewise, the low-grade baseline ALBI group before regorafenib was also significantly correlated with better OS (HR = 1.56, 95% CI: 1.15–2.13, P = 0.005) and PFS (HR = 2.06, 95% CI: 1.37–3.11, P = 0.0005). In addition, the ALBI grade was significantly correlated with disease control rate (DCR) (OR = 2.90, 95% CI: 1.45–5.79, P = 0.003), but not the objective response rate (OR = 1.98, 95% CI: 0.71–5.46, P = 0.19). Conclusions The baseline ALBI grade could be a valuable prognostic indicator for predicting response and outcomes in HCC patients treated with regorafenib.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.040 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".