Early Changes in Alpha-Fetoprotein and Des-γ-Carboxy Prothrombin Are Useful Predictors of Antitumor Response to Durvalumab Plus Tremelimumab Therapy for Advanced Hepatocellular Carcinoma
Bibliographic record
Abstract
The relationship between antitumor response and tumor marker changes was evaluated in patients with advanced hepatocellular carcinoma treated with durvalumab plus tremelimumab (Dur/Tre). Forty patients were enrolled in this retrospective evaluation of treatment outcomes. According to the Response Evaluation Criteria for Solid Tumors version 1.1 at 8 weeks, the objective response (OR) rate was 25% and the disease control (DC) rate was 57.5%. The median alpha-fetoprotein (AFP) ratio at 4 weeks was 0.39 in patients who achieved OR at 8 weeks (8W-OR group), significantly lower than the 1.08 in the non-8W-OR group (p = 0.0068); however, it was 1.22 in patients who did not achieve DC at 8 weeks (non-8W-DC group), significantly higher than the 0.53 in the 8W-DC group (p = 0.0006). Similarly, the median des-γ-carboxy-prothrombin (DCP) ratio at 4 weeks was 0.15 in the 8W-OR group, significantly lower than the 1.46 in the non-8W-OR group (p < 0.0001); however, it was 1.23 in the non-8W-DC group, significantly higher than the 0.49 in the 8W-DC group (p = 0.0215). Early changes in tumor markers after Dur/Tre initiation were associated with antitumor response. In particular, changes in AFP and DCP at 4 weeks may offer useful biomarkers for early prediction of both response and progressive disease following Dur/Tre.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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 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".