A retrospective database analysis to understand treatment patterns and outcomes of intermediate and advanced hepatocellular carcinoma in Alberta, Canada (A-CAPTAIN study)
Bibliographic record
Abstract
Background: With the emergence of new systemic therapies there has been a substantial change in treatment options for hepatocellular carcinoma (HCC). The aim of this study was to assess treatment patterns and outcomes in real-world Canadian HCC patients with intermediate and advanced stage disease who have received systemic treatments prior to 2021. Methods: All HCC patients with intermediate or advanced disease who received at least one dose of systemic therapy between January 1, 2008 to December 31, 2020 in the Canadian province of Alberta were included. Patient characteristics, treatment patterns, overall survival (OS), real-world progression-free survival (rwPFS), clinician-assessed response rates (RRs), and reasons for treatment discontinuation were retrospectively analyzed in all patients. Results: Of the 321 total patients included, 33 (10%) were intermediate and 288 (90%) were advanced stage. With respect to intermediate and advanced HCC patients, most were Eastern Cooperative Oncology Group (ECOG) 0-1 (94%, 85%, respectively) and Child-Pugh A (82% for both). For intermediate and advanced patients, RRs to first-line systemic therapy were 13% and 19%, median rwPFS was 7.4 and 4.2 months, and median OS was 13.5 and 10.9 months, respectively. Conclusions: This study characterized the systemic treatment patterns and outcomes of intermediate and advanced HCC patients treated prior to 2021 and can serve as a baseline for future comparison with HCC patients who predominantly receive first-line immunotherapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".