<p>Japanese patient preferences regarding intermediate to advanced hepatocellular carcinoma treatments</p>
Bibliographic record
Abstract
Purpose: This study aimed to evaluate Japanese patient preferences regarding features of intermediate or advanced (Progressed) hepatocellular carcinoma (HCC) treatments: transarterial chemoembolization (TACE), hepatic arterial infusion chemotherapy (HAIC), and oral anti-cancer therapy. Methods: Patients with HCC, recruited from clinical sites and a patient panel in Japan, completed a cross-sectional web-based survey. Preferences were quantified using best–worst scaling, where patients identified the best and worst among 13 treatment features. Direct elicitation was used to identify preference for TACE, HAIC, or oral therapy, including the likelihood of trying each. Additional items asked for the willingness to try an oral medication that delays progression by six months but has an 8% or 21% risk of severe hand-foot skin reaction (HFSR). Results: The sample (N=119; 29 early stage; 90 Progressed) most preferred “oral medication”, “artery branches plugged”, and “prevents formation of new blood vessels”, and least preferred “risk of liver damage” and “risk of catheter-related complications”. Overall, 51%, 40%, and 8% preferred oral therapy, TACE, and HAIC, respectively ( p <0.05), and the mean likelihood of trying each were 59%, 52%, and 35%, respectively ( p <0.001). Patients with sorafenib or TACE experience most preferred what they had received; however, both groups were equally willing to try the other treatment. Patients preferring oral therapy favored “oral medication” over “artery branches plugged”, “surgery is repeated as required when the cancer grows again”, and “risk of liver damage”, compared to those preferring TACE ( p <0.05). Sixty-eight percent would probably try therapy with an 8% risk of severe HFSR, compared to 50% with a 21% risk. Conclusion: Treatment type, mode of action, and risks may drive HCC patient preferences. Such features likely should be incorporated into physician–patient interactions regarding treatment decision-making. Keywords: hepatocellular carcinoma, patient preference, best-worst scaling
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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 | 0.000 |
| 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) | 0.003 | 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".