Effect of sorafenib starting dose and dose intensity on survival in patients with hepatocellular carcinoma: Results from a Canadian Multicenter Database
Bibliographic record
Abstract
BACKGROUND: Sorafenib has been shown to improve survival in patients with advanced hepatocellular carcinoma (HCC), however, full dose can be difficult to tolerate. The aim of this study was to determine whether sorafenib starting dose and mean dose intensity affect survival. METHODS: Patients treated with sorafenib for HCC from January 2008 to July 2016 in several Canadian provinces were included and retrospectively analyzed. The primary end point was overall survival (OS) of patients starting on sorafenib full dose compared to reduced dose. Secondary analysis compared OS with different mean dose-intensity groups. Survival outcomes were assessed with Kaplan-Meier curves and Cox proportional hazards models. A propensity score analysis was performed to account for treatment bias and confounding. RESULTS: Of 681 patients included, sorafenib was started at full dose in 289 patients (42%). Median survival for starting full and reduced dose was 9.4 months and 8.9 months (P = .15) respectively. After propensity score matching and adjusting for potential confounders there was still no difference in survival (HR 0.8, 95% CI, 0.61-1.06, P = .12). Almost half of the patients (45%) received a dose intensity < 50%. Median survival for mean dose intensity > 75%, 50%-75%, and < 50% were 9.5 months, 12.9 months, and 7.1 months (P = .005) respectively. In multivariable models, starting dose(HR 1.16, 95% CI 0.93-1.44, P = .180) and mean dose intensity were not associated with survival. CONCLUSIONS: Starting HCC patients on a reduced dose of sorafenib compared to full dose may not compromise survival. Mean dose-intensity of sorafenib may also not affect survival.
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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 | 0.000 |
| 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 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".