Impact of Sequencing of Treatment Modalities on Survival in Nonmetastatic Hepatocellular Carcinoma
Bibliographic record
Abstract
OBJECTIVES: Hepatocellular carcinoma (HCC) is the most common type of liver malignancy and the third leading cause of cancer-related death in the world. Liver transplant is a cornerstone in treating nonmetastatic disease, but a significant portion of patients miss the opportunity of upfront liver transplant given the long waiting time for donor organs. Herein, we compare the survival outcomes between upfront liver transplant, liver transplant with bridge systemic therapy, and systemic therapy only. METHODS: The National Cancer Database was queried for patients diagnosed with non-metastatic hepatocellular carcinoma (HCC) between 2004 and 2017. After including only patients with clinical N0 stage who received either systemic therapy alone, liver transplant alone or liver transplant with bridge systemic therapy, we split the cohort into 3 groups: systemic therapy only (including intra-arterial chemotherapy eg, TACE) group, upfront liver transplant group and liver transplant with bridge systemic therapy group. We evaluated overall survival (OS) among the three groups. We studied the OS using Kaplan-Meier estimates and multivariate Cox regression analyses to evaluate factors associated with overall survival (OS). RESULTS: A total of 29,691 patients with nonmetastatic HCC were included for analysis, of which 25,122 (84.6%) were treated with systemic therapy only, 2513 (8.5%) were treated with bridge systemic therapy followed by liver transplant, and 2056 (6.9%) were treated with upfront liver transplant without systemic therapy bridge. We found that patients who were treated with bridge systemic therapy followed by liver transplant and patients who were treated with upfront liver transplant had a statistically significantly better OS compared to patients who were treated with systemic therapy only (mean OS was 101.9 mo and 98.2 vs. 39.4 mo, respectively, with P <0.001 for all). Whereas there was no significant difference in OS between patients who were treated with bridge systemic therapy followed by liver transplant and patients who were treated with upfront liver transplant (mean OS was 101.9 vs. 98.2 months, P =0.187). On multivariate analysis, factors associated with worse OS were older age (HR: 1.011; 95% CI: 1.010-1.013; P <0.001), Male sex (HR: 1.048; 95% CI: 1.014-1.084; P =0.006), White compared with African American race (HR: 1.055; 95% CI: 1.012-1.099; P =0.011), no insurance status (HR: 1.155; 95% CI: 1.079-1.237; P <0.001), clinical T4 stage compared with T0 stage (HR: 1.366; 95% CI: 1.257-1.483, P <0.001), and systemic therapy alone compared with upfront liver transplant and liver transplant with bridge systemic therapy (HR for upfront liver transplant and transplant with bridge systemic therapy vs. systemic therapy was 0.202; 95% CI: 0.184-0.223, and HR: 0.194, 95% CI: 0.178-0.212, respectively, with P <0.001 for all). CONCLUSIONS: Patients with nonmetastatic HCC who were treated with upfront liver transplant or liver transplant with bridge systemic therapy had statistically significant improvement in OS compared with patients who were treated with systemic therapy only. While our study confirms the survival benefit of liver transplant among patients with nonmetastatic HCC, these results raise the importance of proceeding with liver transplant after intra-arterial and/or systemic treatments in patients who are not initially eligible for or missed the opportunity of upfront liver transplant.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".