Comparing resection and stereotactic body radiation therapy for hepatocellular carcinoma with macrovascular invasion: A propensity score matched study.
Bibliographic record
Abstract
521 Background: Macrovascular invasion (MVI) in hepatocellular carcinoma (HCC) patients is a poor prognostic factor. Current guidelines endorse systemic therapy for MVI. Local therapies present a potential for obliteration of MVI and improved survival. Surgery has been the standard local therapy at our institution, and stereotactic body radiotherapy (SBRT) has emerged as an alternative local therapy for this patient population. Methods: In this retrospective study, one-to-one optimal pair propensity score matching was used to compare outcomes of HCC patients with MVI who underwent surgery or received SBRT. Matching was done based on sex, age, ECOG, cirrhosis presence, Child-Pugh class, number of tumours, tumour volume, alpha-fetoprotein level, ALBI score, Japanese Classification of portal vein invasion, and hepatic vein invasion. Overall survival was estimated using the Kaplan-Meier method and between group differences determined using the log-rank test. The cumulative incidence of recurrence, accounting for the competing risk of death, was compared using Gray’s test. Results: Ninety of 193 patients were included after matching (45 patients in both the surgery and SBRT groups) (Table). The SBRT group had a median OS of 15 months (95% CI: 10-38), while in the surgery group it was 24 months (95% CI: 11-81). Comparing the 12-, 36-, and 60-month overall survival (OS) rates between the SBRT group (57%, 33%, 15%) and the surgery group (58%, 37%, 34%), there was no statistically significant differences (p=0.16); the 5-year OS was double in the surgical resection group. The 12-, 36-, and 60-month cumulative incidence of HCC recurrence in the SBRT group (47%, 73%, 75%) was comparable to the surgery group (69%, 69%, 69%) (p=0.89). Conclusions: Long term survival is possible in patients with HCC and MVI in a substantial minority of patients with HCC and MVI treated with local therapies. There was no statistical difference in outcomes; however, surgical resection resulted in numerically longer survival outcomes compared to SBRT after propensity score adjustment. There is rationale for investigating both local therapies with systemic therapies in future clinical trials. [Table: see text]
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".