International Validation and Refinement of Oncological Borderline Resectability Criteria for Hepatocellular Carcinoma Using Tumor Burden Score to Predict Survival
Bibliographic record
Abstract
Objective: The aim of this study is to externally validate the original borderline resectability (BR) category for predicting overall survival (OS) in hepatocellular carcinoma (HCC) following resection and to assess whether incorporating the tumor burden score (TBS) and other clinical factors could enhance predictive accuracy. Background: A recent Japanese expert panel introduced a new HCC classification scheme: resectable (R), borderline resectable 1 (BR1), and borderline resectable 2 (BR2). Methods: Patients undergoing curative-intent hepatectomy for HCC (2000–2023) were classified as R, BR1, and BR2 using the original BR and a novel TBS-BR category. The TBS-BR category replaces BR’s categorical tumor morphology factors with the continuous TBS (TBS² = [maximum tumor diameter]² + [number of tumors]²). Multivariable analysis identified oncologic, morphometric, and patient-level factors associated with OS, which were incorporated into an online predictive tool. Results: Among 1766 patients, the original BR category grouped 1504 (85.2%) as R, 249 (14.1%) as BR1, and 13 (0.7%) as BR2. Utilizing the TBS-BR category, patients were reclassified as TBS-BR R (n = 684, 38.7%), BR1 (n = 1009, 57.1%), and BR2 (n = 73, 4.1%). Both the original and TBS-BR categories correlated with 5-year OS (original: 65.1%, 48.2%, 46.4%; TBS-BR: 70.8%, 58.3%, 40.0%; P < 0.001 for both; area under the curve: 0.54 vs 0.58). On multivariable analysis, TBS-BR1 (hazard ratio [HR]: 1.59 [1.20–2.09]; P = 0.001), TBS-BR2 (HR: 2.45 [1.47–4.07]; P < 0.001, reference: TBS-BR R), American Society of Anesthesiologists (ASA) class >2 (HR: 1.40 [1.09–1.80]; P = 0.007), albumin-bilirubin (ALBI) score (HR: 1.51 [1.21–1.88]; P < 0.001), and log α -fetoprotein (AFP) (HR: 1.07 [1.03–1.11]; P < 0.001) were independently associated with OS. A TBS-BR composite model based on these factors (TBS-BR category, ASA class, ALBI score, and log AFP) was developed and made available online (https://makbn.shinyapps.io/BRHCC/). The model’s area under the receiver operating characteristic at 5 years (0.70) outperformed both the original BR (0.57) and Barcelona Clinic Liver Cancer classification (0.64). Conclusions: The TBS-BR composite model, integrating tumor morphology (TBS), tumor biology (log AFP), overall physical status (ASA class), and liver function (ALBI score) demonstrated superior predictive accuracy for OS compared with the original BR and Barcelona Clinic Liver Cancer classifications.
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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 | 0.002 | 0.001 |
| 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".