Hepatocellular carcinoma tumour burden score to stratify prognosis after resection
Bibliographic record
Abstract
BACKGROUND: Although the Barcelona Clinic Liver Cancer (BCLC) staging system has been largely adopted in clinical practice, recent studies have emphasized the need for further refinement and subclassification of this system. METHODS: Patients who underwent hepatectomy with curative intent for BCLC-0, -A or -B hepatocellular carcinoma (HCC) between 2000 and 2017 were identified using a multi-institutional database. The tumour burden score (TBS) was calculated, and overall survival (OS) was examined in relation to TBS and BCLC stage. RESULTS: Among 1053 patients, 63 (6·0 per cent) had BCLC-0, 826 (78·4 per cent) BCLC-A and 164 (15·6 per cent) had BCLC-B HCC. OS worsened incrementally with higher TBS (5-year OS 77·9, 61 and 39 per cent for low, medium and high TBS respectively; P < 0·001). No differences in OS were noted among patients with similar TBS, irrespective of BCLC stage (61·6 versus 58·9 per cent for BCLC-A/medium TBS versus BCLC-B/medium TBS, P = 0·930; 45 versus 13 per cent for BCLC-A/high TBS versus BCLC-B/high TBS, P = 0·175). Patients with BCLC-B HCC and a medium TBS had better OS than those with BCLC-A disease and a high TBS (58·9 versus 45 per cent; P = 0·005). On multivariable analysis, TBS remained associated with OS among patients with BCLC-A (medium TBS: hazard ratio (HR) 2·07, 95 per cent c.i. 1·42 to 3·02, P < 0·001; high TBS: HR 4·05, 2·40 to 6·82, P < 0·001) and BCLC-B (high TBS: HR 3·85, 2·03 to 7·30; P < 0·001) HCC. TBS could also stratify prognosis among patients in an external validation cohort (5-year OS 79, 51·2 and 28 per cent for low, medium and high TBS respectively; P = 0·010). CONCLUSION: The prognosis of patients with HCC varied according to the BCLC stage but was largely dependent on the TBS.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".