Small Hepatocellular Carcinoma With Low Tumor Marker Expression Benefits More From Anatomical Resection Than Tumors With Aggressive Biology
Bibliographic record
Abstract
OBJECTIVE: We assessed prognostic advantage of anatomical resection (AR) over nonanatomical resection (NAR) for hepatocellular carcinoma (HCC) according to multiplication of α-fetoprotein, des-γ-carboxyprothrombin, and tumor volume (ADV) scores. BACKGROUND: Superiority of AR over NAR is debated. ADV score is surrogate marker of postresection prognosis for solitary HCC. METHODS: This study included 1572 patients who underwent curative resection for solitary HCC of 2.0 to 5.0 cm between 2006 and 2014. RESULTS: Preoperative patient profiles were not statistically different between AR and NAR groups. In 1324 naïve patients without preoperative treatment, AR group showed lower recurrence rates (P = 0.003) and higher patient survival rates (P = 0.012) than NAR group. AR group showed lower recurrence rates in patients with ADV ≤5 log (P ≤ 0.046). ADV scores >4 log and >3 log were independent risk factors for tumor recurrence and patient survival in treatment-naïve patients, respectively. In treatment-naïve group with preserved hepatic functional reserve, AR group showed lower recurrence rates in patients with ADV ≤4 log (P = 0.026). Absence of microvascular invasion also showed lower recurrence rates (P = 0.007) in AR group. In 248 patients with preoperative treatment, AR group showed lower recurrence rates (P = 0.001) and higher patient survival rates (P = 0.006). AR group showed lower recurrence rates in patients with ADV ≤4 log (P < 0.001) and higher survival rates in patients with ADV ≤5 log (P ≤ 0.043). CONCLUSIONS: Prognostic benefit of AR was evident in patients with ADV score ≤4 log or absence of microvascular invasion. Patients with less aggressive tumor biology benefit more from AR than NAR, thus being reasonably indicated for AR.
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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".