Comparison of a Newly Proposed Staging System with 7th Edition AJCC/UICC System for Surgically Resected Patients with Intrahepatic Cholangiocarcinoma
Bibliographic record
Abstract
Background: Intrahepatic cholangiocarcinoma (IHCC) is a rare but lethal primary liver cancer. Debate exists about whether tumor size should be considered in disease staging. This study aimed to examine the association between tumor size and overall survival (OS) in surgically resected patients with IHCC and to compare a newly proposed staging system that includes tumor size with the current American Joint Cancer Committee on Cancer classification/ Union for International Cancer Control (AJCC/UICC) system. Methods: This is a retrospective population-based study from 2002-2012 in Ontario, Canada. Patients with IHCC who underwent surgical resection were identified from the Ontario Cancer Registry and Canadian Institute for Health Information. Pathology data was abstracted from primary pathology reports. The association between largest tumor size and OS was assessed with multivariate Cox proportional hazards regression. The predictive accuracy and discriminative abilities of the 7th edition AJCC/UICC TNM staging system was compared with the newly proposed staging system using Kaplan-Meier survival curves, the proportional hazards model and a concordance index (c-index), respectively. Results: The study cohort of 121 cases had a median age of 63.9 (Range: 30.7-86.0), 43% were men, the median tumor size was 6 cm (Range: 0.6-13.0), and median follow-up time was 37.6 months (Range: 0.3-126.7). After multivariate analysis adjusting for sex and T-category, no association was observed between tumor size and OS (HR for ≥5 cm=1.08, 95% CI: 0.34-3.49, p-value=0.893). Comparison of the TNM staging systems revealed that the 7th edition AJCC/UICC was comparable at predicting and discriminating survival to the newly proposed system (c-index=0.92 vs 0.86). Conclusion: There is no association between tumor size and OS in patients with surgically resected IHCC and these results argue against the inclusion of tumor size into IHCC disease staging.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".