Comparative performances of the 7th and the 8th editions of the American Joint Committee on Cancer staging systems for intrahepatic cholangiocarcinoma
Bibliographic record
Abstract
BACKGROUND: We sought to evaluate and validate the 8th edition of the AJCC classification using a multi-institutional cohort of patients with intrahepatic cholangiocarcinoma (ICC). METHODS: Patients undergoing curative-intent hepatic resection for ICC between 1990 and 2015 at 14 major hepatobiliary centers were included and were staged according to 7th and 8th editions AJCC criteria. RESULTS: A total of 1154 patients underwent liver resection for ICC. When patients were staged using the AJCC 7th edition, T2a, T2b, and T4 patients had a higher hazard ratio (HR) of death compared with T1 (T2a, HR 1.43, P = 0.004; T2b, HR 1.99, P < 0.001; T4, HR 2.20, P < 0.001). T3 patients had a higher HR of death compared with T1 patients (HR 1.30, P = 0.029) but lower than T2a and T2b. According to AJCC 8th edition, T1b, T2, and T4 patients were at higher risk of death compared with T1a patients (T1b, HR 1.91, P < 0.001; T2, HR 2.29, P < 0.001; T4, HR 4.16, P < 0.001). As in the AJCC 7th edition, AJCC 8th edition T3 patients had a higher HR of death compared with T1 patients (HR 1.65, P = 0.001) but lower than T1b and T2. AJCC 8th edition. T-category performed slightly better than AJCC 7th edition with a C-index of 0.609 versus 0.590. CONCLUSIONS: A staging system that perfectly discriminates between stages has not yet been developed, but the AJCC 8th edition was able to better stratify the risk of death of Stage III and T3 patients.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".