External validation of the 8th American Joint Committee on Cancer staging system for gall bladder carcinoma
Bibliographic record
Abstract
Background: To validate the changes within the American Joint Committee on Cancer (AJCC) 8th staging system for gall bladder carcinoma compared to AJCC 7th staging system. Methods: Surveillance, Epidemiology and End Results (SEER) database [2004–2014] was queried. Kaplan-Meier survival analyses and Log-rank testing were assessed according to both AJCC 7th and 8th staging systems. Likewise, Cox cancer-specific hazard ratio was evaluated according to both staging systems. Results: Overall survival was assessed according to the two staging systems; and P values for overall trend (log/rank test) were significant (P<0.001) for both scenarios. Cox regression cancer-specific hazard adjusted for age, gender, histology, gender and surgery was evaluated according to the two staging systems. According to AJCC 7th staging system, the following pair wise hazard ratio comparisons were significant (II vs. IIIA; IIIB vs. IVA; IVA vs. IVB). According to AJCC 8th staging system, the following pair wise hazard ratio comparisons were significant (II vs. IIIA; IVA vs. IVB). C-statistic was assessed using death from gall bladder carcinoma as the dependent variable; and the findings for the two staging systems were as follows: AJCC 7th staging system: 0.684 (SE: 0.008; 95% CI: 0.667–0.701); AJCC 8th staging system: 0.682 (SE: 0.009; 95% CI: 0.665–0.698). Conclusions: There is a comparable discriminatory performance for AJCC 8th staging system compared to AJCC 7th staging system. Change form location-based to number-based N category assessment does not improve the overall prognostic performance of the staging system.
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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 | 0.049 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".