Examining stage IIB survival in a population‐based cohort of patients with colorectal cancer
Bibliographic record
Abstract
BACKGROUND: In Nova Scotia, Canada, a previous study of colorectal cancer (CRC) cases diagnosed between January 1, 2001, and December 31, 2005, found that patients with stage IIB CRC had similar 5-year overall survival (OS) to those with stage IIIC cancer. This study sought to examine factors contributing to the observed stage IIB outcome, specifically nodal harvest, receipt of chemotherapy, and use of a new coding system to derive stage. METHODS: The provincial cancer registry identified all CRC cases diagnosed during the study period and staged this cohort using the Collaborative Stage (CS) Data Collection System. All patients with stage II and III cancer in the cohort were examined. Kaplan-Meier (KM) survival curves compared 5-year OS for patients with stage IIB cancer based on the factors of interest, and compared patients with stage IIB cancer to those with stage IIA and III cancer. RESULTS: OS for patients with stage IIB cancer (n = 187) was 44.7%, and differed depending on adequacy of nodal harvest (P = .005) and whether pathological or clinical/mixed evidence was used to derive stage (P = .013). Pathologically-staged patients with stage IIB cancer who had adequate nodal harvest had marginally improved OS compared to pathologically-staged patients who had inadequate nodal harvest (P = .07), and improved survival compared to patients with clinical/mixed stage (P = .004). Pathologically-staged patients with stage IIB cancer with adequate nodal harvest demonstrated similar 5-year OS to those with stage IIA and III cancer (P = .52 and P = .25, respectively). Cox proportional hazards models supported these findings. CONCLUSIONS: The inclusion of clinical/mixed evidence into staging classification and, perhaps to a lesser extent, the adequacy of nodal harvest appear to contribute to the observed worse survival for patients with stage IIB versus stage III cancer.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".