Impact of lymph node retrieval and pathological ultra‐staging on the prognosis of stage II colon cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: A minimum number of lymph nodes must be assessed for accurate diagnosis of stage II colon cancer. We assessed number of lymph nodes retrieved, pathological ultra-staging, and outcome in stage II colon cancer. MATERIALS AND METHODS: Consecutively treated patients with stage II colon cancer were identified. Baseline and outcome data were collected. Retrospective ultra-staging using lymphovascular invasion (LVI) and nodal micrometastases was performed. Patients were divided into two groups: group I had <or=6 nodes and group II had >6 nodes retrieved. Survival was analyzed. RESULTS: One hundred and fifteen patients were included in the study. The 5 year overall survival was worse in group I versus II (P = 0.03). LVI and micrometastases were identified but neither predicted survival. Disease failure in group I was due to distant metastases rather than local recurrence. CONCLUSIONS: Inadequate retrieval and assessment of lymph nodes is associated with worse outcome in stage II colon cancer patients. Recurrence patterns support the hypothesis that disease recurrence occurred due to inaccurate staging. In this small study, LVI or nodal micrometastases did not predict survival. Maximal attention should be paid to the total number of lymph nodes retrieved before embarking on potentially more resource intensive staging methods.
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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 | 0.001 | 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) | 0.001 | 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 it