Ratio of metastatic to examined lymph nodes is a powerful predictor of overall survival in rectal cancer: An analysis of Intergroup 0114
Bibliographic record
Abstract
4006 Background: Lymph node (LN) metastasis is associated with decreased survival in rectal cancer. It has been suggested that at least 14 LN be evaluated for adequate staging. However, a large percentage of patients have fewer than the recommended number of LN examined. We hypothesized that LN ratio would be predictive of overall survival in rectal cancer. Methods: Data was analyzed from Intergroup 0114, a mature trial of postoperative adjuvant chemotherapy and radiation in T 3/4 and/or LN positive rectal cancer. Survival was the same for all arms allowing the entire group to be considered as one. The primary endpoint evaluated was overall survival. A proportional hazards model was used to determine the relative prognostic impact of LN ratio compared to number of LN examined, number of positive LN, number of negative LN and AJCC nodal stage. LN ratio was defined as the number of positive LN divided by the total number of LN examined. Four groups were analyzed based on proportion of positive LN: =0.25, >0.25–0.50, >0.50–0.75 and >0.75. Results: 1,648 patients were evaluable. There were 251 T 1/2 , 1,251 T 3 and 146 T 4 tumors. 513 patients were N 0 , 743 N 1 and 392 N 2 . Median number of LN was 9. LN ratio was predictive of 5-year overall survival with rates of 0.71, 0.56, 0.50 and 0.43 respectively when analyzed by quartile (p<0.0001). LN ratio remained significant when overall survival was analyzed by number of LN examined and grouped into <10, <15 and >15 nodes evaluated (p<0.0001 for all). LN ratio also predicted overall survival in N 1 (p=0.04) and N 2 (p=0.0002) disease. When comparing LN ratio (χ 2 =79.5, p<0.0001) to number of LN examined (χ 2 =4.7, p=0.03), number of positive LN (χ 2 =38, p<0.0001), number of negative LN (χ 2 =32, p<0.0001) and AJCC nodal stage (χ 2 =55.5, p<0.0001), LN ratio appears to be the strongest predictor of overall survival. Conclusion: LN ratio predicts overall survival in patients with resected rectal cancer. Importantly, this is true in patients who have had a small number of LN evaluated, in addition to those with a large number of LN examined. LN ratio also appears to be a stronger predictor of overall survival than other described LN prognostic factors. LN ratio may be a useful variable to stratify outcome in patients with node-positive rectal cancer. No significant financial relationships to disclose.
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How this classification was reachedexpand
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".