Prognostic value of lymph node ratio in survival of patients with locally advanced rectal cancer
Bibliographic record
Abstract
BACKGROUND: The lymph node ratio (LNR) has been shown to be an important prognostic factor in patients with gastric, breast, pancreatic and colorectal cancer. We investigated the prognostic impact of the LNR in addition to TNM classification in patients with locally advanced rectal cancer. METHODS: We retrospectively analyzed patients who underwent curative resection for locally advanced rectal cancer between July 2005 and December 2010. We determined the LNR cutoff value using a receiver operating characteristic curve. The Kaplan-Meier method was used to estimate survival curves, while Cox regression analyses were used to evaluate the relationship between LNR and survival. RESULTS: We included 180 patients aged 28-83 years with median follow-up of 41.8 months. The median number of lymph nodes examined and lymph nodes involved were 11.5 and 4, respectively, and the median LNR was 0.366. An LNR of 0.19 (19%) was the cutoff point to separate patients with regard to median overall survival. Median overall survival was 64.2 months for patients with an LNR of 0, 59.1 for an LNR of 0.19 or less and 37.6 for an LNR greater than 0.19 (p = 0.004). The median disease-free survival was 32.9 months for patients with an LNR of 0, 30.4 for an LNR of 0.19 or less and 17.8 for an LNR greater than 0.19 (p = 0.002). CONCLUSION: Our results suggest that LNR should be considered an additional prognostic factor in patients with locally advanced rectal cancer.
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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".