Lymphocytic Reaction to Colorectal Cancer Is Associated with Longer Survival, Independent of Lymph Node Count, Microsatellite Instability, and CpG Island Methylator Phenotype
Bibliographic record
Abstract
PURPOSE: Host immune response to tumor may be an important prognostic factor for colon cancer patients. However, little is known on prognostic significance of histopathologic lymphoid reaction to tumor, independent of the number of lymph nodes examined and tumoral molecular alterations, including microsatellite instability (MSI) and the CpG island methylator phenotype (CIMP), both of which are associated with lymphocytic reaction and clinical outcome. EXPERIMENTAL DESIGN: Using 843 colorectal cancer patients in two independent prospective cohorts, we examined patient prognosis in relation to four components of lymphocytic reaction (i.e., Crohn's-like reaction, peritumoral reaction, intratumoral periglandular reaction, and tumor-infiltrating lymphocytes) and overall lymphocytic score (0-12). CIMP was determined using eight markers including CACNA1G, CDKN2A (p16), CRABP1, IGF2, MLH1, NEUROG1, RUNX3, and SOCS1. Cox proportional hazard models computed hazard ratio for mortality, adjusted for covariates including tumor stage, body mass index, lymph node count, KRAS, BRAF, p53, cyclooxygenase-2 (PTGS2), MSI, CIMP, and LINE-1 methylation. RESULTS: Increasing overall lymphocytic reaction score including tumor-infiltrating lymphocytes was associated with a significant improvement in colorectal cancer-specific and overall survival (log-rank P < 0.003). These findings remained significant (adjusted hazard ratio estimates, 0.49-0.71; P(trend) < 0.009) in multivariate models that adjusted for covariates, including body mass index, MSI, CIMP, LINE-1 hypomethylation, and cyclooxygenase-2. The beneficial effect of tumoral lymphocytic reaction was consistent across strata of clinical, pathologic, and molecular characteristics. CONCLUSIONS: Lymphocytic reactions to tumor were associated with improved prognosis among colorectal cancer patients, independent of lymph node count and other clinical, pathologic, and molecular characteristics.
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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 | 0.000 | 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) | 0.002 | 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".