Guanylyl cyclase C (GCC) expression in lymph nodes (LNs) as a determinant of recurrence in stage II colon cancer (CC) patients (pts).
Bibliographic record
Abstract
3639 Background: The first phase of the multi-center prospectively specified retrospective study Validating Indicators To Associate Recurrence (VITAR), assessing the relationship between GCC gene expression in formalin fixed (FFPE) LNs and time to recurrence (TTR) in stage II CC pts not treated with adjuvant chemotherapy (Sargent, Annals Surg Onc 2011), showed promising initial results. Here we report a validation set of 463 new stage II CC pts. Methods: GCC mRNA was quantified by RT-qPCR using FFPE LNs from untreated T3N0 CC pts diagnosed from 1999-2008 with at least 12 LNs examined , blinded to clinical outcomes. Patients were classified by GCC LN ratio (LNR) (high risk: LNR > 0.1; low risk: LNR ≤ 0.1), with LNR defined as ratio of GCC positive to GCC informative LNs. Cox regression models tested the relationship between GCC and the primary endpoint of TTR, adjusted for age, tumor grade, number of LN examined pathologically, and lymphovascular invasion. Mismatch repair (MMR) status was also assessed. All primary analyses and cut-points were pre-specified. Results: 46pts (10%) recurred (rec), median follow-up was 65 months, median LNs examined was 20, and 42% (195/463) were classified high risk. Overall, TTR was not significantly associated with binary GCC LNR risk class (HR=1.47, p=.208) or DFS (HR= 1.39, p=.097). One site’s (n=97) tissue grossing method precluded appropriate LN assessment with existing GCC qualification methods. Excluding this site resulted in a TTR HR=1.91, p=0.051 (multivariate). In a post-hocanalysis excluding this site and using a 3-level GCC risk group of high (LNR > 0.20), intermediate (0.10 < LNR < 0.20) and low (LNR < 0.10), high risk group pts had a 5-yr rec risk of 22% versus 8% in low risk (HR 2.72, p=0.006). MMR status was not significantly associated with TTR (multivariate p=0.30). Conclusions: GCC status is a promising prognostic factor in appropriately staged stage II CC pts not treated with adjuvant therapy independent of traditional histopathology risk factors, but GCC determination must be performed with methodology adapted to the tissue procurement and fixation technique. Outcome associations were strengthened when considering a 3-level GCC categorization.
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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) | 0.001 | 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".