Prognostic and Inflammatory Differences Between Upper and Mid–Lower Rectal Cancers in Non-Metastatic Stage II–II Disease
Bibliographic record
Abstract
Background: This study aimed to compare the clinical, pathological, and biochemical characteristics of upper rectal cancer (URC) and mid–lower rectal cancer (MLRC) in stage II and III non-metastatic rectal cancer and to identify distinct prognostic factors influencing survival and recurrence. Material and Methods: This retrospective cohort study included 100 patients with stage II and III non-metastatic rectal adenocarcinoma who underwent neoadjuvant chemoradiotherapy (nCRT) followed by curative-intent surgery between 2021 and 2024. Patients were categorized into URC (n = 53) and MLRC (n = 47) groups. Parameters analyzed included demographic factors, ASA score, surgical characteristics, pathological features (tumor stage, lymph node involvement, lymphovascular invasion (LVI), perineural invasion (PNI), tumor budding, tumor regression grade (TRG)), and biochemical markers (carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), white blood cell (WBC) count, neutrophil count, platelet count (PLT), and C-reactive protein (CRP)). One-year overall survival (OS) and disease-free survival (DFS) were analyzed using Kaplan–Meier survival curves, and Cox regression models identified independent prognostic factors. Results: Preoperative CEA levels were higher in MLRC (p = 0.05), whereas WBC count (p = 0.01), neutrophil count (p = 0.02), PLT (p = 0.01), and CRP levels (p = 0.01) were higher in URC. Pathological analysis revealed higher LVI (p = 0.04), PNI (p = 0.04), and tumor budding (p = 0.03) in MLRC. At one-year follow-up, OS rates were 82.1% (URC) vs. 80.3% (MLRC) (p = 0.85), and DFS rates were 78.6% (URC) vs. 73.4% (MLRC) (p = 0.72). Multivariate Cox regression analysis identified age (HR: 1.04, p = 0.03), ASA score (HR: 1.22, p = 0.01), CRP (HR: 1.18, p < 0.001), preoperative CEA (HR: 1.12, p = 0.02), preoperative CA19-9 (HR: 1.09, p = 0.03), LVI (HR: 1.42, p < 0.001), PNI (HR: 1.35, p = 0.02), and tumor budding (HR: 1.28, p = 0.03) as independent prognostic factors for OS. Similar trends were observed for DFS, with T stage (HR: 1.35, p = 0.01) and tumor size (HR: 1.22, p = 0.01) also being found significant. Conclusions: Inflammatory markers, tumor burden indicators (LVI, PNI, budding, tumor size, T stage), and preoperative CEA/CA19-9 were identified as significant predictors, suggesting a risk-adapted approach to rectal cancer treatment.
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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".