Preoperative Chemoradiotherapy for Locally Advanced Rectal Cancer: A Retrospective Analysis
Bibliographic record
Abstract
Purpose To evaluate the outcomes of patients with locally advanced rectal cancer (LARC) treated with preoperative chemoradiotherapy (CRT) at a community cancer center. Methods A retrospective chart review was conducted for patients with biopsy-proven rectal adenocarcinoma treated with CRT between January 2017 and June 2020. Patients were excluded if there was metastatic disease (stage IV) at presentation, if curative resection was not planned, or if they received additional preoperative chemotherapy. Preoperative radiotherapy was typically 50.4 Gy in 28 fractions with concurrent capecitabine chemotherapy, followed by surgery six to eight weeks later. Postoperative adjuvant FOLFOX chemotherapy was typically recommended in suitable patients. Outcomes measured included surgical margin status, pathological complete response (pCR), local recurrence rate, distant metastases, cancer-specific survival, and overall survival. Results A total of 120 patients underwent preoperative CRT during this period. Seven patients did not undergo subsequent surgical resection. The pCR rate was 14%, and R0 resection (negative margins) was achieved in 93% of cases. The cumulative incidence of local recurrence was 6%, and distant metastases developed in 23% of patients. The most common metastatic sites were the liver and lungs. With a median follow-up of 28 months, Kaplan-Meier analyses demonstrated a 78% cancer-specific survival (CSS) and 75% overall survival (OS). Conclusion Preoperative CRT resulted in a 14% pCR rate, which was associated with high R0 (93%) and low local recurrence rates (6%). Distant metastatic recurrence rate remains a concern (23%).
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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 | 0.001 | 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) | 0.001 | 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".