Adjuvant Radiotherapy in Incidental Positive Nodal Disease in Rectal Cancer—A Systemic Review
Bibliographic record
Abstract
BACKGROUND: The optimal adjuvant treatment strategy for incidentally detected node-positive rectal cancer following curative surgery remains uncertain. While preoperative chemoradiotherapy (CRT) is the standard for locally advanced rectal cancer, the role of adjuvant radiotherapy (RT) in early stage node-positive disease (stage IIIA) remains debated. This systematic review evaluates survival outcomes associated with different adjuvant modalities and identifies key prognostic factors influencing disease progression. METHODS: A systematic search of PubMed, EMBASE, MEDLINE and the Cochrane Library was conducted up to August 2024, following PRISMA guidelines. Retrospective studies assessing oncological outcomes in patients with incidental nodal disease rectal cancer who underwent curative surgery without prior neoadjuvant therapy were included. Risk of bias was assessed using the Newcastle-Ottawa Scale. Due to heterogeneity of studies, a meta-analysis was not performed. This review is registered with PROSPERO (CRD42024596805). No funding was received. RESULTS: Nine studies comprising 5989 patients were analysed. Adjuvant therapy was associated with improved outcomes compared to observation alone. Overall survival (OS) ranged from 61.3% to 92% for adjuvant chemotherapy (CT), 63% to 93% for CRT, and 42% to 82.1% for no adjuvant therapy. Disease-free survival (DFS) ranged from 43% to 90%. Local recurrence (LR) was lowest with CRT (2%-9.1%), while metastatic disease (MD) ranged from 20% to 50%. Poorer outcomes were linked to pN2 disease, positive margins, perineural invasion, high lymph node ratio and low tumour location. CONCLUSION: Adjuvant CT improves survival in incidental node-positive rectal cancer; RT may benefit high-risk subgroups. Further prospective studies are warranted.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".