O130 Transarterial chemoembolization in rectal cancer: a systematic review
Bibliographic record
Abstract
Abstract Background Locally advanced rectal cancer (LARC) is typically treated with neoadjuvant chemoradiotherapy. Response can be unpredictable, with 8-20% of patients achieving complete pathological response, whilst 20-30% have no response or progression. Transarterial chemoembolisation (TACE) is established as a non-surgical option to treat colorectal liver metastases by delivering chemotherapy and an embolic agent via its primary arterial supply. This allows for reduction in systemic toxicity whilst delivering higher doses to tumours. There have been trials of TACE in LARC, but its role as a therapeutic modality is still unknown. Therefore, this review aims to assess existing evidence of TACE in LARC and whether it warrants further investigation as a treatment. Methods A systematic literature search was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Databases searched included PubMed, Scopus and Web of Science. Risk of bias was assessed using the Newcastle-Ottawa scale. The assessed outcomes included complete pathological response, objective response rate, complications, recurrence, disease-free and overall survival. Results Five reports were considered for inclusion. Minimal complications and adverse events were noted. Improved pathological complete response or objective response rates were noted in four out of five studies when compared to systemic neoadjuvant regimes. One study showed TACE reduced the risk of distant recurrence. Significant heterogeneity and bias were noted in all studies. Conclusion TACE is a safe modality, but its superiority over conventional treatment has yet to be demonstrated. Current literature is of inadequate quality but warrants further investigation in preclinical and clinical settings.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".