Small Particle DEBIRI TACE as Salvage Therapy in Patients with Liver Dominant Colorectal Cancer Metastasis: Retrospective Analysis of Safety and Outcomes
Bibliographic record
Abstract
The aim of this study was to examine the safety and efficacy of 40 µm and 75 µm calibrated irinotecan-eluting beads (DEBIRI-TACE) for the treatment of colorectal cancer metastases. We conducted a retrospective review of 36 patients with unresectable liver metastases from colorectal cancer who were treated with DEBIRI-TACE between 2017 to 2020. Patients who received at least one session of DEBIRI were included in our analysis. A total of 105 DEBIRI sessions were completed. 86% of patients (n = 31) underwent one round of treatment, 14% of patients (n = 5) underwent two distinct rounds of treatment. The majority of patients were discharged the next day (92%, n = 33 patients) with no 30-day post-DEBIRI mortality. Five high-grade adverse events occurred, including longer stay for pain management (n = 2), postembolization syndrome requiring readmission (n = 2), and liver abscess (n = 1). The average survival from diagnosis of metastatic disease was 33.3 months (range 11–95, median 28). Nine of 36 patients are still alive (December 2020) and have an average follow-up time of 36.8 months from T0 (range 12–63, median 39). Small particle DEBIRI is safe and well-tolerated in the salvage setting, with outcomes comparable to that of larger bead sizes.
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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 | 0.001 | 0.002 |
| 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".