Hepatic arterial infusion pump chemotherapy in the management of colorectal liver metastases: expert consensus statement
Bibliographic record
Abstract
Despite significant improvements in systemic therapy for patients with colorectal liver metastases (crlms), response rates in the first-line setting are not optimal, and response rates in the second-line setting remain disappointing. Hepatic arterial infusion pump (haip) chemotherapy has been extensively studied in patients with crlms, but it remains infrequently used. We convened an expert panel to discuss the role of haip in the contemporary management of patients with crlm. Using a consensus process, we developed these statements: haip chemotherapy should be given in combination with systemic chemotherapy.haip chemotherapy should be offered in the context of a multidisciplinary program that includes expertise in hepatobiliary surgery, medical oncology, interventional radiology, nursing, and nuclear medicine.haip chemotherapy in combination with systemic therapy should be considered in patients with unresectable crlms who have progressed on first-line systemic treatment. In addition, haip chemotherapy is acceptable as first-line treatment in patients with unresectable colorectal liver metastases.haip chemotherapy is not recommended in the setting of extrahepatic disease outside the context of a clinical trial.haip chemotherapy in combination with systemic therapy is an option for select patients with resected colorectal liver metastases. These consensus statements provide a framework that clinicians who treat patients with crlm can use when considering treatment with haip.
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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 | 0.048 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".