Recommendations for radioembolisation after liver surgery using yttrium-90 resin microspheres based on a survey of an international expert panel
Bibliographic record
Abstract
Guidelines on how to adjust activity in patients with a history of liver surgery who are undergoing yttrium-90 radioembolisation (90Y-RE) are lacking. The aim was to study the variability in activity prescription in these patients, between centres with extensive experience using resin microspheres 90Y-RE, and to draw recommendations on activity prescription based on an expert consensus. The variability in activity prescription between centres was investigated by a survey of international experts in the field of 90Y-RE. Six representative post-surgical patients (i.e. comparable activity prescription, different outcome) were selected. Information on patients’ disease characteristics and data needed for activity calculation was presented to the expert panel. Reported was the used method for activity prescription and whether, how and why activity reduction was found indicated. Ten experts took part in the survey. Recommendations on activity reduction were highly variable between the expert panel. The median intra-patient range was 44 Gy (range 18–55 Gy). Reductions in prescribed activity were recommended in 68% of the cases. In consensus, a maximum DTarget of 50 Gy was recommended. With a current lack of guidelines, large variability in activity prescription in post-surgical patients undergoing 90Y-RE exists. In consensus, DTarget ≤50 Gy is recommended. • BSA method does not account for a decreased remnant liver volume after surgery. • In post-surgical patients, a volume-based activity determination method is recommended. • In post-surgical patients, a mean D Target of ≤ 50Gy should be aimed for.
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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 | 0.030 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".