Efficacy and Prognostic Factors for Y-90 Radioembolization (Y-90) in Metastatic Neuroendocrine Tumors with Liver Metastases
Bibliographic record
Abstract
Background. Yttrium-90 (Y-90) can be an effective liver-directed therapy for patients with metastatic neuroendocrine tumors (NETs), but population-based data are limited. We characterized the use of Y-90 in NET patients and identified factors associated with response. Methods. We identified 49 patients with metastatic liver-dominant NETs across BC Cancer’s six regional centres who received Y-90 between June 2011 and January 2017 in British Columbia, Canada. Baseline characteristics, radiographic responses, and outcomes were summarized. Results. Of the 49 patients who received Y-90, the median age was 56 years (range 21–78), 49% were male, and 94% had an ECOG performance status of 0–1. The primary location of the NET included pancreas (31%), small bowel (41%), large bowel (6%), unknown (14%), and others (12%). 69% of these patients had liver metastases alone, and tumors were graded as G1 (61%), G2 (25%), G3 (2%), and unknown (12%). Prior therapies included surgery (63%), local ablative therapy (25%), somatostatin analogue (69%), and systemic therapy (35%). The median Y-90 dose was 2.2 GBq (range 0.8–3.6), as SIR-spheres (69%) or TheraSpheres (29%). Median time to Y-90 from diagnosis of metastases measured 1.54 years. 88% received segmental Y-90, with 1 (69%), 2 (29%), and 3 (2%) treatments. Y-90 resulted in partial response (53%), stable disease (33%), and progressive disease (12%). Y-90 was well-tolerated, with infrequent grade 3-4 biochemical toxicities (2%) and grade 3 abdominal pain (6%). Longer overall survival (OS) was associated with resection of primary tumor, well-differentiated histology, and low Ki-67. Median OS was 27.2 months (95% CI 8.0–46.5).Conclusions. In our population-based cohort, Y-90 was well-tolerated in patients with metastatic liver-dominant NETs. Prior surgical resection was an important predictor of OS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".