Feasibility and safety of endoscopic ultrasound-guided diffusing alpha emitter radiation therapy for advanced pancreatic cancer: Preliminary data
Bibliographic record
Abstract
Abstract Background and study aims Pancreatic cancer is a devastating disease with limited locoregional treatment options. Diffusing alpha-emitter radiation therapy (Alpha DaRT), a novel cancer treatment using alpha-particle interstitial radiotherapy, may help address this challenge. The aim of this study was to evaluate the feasibility and safety of endoscopic ultrasound (EUS)-guided Alpha DaRT for advanced pancreatic cancer. Patients and methods Patients with inoperable locally advanced or metastatic pancreatic adenocarcinoma were treated with EUS-guided Alpha DaRT insertion. The Alpha DaRT sources were delivered into pancreatic tumors using a standard EUS needle with a novel proprietary applicator. Adverse events (AEs) were assessed based on the Common Terminology Criteria for Adverse Events version 5.0. Tumor response was evaluated by imaging 4 to 6 weeks post treatment. Results The first five patients were treated between March and September 2023. The procedure was technically successful in all cases, with Alpha DaRT sources inserted into the target tumor. Estimated gross tumor volume coverage ranged from 8% to 44%. Fourteen AEs were reported among three patients. Four were serious AEs, none of which was associated with the treatment, but rather, with disease progression or medical assistance in dying. Only two AEs (mild) were deemed possibly related to the study device. At the 35-day visit, two patients had progressive disease and three had stable disease, with one of the latter showing partial response 2 months post procedure. Conclusions Preliminary results from this first-in-human trial indicate that EUS-guided Alpha DaRT treatment for unresectable pancreatic cancer is feasible and safe, with no device-associated serious AEs. Further investigation of this promising novel modality is underway.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".