Stereotactic Radiotherapy for Pancreatic Cancer: A Single-Institution Experience
Bibliographic record
Abstract
Introduction Despite treatment advances, the prognosis of locally advanced pancreatic cancer is poor. Treatment remains varied and includes systemic and radiotherapy (RT). Stereotactic body radiotherapy (SBRT), highly conformal high-dose RT per fraction, is an emerging treatment option. Materials and methods We performed a single-institution retrospective review of patients with pancreatic adenocarcinoma treated with SBRT from 2015-2017. The median dose was 27 Gy (range: 21-36 Gy) in three fractions. Endpoints included local progression (RECIST 1.1; Response Evaluation Criteria in Solid Tumors 1.1), distant metastasis, overall survival, and toxicity. Results Forty-one patients were treated, with a median follow-up of eight months. Patients who received SBRT had unresectable (49%), metastatic (17%), or borderline resectable (7%) disease, declined surgery (17%), medically inoperable (7%), or developed local recurrence following the Whipple procedure (2%). The six-month and one-year rates of local progression-free survival, distant metastasis-free survival, and overall survival were 62% and 55%, 44% and 32%, and 70% and 49%, respectively. Five patients (12%) experienced seven late gastrointestinal (GI) grade 3 events. Conclusion SBRT may be considered a treatment option to achieve local control of pancreatic cancer and is associated with a modest risk of severe late GI toxicities. Systemic therapies remain important, given the proportion of patients who develop distant metastases.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".