A 15-Year Single-Institution Retrospective Study of Primary Pancreatic Cancer Treated with Non-Ablative Palliative Radiotherapy
Bibliographic record
Abstract
We studied the use of palliative radiotherapy (RT) among patients with primary, non-curable, locally advanced pancreatic cancer. In this subset of patients, with very poor survival, various palliative RT dose fractionation schemes are used; but, in the absence of a guideline, practice patterns vary, and dose choice is mainly based on the physician’s intuition. We divided the patients into three groups, according to the dose fractionation schedules received: low (A), intermediate (B), and high (C) dose groups, to study the potential differences in outcome between the different dose prescriptions. Cohort: n = 184. Median age: 69 years. Male: n = 105 (57%), female: n = 79 (43%). Stage IV: n = 117 (64%). T4: n = 127 (69%). Tumor location: head: n = 109 (59%), body: n = 37 (20%), tail: n = 25 (14%), neck: n = 11 (6%), and uncinate: n = 2 (1%). Prior systemic therapy: n = 66 (36%). Most common dose fractionations received: 20 Gy in five fractions n = 67 (36%), 30 Gy in 10 fractions n = 49 (27%), and 8 Gy in one fraction n = 23 (13%). Group A: n = 33 (18%), median overall survival (OS) 19 days (95% CI 4–33). Group B: n = 84 (46%), median OS 52 days (95% CI 43–60). Group C: n = 67 (36%), median OS 126 days (95% CI 77–174). Median days to in-field progression: Group A 59 days (range 7–109), Group B 96 days (range 19–173), and Group C 97 days (range 13–475). To our knowledge, this is the largest reported retrospective cohort of patients receiving non-ablative palliative RT to treat their primary pancreatic tumors. Most patients had metastatic disease, T4 tumors of the pancreatic head and had not received prior systemic therapy. A significant survival benefit was seen favoring the high dose/longer RT fractionation group, presumably due to appropriate patient selection rather than an RT effect. Despite the relatively short median overall survival, one fifth of the patients were found to experience an in-field progression following RT.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".