Trends in Survival Based on Treatment Modality in Patients with Pancreatic Cancer: A Population-Based Study
Bibliographic record
Abstract
Background: Pancreatic cancer (pcc) is one of the most lethal types of cancer, and surgery remains the optimal treatment modality for patients with resectable tumours. The objective of the present study was to examine and compare trends in the survival rate based on treatment modality in patients with pcc. Methods: This population-based retrospective analysis included all patients with known-stage pcc in Ontario between 2007 and 2015. Flexible parametric models were used to conduct the survival analysis. Survival rates were calculated based on treatment modality, while adjusting for patient- and tumour-specific covariates. Results: The study included 6437 patients. We found no noticeable improvement in survival for patients with stage iii or iv tumours; however, for stage i disease, the 1-, 2-, and 5-year survival rates increased over time to 81% from 51%, to 71% from 35%, and to 61% from 22% respectively. Most improvements were seen for surgical modalities, with 2-year survivals increasing to 89% from 65% for distal pancreatectomy (dp) without radiation (rt) or chemotherapy (ctx), to 65% from 37% for dp plus rt or ctx, to 60% from 44% for Whipple-only, and to 50% from 36% for Whipple plus rt or ctx. Lastly, 5-year survival improved to 81% from 52% for dp only, to 41% from 12% for dp plus rt or ctx, to 49% from 25% for Whipple-only, and to 26% from 12% for Whipple plus rt or ctx. Conclusions: Most cases of pcc continue to be diagnosed at a late stage, with poor short-term and long-term prognoses. After adjustment for patient age, sex, and year of diagnosis, the survival for stage i tumours and for surgical modalities increased over time. Further research is needed to identify the reasons for improvement in survival during the study period.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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 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".