Prognostic factors associated with short-term survival (STS) in advanced pancreatic cancer (APC): A Canadian multicenter analysis from the CHORD Consortium.
Bibliographic record
Abstract
e15717 Background: The survival of patients (pts) with APC (locally advanced/metastatic) is slowly improving; however in some pts it remains extremely short. Few studies have evaluated the clinical, pathologic and treatment characteristics associated with STS in APC. Methods: Pts with APC (between 2011-2017) were included in the analysis. Descriptive analyses were conducted for demographic, tumor and treatment characteristics between pts who survived ≤ and > 90 days using Wilcoxon rank-sum test and Chi-square test for continuous and categorical variables respectively. Multivariable logistic regression was performed to identify association between pts’ characteristics and STS. Results: A total of 580 pts were included in the analysis: median age 68, 53% male, 92% metastatic and 53% ECOG 0/1. STS ≤90 days occurred in 152 pts (26.2%), with 65.1% not receiving any chemotherapy. Median overall survival for STS was 49 days vs. 276 for non-STS. At least 1 cycle of chemotherapy was administered to 358 pts; mean duration of 1st line chemotherapy for pts with STS ≤90 was 1.5(SD 2.5) cycles (N = 53), compared to 7.6(SD 11.1) cycles (N = 305) for pts surviving > 90 days. Prognostic factors associated with STS ≤90 days were neutrophil:lymphocyte ratio, LDH, metastatic disease, ECOG and not receiving chemotherapy (Table). Other clinical factors (BMI, smoking history, diabetes) and laboratory values (platelet, baseline CA19-9, estimated GFR) were not prognostic. Conclusions: In a multicenter database of Canadian academic centers, < 2/3 of pts received at least 1 cycle of chemotherapy. STS ≤90 days occurred most often in pts who did not receive chemotherapy. Prognostic factors associated with STS include routine laboratory values, receipt of chemotherapy, ECOG and the presence of metastatic disease. Further analyses of these factors may help improve survival in APC. [Table: see text]
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".