Outcomes and Characteristics of Patients Receiving Second-line Therapy for Advanced Pancreatic Cancer
Bibliographic record
Abstract
OBJECTIVES: There is limited randomized data to guide second-line chemotherapy selection in advanced pancreatic cancer (APC). We aimed to characterize predictors and outcomes of second-line chemotherapy in patients with APC. METHODS: We identified all patients with APC [locally advanced (LAPC) or metastatic (MPC)] who received ≥1 cycle of first-line chemotherapy between January 2012 and December 2015 across 6 cancer centers in British Columbia, Canada. Baseline characteristics and survival outcomes were summarized. RESULTS: Of 676 patients with APC (31% LAPC, 69% MPC) who received ≥1 cycle of chemotherapy, 164 (24%) received second-line chemotherapy. These patients were younger, with lower ECOG and higher CA19-9 at presentation, compared with patients who did not receive second-line chemotherapy. There were no differences in rates of second-line chemotherapy between LAPC and MPC (28% vs. 23%; P=0.18). Only first-line FOLFIRINOX was associated with second-line chemotherapy. Median overall survival (OS) from second-line chemotherapy was longer with second-line gemcitabine/nab-paclitaxel than fluoropyrimidine or gemcitabine (7.9 vs. 5.1 vs. 4.3 mo; P=0.008). On multivariable analysis, longer OS from second-line chemotherapy was associated with gemcitabine/nab-paclitaxel, lower ECOG, and LAPC. CONCLUSIONS: In this population-based cohort, first-line FOLFIRINOX was the strongest predictor of second-line chemotherapy. Duration of therapy remains short and novel treatments are urgently needed.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".