A real world multicenter study of first (1L) and second (2L) line treatment patterns and outcomes in advanced pancreatic cancer (APC).
Bibliographic record
Abstract
476 Background: FOLFIRINOX (FFX), gemcitabine plus nab-paclitaxel (GN), and gemcitabine (gem) are 3 publicly funded and available treatment options for locally advanced (LAPC) and metastatic pancreatic cancer (MPC) in Canada since 2014. Without head-to-head trials that directly compare all 3 regimens, treatment selection and outcomes in 1L and 2L remain poorly characterized in routine clinical practice. Methods: Data from 4 tertiary, 8 regional, and 28 community hospitals in Canada were pooled. LAPC and MPC patients diagnosed from 2014 onwards and who received at least 1 line of systemic therapy were included. Analyses were conducted to identify predictors of treatment choice and to determine the relationship between treatment patterns and overall survival (OS) from APC diagnosis to death. Results: We identified 279 eligible patients. Median age was 64 (IQR 56-69) years, 55% were men, and 46% were ECOG ≥2. There were 27% LAPC and 73% MPC. In the 1L setting, FFX and GN were given in 44% and 41% of patients, respectively, and gem in 15%. GN was the preferred multi-agent therapy in worse ECOG patients (66% in ECOG 2+ vs 21% in ECOG 0, p = .001) and in more recently diagnosed cases (63% in 2016 vs 25% in 2014, p = .001). 1L treatment selection was not influenced by other baseline characteristics, such as age, sex, tumor location, or LAPC vs MPC status (all p > 0.05). A total of 91 patients proceeded to subsequent therapies, of whom 55 (60%), 27 (30%), and 9 (10%) had received 1L FFX, GN, and gem, respectively. In the 2L setting, GN after 1L FFX (41/55; 75%) and fluoropyrimidine (FP) after 1L GN (21/27; 78%) were the most common sequential approaches. Patients who underwent 2L therapy had better OS than those who did not (13 vs 7 months, p = .001). After adjusting for confounders, receipt of 1L FFX plus 2L GN or 1L GN plus 2L FP resulted in improved OS when compared to other treatment sequences (HR 0.43, 95%CI 0.28-0.67, p = 0.001 and HR 0.57, 95%CI 0.39-0.83, p = 0.004, respectively). Conclusions: One third of APC patients receive 2L therapy, highlighting the feasibility of 2L trials. Use of 1L multi-agent therapy followed by 2L non-cross-resistant regimens represents a reasonable treatment strategy for APC in the real world.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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 | 0.000 |
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".