Treatment sequencing in MPC, insights from a 3˚ care center.
Bibliographic record
Abstract
400 Background: Since 2011, options for treatment of metastatic pancreatic cancer (mPC) have improved with the use of nab-paclitaxel plus gemcitabine (n-PGEM) or FOLFIRINOX (FFX) as first line treatments (1LTx). In 2016, Nanoliposomal irinotecan plus 5FU (nal-IRI-5FU) demonstrated efficacy in 2LTx. Yet, optimal sequential Tx has not been established. Methods: We evaluated oncologist-selected Tx algorithms and resultant progression free & overall survival (PFS, OS) for pts with mPC from 2010 and 2018 at the Jewish General Hospital, Montreal, QC. This retrospective study included 203 pts with mPC (33 to 89 years, 54% male). Results: 1LTx included 66 pts on FFX, 60 pts on n-PGEM, and 66 pts on single-agent GEM. The remaining pts received Capecitabine (CAP) or another Tx (N = 11). Mean PFS in FFX, n-PGEM, and GEM groups was 5.07, 5.52, and 4.10 months, respectively (progression was 1˚ or 2˚ disease progression or a change of Tx due to adverse events or intolerance). Only the FFX and GEM groups were significant when compared (p = 0.049). Only 43.8% of pts (N = 89/203) advanced to 2LTx most receiving GEM (N = 27), n-PGEM (N = 21), or FFX (N = 11), PFS 3.87, 7.04, and 2.30 months, respectively. FFX and n-PGEM groups were significant when compared (p=0.011). CAP and nal-IRI-5FU were 2LTx options for 25.8% (N=23/89) and 7.9% (N = 7/89) of pts, respectively. For 30 pts in 3LTx, Txs included: nal-IRI-5FU (N = 8), clinical trials (CT) (N = 7), GEM (N = 5), FFX (N = 4), n-PGEM (N = 2), CAP (N = 2) and Irinotecan (IRI) (N = 2). Only 7 pts received 4LTx: GEM (N = 3), CAP (N = 2), CT (N = 1), and IRI (N = 1). Median OS from start of 1LTx for pts in FFX (N = 60), n-PGEM (N = 41), and GEM (N = 60) groups was 11.42, 9.50, and 6.23 months, respectively. (Excluding pts on ongoing tx and other censored data points). GEM tx was a significant prognostic factor for shorter OS, GEM verus FFX, HR 1.673 (1.165 to 2.402, p = 0.0053), GEM versus n-PGEM, HR 1.511 (1.012 to 2.258, p = 0.0437). No difference in survival was seen between FFX and n-PGEM groups, HR 0.903 (95% CI 0.605-1.349, p = 0.6196). Conclusions: Though FFX and n-PGEM are considered mainstays of 1LTx, GEM was chosen by physicians in ~1/3 of cases despite reduced PFS. Pts on FFX or n-PGEM had better OS compared to GEM alone, as expected. Further investigation into Tx sequencing in this and larger cohorts, is 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".