Comparative eligibility of metastatic pancreatic adenocarcinoma (MPA) patients for first-line palliative intent FOLFIRINOX (FIO) versus nab-paclitaxel plus gemcitabine (NG).
Bibliographic record
Abstract
e15264 Background: The ACCORD and MPACT trials demonstrated superiority of FIO and NG over gemcitabine alone, respectively, in the treatment of MPA. In the absence of a direct comparison between these regimens, it is unclear whether FIO or NG is superior. Because both trials had stringent yet different inclusion criteria, our aim was to determine the proportion of MPA patients (pts) who would be potentially eligible for first-line palliative intent FIO vs. NG in routine clinical practice. Methods: Consecutive pts diagnosed with MPA from 2000 to 2011, referred to any 1 of 5 regional cancer centers in British Columbia, Canada and who initiated palliative chemotherapy with gemcitabine were reviewed. Clinicopathological variables and treatment outcomes were retrospectively collected and compared among groups. For this study, eligibility criteria for each regimen were based on those described in the respective phase III trials. Results: A total of 473 pts were identified: median age was 66 years (range 34–89) and 258 (55%) were men. Only 25% of pts would be eligible for FIO as compared to 45% for NG. The main reasons for ineligibility to FIO were age >/= 75 years (19%), ECOG performance status (PS) >/= 2 (57%), and bilirubin > 1.5 times upper limit of normal (ULN) range (18%). The main reasons for ineligibility to NG were ECOG PS >/= 3 (15%), bilirubin > ULN (25%), and cardiac dysfunction (14%). Median overall survival (OS) for the entire cohort treated with gemcitabine was 5.8 months (95% CI 5.4-6.2). On univariate analyses, eligible pts for FIO had longer median OS than ineligible pts (8.6 vs. 4.7 months, p<0.001). Pts eligible for NG also had longer median OS than those deemed ineligible (6.7 vs 4.9 months, p=0.008). After accounting for ECOG PS in the multivariate model, eligibility for either FIO or NG no longer predicted for better OS. Conclusions: In this population-based analysis, almost twice as many MPA pts would be eligible for NG than FIO. The longer OS observed in the FIO-eligible population likely reflects the exclusion of ECOG PS 2 pts. Accurate assessment of PS in MPA pts can facilitate treatment decision making and help with the selection between FIO and NG.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".