A network meta-analysis of adjuvant systemic therapy in resected pancreatic cancer.
Bibliographic record
Abstract
396 Background: Multiple randomized controlled trials (RCTs) have established several systemic therapy regimens as adjuvant therapy treatment options for resected pancreatic cancer, including modified FOLFRINOX (mFFX), gemcitabine and capecitabine (GemCap) and S1, mostly based on comparison with gemcitabine (Gem) alone. Many of these regimens have not been directly compared in RCTs and their relative survival benefits are unknown. Methods: A systematic review was conducted using MEDLINE, EMBASE, Cochrane Central and ASCO abstracts to identify phase III RCTs up to June 2018 that examined adjuvant systemic therapy in resected pancreatic cancer. Two reviewers independently reviewed the studies and discrepancies were resolved either by discussion or by a third reviewer. Data including study characteristics and outcomes including overall survival (OS) and disease-free survival (DFS) were extracted. Indirect comparisons of all regimens were simultaneously compared using random-effects network meta-analyses (NMA) (R package “netmeta”) which maintains randomization within trials. Results: Nine phase III RCTs involving 3,394 patients and 6 regimens (5-flourouracil and folinic acid, Gem, gemcitabine and erlotinib (GemErl), GemCap, mFFX and S1) were identified. Hazard ratios (HR) and 95% confidence intervals (CI) of OS and DFS of selected comparisons from the results of the NMA are shown in the table. Conclusions: Both mFFX and S1 appeared to be superior to GemCap and can be considered as reasonable standard treatment options for suitable patients and as control arm regimens of future adjuvant clinical trials. [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 | 0.042 | 0.069 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.058 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".