Real-world treatment patterns and clinical outcomes in patients receiving second-line (2L) treatment for advanced or metastatic gastric cancer (GC).
Bibliographic record
Abstract
102 Background: Despite increased survival demonstrated for patients with advanced / metastatic GC due to 2L chemotherapy, different standard of care options exist. This study aims to describe RW treatment patterns and clinical outcomes in patients with advanced / metastatic GC receiving 2L treatment. Methods: Retrospective chart review study conducted in Australia, Canada, Italy and UK. Patients diagnosed with metastatic / unresectable GC receiving 2L treatment between January 2013 and July 2015 were enrolled. Patient characteristics, treatment patterns and clinical outcomes were captured for 12 months from the start of 2L treatment or until death. Results: 280 patients were included (mean age 60.9 years, 68.9% male). Half of the patients (51.8%) received monotherapy in 2L. Among these, taxanes were most prescribed (69.0%) followed by irinotecan (22.1%). Doublet chemotherapy was the most common combination therapy in 2L (75.6%) with fluoropyrimidine + irinotecan (33.3%) being the most used, followed by fluoropyrimidine + platinum (17.8%). Less than a third of patients (29.3%) received subsequent third-line (3L) treatment; 62.7% received monotherapy [mainly taxanes (69.2%) or irinotecan (19.2%)]. Most 3L patients who had combination therapy received a doublet (86.7%), most frequently fluoropyrimidine combined with irinotecan (53.3%) or platinum (20.0%). The majority of 2L patients (93.6%) had received combination therapy as first-line treatment, of whom 67.9% had received triplet chemotherapy, most commonly anthracycline + fluoropyrimidine + platinum (51.1%). Estimated median real-world progression free survival (PFS) and overall survival (OS) after 2L treatment initiation was 3.09 (95% CI: 2.76-3.68) and 6.54 (5.29-7.76) months, respectively, and estimated probability of PFS and OS at 12 months was 8% and 26%, respectively. Conclusions: The clinical management of advanced / metastatic GC patients in 2L treatment commonly involves taxanes or irinotecan as monotherapy, or irinotecan or platinum-based combinations with fluoropyrimidines. RW clinical outcomes for 2L treatment are similar to randomised controlled trials but remain poor.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".