Efficacy of Second-Line Chemotherapy after a First-Line Triplet in Patients with Metastatic Colorectal Cancer
Bibliographic record
Abstract
Background: Exposing patients with metastatic colorectal cancer (mcrc) to all three active chemotherapeutic agents (oxaliplatin, irinotecan, fluorouracil) has improved survival. The benefit of second-line chemotherapy after a first-line triplet is not clearly defined. We evaluated the efficacy of second-line chemotherapy in patients who had received first-line triplet therapy. Methods: The medical records of patients treated on a prospective trial of first-line triplet therapy were reviewed for second-line treatment. Univariate and multivariate analyses were performed to establish factors of prognostic significance. Results: in 10, wild-type in 15, and unknown status in 3; Eastern Cooperative Oncology Group performance status (ps) of 1 in 16 patients, ps 2 in 3, ps 3 in 2, and unknown in 7; involved organs: liver in 17 patients, lung in 16, and peritoneum in 8]. Second-line chemotherapy consisted of xelox or folfox in 13 patients, xeliri or folfiri in 12, and single-agent irinotecan in 3. Concurrent bevacizumab was given in 16 patients (57%), and cetuximab, in 2 (7%). Median survival was 28.0 months [95% confidence interval (ci): 22.8 months to 33.2 months] for patients receiving second-line therapy and 23.0 months (95% ci: 13.2 months to 32.8 months) for those not receiving it. Best response was partial in 6 patients (21%), stable disease in 11 (39%), and progressive disease in 11 (39%). Median progression-free survival was 4.8 months (95% ci: 2.4 months to 9.6 months), and overall survival was 15 months (95% ci: 9.6 months to 20.4 months). Conclusions: Second-line chemotherapy after first-line triplet therapy in mcrc is feasible and suggests efficacy comparable to that reported for second-line therapy after a doublet, regardless of the agent used.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".