Treatment Settings and Outcomes with Regorafenib and Trifluridine/Tipiracil at Third-Line Treatment and beyond in Metastatic Colorectal Cancer: A Real-World Multicenter Retrospective Study
Bibliographic record
Abstract
Background: Patients with refractory mCRC rarely undergo third-line or subsequent treatment. This strategy could negatively impact their survival. In this setting, regorafenib (R) and trifluridine/tipiracil (T) are two key new treatment options with statistically significant improvements in overall survival (OS), progression-free survival (PFS), and disease control with different tolerance profiles. This study aimed to retrospectively evaluate the efficacy and safety profiles of these agents in real-world practice. Materials and Methods: In 2012–2022, 866 patients diagnosed with mCRC who received sequential R and T (T/R, n = 146; R/T, n = 116]) or T (n = 325]) or R (n = 279) only were retrospectively recruited from 13 Italian cancer institutes. Results: The median OS is significantly longer in the R/T group (15.9 months) than in the T/R group (13.9 months) (p = 0.0194). The R/T sequence had a statistically significant advantage in the mPFS, which was 8.8 months with T/R vs. 11.2 months with R/T (p = 0.0005). We did not find significant differences in outcomes between groups receiving T or R only. A total of 582 grade 3/4 toxicities were recorded. The frequency of grade 3/4 hand-foot skin reactions was higher in the R/T sequence compared to the reverse sequence (37.3% vs. 7.4%) (p = 0.01), while grade 3/4 neutropenia was slightly lower in the R/T group than in the T/R group (66.2% vs. 78.2%) (p = 0.13). Toxicities in the non-sequential groups were similar and in line with previous studies. Conclusions: The R/T sequence resulted in a significantly longer OS and PFS and improved disease control compared with the reverse sequence. R and T given not sequentially have similar impacts on survival. More data are needed to define the best sequence and to explore the efficacy of sequential (T/R or R/T) treatment combined with molecular-targeted drugs.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".