Trifluridine/Tipiracil Based Chemoradiation in locally Advanced Rectal Cancer: The Phase I/II TARC Trial
Bibliographic record
Abstract
BACKGROUND: Optimizing functional outcomes and securing long-term remissions are key goals in managing patients with locally advanced rectal cancer. In this proof-of-concept study, we set out to further optimize neoadjuvant therapy by integrating the radiosensitizer trifluridine/tipiracil and explore the potential of cell free tumor DNA (ctDNA) to monitor residual disease. METHODS: About 10 patients were enrolled in the phase I dose finding part which followed a 3 + 3 dose escalation design. Tipiracil/trifluridine was administered concomitantly to radiotherapy. ctDNA monitoring was performed before and after chemoradiation with patient-individualized digital droplet PCRs. RESULTS: No dose-limiting toxicities were observed at the maximum tolerated dose level of 2 × 35 mg/m² trifluridine/tipiracil. There were 9 grade 3 adverse events, of which 8 were hematologic with anemia and leukopenia. Chemoradiation yielded a pathological complete response in 1 out of 8 assessable patients, downstaging in nearly all patients, and 1 clinical complete response referred for watchful waiting. Three of 4 assessable patients with residual tumor cells at pathological assessment remained liquid biopsy positive after chemoradiation, but 1 turned negative. CONCLUSION: In this exploratory phase I trial, the novel combination of neoadjuvant trifluridine/tipiracil and radiotherapy proved to be feasible, tolerable, and effective. However, the application of liquid biopsy as a potential marker for therapeutic de-escalation in the neoadjuvant setting requires additional research and prospective validation. The trial was registered at ClinicalTrials.gov: NCT04177602.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".