Optimizing the Use of Irinotecan in Colorectal Cancer
Bibliographic record
Abstract
The introduction of new agents with novel mechanisms of action has led to considerable changes in the management of colorectal cancer in recent years. One of these novel agents, irinotecan, has been shown to offer survival benefits in both the first- and second-line treatment of advanced/metastatic colorectal cancer. Irinotecan monotherapy improves survival compared with both best supportive care and infused 5-fluorouracil (5-FU) in patients with 5-FU-pretreated disease, without impacting negatively on patients' quality of life. As a result, irinotecan monotherapy is now considered to be the standard treatment in this setting. Irinotecan in combination with 5-FU/leucovorin (LV) was subsequently evaluated as first-line therapy for metastatic colorectal cancer in two randomized, phase III studies. Both trials confirmed that irinotecan plus infused or bolus 5-FU/leucovorin LV provide a modest survival benefit without compromising patients' quality of life. Combined irinotecan/5-FU/LV represents a new standard in the first-line treatment of metastatic colorectal cancer. In an attempt to further improve efficacy and tolerability, recent studies have investigated irinotecan in combination with capecitabine as first-line treatment for colorectal cancer. The replacement of infused 5-FU with oral capecitabine provides a more convenient treatment option. A phase I study was conducted to establish the maximum tolerated dose, and demonstrated encouraging antitumor activity and a manageable safety profile with the combination. This article provides a brief overview of the pivotal clinical trial data for irinotecan and discusses how irinotecan-based therapy may be improved in the future. It also discusses potential optimization of irinotecan use through identification of patient subpopulations most likely to benefit from combination or sequential strategies, and the potential of new, oral agents such as capecitabine to replace i.v. 5-FU as a combination partner for irinotecan.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".