Difficult to Swallow: Issues Affecting Optimal Adherence to Oral Anticancer Agents
Bibliographic record
Abstract
The number of anticancer drugs currently available in oral formulation has increased dramatically over the past 15 to 20 years, especially with the recent development of new hormonal and targeted therapies. 1 , 2 At present, approximately 25% of all cancer drugs are available in oral formulation, with numbers expected to increase exponentially in the coming years. 1 , 3 , 4 The convenience associated with the self-administration of oral therapy, the requirement of fewer trips to the physician's office, and the lack of infusion reactions are all benefits for patients, allowing them to potentially maintain their relative independence while undergoing active anticancer treatment. On the other hand, there are growing concerns regarding patients' poor adherence to oral therapy as well as the challenges of monitoring patient compliance when treatment administration does not occur in the presence of health care professional (HCPs). More importantly, poor adherence to proven therapies may detrimentally affect the patients' clinical outcomes, such as survival. Thus, there is an urgent need to identify more effective strategies to measure and monitor adherence to oral anticancer agents in an effort to maximize their therapeutic benefits.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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; both teacher heads agree on what is shown here.
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".