Approach to initiating QT-prolonging oncology drugs in the ambulatory setting
Bibliographic record
Abstract
Since the introduction of regulatory drug approval guidance on the evaluation of QT interval prolongation, an increasing number of drug monographs has included cautions on the risk of QT prolongation. For example, QT prolongation is mentioned in the Canadian product monographs of 29 drugs commonly seen in oncology practice. This presents two major challenges. First, most guidelines and risk predictive tools for QT prolongation have been developed for hospitalized patients in acute care settings. In contrast, most QT-prolonging oncology drugs are used in medically stable patients in the ambulatory setting. Second, many oncology drugs are unique for their indications and non-QT prolonging alternative agents are often not available. In this review, we will outline an empiric initial approach to ambulatory cancer patients who are treated with oncology drugs which may prolong QT interval. This includes the predictive value of QT prolongation on torsades de pointes, the risk factors of the patients and the drugs, and the limitations of existing guidance in this area.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".