4CPS-099 Clinically relevant drug–drug interaction events in patients with abiraterone, enzalutamide or apalutamide treatment
Bibliographic record
Abstract
Background and importance Cytochrome P enzymes play a key role in drug metabolism and it is essential to understanding some interactions. Aim and objectives Optimising pharmacotherapy in prostate cancer patients through the identification of drug interactions between anti-androgenic therapy and the patient’s usual medication. Material and methods Patients on abiraterone, enzalutamide or apalutamide treatment were identified through the pharmacy computerised record of dispensations. Their usual medication was obtained from the pharmacotherapeutic history. The evaluation of abiraterone and enzalutamide interactions was performed with Liverpool and Uptodate databases. For apalutamide, Micromedex and Uptodate were used because apalutamide is not registered in Liverpool. Clinically relevant interactions were reported to the urologist, performing the pertinent pharmaceutical interventions. Results 32 prostate cancer patients were identified; 21 (65.6%) were treated with abiraterone, 8 (25%) with enzalutamide and 3 (9.4%) with apalutamide. The median of age was 79 (53–90) years and the median of concomitant treatments was 7 (3–13). 18 relevant interactions were detected; 2 (11.1%) with abiraterone, 10 (55.6%) with enzalutamide and 6 (33.3%) with apalutamide. The drugs with relevant interactions belonged to the following therapeutic groups: Cardiovascular system (61.1%). In the co-administration of bisoprolol with abiraterone or apalutamide we recommended reducing the bisoprolol doses. In treatments with enzalutamide and doxazosin, lecardipine, torasemide or nevibolol we advised changing the therapy to hydralazine, angiotensin-converting enzyme inhibitors, furosemide or atenolol. Statins should be replaced by ezetimibe or fibrates in enzalutamide or apalutamide treatment. Antithrombotics (16.7%). Dabigatran, apixaban or acenocoumarol are contraindicated with anti-androgenic therapy.We proposed the use of heparins or oral anticoagulants with strict international normalised ratio (INR) control. Proton pump inhibitors (PPIs) (11.1%). In patients treated with enzalutamide, pantoprazole or ??? changing to an anti-H2 was suggested. Analgesics (11.1%). Metamizole and tramadol are not recommended in cases of concomitant administration with abiraterone or apalutamide. In the consulted databases a discrepancy of 25% was found, which illustrates the need to compare at least two databases to obtain an optimal review of interactions. Conclusion and relevance Abiraterone, apalutamide and, mainly, enzalutamide suffer a large number of interactions, which may modify a treatment’s efficacy and/or its safety. The use of multiple concomitant medications is a risk factor that increases the possibility of hospitalisation and mortality. The pharmacist must achieve the correct review of drug interactions with reference to at least two databases. References and/or acknowledgements Conflict of interest No conflict of interest
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".