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Record W2523790029 · doi:10.1136/bmj.i5309

Revisiting the drug interaction between tamoxifen and SSRI antidepressants

2016· letter· en· W2523790029 on OpenAlexaff
David N. Juurlink

Bibliographic record

VenueBMJ · 2016
Typeletter
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsSunnybrook Health Science CentreHealth Sciences Centre
Fundersnot available
KeywordsTamoxifenCYP2D6Breast cancerDrugMedicineHarmPharmacologyAntidepressantAttributionPsychologyPsychiatryCancerInternal medicineCytochrome P450AnxietySocial psychology

Abstract

fetched live from OpenAlex

Few topics in therapeutics are more vexing than drug interactions. They number in the thousands, involve confusing terminology, and are rarely supported by evidence stronger than case reports and volunteer studies. It’s not surprising, therefore, that experts disagree on which interactions are serious and which ones are not. And yet their importance is undeniable because they can cause serious morbidity or even death, despite epitomizing, in theory at least, avoidable drug related harm. Over the past decade, few drug interactions have been as controversial as those involving tamoxifen and selective serotonin reuptake inhibitor (SSRI) antidepressants, explored yet again by Donneyong and colleagues in a linked study (doi:10.1136/bmj.i5014). On its surface, the issue seems straightforward: as a prodrug, tamoxifen requires conversion to active metabolites, the most important of which is endoxifen. This process is influenced by cytochrome-P450 isoenzyme 2D6 (CYP2D6), an enzyme characterized bymarked variability from person to person. Some SSRIs but not others inhibit CYP2D6, conceivably attenuating or even abolishing the benefits of tamoxifen. The importance of this potential interaction is amplified by three factors. First, tamoxifen is a monumental treatment, conferring dramatic reductions in breast cancer recurrence and associated mortality. Second, antidepressants are often co-prescribed with tamoxifen for extended periods, in part because depression often coexists with breast cancer and in part to offset vasomotor symptoms induced by tamoxifen. Third, and in contrast with most drug interactions, the consequences are delayed by years and manifest simply as treatment failure, undermining causal attribution at the patient level. Why does the interaction between tamoxifen and SSRIs remain controversial? One reason is that tamoxifen’s pharmacokinetic fate involves processes other than CYP2D6. Another is that studies of the relation between CYP2D6 activity and outcomes in women receiving tamoxifen yield remarkably inconsistent results. Finally, with some exceptions, 11 observational studies show little evidence that use of antidepressants is associated with adverse outcomes in women receiving tamoxifen. Donneyong and colleagues used data from five US health insurance databases to study women already being treated with an SSRI at the outset of treatment with tamoxifen or who received an SSRI later during its course. Over a median follow-up of about two years, they found no difference in overall mortality among women receiving SSRIs that inhibit CYP2D6 (paroxetine and fluoxetine) relative to SSRIs that do not (citalopram, escitalopram, fluvoxamine and sertraline). These findings are unsurprising, if for no other reason than follow-up was too brief for any differential survival to show up. Studying total mortality rather than cancer specific outcomes further diminished the investigators’ ability to discern signal from noise. Consequently, this study does little to disprove a meaningful interaction between tamoxifen and CYP2D6 inhibitors. It does, however, illustrate just how challenging such studies can be. Pharmacoepidemiology is a relative newcomer to the science of drug interactions, with most studies exploring short term toxicities after the co-prescription of drugs with well established interactions. In contrast, the interaction between tamoxifen and CYP2D6 inhibiting SSRIs is characterized by an elusive outcome (treatment failure), a long latent period, and many other factors (including non-adherence, therapeutic switching, CYP2D6 polymorphisms, dose-response effects, variable mechanisms and degrees of inhibition, and a probable endoxifen threshold below which treatment failure is more likely) that collectively attenuate any signal that might exist. For these reasons, the tamoxifen-SSRI interaction is perhaps the most difficult drug interaction to explore using the techniques of pharmacoepidemiology. Where does this leave patients and clinicians? In my view it is premature to dismiss an interaction between tamoxifen and SSRIs, particularly given the stakes and the ease with which harm can bemitigated.We know tamoxifen prevents recurrence and death from breast cancer, that endoxifen is its dominant metabolite, and that CYP2D6 plays an important role in its

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.184
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.139
GPT teacher head0.461
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations38
Published2016
Admission routes1
Has abstractyes

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