Drug–drug interaction potential in men treated with enzalutamide: Mind the gap

Abstract

Aims

Metastatic castration‐resistant prostate cancer (mCRPC) patients are generally older patients with several co‐morbidities and are therefore at increased risk of complications due to drug–drug interactions (DDIs). We assessed the prevalence of potential DDIs in a cohort of mCRPC patients treated with enzalutamide.

Methods

We conducted a retrospective review of pharmacy records to retrieve individual drug histories of mCRPC patients who started enzalutamide therapy in a tertiary care setting. Potential DDIs were analysed using two international drug interaction compendia: Lexicomp^® and Micromedex^®, and the Dutch drug database. Two potential pharmacodynamic DDIs were analysed.

Results

A total of 105 records were evaluated for potential DDIs with enzalutamide. Of 205 different co‐medications, 56 were flagged by at least one of the three compendia: Lexicomp, Micromedex and the Dutch drug database flagged for potential DDIs in 85%, 54% and 32%, respectively. Eighty‐five per cent of DDIs were classified as major. The median number of co‐medications per patient was 11 (range 1–26). The median (range) number of interactions per patient was 4 (0–10), 1 (0–5) and 0 (0–2) for Lexicomp, Micromedex and the Dutch drug database, respectively. In 23% and 45% of all patients, a potential DDI was found with PPIs and CNS depressants, respectively.

Conclusions

A high prevalence of potential DDIs was found. The inclusion and grading of potential DDIs was highly variable between the three drug interaction compendia. Physicians, nurses and pharmacists should be aware of this potential problem, which might require intensive monitoring or alternative treatment strategies to prevent suboptimal treatment of the co‐morbidities in patients treated with enzalutamide.

What is Already Known about this Subject

• Enzalutamide is an inducer of several CYP450 enzymes; a strong inducer of CYP3A4 and a moderate inducer of CYP2C19 and CYP2C9.

• mCRPC patients are generally older patients potentially with several co‐morbidities and therefore at increased risk of complications due to drug–drug interactions.

What this Study Adds

• There is limited awareness of the drug interaction potential of enzalutamide. This is the first study that describes the high prevalence (85%) of potential major DDIs for patients treated with enzalutamide in a real live cohort.

• The high prevalence (45%) of CNS interactions in this cohort requires attention, especially as the use of CNS depressants in combination with enzalutamide further increases the risk for cognitive side effects.

• Future drug interaction studies with potential victims of enzalutamide are needed to assess the clinical relevance of these potential interactions.

Introduction

Prostate cancer (PCa) is the most commonly diagnosed cancer among men in Western countries 1. Hormone‐sensitive prostate cancer (HSPC) responds well to bilateral orchidectomy or androgen deprivation therapy (ADT) alone, but is associated with adverse effects on metabolic, cardiovascular, sexual, as well as on cognitive health 2. When the disease recurs as castration‐resistant prostate cancer (CRPC), it is associated with a median overall survival of approximately 2–3 years with significant decrement in quality of life due to additional cancer‐specific and treatment‐induced morbidity 3, 4, 5, 6, 7, 8, 9. Palliative agents currently used in the CRPC setting include the second‐generation hormonal agents abiraterone acetate and enzalutamide, radium‐223, docetaxel and cabazitaxel 10. Optimal sequencing of these life‐prolonging agents remains challenging, but greatest effort should be made on mitigating further adverse effects to maintain maximum health and quality of life. Abiraterone acetate and enzalutamide are both well tolerated, oral drugs that improve progression‐free survival and overall survival in the pre‐ and post‐chemotherapy setting, with only partially overlapping side‐effects and different drug–drug interaction (DDI) potential 6, 7, 8, 9. DDIs occur as a consequence of pharmacokinetic or pharmacodynamic interactions and could interfere with the effect of the anti‐cancer therapy as with the drugs that are prescribed to treat co‐morbidities.

Since the introduction of second‐generation anti‐hormonal agents with a more favourable toxicity profile than docetaxel, a broader population of CRPC patients is currently treated earlier in their castration‐resistant state. Optimal selection of anti‐hormonal therapy in the castrate state is a multifactorial decision and based on patient age and co‐morbidity, drug toxicity profile, patient and physician preference, and drug cost and availability. In addition, it is of key importance to recognize the potential of DDIs, particularly as CRPC patients are commonly between 65 and 75 years, have multiple co‐morbidities and use several potent drugs, often with a narrow therapeutic window that may lead to events necessitating hospital admission and fatal adverse drug events 11, 12.

DDIs should therefore be routinely monitored in patients with CRPC; two retrospective studies suggested that approximately 20% and 40% of patients treated with abiraterone acetate were at risk for major DDIs 13, 14. Abiraterone is a strong inhibitor of hepatic cytochrome p450 (CYP450) enzymes CYP1A2 and CYP2D6 in vitro, while only showing relevant interactions between abiraterone and substrates of CYP2D6 in vivo 15. To the best of our knowledge, no studies have reported on prevalence of potential DDIs in patients treated with enzalutamide. Enzalutamide is a strong inducer of CYP3A4 and moderate inducer of CYP2C19 and CYP2C9. A decrease in exposure of 86%, 70% and 56%, respectively, were observed for the CYP3A4 substrate midazolam, the CYP2C19 substrate omeprazole and the CYP2C9 substrate S‐warfarin when co‐administered with enzalutamide 16. Due to induction of these hepatic enzymes by enzalutamide, co‐medication may be metabolized faster, resulting in lower plasma levels and potential suboptimal treatment of patient's co‐morbidities.

The aim of this study was to investigate the prevalence of potential DDIs in a cohort of patients treated with enzalutamide and to compare the notification and grading of potential DDIs with enzalutamide of three different drug interaction compendia. We emphasize that the choice of anti‐hormonal androgen therapy should in part be based on co‐medications used by the patients and the DDI potential introduced by starting anti‐hormonal androgen therapy. We provide clinicians with guidance to support clinical decision making of therapeutic drugs of choice.

Patients and methods

An observational single‐centre retrospective study of the prevalence of potential DDIs associated with the use of enzalutamide was conducted at Radboud University Medical Center, Nijmegen, The Netherlands. With the approval of the Research Ethics Board, pharmacy records were reviewed to identify patients who started enzalutamide therapy between November 2013 and July 2016. Information regarding individual drug histories was extracted from pharmacy records. All co‐medicated drugs that were found in pharmacy records were included. In case of combination therapy, the active drugs were counted separately.

Co‐administered drugs of individual patients on enzalutamide therapy were analysed for potential DDIs using two international DDI compendia (Lexicomp and Micromedex) and the Dutch drug database that is integrated in Dutch pharmacy surveillance systems 17, 18, 19.

We counted the number of potential drugs that interact with enzalutamide according to the compendia. Thereafter we analysed the number of patients at risk of a potential drug interaction with enzalutamide. The results were compared between the three compendia. To describe the severity of potential DDIs, we applied the risk rating used by Lexicomp, Micromedex and the Dutch drug database (Table 1).

Table 1.

Lexicomp, Micromedex and Dutch database drug–drug interaction classifications

Lexicomp®		Micromedex®		Dutch database
Level		Level		Level
A No known interaction	Data have not demonstrated either pharmacodynamic or pharmacokinetic interactions	Unknown	Unknown	No interaction
B No action needed	Data demonstrate that the specified agents may interact with each other, but there is little to no evidence of clinical concern resulting from their concomitant use.	Minor	The interaction would have limited clinical effects. Manifestations may include an increase in the frequency or severity of the side effects but generally would not require a major alteration in therapy.	Not relevant interaction
C Monitor therapy	Data demonstrate that the specified agents may interact with each other in a clinically significant manner. The benefits of concomitant use of these two medications usually outweigh the risks. An appropriate monitoring plan should be implemented to identify potential negative effects. Dosage adjustments of one or both agents may be needed in a minority of patients.	Moderate	The interaction would have limited clinical effects. Manifestations may include an increase in the frequency or severity of the side effects but generally would not require a major alteration in therapy	Relevant interaction
D Consider therapy modification	Data demonstrate that the two medications may interact with each other in a clinically significant manner. A patient‐specific assessment must be conducted to determine whether the benefits of concomitant therapy outweigh the risks. Specific actions must be taken in order to realize the benefits and/or minimize the toxicity resulting from concomitant use of the agents. These actions may include aggressive monitoring, empiric dosage changes, choosing alternative agents.	Major	The interaction may be life‐threatening and/or require medical intervention to minimize or prevent serious adverse effects.
X Avoid combination	Data demonstrate that the specified agents may interact with each other in a clinically significant manner. The risks associated with concomitant use of these agents usually outweigh the benefits. These agents are generally considered contraindicated	Contraindicated	The drugs are contraindicated for concurrent use.

To assess possible pharmacodynamic effects of enzalutamide on co‐medication, we counted two potential DDIs: the number of patients who used drugs with an increased risk of falling, i.e., a combination of two or more CNS depressant agents, and the number of patients at risk for GI bleeding, i.e., a combination of drugs that may increase the risk of GI bleeding. These analyses were initiated because: (1) enzalutamide causes CNS depression, and (2) enzalutamide decreases the plasma concentration of omeprazole through induction of CYP2C19, and by this mechanism possibly decreases the efficacy of all PPIs. This interaction might, in particular, be relevant in patients with increased risk for GI bleeding.

Results

We identified 105 mCRPC patients who started enzalutamide therapy between November 2013 and July 2016. The median age in this cohort was 69 years (range 48–91) (Figure 1). In these 105 patients, a total of 1200 co‐administered drugs was counted, consisting of 205 different types of drugs. The median number of co‐medications per patient was 11 (range 1–26) (Figure 2).

Figure 1.

Age groups: the distribution of patients in the cohort in six age groups. Median age was 69 years (range 48–91 years)

Figure 2.

Number of co‐medications per patient. The median number of co‐medications per patients was 10 (range 1–26)

Groups of co‐medications

The most common therapeutic classes based on ATC code of all (1200) co‐medications used in combination with enzalutamide were gastro‐intestinal (18%), cardiovascular (18%), analgesic (17%) and urological (12%) drugs (detailed in Figure 3).

Figure 3.

Classes of co‐medications during enzalutamide therapy represented as percentages of the total number of co‐medications (n = 1200) administrated to all patients included in the study (n = 105)

Potential pharmacokinetic drug–drug interactions

Overall, 56 out of the 205 (27%) different types of co‐medications were identified to have a potential DDI with enzalutamide in at least one of the DDI compendia. Out of these 56 co‐medications with a potential DDI, four different co‐medications (Fentanyl, carbamazepine, nifedipine, ticagrelor) had the highest risk rating in the Lexicomp compendium (Level X: avoid). These potential DDIs were not recognized by Micromedex or the Dutch drug database. At least one of these four different types of co‐medications were used by 31% of the patients.

The second risk rating category (Major: Level D ‘treatment modification suggested’) was the most observed level of potential DDI. Of the 205 different types of co‐medications, 21% were graded with this risk rating by Lexicomp. Micromedex flagged 4.5% of all co‐medications. The Dutch drug database flagged 2.5% of all co‐medication with this risk rating. Overall, 85% of the patients used at least one of the co‐medications with this risk rating.

In the third risk rating category (moderate/level C: monitor therapy), in total 4.5% of the 205 co‐medications were flagged; Lexicomp identified 3% of all co‐medications with Level C and Micromedex flagged 1.5% of all co‐medications with this risk rating. Overall, 44% (46/105) of the patients used at least one of the co‐medications in this risk rating category.

The 10 most frequently used drugs with a risk rating Level X and D in our cohort are shown in Table 2. The full list of co‐medications in this cohort can be found in the supplementary Table S1.

Table 2.

The 10 most frequently used drugs with a risk rating level X and D in the cohort

Drug	Frequency (%)	Dutch database	Lexicomp (risk rating)	Comment	Micromedex (risk rating)	Comment
Oxycodone	48	Unknown	D	Enzalutamide is a strong CYP3A4 inducer, oxycodone levels ↓	Major	Enzalutamide is a strong CYP3A4 inducer, oxycodone ↓
Pantoprazole	34	Unknown	D	Enzalutamide is a CYP2C19 inducer, pantoprazole levels ↓	No interaction
Omeprazole	26	Interaction	D	Enzalutamide is a CYP2C19 inducer, omeprazole levels ↓	No interaction
Fentanyl	26	Unknown	X	Enzalutamide is a strong CYP3A4 inducer, fentanyl levels ↓	Major	Enzalutamide is a strong CYP3A4 inducer, fentanyl levels ↓
Dexamethasone	25	Unknown	D	Enzalutamide is a strong CYP3A4 inducer, dexamethasone levels↓	Major	Enzalutamide is a strong CYP3A4 inducer, dexamethasone levels↓
Simvastatin	15	Unknown	D	Enzalutamide is a strong CYP3A4 inducer, simvastatin levels↓	No interaction
Tamsulosin	14	Unknown	D	Enzalutamide is a strong CYP3A4 inducer, tamsulosin levels ↓	No interaction
Cyproterone	10	Unknown	D	Enzalutamide is a strong CYP3A4 inducer, cyproterone levels ↓	No interaction
Tramadol	10	Unknown	D	Enzalutamide is a strong CYP3A4 inducer, tramadol levels ↓	No interaction
Nifedipine	3	Unknown	X	Enzalutamide is a strong CYP3A4 inducer, nifedipine levels ↓	Major	Enzalutamide is a strong CYP3A4 inducer, nifedipine levels ↓

Potential pharmacodynamic drug–drug interactions

In 63% (n = 66) of the 105 patients, central nervous system (CNS) depressants were used. Forty‐five percent (n = 47) of all patients used a combination of at least two CNS depressant drugs. Enzalutamide might further contribute to CNS depressing effects in these patients due to its side‐effect profile.

In 56% (n = 59) of the 105 patients, a proton pump inhibitor (PPI) was used. Of these patients, 40% (n = 24) had more than one risk factor to develop gastrointestinal bleeding and were entitled to receive a PPI according to the guidelines. Enzalutamide decreases the plasma concentrations of PPIs metabolized through CYP2C19 by ~70%.

Comparison between databases

Lexicomp flagged an interaction (of any level) for 53 different types of co‐medication. The total number of potential DDIs was 388 for Lexicomp, and this involved 85% (n = 89) of the patients. This percentage is much higher than for Micromedex, which flagged an interaction (of any level) for 12 different types of co‐medication. The total number of potential DDIs was 138 and involved 52% (n = 57) of the patients. The Dutch drug database flagged a potential DDI (of any level) for five different types of co‐medication, and the total number of potential DDIs was 45 in 33% (n = 35) of the patients. The number of potential DDIs per risk rating of the three compendia is shown in Figure 4.

Figure 4.

Number of DDIs per database for the three highest risk rating categories

When Lexicomp was used, the median of potential DDIs in all patients was 4 (range 0–10) compared to 1 (range 0–5) and 0 (range 0–2) with Micromedex and the Dutch drug database, respectively.

Agreement on inclusion of the potential DDIs was found for 18% of the co‐medications with potential DDIs between Lexicomp and Micromedex. Between Lexicomp and the Dutch drug database, agreement on inclusion was found for only 5% of the co‐medications. For Lexicomp and Micromedex we found agreement on both inclusion and grading for 7% of the co‐medications with potential DDIs. In eight out of the 13 co‐medications with agreement on inclusion (>1 compendium), a discrepancy in grading was found, representing 60 occasions of DDIs in 22 patients (21%). No agreement on inclusion and/or rating was found for all three compendia.

Discussion

To the best of our knowledge, this is the first study that describes the prevalence of potential drug–drug interactions in a cohort of enzalutamide users. Surprisingly, we found that in 31% of the patients, co‐medication was used, contrary to the advice for it to be avoided in combination with enzalutamide by at least one of the drug compendia. Moreover, 85% of the patients were at risk for potential DDIs that require therapy modification, e.g. intensive monitoring, empiric dosage changes or choosing alternative agents. The high prevalence (45%) of CNS interactions in this cohort requires attention, especially as the use of CNS depressants in combination with enzalutamide further increases the risk for cognitive side effects. A post‐hoc analysis of the PREVAIL study showed that age and enzalutamide use were associated with a higher risk of falling 20. This is even more important for this population as long‐term ADT also increases the risk of fractures and neurocognitive effects 21, 22. It is therefore essential to assess combinations of CNS drugs and monitor patients for risk of falling when enzalutamide is prescribed. The metabolism of some of these CNS depressants might be induced by enzalutamide, and the complexity of both pharmacodynamic and pharmacokinetic DDI at the same time complicates the evaluation hereof.

Only one potential DDI was found in which enzalutamide is the victim of the DDI, i.e. that co‐medication (carbamazepine, a potent CYP3A4 inducer) might decrease the exposure of enzalutamide. In all other cases enzalutamide is the perpetrator of the DDI by lowering the plasma concentration of co‐administered drugs which could result in less effective treatment of co‐morbidities. This may cause treatment failure, especially when co‐administered drugs have a narrow therapeutic index or a protective role in preventing serious adverse events. In our study, 24 out of 59 patients were at high risk for GI bleeding due to low dose aspirin or NSAID use in combination with additional risk factors such as age, use of ulcerogenic medication or co‐morbidity and were therefore treated with a PPI according to the guidelines 23, 24. Due to the proven DDI between enzalutamide and PPIs, these patients are possibly at greater risk of developing GI bleeding as a result of decreased plasma concentration of the PPI 25. This DDI adds to the already augmented risk (age, severe co‐morbidity) on GI bleeding events in this group of elderly patients 24.

This study compared three compendia and observed several disparities on both inclusion of the potential DDI and grading. Especially the Dutch drug database, which is integrated in electronic prescribing systems and pharmacy systems, showed a very low number of potential DDI warnings. Furthermore, a high number of discrepancies in grading was found between the three compendia, in the case of agreement on inclusion. There was no co‐medication with DDI that had complete agreement between all three compendia. The difference in inclusion and grading seemed to be caused by the appraisal of evidence for DDIs, as Lexicomp also included CYP450 substrates, probably based on pharmacological mechanism, that were not included by Micromedex and the Dutch database. These findings confirm the lack of standardization and classification of DDIs that has been discussed by other authors previously 26, 27. Apparently, the Dutch drug interaction database contained mainly information on the DDIs that were studied by Gibbons et al. in a drug–drug interaction study 16; Micromedex and, in particular Lexicomp, added DDIs based on their own prediction that such DDIs might occur with enzalutamide. It must be noted that these additional DDIs not explicitly mentioned in the product label are not formally reviewed by external assessors, such as regulatory authorities 28.

In the optimal situation, warnings should only be shown if potential DDIs are clinically relevant. To assess clinical relevance more research is needed, but for the time being, Lexicomp proved to be the most informative in this cohort in our opinion, as it shows the most potential DDIs. Until clinical relevance is proven, collaboration with pharmacists or clinical pharmacologists might be appropriate to make clinical decisions on the management of DDIs with enzalutamide. The current discrepancy between the information in drug interaction databases as well as the product labels displays an important problem when potential DDIs are encountered. Currently a database (http://cancer‐druginteractions.org) is developed to overcome this knowledge gap and to bring standardized and comprehensive guidance to clinicians.

Although comparisons between patient cohorts can be difficult, our study suggests that enzalutamide has a higher drug interaction potential than abiraterone acetate because 85% of the patients treated with enzalutamide in our cohort had a major potential DDI vs. 20–40% of the patients treated with abiraterone acetate in two separate cohorts 13, 29. In our cohort we also found that almost one third of the patients with enzalutamide had potential DDIs resulting in the advice to avoid the use of the co‐administered drug (contraindicated), unlike the studies with abiraterone acetate where no potential DDI of this risk rating category were found 13, 29. The DDI profiles of abiraterone and enzalutamide have recently been described by Del Re et al. and are shown to be very different 14, 30. Potential DDIs with abiraterone are likely to cause increased plasma levels of co‐administered drugs metabolized through CYP2D6 (risk of toxicity) which are ~20% of all drugs, while enzalutamide causes decreased plasma levels of co‐administered drugs (risk of subtherapy) metabolized through CYP3A4, CYP2C19 and CYP2C9, which are involved in the biotransformation of ~50% of all drugs 15. It is essential for prescribers to be aware of this difference for clinical decision making in anti‐androgen therapy.

It is important to consider that in our study a real‐life cohort of mCRPC patients are represented in whom the large interaction potential of enzalutamide is noticed. These findings were not described in the Phase 3 studies, possibly due to strict exclusion criteria on co‐morbidities and co‐medication 8, 9. We have to point out that the type of cohort thus importantly affects the number of reported DDIs and makes comparison between real‐life patients and patients participating in registration studies difficult.

One of the limitations of this study is that we were not able to investigate the number of interventions due to DDIs or their clinical relevance as this kind of information is generally not recorded in electronic patient records.

Another limitation could be that our cohort is a selected cohort as some DDIs may have been prevented by changing co‐medication prior to starting enzalutamide. It must be noted, however, that we expect minimal interventions prior to starting enzalutamide as we used the Dutch drug interaction database that actually has the lowest number of warnings at the time of the study. A previous study of clinical interventions for DDIs in patients with any kind of cancer treated with anticancer drugs showed that 13% of the clinically relevant DDIs resulted in an intervention before start of therapy, and additionally 14% of the DDIs needed an intervention after start of therapy 31. Although it is difficult to extrapolate these results to our current study, it is likely that the potential DDIs that we found in 31% of the patients with the advice to avoid these co‐medications are clinically relevant, and need intervention before start of therapy. An intervention (intensive monitoring, dose adjustments) during therapy might be needed for 85% of the patients in this cohort with major potential DDIs.

When either abiraterone acetate or enzalutamide are considered as anti‐androgen therapy, knowledge of the pharmacological profiles of enzalutamide and abiraterone acetate can support decision making. For patients with many co‐morbidities and co‐medications, the pharmacological profile of abiraterone might be more favourable as this requires less adjustments of co‐medications. Patients with cognitive impairment at baseline or symptoms of depression, or using multiple CNS depressants, might experience fewer side effects when treated with abiraterone acetate. Patients that are sensitive for corticosteroid use (diabetic patients), patients with cardiovascular co‐morbidities, patients who experienced hepatotoxicity on abiraterone, or who have trouble with the fasted intake of abiraterone might experience less side effects when treated with enzalutamide.

In conclusion, large numbers of potential drug–drug interactions of a high risk rating were found in a population using enzalutamide. Prospective research is therefore needed to assess the true clinical relevance of these drug–drug interactions. For the time being, understanding of the information gap between different drug compendia is needed. The development of databases with complete information on drug–drug interactions such as http://cancer‐druginteractions.org can guide clinicians with standardized recommendations and can help to overcome this information gap. Awareness of the potential for drug–drug interactions which might require intensive monitoring or alternative treatment strategies is needed to prevent suboptimal treatment of the co‐morbidities in patients treated with enzalutamide.

Nomenclature of targets and ligands

Key protein targets and ligands in this article are hyperlinked to corresponding entries in http://www.guidetopharmacology.org, the common portal for data from the IUPHAR/BPS Guide to PHARMACOLOGY 32, and are permanently archived in the Concise Guide to PHARMACOLOGY 2015/16 33.

Competing Interests

N.P.v.‐E. reports grants from Janssen Cilag, Astellas, Novartis, Gilead, Boehringer Ingelheim and Astrazenica, outside the submitted work. I.M.v.‐O. reports personal fees from Astellas and Janssen, outside the submitted work. All remaining authors have declared no conflicts of interest.

Supporting information

Table S1 List of all co‐medications found in this cohort

Benoist, G. E. , van Oort, I. M. , Smeenk, S. , Javad, A. , Somford, D. M. , Burger, D. M. , Mehra, N. , and van Erp, N. P. (2018) Drug–drug interaction potential in men treated with enzalutamide: Mind the gap. Br J Clin Pharmacol, 84: 122–129. doi: 10.1111/bcp.13425.