Interactions and drug-metabolizing enzymes

Significant Drug–Drug Interactions with Antineoplastics

Goal

The goal of this program is to inform the participant about the clinical and economic significance of drug interactions, review their potential mechanisms, present significant interactions related to antineoplastics, and provide resources for managing them.

Objectives

At the completion of this program, the participant will be able to: 1. Describe the scope and economic impact of preventable drug interactions. 2. Explain why oncology patients are at increased risk for drug interactions. 3. Define the pharmacokinetic, pharmacodynamic, and pharmaceutic principles underlying antineoplastic related drug–drug interactions. 4. List specific classes of antineoplastics involved in significant drug–drug interactions. 5. Identify multiple resources for obtaining drug interaction information.

Role of cytochrome P450 in drug interactions

Drug-drug interactions have become an important issue in health care. It is now realized that many drug-drug interactions can be explained by alterations in the metabolic enzymes that are present in the liver and other extra-hepatic tissues. Many of the major pharmacokinetic interactions between drugs are due to hepatic cytochrome P450 (P450 or CYP) enzymes being affected by previous administration of other drugs. After coadministration, some drugs act as potent enzyme inducers, whereas others are inhibitors. However, reports of enzyme inhibition are very much more common. Understanding these mechanisms of enzyme inhibition or induction is extremely important in order to give appropriate multiple-drug therapies. In future, it may help to identify individuals at greatest risk of drug interactions and adverse events.

Potential for drug interactions in hospitalized cancer patients

OBJECTIVES

To quantify the frequency of potential drug interactions unrelated to chemotherapy in cancer patients admitted to our institution, and to define risk factors for such interactions.

METHODS

Charts of 100 consecutive hospitalized cancer patients were reviewed. Patients receiving chemotherapy and/or hormone therapy were excluded, as were patients admitted for intensive care. Drug-drug interactions were screened with Drug Interaction Facts software, and manually by the authors. Potential interactions were graded by levels of severity (severe, moderate, minor) and significance (one to five, with one representing the highest level of evidence).

RESULTS

The median age of the patients was 67 years, and the length of hospital stay and the number of drugs per patient were 6 days and eight drugs, respectively. In 63 patients 180 potential interactions were detected. Of the potential interactions, 18.3% were severe, 56.7% were moderate, and 25% were minor. Approximately 7%, 18% and 13% of potential interactions were graded as level 1, 2 and 3, respectively. In multivariate analysis, prescriptions with eight or more drugs (P=0.0004) and six or more days of hospital stay (P=0.014) were independent risk factors for potential interactions.

CONCLUSION

Potential drug interactions are common among hospitalized cancer patients. Length of hospital stay and number of prescribed drugs are risk factors.

The interaction of medications used in palliative care

Palliative care uses several classes of drugs, which are handled by the CYP P450 system. Interaction of drugs in this setting requires ongoing vigilance by the physician. Phenocopying may be more common than previously realized.

Significant Drug–Drug Interactions with Antineoplastics

Goal

The goal of this program is to inform the participant about the clinical and economic significance of drug interactions, review their potential mechanisms, present significant interactions related to antineoplastics, and provide resources for managing them.

Objectives

At the completion of this program, the participant will be able to: 1. Describe the scope and economic impact of preventable drug interactions. 2. Explain why oncology patients are at increased risk for drug interactions. 3. Define the pharmacokinetic, pharmacodynamic, and pharmaceutic principles underlying antineoplastic related drug–drug interactions. 4. List specific classes of antineoplastics involved in significant drug–drug interactions. 5. Identify multiple resources for obtaining drug interaction information.

Drug interactions in palliative care

PURPOSE

This review of drug interactions in palliative care examines the relevant literature in this area and summarizes the information on interactions of drugs, nutrients, and natural products that are used in the palliative care setting. Particular emphasis is placed on describing the newer information on the cytochrome P450 (CYP) system and the interactions of opioids, antidepressants, and the antitussive, dextromethorphan.

METHODS

We performed a search of the MEDLINE database of the time period from 1966 until April 1998, using medical subject headings such as the names of selective serotonin reuptake inhibitors and other relevant medications in palliative care. Literature reviewed included both human and animal articles as well as non-English literature. Bibliographies of these articles and the personal libraries of several palliative care specialists were reviewed. Software developed by The Medical Letter-The Drug Interaction Program was also used.

RESULTS

Drug interactions can be categorized in several ways. Drug-drug interactions are the most well known and can be kinetic, dynamic, or pharmaceutical. Pharmacokinetic interactions can involve CYP 2D6, which acts on drugs such as codeine and is responsible for its conversion to morphine. Poor metabolizers, either genotypic or due to phenocopying, are at risk for undertreatment if not recognized. Pharmacodynamic interactions with dextromethorphan may produce serotonin syndrome.

CONCLUSION

Drug interactions are important in palliative care as in other aspects of medicine. These interactions are similar to those seen in other areas of medical care but have significant consequences in pain management. Failure to recognize these interactions can lead to either overdosing or undertreatment.

Quantitative analysis of constitutive and inducible CYPs mRNA expression in the HepG2 cell line using reverse transcription-competitive PCR

Drug interactions which affect drug metabolism are of clinical importance. It is, however, difficult to estimate drug interactions in human from results obtained in animal experiments. In our previous study, we demonstrated that a combination of the HepG2 cell line and semiquantitative reverse transcription-PCR (RT-PCR) could be used to evaluate the degree of CYP3A mRNA induction by various drugs. Using an RT-competitive PCR (RT-cPCR) with beta-actin as the standard in this study, the constitutive and rifampicin (RFP)-induced expression of CYP3A4, CYP2C9, CYP2E1, and CYP1A2 mRNA in the HepG2 cells could be quantitatively and reproducibly determined. 120 h-treatment of HepG2 cells with 50 micromol/l RFP induced maximally 8.4- and 6.0-fold the expression of CYP3A4 and CYP2C9 mRNA, respectively, in comparison with untreated cells. On the other hand, mRNA level in CYP2E1 and CYP1A2 was not significantly changed by 50 micromol/l RFP after 24 to 120 h. To our knowledge, we report for the first time quantitative profiles of CYPs mRNA in HepG2 cells. This study demonstrates the efficiency of a combination of HepG2 cells and RT-cPCR in the evaluation of CYPs mRNA-induction by drugs.

Drug interactions and anti-infective therapies

Drug interactions are an important and often underappreciated cause of adverse clinical outcomes. This review considers the mechanisms for several clinically important drug interactions that involve the major classes of anti-infective agents. This approach is intended to complement the use of text-based references and computer databases so that physicians and pharmacists can avoid prescribing and dispensing drugs that have adverse interactions.

Torsade de pointes induced by cisapride/clarithromycin interaction

OBJECTIVE

To highlight a case of torsade de pointes ventricular arrhythmia induced by the concomitant use of cisapride and clarithromycin.

CASE SUMMARY

A 77-year-old white woman was admitted to the hospital with a diagnosis of pneumonia and exacerbation of congestive heart failure. In addition to her usual medications, which included cisapride, the patient was prescribed trimethoprim/sulfamethoxazole and clarithromycin for pneumonia. Within 48 hours, the patient had documented episodes of symptomatic torsade de pointes arrhythmia, which eventually responded to therapy. Both cisapride and clarithromycin were discontinued, and the patient did not have any recurring episodes during a 32-month follow-up.

DISCUSSION

Cisapride has been implicated in causing adverse cardiac events, including torsade de pointes arrhythmia. In most cases, the patients had preexisting risk factors for torsade de pointes and/or were receiving other medications known to inhibit the hepatic CYP3A4 enzyme system and the metabolism of cisapride. There is evidence that clarithromycin, a relatively new macrolide antibiotic, also inhibits the isoenzyme CYP3A4. The resulting accumulation of cisapride caused by concomitant clarithromycin therapy was believed to have been the cause of the torsade de pointes arrhythmia in this patient.

CONCLUSIONS

Concomitant use of cisapride and clarithromycin may cause torsade de pointes arrhythmia.

Clinically important pharmacokinetic drug-drug interactions: role of cytochrome P450 enzymes

Drug-drug interactions have become an important issue in health care. It is now realized that many drug-drug interactions can be explained by alterations in the metabolic enzymes that are present in the liver and other extra-hepatic tissues and many of the major pharmacokinetic interactions between drugs are due to hepatic cytochrome P450 (P450 or CYP) enzymes being affected by previous administration of other drugs. After coadministration, some drugs act as potent enzyme inducers, whereas others are inhibitors. However, reports of enzyme inhibition are very much more common. Understanding these mechanisms of enzyme inhibition or induction is extremely important in order to give appropriate multiple-drug therapies. In the future, it may help to identify individuals at greatest risk of drug interactions and adverse events.

Quantifying the clinical significance of drug-drug interactions: scaling pharmacists' perceptions of a common interaction classification scheme

OBJECTIVE

To develop a precise, interval level scale of the clinical significance of drug-drug interactions that reflects the professional judgments of practicing pharmacists.

PARTICIPANTS

A convenience sample of 63 practicing pharmacists representing hospital (clinical and staff) and retail (chain and independent) practice settings.

METHOD

Pharmacists judged the similarity among 15 interaction categories that have been commonly used to classify drug-drug interactions. A multidimensional scaling technique produced a spatial representation (i.e., a psychological map) of the structure inherent in those similarity judgments. Pharmacists' ratings of clinical significance were projected onto that same spatial representation using a multiple regression procedure, and the resulting information was used to develop a scale of clinical significance.

RESULTS

The clinical significance scale developed from pharmacists' judgments was substantially different from a comparison scale published in a popular reference. The new scale was more precise than the comparison scale, and it also approximated an interval level of measurement. The judgments used to produce the new clinical significance scale were not reliably influenced by pertinent demographic characteristics of the sample.

CONCLUSIONS

Inconsistencies between published clinical significance scales and the professional judgments of practitioners could affect patient care to the degree that a summary measure of clinical significance affects a practitioner's response to a potential drug-drug interaction. The clinical significance scale developed in this study has good measurement characteristics and reflects the professional judgments of practicing pharmacists. Use of the new scale is recommended on these grounds, although further assessment of its generality is warranted.

Drug-drug interactions involving antidepressants: focus on venlafaxine

Selection of an antidepressant is influenced by many factors, including the patient's current drug regimen and the drug's potential for drug-drug interactions. Many psychotropic agents are known to be involved in drug-drug interactions because they are metabolized by various cytochrome pigment 450 (CYP) isoenzymes. In vitro testing with human hepatic microsomal preparations and monoclonal antibody techniques has allowed for the identification and investigation of many of these isoenzymes. Also, screening of substrates (both drug and probe) at the level of the various enzymes expressed in the human liver has allowed for the development of models that predict the risk for drug-drug interactions in vivo. Antidepressants are metabolized by and are competitive inhibitors of several isoenzymes: CYP1A2, CYP2D6, CYP3A3/4, CYP2C8/9, CYP2C19, and others. Of these, CYP2D6 has been the most thoroughly investigated and is the most extensively characterized, whereas CYP3A3/4 are more abundant and play a major role in the metabolism of many commonly used drugs. CYP2D6, but not CYP3A3/4, is subject to genetic polymorphism, which has been identified through the administration of a probe drug (sparteine, debrisoquin, or dextromethorphan). This analysis allows for the determination of an individual's "metabolizer status." This article discusses the CYP isoenzyme system in general terms and presents selected in vitro information that has been used to determine the likelihood of in vivo drug-drug interactions with various antidepressants. Of the marketed antidepressants, venlafaxine seems to have one of the most favorable drug-interaction profiles, and data specific to it are highlighted. In vitro and in vivo data indicate that venlafaxine either does not significantly inhibit or weakly inhibits the activity of isoenzymes CYP2C9, CYP2D6, CYP1A2, or CYP3A3/4.