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Cochrane Database of Systematic Reviews Protocol - Intervention

Interaction of calcium channel blockers and grapefruit juice in healthy adults

Authors' declarations of interest

Version published: 30 December 2014 Version history

https://doi.org/10.1002/14651858.CD011452
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Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To evaluate whether and to what extent grapefruit juice interacts with individual calcium channel blockers in healthy adults.

Background

Description of the condition

Calcium channel blockers prevent the entry of extracellular calcium through voltage sensitive L‐type calcium channels in the smooth muscles, cardiac myocytes, sinoatrial and atrioventricular nodal cells in response to electrical depolarization (Michel 2011). Their main actions are dilation of systemic arterial vasculature, a negative inotropic action, reduction of heart rate and slowing of atrioventricular (AV) conduction (McDonagh 2005). They are indicated for the management of systemic hypertension, angina, and supraventricular arrhythmias (Sica 2006). Non‐cardiac therapeutic implications for calcium channel blockers include cluster headache, mood disorders, threatened preterm labor, subarachnoid haemorrhage, epilepsy, migraine and Meniere's disease (Michel 2011). They undergo a considerable but varying first pass metabolism both in the intestine and in the liver and their bioavailability varies from around 5% in case of nisoldipine to 80% to 90% in case of amlodipine. The major enzyme that carries out both the first pass metabolism and hepatic metabolism is CYP3A4 (Kolars 1992; Sica 2005). Except for diltiazem and verapamil, most of the other calcium channel blockers produce inactive metabolites (Talbert 1983). Along with the various drug interactions, calcium channel blockers also exhibit drug‐food interactions, especially with grapefruit juice (Michel 2011).

Description of the intervention

Grapefruit juice is an extract from grapefruit and is rich in vitamin C and dietary fiber (Fellers 1990). Developed in the West Indies around the 1700s, it is now widely used internationally. As it is claimed to have antioxidant, antiseptic, cardiotonic, and hypocholesteraemic activities, it has been traditionally indicated for treating infections, benign prostatic hypertrophy, atherosclerosis and cardiovascular diseases (Kiani 2007). Grapefruit juice carries the American Heart Association's heart‐check mark as it decreases cholesterol and cardiovascular disease risk (Sterling 2005). It is known to interact with those drugs that are predominantly metabolized by CYP3A4, thereby markedly attenuating their first pass metabolism (Lown 1997). The components that have been studied for this interaction include naringin, quercitin, kaemferol (Miniscalco 1992) and the non flavanoid, 6'7' dihydroxybergamottin (Edwards 1996). Also, inhibition of the intestinal efflux transporter, P‐glycoprotein, has been reported with the ingredients of grapefruit juice (Takanaga 1998; Eagling 1999; Dahan 2004).

How the intervention might work

The active ingredients in grapefruit juice inhibit the intestinal and hepatic CYP3A4 enzyme and thereby markedly elevate the amount of systemic exposure as well as affect the pharmacokinetics of the drug that is predominantly inactivated by the enzyme (Pirmohamed 2013). Reports suggest that the effect of the interaction is greater with drugs that have lower bioavailability (Ohnishi 2006). Since calcium channel blockers are substrates for intestinal CYP3A4 and some of them have lower bioavailability, it may be prudent to investigate the effect of inhibition of first pass metabolism and a consequent increase in the systemic exposure by concurrent administration of grapefruit juice. Reports have suggested a marked increase in the absorption of diazepam and triazolam which are also predominantly metabolized by the intestinal CYP3A4 (Ozdemir 1998; Lilja 2000).

Why it is important to do this review

Firstly, this interaction is a potential concern because both grapefruit juice and calcium channel blockers are often consumed together at breakfast and hence, patients need to be educated about the interaction. Secondly, although randomized controlled clinical trials have been conducted with various calcium channel blockers to study their interaction with grapefruit juice (Bailey 1993; Bailey 1995; Uno 2006), this effect has not been systematically reviewed to date.

Objectives

To evaluate whether and to what extent grapefruit juice interacts with individual calcium channel blockers in healthy adults.

Methods

Criteria for considering studies for this review

Types of studies

We will include randomized controlled clinical trials.

Types of participants

Adults (aged > 18 years) of either sex diagnosed as healthy by either history, medical examination and/or laboratory examination, irrespective of ethnic group.

Types of interventions

Comparison: calcium channel blockers with and without grapefruit juice.

We will include those trials in which calcium channel blocker is administered either with or without grapefruit juice. Trials that have evaluated other interventions in addition to these two arms will also be included and only the data from those relevant arms will be considered for review. We will also include cross‐over trials wherein the same participant receives both the intervention and the comparison with a wash out period of at least seven days. We will include studies irrespective of the dose and duration of grapefruit juice as well as the formulation, chemical entity, dose and duration of calcium channel blockers, and irrespective of whichever is administered first. Only those trials that have evaluated the drug concentration using a standard pharmacokinetic method will be included.

Types of outcome measures

Primary outcomes

  1. Area under concentration‐time curve (AUC 0‐t and AUC0‐∞) which is a measure of rate and extent of absorption of a drug.

  2. Maximum concentration achieved in the plasma (Cmax) following a dose of calcium channel blocker.

  3. Time to achieve the maximum concentration of calcium channel blocker in the plasma (Tmax).

Secondary outcomes

  1. Elimination half life (t1/2) ‐ time taken for the drug concentration to reduce to half of its initial value.

  2. Clearance (CL) of the drug that represents the volume of plasma or blood that is completely cleared of the drug in a unit time.

  3. Volume of distribution (Vd) of the drug which is an apparent volume that contains the drug in the same concentration as that of blood.

  4. Absorption rate constant (ka) of the drug.

  5. Change in heart rate.

  6. Change in blood pressure.

  7. Flushing.

  8. Headache.

Search methods for identification of studies

Electronic searches

We will search the Database of Abstracts of Reviews of Effects (DARE) for related reviews.

We will search the following electronic databases for primary studies: the Cochrane Hypertension Group Specialized Register (1946 to present), the Cochrane Central Register of Controlled Trials (CENTRAL, latest issue), Ovid MEDLINE (1946 to present), Ovid EMBASE (1974 to present), and ClinicalTrials.gov. The Specialized Register includes searches of the WHO International Clinical Trials Registry Platform (ICTRP).

Electronic databases will be searched using a strategy combining the Cochrane Highly Sensitive Search Strategy for identifying randomized trials in MEDLINE: sensitivity‐maximizing version (2008 revision) with selected MeSH terms and free text terms relating to calcium channel blockers and grapefruit juice.  No language restrictions will be used.  The MEDLINE search strategy (Appendix 1) will be translated into the other databases using the appropriate controlled vocabulary as applicable.

Searching other resources

  1. We will search reference lists of all papers and relevant reviews identified.

  2. Authors of relevant papers will be contacted regarding any further published or unpublished work.

Data collection and analysis

Selection of studies

Two authors (KS and NG) will screen the results of the searches. When potentially relevant abstracts are identified, full text articles will be retrieved and two authors (KS and NG) will independently assess them against the eligibility criteria. Any disagreement will be resolved by the third author (UT). A complete accounting of the searches will be provided as a PRISMA study flow diagram (Liberati 2009).

Data extraction and management

Two review authors (KS and NG) will extract data from the related articles independently using a data extraction form. Any disagreement will be resolved by the third author (UT).

The information that will be included in the data extraction form includes:

  1. General information: study ID, review author ID, citation and contact details of the authors of the study.

  2. Characteristics of the included trial: design, sequence generation, allocation concealment, blinding.

  3. Participants: total number of participants in the experimental and control group, age, sex, race.

  4. Intervention: name, formulation, dose and duration of the drug as well as strength and duration of grapefruit juice and the time of administration of grapefruit juice and the drug.

  5. Outcomes: Outcome measures that have been mentioned in this protocol will be collected.

Sample size, mean and standard deviation for continuous data and proportion of individuals for dichotomous data will be extracted for each group.

Assessment of risk of bias in included studies

Risk of bias of selected trials will be assessed using the tool described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011) by two review authors (KS and NG) independently. Any disagreement will be resolved by the third author (UT). We will contact the authors of the relevant studies to obtain additional information. The 'Risk of bias' assessment will be presented in tables organized according to the following domains (Higgins 2011):

  1. Sequence generation

  2. Allocation concealment

  3. Blinding of participants and personnel

  4. Blinding of outcome assessment

  5. Incomplete outcome data

  6. Selective outcome reporting

  7. Other bias

The risk of bias for each domain will be categorized as:

  • low risk of bias

  • high risk of bias

  • unclear risk of bias

Measures of treatment effect

The extracted data will be analyzed using Review Manager 5.3 software (RevMan 2014). We will measure the mean difference for the continuous outcome variables and risk ratio for dichotomous outcome variables between the groups. We will provide 95% confidence intervals (CIs) and P values for the comparison.

Unit of analysis issues

For cross‐over trials, the effect estimate will be calculated as the difference in outcome measurement for each participant and may be included in meta‐analysis using the generic inverse variance method in Review Manager 5.

When the study has more arms than two treatment groups, they will be considered only if they are relevant to this review. Otherwise, data from only the relevant arms will be included.

Dealing with missing data

When there are missing data, we will contact the original authors to request the necessary information.

Assessment of heterogeneity

We will assess clinical heterogeneity by considering variability in the participants, interventions and outcomes of the studies. Statistical heterogeneity will be assessed by the Chi2 test and I2 test. For the Chi2 test, the P value will be considered significant if it is < 0.1 whereas if the I2 value ranges between 75% to 100% we will assume the presence of substantial heterogeneity (Higgins 2011).

Assessment of reporting biases

Potential publication bias of selected studies will be investigated by funnel plot (Egger 1997) if there are more than 10 studies.

Data synthesis

Each outcome of the included studies will be combined and calculated via Review Manager 5 in an attempt to estimate the overall effect. The Mantel‐Haenszel method for the fixed‐effect model will be used except when statistical heterogeneity is observed, in which case the random‐effects model will be applied.

We will create one (or more) 'Summary of findings' table(s) using the GRADE methodology described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011).

Subgroup analysis and investigation of heterogeneity

We will perform the following subgroup analyses:

  1. Between different calcium channel blockers (dihydropyridine and non dihydropyridine)

  2. Single and double concentrations of grapefruit juice

  3. Different doses of each calcium channel blocker

  4. Immediate versus delayed release preparation of each calcium channel blocker

  5. Single and multiple doses of grapefruit juice

  6. Grapefruit juice prior to and post administration of calcium channel blocker

Sensitivity analysis

We will perform sensitivity analysis where in doubt of the risk of bias, eligibility criteria or publication status of included studies, in order to assess the impact on the overall result.