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. Author manuscript; available in PMC: 2023 Feb 23.
Published in final edited form as: Pharmacotherapy. 2017 Sep 19;37(10):1197–1203. doi: 10.1002/phar.2012

Factors in Variability of Serial Gabapentin Concentrations in Elderly Patients with Epilepsy

Jeannine M Conway 1, Lynn E Eberly 2, Joseph F Collins 4, Flavia M Macias 3, R Eugene Ramsay 3, Ilo E Leppik 1,5, Angela K Birnbaum 1
PMCID: PMC9949609  NIHMSID: NIHMS899285  PMID: 28801938

Abstract

Objectives

To characterize and quantify the variability of serial gabapentin concentrations in elderly patients with epilepsy.

Methods

This study included 83 patients (age ≥60 years) from an 18-center, randomized, double-blind, double dummy, parallel study from the Veterans Affairs Cooperative 428 Study. All patients were taking 1500 mg/day of gabapentin. Within-person coefficient of variation (CV) in gabapentin concentrations, measured weekly to bimonthly for up to 52 weeks, then quarterly, was computed. Impact of patient characteristics on gabapentin concentrations (linear mixed model) and CV (linear regression) were estimated.

Results

A total of 482 gabapentin concentration measurements were available for analysis. Gabapentin concentrations and intrapatient CVs ranged from 0.5–22.6 µg/mL (mean 7.9 µg/mL, standard deviation [SD] 4.1 µg/mL) and 2%–79% (mean 27.9%, SD 15.3%), respectively, across all visits. Intrapatient CV was higher by 7.3% for those with a body mass index (BMI) of greater than or equal to30 kg/m2 (coefficient=7.3, p=0.04). CVs were on average 0.5% higher for each 1 unit higher CV in creatinine clearance (coefficient=0.5, p=0.03), and 1.2% higher for each 1-hour longer mean time after dose (coefficient=1.2, p=0.04).

Conclusions

Substantial intrapatient variability in serial gabapentin concentration was noted in elderly patients with epilepsy. Creatinine clearance, time of sampling relative to dose, and obesity were found to be positively associated with variability.

Keywords: antiseizure drug, variability, concentration, elderly, epilepsy, gabapentin

Therapeutic drug monitoring can be helpful in guiding treatment of epilepsy with antiseizure drugs (ASDs), especially in the elderly.1 Even under conditions of stable dosing, concentrations of ASDs may fluctuate due to day-to-day variations in absorption and elimination, and the extent of the fluctuations must be understood in order to properly interpret laboratory results. The variability in some ASDs has been reported to be in the range of 20% for phenytoin and 25% for carbamazepine and valproate in adherent younger adult patients.2–4 Changes in physiology due to age may have an impact on the pharmacokinetics, pharmacodynamics, and daily fluctuations in ASD concentrations. Antiseizure drug concentrations in older patients may not need to be maintained at the levels used in younger adults, and may be more highly variable in elderly patients with epilepsy. Indeed, previous studies presenting ASD concentrations in elderly community-dwelling and nursing home patients taking phenytoin, valproic acid, and carbamazepine have concluded that these patients might need lower daily doses to achieve similar concentrations and may experience more variability in concentrations.5–11

Gabapentin, initially approved as an adjunct treatment for epilepsy, has also been approved for treatment post-herpetic neuralgia. Gabapentin is actively absorbed from the gut by an amino-acid transporter that can become saturated at the higher daily doses normally used in the clinic.12 Studies in younger healthy volunteers show gabapentin concentrations have high intersubject variability and low intra-subject variability in bioavailability13; however, no studies on concentration variability in elderly individuals are available. Gabapentin is not metabolized by the liver and is primarily excreted unchanged in the urine. Therefore, age-related changes in gut absorption and declining kidney function could affect variability of ASD concentrations.13, 14

We conducted a repeated-measures longitudinal analysis of gabapentin serum concentrations obtained in the VA Cooperative 428 Study (VA 428 Study)15 to evaluate the variability within an individual patient over time. Demographic and physiologic factors that could affect variability, such as age, sex, weight and creatinine clearance (CrCl), were used in this analysis to obtain an understanding of how these factors might contribute to variability of measurements over time in individual patients.

Methods

Study Design

Data were from a prospective study of community-dwelling elderly veterans (age ≥60 years at enrollment) completing the VA 428 Study, a randomized, double-blind, parallel, three-arm efficacy and tolerability trial of monotherapy treatment for epilepsy with carbamazepine, gabapentin, and lamotrigine.15 Elderly veterans with newly diagnosed seizures, subtherapeutic treatment with concurrent ASDs, or treatment with an ASD for less than four weeks prior to randomization were eligible for inclusion. The target dose of gabapentin was 1500 mg/day given in three doses, initiated at 300 mg/day and titrated to the target dose over three days in increments of 300 mg. The target dose was not intended to be fixed; it could be altered in response to inadequate seizure control or toxicity. This analysis was conducted using only those concentrations from 1500 mg/day dosing.

Protocol Approval

The original trial was approved by the Central Veterans Affairs Human Rights Committee and individual local institutional review boards at the participating centers. Our analysis was approved by the University of Minnesota’s Institutional Review Board for Human Subjects.

Database Description

Blood for gabapentin and creatinine concentration determinations was obtained biweekly to week 8, monthly to week 28, and bimonthly until week 52. For patients remaining in the trial for more than one year, blood was obtained every three months. The amount of the three previous gabapentin doses (to calculate total daily dose), and the time of blood sampling were recorded; no constraint was placed on the timing of blood sampling. Time after dose (TAD) of the sampling was calculated as the time elapsed from the most recent dose to the blood sampling. Serum samples were analyzed by high performance liquid chromatography in a central laboratory using a method developed by Lensmeyer16 and drug levels were measured at the time of completion of the VA 428 Study. Quality control analysis at the lowest limit of quantitation (0.17 mg/L) indicated that the assay was precise (coefficient of variation [CV] <8%). Accuracy of the assay at the lowest limit ranged from 98% to 113%. Data were checked for potential inconsistencies or errors by visual inspection for outliers. From the main trial database, the creation of the gabapentin subset and data quality control were done using SPSS version 13 (SPSS, Inc., Chicago, IL).

Study Sample

We selected only patients taking gabapentin therapy who: (i) were on a 1500 mg/day dose, (ii) had three or more measured gabapentin serum concentrations at this dose, and (iii) were at steady-state dosing. Gabapentin has a half-life of approximately 5–9 hours, so patients would achieve steady-state by their first clinic visit at week two.17 One patient with an outlying weight of 149.5 kg was excluded. The master database of elderly patients taking gabapentin in the VA 428 Study contained demographic, clinical, and dosing regimen data from 132 patients. Of these, 83 patients (63%), having 482 gabapentin concentrations, met inclusion criteria.

Statistical Methods

Gabapentin concentrations and clinical characteristics were summarized by mean and standard deviation (SD), , or frequency (%), as appropriate. Intrapatient variability in gabapentin concentrations was summarized graphically and via CV. Within-patient CV was computed by dividing the SD of an individual’s concentrations by their mean concentration.

Patient characteristics considered for inclusion in the modeling were age, race, sex, weight, calculated CrCl, and TAD. Age was considered as a continuous measure (years) and also as age groups (60–74 y, , ≥75 years) at trial baseline. Race was categorized as nonwhite or white. Weight (kg) was considered as a continuous measure (kg) and also as obese status (body mass index [BMI] <30 kg/m2 or ≥30 kg/m2) at first visit where the dose inclusion criterion was met. Creatinine clearance was calculated from serum creatinine measurements using the Cockcroft-Gault equation18, which takes into account patient characteristics, such as age, weight and gender, to estimate CrCl from serum creatinine measurements. If the patient’s BMI was less than 30 kg/m2, actual body weight was used. If the patient’s BMI was ≥30 kg/m2, lean body weight was calculated and used.18, 19 Creatinine clearance and TAD were summarized across visits as intraindividual mean and variability (CV) in CrCl, and intraindividual mean and variability (CV) in TAD. Few patients were receiving more than one ASD, and these drugs were not considered in our modeling because of their lack of pharmacokinetic drug interactions with gabapentin.17 Less than 10% of patients were taking drugs for conditions other than epilepsy; because these concomitantly administered drugs do not interfere with gabapentin pharmacokinetics, they were not included in the analysis.

Impact of patient characteristics on gabapentin serum concentrations was assessed using a linear mixed model with concentration as the response variable, including a piecewise linear slope to account for the trend in concentration across weeks and a random effect for patient to account for the within-patient correlation in concentration across weeks. For these analyses only, concentrations at week 60 and later were excluded because there were few data points available (8 from 5 patients). Impact of patient characteristics on variability in gabapentin concentrations was assessed in a linear regression model with intrapatient gabapentin concentration CV as the response variable.

In a forward selection procedure, each characteristic was assessed singly with each outcome and then significant characteristics (p<0.20) were assessed together in a multivariate model. Because the CV outcomes reflect gabapentin concentrations summarized across visits into one measure per person, the respective models with CrCl and TAD were also summarized across visits, and were each included in the models as two separate variables: their intrapatient averages and their intrapatient CVs. Since individuals had widely varying numbers of visits, the models for CV first included, and then excluded, those people with very few (<4) or very many (>8) visits. Results were similar, except that the associations of CrCl and TAD with gabapentin CV were stronger and more significant, and the association of BMI with gabapentin CV was weaker and no longer significant, when only those with 4–8 visits were included. Significance was determined at p<0.5. Only those results including all patients (no matter how many visits they had) are reported in detail in the Results section. All model implementation and graphs were done in SAS, version 9.3 (SAS Institute, Inc., Cary, NC).

Results

Overview of Study Population

Demographics and baseline characteristics are outlined in Table 1. The number of visits at which gabapentin dose criterion was met ranged from 3 to 14 per patient (mean 5.8, SD 2.4). Eligible patients were predominantly white men, with mean age at trial baseline of 72.8 years (SD 7.3 years). Across all included visits, mean intrapatient average CrCl was 62.3 mL/min (SD 21.8 mL/min) and mean intrapatient CV in CrCl was 10.0% (SD 6.5%). Mean intrapatient average TAD was 5.2 hours (SD 2.8 hours) and mean intrapatient CV in TAD was 47.4% (SD 32.5%). Figure 1 presents the spread of daily doses and gabapentin concentrations in the study by weight group.

Table 1.

Characteristics of elderly veterans taking gabapentin at a total daily dose of 1500 mg and with three or more gabapentin concentration measurements

Characteristic Mean (SD) or N (%)
Number of patients 83
Number of visits per patient 5.8 (2.4)
Male, N (%) 76 (91.6%)
Nonwhite race, N (%) 22 (26.5%)
Age at trial baseline (years) 72.8 (7.3)
Weight at first included visit (kg) 82.6 (13.6)
BMI at first included visit (kg/m2) 27.7 (4.4)
Overweight at first included visit, N (%) 25 (30.1%)
Intraindividual average creatinine clearance (mL/min) 62.3 (21.8)
Intraindividual CV in creatinine clearance (%) 10.0 (6.5)
Intraindividual average time after dose (hours) 5.2 (2.8)
Intraindividual CV in time after dose (%) 47.4 (32.5)
Mean gabapentin concentration at first included visit (μg/mL) 7.9 (4.1)
Intraindividual CV of gabapentin concentrations (μg/ml) 27.9 (15.3)
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BMI = body mass index; CV = coefficient of variation; SD = standard deviation,

Figure 1.

Figure 1

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Individual gabapentin concentrations according to total daily dose (in mg/kg) in patients with a body mass index less than 30 kg/m2 (closed circles) and ≥30 kg/m2 (open triangles). All total daily doses were 1500 mg.

Population Results

The mean gabapentin clearance was 3.3 L/kg/day (SD 3.4 L/kg/day). Gabapentin concentrations ranged from 0.5 µg/mL to 22.6 µg/mL across all visits, with a mean at first included visit of 7.9 µg/mL (SD 4.1 µg/mL) with intrapatient CVs ranging from 2% to 79% (mean 27.9%, SD 15.3%) (Table 1). Intra- and interpatient variability in gabapentin concentrations in order of patient age at first included visit are shown in Figure 2A and in order of intraindividual CV are shown in Figure 2B. In the linear mixed model for gabapentin concentration, TAD (p=0.0002 for quadratic trend) and CrCl (p<0.0001 for quadratic trend) were significantly associated with gabapentin concentrations. Mean concentrations differed across the weeks (p=0.002), and tended to be higher in the later weeks; however, the difference overall was small (< 2 µg/mL). Age was inversely related (p=0.01) to gabapentin concentrations. Gender (p=0.50), race (p=0.48), and weight (p=0.16) were not significantly associated with gabapentin concentrations.

Figure 2.

Figure 2

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Intra- and intersubject variability in gabapentin concentrations in order of patient age at first included visit (A) and in order of intraindividual coefficient of variation (B). Each open circle represents a single total gabapentin measurement. A vertical line connects all of the gabapentin measurements within each individual (N=83). GBP = gabapentin.

Intraindividual CV as Outcome

The distribution of CVs is shown in Figure 3 demonstrating the majority of patients CVs were less than 30%. In the univariate linear regression models, weight (p=0.09), age (p=0.06), gender (p=0.17), CrCl (p=0.05), and TAD (p=0.18) were for included in the multivariate linear regression model. From the multivariate linear regression model, intrapatient CV was higher by 7.3% for those with a BMI of 30 kg/m2 or greater compared with those with a BMI less than 30 kg/m2 (coefficient=7.3, p=0.04). CVs were significantly higher with higher CrCl and with higher mean TAD: CVs were on average higher by 1.5% for each 10 mL/min higher mean CrCl (coefficient=1.5, p=0.10), higher by 0.5% for each 1 unit higher CV in CrCl (coefficient=0.5, p=0.03), and higher by 1.2% for each 1 hour longer mean TAD (coefficient=1.2, p=0.04).

Figure 3.

Figure 3

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Distribution of coefficient of variation of gabapentin concentrations in 83 elderly community-dwelling patients with epilepsy taking 1500 mg/day of gabapentin.

Discussion

Therapeutic drug monitoring can be a useful guide to treatment of patients with epilepsy.1 However, even under steady dosing conditions, drug serum concentrations can vary within a patient.5, 9 Understanding the extent of variability within a patient is important in the proper interpretation of serial concentrations. The extent of within-patient variability may be due to a number of factors, including age, CrCl, dose and weight. To the best of our knowledge, this study is the first to characterize variability of gabapentin over repeated dosing among elderly community-dwelling patients with epilepsy. There was a wide range in variability of serial gabapentin concentrations determined by intraindividual CVs (2%–79%). Time after dose and CrCl were positively associated with intrapatient CV. Of interest, patients who were obese (BMI ≥30 kg/m2) had a 7.3% higher CV on average than those who were not obese (p=0.04).

Within our elderly group of patients, age was inversely related to gabapentin concentrations (p=0.01), that is, older patients had lower gabapentin levels. We also found that after adjusting for CrCl, age did not influence gabapentin concentration variability. CrCl being more predictive of gabapentin clearance than age is consistent with previous findings in a study that included patients from age 5 to 84.20 One study that found age to be correlated with gabapentin concentration–to–dose ratio did not adjust for serum creatinine or CrCl.21 Age has also been found to be correlated with drug clearance in patients on levetiracetam which is renally cleared..22 Thus, age may be a surrogate marker for CrCl. Our study is consistent with other findings (23) and suggests that CrCl may be a more useful factor than age in evaluating the pharmacokinetics of ASDs that are renally eliminated in elderly patients..23

Variability of gabapentin concentrations could be due to several pharmacokinetic and patient characteristics. Not taking a prescription regularly or missing doses can lead to widely varying concentrations. The overall self-reported adherence of patients in VA 428 Study was 89% with no significant differences among elderly patients taking gabapentin, carbamazepine, and lamotrigine.15 For gabapentin, the adherence rate was approximately 90%. This value is higher than the 77% reported in patients on a thrice-daily regimen.24 Thus, drug adherence is not a likely source of the intrapatient variability in our study. Variability due to analytical assay should also be considered. For gabapentin, all samples were analyzed in one laboratory with the CV at the lowest standard being 8%, thus explaining only a small fraction of the observed total variability.

Because gabapentin displays dose-dependent absorption12, we selected only individuals at the same dose of gabapentin for inclusion in this analysis to control for this variable. Gabapentin is a highly polar, hydrophilic amino-acid type drug that is absorbed systemically through a large neutral amino-acid transporter system. It is absorbed primarily from the small intestine. Two factors that might contribute to absorption-related variability are food effects and gastric motility. In general, the presence of food can have unpredictable effects on the absorption process. One study demonstrated that after a high-protein meal, the maximum concentration of gabapentin was significantly increased but no significant difference in area-under-curve of gabapentin occured.25 Gastrointestinal motility can be affected by fluid intake and hydration status.26 Gastric emptying time could vary, leading to variable absorption from the small intestine secondary to changes in fluid intake. Variability due to change of formulation or dosage form was not a factor in this study, because all patients were administered the same brand and dosage form (300 mg capsules) of gabapentin.15 Whether the variability seen in gabapentin concentrations at the same steady-state dose is specific to the elderly is not known, as this study did not include a comparator group of younger adult patients.

There are several limitations in this study. Although the veterans in this study were predominantly male and consisted of community-dwelling patients, our results may be applicable to the general elderly patient population, including females, because of the pharmacokinetic properties of gabapentin. For example, gabapentin is not metabolized by hepatic enzymes and is not protein-bound, therefore, it does not undergo pharmacokinetic interactions with concomitant enzyme-inducing or enzyme-inhibiting ASDs.17 Furthermore, gabapentin is not likely to be affected by hormonal fluctuations.27 Based on single-dose pharmacokinetics, gabapentin pharmacokinetics have been shown to be similar in men and women.20 Data describing seizure outcomes or side effects were not available for our analysis; therefore, the consequences of variability on seizure frequency and side effects could not be explored.

In conclusion, substantial variability in gabapentin serial concentrations in elderly patients who are on the same dose of gabapentin exists. Thus, if seizure control does not occur, it might be due to intrapatient variability. More than one concentration measurement may be necessary within a patient to determine the true systemic exposure trend. Although therapeutic drug monitoring is not usually practiced in other conditions for which gabapentin is prescribed, such as pain or restless leg syndrome, an appreciation of the variability in concentration within a patient is useful when assessing side effects and symptom relief when gabapentin is used for these indications.

Acknowledgments

The authors thank the VA Cooperative Study 428 (RER, FMM, JFC) for providing the data set used in this study.

Funding: This work was supported by NIH/NINDS P50-NS16308 (LEE, JMC, IEL, AKB) from the National Institute of Neurological Disorders and Stroke (NINDS) and R01AG026390 (AKB) from the National Institute on Aging (NIA). The content is solely the responsibility of the authors and does not necessarily represent the official views of NINDS, NIA, or the National Institutes of Health.

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