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Antidepressants are among the most commonly prescribed psychotropic agents for older patients. In particular, there has been a dramatic increase in the frequency at which antidepressants are prescribed to older nursing home patients. Specifically, antidepressant use has increased from 21.9% in 1996 to 47.5% in 2006.1 Of potential concern is that antidepressants are associated with an increased risk for potentially clinically significant adverse drug events (ADEs) in the elderly such as falls and fractures.2 The increased risk of ADEs might be due in part to dosing that does not take into account known age-related changes in antidepressant pharmacokinetics and/or drug-drug interactions (DDIs).3–4 Indeed a recently published study in 877 older nursing home patients showed that 43.1% of antidepressant prescribing for those with depression was potentially inappropriate.5 In particular, dosage problems were seen in 8.8% and DDIs in 25.9%. This latter point is important, as DDIs may be more common in older adults due to the greater number of medications needed to treat persons with multiple comorbid conditions.5
Thus prescribers are faced with a tension that requires that they consider the potential benefits and harms with the use of antidepressants in older patients. Therefore clinicians need accurate up to date pharmacotherapy information sources to correctly dose antidepressants and avoid potential DDIs with antidepressants. One potential source of pharmacotherapy information is the Food and Drug Administration (FDA) approved package inserts (PIs) for marketed antidepressants. However, previous work has shown that PIs for medications commonly used in hospitalized older adults rarely contain comprehensive information about age-related changes in pharmacokinetics.6 Moreover, two separate studies showed that only a minority of potentially clinically significant DDIs appear in the PI compared to other evidence-based sources.7,8 To the best of our knowledge, no study has compared antidepressant PI’s with the evidence-based primary scientific literature regarding the completeness of information about geriatric pharmacokinetics and DDIs.
Given this background, the objective of this study is to synthesize and contrast information in the PI versus that found in the scientific literature regarding antidepressants age-related changes in systemic clearance and potential pharmacokinetic DDIs.
Currently-marketed antidepressants were identified by searching the Martindale drug reference for drugs indicated for the treatment of depression. Those listed in the “drugs@FDA” database were included in this study.9,10 Appendix A list the 26 agents available as of the start of our study (September, 2011). FDA-approved PIs were retrieved when possible for these 26 currently -marketed antidepressants from the 2011 Physicians’ Desk Reference® (PDR).11 In cases where we could find no relevant package insert in the PDR, one was retrieved from the National Library of Medicine’s DailyMed website.12
We identified published studies examining age-related pharmacokinetic changes affecting antidepressants by searching MEDLINE and EMBASE from January 1975 through September 2011. The searches combined the generic names of each antidepressant with the term “pharmacokinetics” and limited the results to studies published in English that included persons age ≥65. Additional articles were found by a manual search of the reference lists of identified articles and the authors’ files, book chapters, and recent review articles.13–25 Two of the investigators (JTH and RDB) independently screened the search results for studies that compared the systemic clearance (Cl) of an antidepressant between the younger and older. We considered a drug to have an age-related change in Cl if any pharmacokinetic study reported a quantitative decrease in Cl in older adults as compared with younger adults. The same two investigators independently identified PI statements referring to age-related pharmacokinetic changes and reporting the quantitative difference in Cl of the antidepressant between the young and old study populations. PIs statements discussing the results of pharmacokinetic studies as “no effect” or “no change” were not included.” Any discordances were resolved by another author (SMH).
We identified published studies examining pharmacokinetic DDIs affecting antidepressants by searching MEDLINE and EMBASE from January 1975 through September 2011. The searches combined the names of each antidepressant with the terms “clinical trial”, “drug interactions”, and “interaction.” and the results were limited to studies published in English. Additional articles were found by a manual search of the reference lists of identified articles and the authors’ files, book chapters, and recent review articles.13–25 Studies involving precipitant drugs that are no longer marketed or cytochrome P450 (CYP) enzyme inducing agents were excluded. Two of the investigators (JTH and RDB) independently reviewed each study and included only those studies that measured systemic Cl and/or area under the concentration time curve (AUC) of the object antidepressant drug in the presence of a precipitant drug. A DDI was operationally defined as any increase in the AUC or decrease in Cl of an antidepressant in the presence of a precipitant drug. The same two investigators independently identified PIs for quantitative information regarding the impact of specific medications on antidepressant AUC and/or Cl. Any discordances were resolved by the another author (SMH).
Descriptive statistics (i.e. percentages) were calculated for literature and PI derived studies showing evidence of age-related decline in systemic clearance and potential DDIs. Agreement between the literature or PI statements for both age-related pharmacokinetic changes and potential DDIs were calculated by the Kappa statistic (a measure of chance-adjusted agreement).26 A Kappa statistic of >0.75 was ranked as “excellent” agreement, one between 0.40 and 0.75 was considered “good to fair,” and less than 0.40 was considered to be “marginal” or “poor” agreement. The Kappa statistic was calculated using SAS (version 9.0, Cary, NC).
Table 1 shows the studies from the scientific literature regarding potential age-related changes in systemic Cl for the 26 antidepressants. It was determined that 13 of the 26 (50%) antidepressants had evidence of age-related decline in systemic Cl.27–44
Table 2 shows information about age-related changes in Cl from PIs. The PIs provided sufficient information on age-related decline in systemic Cl for four antidepressants.45–48. Overall, agreement between the literature and PI regarding age-related Cl changes was marginal or poor as indicated by a Kappa statistic of less than 0.40.
Our search also revealed 52 articles from the scientific literature involving 45 drug-antidepressant pairs that were deemed to be pharmacokinetic DDIs due to changes in AUC and/or Cl (Table 3).49–101 In contrast, the PI shows that only 12 drug-antidepressant interactions involving 8 antidepressants as per changes in AUC or Cl parameter. (Table 4).45–47, 102–106 Again, overall agreement between the PIs and literature was marginal or poor with a Kappa statistic of less than 0.40.
This study demonstrated that the scientific literature provides more complete information regarding age-related decline in antidepressant systemic Cl than does the PI (50% of antidepressants vs 15%). These findings are concordant with a study by Steinmetz et al. found that only 8% of the 50 PIs for commonly used medications in hospitalized older adults stated age- or disease-related pharmacokinetic changes quantitatively.6 It is important to note that despite the marginal to poor overall agreement between the two information sources, the PI did identify two antidepressants with age-related decline in systemic Cl that were not identified in the literature (i.e., mirtazapine and duloxetine).46,47
This study also determined that the literature reported almost four times as many pharmacokinetic DDIs affecting AUC or Cl than did the PIs (47 vs 12). This is consistent with a study by Hines et al. that found that only 15% of the PIs for drugs commonly known to interact with warfarin stated so.7 Similarly, Chao and Maibach found that PIs contained only between 13–48% of the known DDIs affecting four commonly-prescribed dermatologic drugs (i.e., dapsone, erythromycin, methotrexate, and prednisone).8 In this study the PIs did however identify 4 potential DDIs not found in the literature (i.e., cimetidine-citalopram, ketoconazole-mirtazapine, cimetidine-sertraline, and ketoconazole-vilazodone).46,104–106 Fortunately, neither cimetidine or ketoconazole are commonly used medications in older patients.5
Our review of the literature and PIs found twelve antidepressants that have evidence of both an age-related decrease in Cl and at least one Cl-reducing pharmacokinetic DDI. These include three SSRIs (citalopram, escitalopram, and sertraline), two SNRIs (duloxetine, venlafaxine,), four TCAs (amitriptyline, doxepin, imipramine, and nortriptyline) and three other newer antidepressants (bupropion, mirtazapine, and trazodone). Clinicians should be aware that the combination of two or more factors reducing drug clearance can increase the chance that their elderly patient will experience an adverse drug event.4,107 This phenomena was seen in a study by Zint et al. that examined the association between benzodiazepines and hip fracture among older adults.108 Specifically the association between alprazolam alone and falls was not statistically significant (Adjusted Relative Risk [ARR] 1.01, 95% confidence interval [CI] 0.92–1.11). However, the combination of alprazolam with an interacting drug resulted in a point estimate for risk that was increased by nearly 50% (RR 1.51, 1.34–1.69).108
Our study has a number of potential limitations. One potential limitation of this study is that we excluded drug interactions with possible pharmacokinetic and/or pharmacodynamic mechanisms that were found by observational studies. In addition, no distinction was made between age-related changes in free systemic clearance versus clinically important decline. Moreover, we included DDI studies that observed any decrease in Cl or increase in AUC, even if the difference between groups did not reach statistical significance (p<0.05). Nonetheless, we believe that using these more sensitive approaches for inclusion was justified due to the small number of subjects in these studies which could have limited their statistical power to detect meaningful differences. Finally, our search strategy might have missed some studies published in languages other than English, and studies available in unpublished technical reports, white papers, or other “grey literature” sources.
The evidence-based literature compared to PIs is the most complete pharmacotherapy information source regarding both age-related Cl changes and pharmacokinetic DDIs with antidepressants. Future rigorously designed observational studies are needed to examine the combined risk of antidepressants with age-related decline in clearance and potential DDIs on important health outcomes such as falls and fractures in older patients. 108,109
We would like to thank Subashan Perera, PhD for his help calculating the Kappa statistics.
The first author (RDB) was funded by grant K12HS019461 from the Agency for Healthcare Research and Quality. Additional grant support for the co-authors was provided by an Agency for Healthcare Research and Quality grant (R01HS018721 and R01 HS017695), National Institute on Aging grants (K07AG033174, P30AG024827, T32 AG021885, R01AG034056, R56AG0207017 and AG033575), a National Institute of Nursing Research grant (R01 NR010135), National Center for Research Resources grants (KL2 RR024154, 3 UL1 RR024153-04S4), and a VA Health Services Research grant (IIR-06-062). The content is solely the responsibility of the authors and does not represent the official views of the Agency for Healthcare Research and Quality or any of the other funding sources.
CONFLICT OF INTEREST STATEMENT
The authors acknowledge no conflicts of interest. JK has been an advisor for Eli Lilly and Theravance, but not within the last 18 months. He is also a stock owner of Corcept.