Impact of FDA Black Box Warning on Psychotropic Drug Use in Noninstitutionalized Elderly Patients Diagnosed With Dementia: A Retrospective Study
Journal of Pharmacy Practice 1-8 ª The Author(s) 2015 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0897190015579451 jpp.sagepub.com
Rakesh R. Singh, MS1, and Rajesh Nayak, PhD2
Abstract Background: The study seeks to investigate the impact of Food and Drug Administration’s black box warning (BBW) on the use of atypical antipsychotics (AAP) and nonantipsychotic psychotropic alternatives in noninstitutionalized elderly population diagnosed with dementia. Method: The Medical Expenditure Panel Survey (2004 through 2007) was utilized as the data source. Medication use in elderly patients (65 years) was defined as taking at least 1 medication for dementia. We performed a statistical comparison of prewarning (2004-2005) and postwarning (2006-2007) periods with respect to AAP and nonantipsychotic psychotropic use to examine the impact of labeling changes. Results: A bivariate analysis did not yield statistically significant change in either the AAP or nonantipsychotic psychotropic use, pre- versus postwarning. However, multivariate logistic-regression analyses revealed greater odds for antidementia (odds ratio [OR] ¼ 1.976, P ¼ .0195) and benzodiazepine (OR ¼ 3.046, P ¼ .0227) medication use in postwarning period compared to the prewarning period. Conclusion: The regulatory warnings and labeling changes regarding offlabel use of AAPs in dementia treatment showed minimal impact on their actual use in noninstitutionalized populations. A corresponding increase in the use of nonantipsychotic psychotropics explains that BBW might have resulted in a compensatory shift in favor of benzodiazepines and antidementia medications. Additional research should be conducted to examine the longterm impact of BBW on antipsychotic prescribing changes. Keywords medication safety, neurology, pharmacy administration, drug information, social and administrative sciences
Background Antipsychotic medications were primarily approved for managing symptoms of schizophrenia and schizophrenia-related disorders. Utilization of antipsychotics (typical and atypical) has scaled steadily since its introduction in early 1970s, and atypical antipsychotics (AAPs) alone accounted for more than US$7 billion in annual expenditures in 2007.1 Besides the approved indications, antipsychotics are increasingly being prescribed off-label, in the elderly as well as children, for a range of mental health conditions.2 Previous reports suggested an increase in use of antipsychotics in the dementia population, particularly for managing behavioral and psychological disorders associated with the disease. Evidence from randomized clinical trials clearly suggests that the use of antipsychotics in the elderly dementia population is associated with fatal side effects.3 In a meta-analysis of community dwelling cohort, antipsychotic use was associated with statistically significant increase in mortality compared to the nonantipsychotic cohort.4 Although the exact mechanism of action is not known, few plausible causes have been outlined in the literature. AAPs affect
the cardiac system and increase the likelihood of arrhythmias and sudden cardiac death. Studies have also indicated association with aspiration pneumonia, venous thromboembolism, and cerebrovascular events.5-15 In response to rising safety concerns and mounting evidence against use of antipsychotic medications in dementia, the US Food and Drug Administration (FDA), in 2005, issued a black box warning (BBW) of excess mortality associated with the use of all 6 AAPs in dementia for persons aged 65 years and above.16 In June 2008, the US FDA extended the BBW to typical antipsychotics as well.17
1 Department of Health Outcomes and Pharmacy Practice, College of Pharmacy, The University of Texas at Austin, Austin, TX, USA 2 Department of Pharmacy Administration and Allied Health Sciences, College of Pharmacy and Health Sciences, St John’s University, Queens, NY, USA
Corresponding Author: Rakesh R. Singh, The University of Texas at Austin, 2409 University Ave., STOP A1930, Austin, TX, USA. Email: [email protected]
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Since the imposition of the BBW, numerous studies have investigated the impact of regulatory labeling changes on the utilization of antipsychotics in patients with dementia. A study by Dorsey et al evaluating the impact of the BBW among all individuals 18 years and older reported a 34% increase in the use of AAPs overall, and 16% among individuals with dementia.18 Another study by Kales et al that evaluated the impact of BBW on the use of AAPs in veterans 65 years and above who were diagnosed with dementia reported significant decline in the use of AAPs in the veteran population after the BBW was issued.19 However, both the studies are indicative of physicians practice rather than actual prescribing practice. The impact of the warning extended beyond the intended classes. Previous studies have also evaluated the impact of the BBW on the spillover or compensatory change in utilization of nonantipsychotic medications (antidepressants, anticonvulsants, and benzodiazepines) used in patients with dementia.18,19 In the absence of clinical evidence to support the use of AAPs in dementia, nonantipsychotics drugs might appear as the only viable alternative. To this end, the study by Dorsey et al provided some early evidence that spillover effects might have led to decreased prescribing of AAPs in younger population even though the BBW was clearly meant for the elderly population.18 Furthermore, a study by Kales et al, on a group of veterans 65 years and older diagnosed with dementia, also observed spillover effects, particularly in nonantipsychotic drug classes, providing further evidence that such effects could be a probable consequences of the regulations.19 Although previous studies focused on the impact of BBW on the use of AAPs in the physician reported surveys and/or veteran population prescribing, very few of them explored patient reported data from noninstitutionalized individuals 65 years of age and over and diagnosed with dementia.18,19 Exploring noninstitutionalized patients might be important because individuals suffering with dementia might get their first diagnosis from a primary care provider in an officebased setting. It is highly unlikely for a patient with dementia to be hospitalized during the initial phase of their illness. More importantly, patients being hospitalized might be at a more advance stage of their illness where antipsychotics might be the only treatment available given the lack of evidencebased trials for other nonantipsychotic medications. Furthermore, since AAPs are being prescribed off-label, they are less likely to be recorded in physicians surveys. Patient reported administrative data will provide a more wide ranging and accurate picture of the practice trends. The current study addressed this important research gap, as well as evaluated the utilization patterns and consequences of labeling changes for both AAP and nonantipsychotic use in the noninstitutionalized population.
Methods Data and Sample The Medical Expenditure Panel Survey (MEPS) is a complex national probability sample survey of the US civilian
noninstitutionalized population. MEPS database has 2 components for which the data are collected, that is, the Household Component (MEPS-HC) and the Insurance Component (MEPS-IC). MEPS-HC is a nationally representative data of households that includes demographic characteristics, health conditions, health status, use of medical services, charges and payments, access to care, satisfaction with care, health insurance coverage, income, and employment.20 The MEPS-HC is a sample of households subsampled from the previous year’s National Health Interview Survey. 20 Each new MEPS sample is referred to as a panel, and data for each panel are collected through 5 rounds of computer-assisted personal interviews spread over a 2.5-year period. 20 MEPS-IC is an annual survey of employers that collects data regarding the number and types of private health insurance plans offered, associated benefits, annual premiums, annual contribution by employees, eligibility requirements, and employer characteristics. MEPS-IC component comprises of MEPS-IC list sample and MEPS-IC household sample. MEPS-IC list component comprises of nationwide sample of state and local governments and other establishments. However, these data are not available for public use and can be accessed only through the census bureau’s research center. The MEPS-IC household component comprises of a sample of employers that were identified from the responses in the MEPS-HC survey component.20 We used publicly available household component files (MEPS-HC) from year 2004 through 2007.20 In our study, we selected individuals from the prescription file based on their medication use. Cases with associated dementia diagnosis were subsequently identified based on the clinical classification code (CCCODEX; CCCODEX-653), a coding system developed by MEPS.20 The initial sample consisted of 339 subjects (unweighted) 65 years of age who were being prescribed at least 1 medication of interest, that is, AAPs, antidepressant, anticonvulsants, antidementia (cholinesterase inhibitors and memantine) agents, and/or benzodiazepines for dementia. We excluded 23 subjects who were taking typical antipsychotics and 24 subjects who did not have a matching diagnosis of dementia in the medical file.
Outcome Measures AAP medications were identified by the Multum-Lexicon categories as described in the MEPS database. Antipsychotic medication use was dichotomized as 1 for ‘‘YES’’ and 0 for ‘‘NO.’’ Psychotropic medications, such as anticonvulsants, antidepressants, benzodiazepines, and/or antidementia medications (cholinesterase inhibitors or memantine), were also identified by the Multum-Lexicon categories. Because the patient could use more than 1 such medication, separate variables for each additional psychotropic medication use were also created.20 Dependent variables developed for the study were antipsychotic medication use and nonantipsychotic psychotropic medication use. The main independent variable in the model was
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the warning period. The warning period was split into 2 phases: prewarning period (years 2004-2005) and postwarning period (years 2006-2007).
Study Covariates Other covariates included in the model were race (black/white), education (0-15/>15 years), marital status (single/married), prescription drug coverage (yes/no), gender (male/female), family income (low/low to poor/middle to high income), insurance status (uninsured/private/public), region (northeast/midwest/west/south), usual source of care (yes/no), and metropolitan statistical area (MSA; urban/rural).
Statistical Analysis 2
The analysis reported includes chi-square (w ) tests stratified by each class of medication to analyze differences in medication use between the pre- and the postwarning periods with respect to sociodemographic and other variables. Further, multivariate logistic regression models explain the effect of BBW on each medication class. The regression models controlled for demographic confounders such as race, gender, marital status, education, family income, region, insurance status, prescription drug coverage, usual source of care, and MSA. All statistical analyses were performed using statistical package SAS version 9.1 (SAS Institute Inc, North Carolina).21
Results Figure 1 represents the number of persons taking medications in the study, stratified by survey years. The overall medication use declined in 2005, indicating a possible impact of the BBW on AAP medication use. Table 1 summarizes the demographic characteristics of all persons 65 years and above with a diagnosis of dementia. A majority of the medication users were whites (76%), females (56%), single (51%), attained lower educational status (77%), residing in the south (36%), had a prescription drug coverage (53%), middle to high income group (51%), had a public insurance coverage (47%), and a usual source of care (87%).
Bivariate Analysis of Medication Use Table 2 shows that proportions of persons diagnosed with dementia who were using medications (antipsychotics, antidepressants, anticonvulsants, benzodiazepines, or antidementia agents) were higher in the postwarning (53.09%) period as compared to the prewarning period (46.91%). Although the overall medication use increased, the percentage of people using AAPs in the postwarning period actually (46.88%) declined in comparison to the prewarning period (53.12%). However, the decrease in use of AAPs was not statistically significant. The use of anticonvulsants (pre [39.41%] vs post [60.59%]), benzodiazepine (pre [35.69%] vs post [64.31%]), antidepressants (pre [44.19%] vs post [55.81%)]), and antidementia (pre [46.52%] vs post
Number of patients in thousands
Singh and Nayak
60 50 40
53.64
30 26.35
30.05
20 10 10.26
0 2004
2005
2006
2007
Year
Figure 1. Number of respondents being prescribed atypical antipsychotics associated with dementia—stratified by each year.
[53.48%]) agents increased in the postwarning period as compared to the prewarning period. However, this increase was not statistically significant.
Sociodemographic Characteristics Differences for a Typical Antipsychotic Use and Nonantipsychotic Psychotropic Use A w2 test revealed significant differences in the proportion of respondents receiving AAP medications in the postwarning period, with respect to race (w2 ¼ 4.17, P ¼ .0412) and availability of prescription drug coverage (w2 ¼ 21.63, P < .0001). Significant differences in the proportion of respondents receiving medications (nonantipsychotic psychotropic) in the postwarning period, with respect to the availability of prescription drug coverage (w2 ¼ 56.67, P < .0001) and usual source of care (w2 ¼ 4.96, P ¼ .0259) were also observed.
Logistic Regression for Change in Medication Use A multivariate logistic regression (Table 3) analysis revealed a significant year-effect, after controlling for confounders such as age, race, gender, education, marital status, insurance status, family income, region, usual source of care, and MSA. Although insignificant, the regression analysis revealed that the individuals diagnosed with dementia were almost 17% less likely to be prescribed an AAP in the postwarning period as compared to the prewarning period (odds ratio [OR] ¼ 0.835, confidence interval [CI] ¼ 0.369-1.891, P ¼ .6578). In the case of nonantipsychotic psychotropic alternatives such as cholinesterase inhibitors or memantine (approved for the treatment of dementia), the individuals diagnosed with dementia were almost twice as likely to be prescribed antidementia agents (cholinesterase inhibitor or memantine) in the postwarning period as compared to the prewarning period (OR ¼ 1.979, CI ¼ 1.126-3.643, P ¼ .0195). The use of other nonantipsychotic psychotropic alternatives such as benzodiazepines also increased significantly in the postwarning period as compared to the prewarning period. Respondents diagnosed with dementia were 3 times more likely to receive benzodiazepines in the postwarning period as compared to the prewarning period (OR ¼ 3.070, CI ¼ 1.188-7.935,
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Table 1. Weighted and Un-Weighted Baseline Characteristics of Respondents with Dementia 65 Years and Above (N ¼ 339). Dementia Characteristics Age, mean Race Whites Nonwhites Gender Male Female Educationb 0-15 years >15 years Married Married Single Rx coverage Rx coverage No Rx coverage MSAc Rural Urban Regiond Northeast Midwest South West Family income Poor Low to near poor Middle to high Insurance Uninsured Private Public Usual source of caree No usual source of care Usual source of care
Dementia
Medication Users (N ¼ 292)
Weighted (N ¼ 773 995)
Medication Nonusers (N ¼ 39)
Weighted (N ¼ 81 917)
292 225 67 292 106 186 275 246 29 292 121 171 292 127 165 271 57 214 271 49 41 132 49 292 52 92 148 292 2 126 164 269 10 259
79.97 + 5.84 773 995 (90.43%) 654 968 (76.53%) 119 027 (13.90%) 774 995 (90.43%) 294 576 (34.42%) 479 419 (56.01%) 719 658 (89.78%) 620 926 (77.46%) 98 732 (12.32%) 773 995 (90.43%) 334 706 (39.11%) 439 289 (51.32%) 773 995 (90.43%) 451 161 (52.71%) 322 834 (37.72%) 676 447 (90.43%) 118 068 (15.79%) 558 379 (74.68%) 676 447 (90.43%) 147 910 (19.78%) 109 387 (14.63%) 267 303 (35.75%) 151 847 (20.31%) 773 995 (90.43%) 93 160 (10.88%) 244 395 (28.55%) 436 440 (50.99%) 773 995 (90.43%) 2530 (0.30%) 372 030 (43.47%) 399 435 (46.67%) 673 500 (90.43%) 23 544 (3.16%) 649 956 (87.27%)
39 27 12 39 10 29 39 39 0 39 10 29 35 19 20 35 7 28 35 7 5 18 5 39 11 17 11 39 0 10 29 35 1 34
79.36 + 4.64 81 917 (9.57%) 59 480 (6.95%) 22 437 (2.62%) 81 917 (9.57%) 62 271 (7.28%) 19 646 (2.29%) 81 917 (10.22%) 81 917 (10.22%) 0 81 917 (9.57%) 24 989 (2.92%) 56 928 (6.65%) 81 917 (9.57%) 38 678 (5.05%) 43 239 (4.52%) 71 281 (9.57%) 9750 (1.30%) 61 576 (8.24%) 71 281 (9.57%) 20 920 (2.80%) 12 051 (1.61%) 28 445 (3.80%) 9865 (1.32%) 81 917 (9.57%) 10 473 (1.22%) 41 921 (4.90% 29 523 (3.45%) 81 917 (9.57%) 0 30 294 (3.54%) 51 623 (6.03%) 71 281 (9.57%) 1916 (0.26%) 69 365 (9.31%)
Totala 331
331
314
331
331
306
306
331
331
304
Abbreviation: MSA, metropolitan statistical area. a There were 8 cases with nonpositive weights that were excluded from the study. b There were 17 unweighted and 28 456 weighted missing cases for education. c There were 25 unweighted and 39 422 weighted missing cases for metropolitan statistical area. d There were 25 unweighted and 39 422 weighted missing cases for region. e There were 27 unweighted and 40 770 weighted missing cases for usual source of care.
Table 2. Bivariate Analysis for Change in Utilization of Each Medication Class Between the Prewarning and Postwarning Periods. Medication Atypical antipsychotic Antidepressants Anticonvulsants Benzodiazepines Antidementiab At least 1 medication
Prewarning Weighted 63 905 140 570 47 376 28 263 303 033 363 078
(53.12%) (44.19%) (39.41%) (35.69%) (46.52%) (46.91%)
Postwarning Weighted 56 177 72 50 348 410
Chi-Square Value
df
P Valuea
0.81 1.13 1.91 2.54 2.25 2.76
1 1 1 1 1 1
.3668 .2883 .1674 .1110 .1332 .0967
395 (46.88%) 504 (55.81%) 827 (60.59%) 937 (64.31%) 363 (53.48%) 918 (53.09%)
a
P < .05. Antidementia medications comprise of cholinesterase inhibitors and memantine.
b
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Table 3. Logistic Regression to Determine the Year Effect of Atypical Antipsychotic Black Box Warning on Medication Use in the Dementia Population After Controlling for Possible Confounders. Variable
Estimate
Atypical antipsychotics Prewarning period Postwarning 0.1851 period Antidementia Prewarning period Postwarning 0.6810 period Benzodiazepines Prewarning period Postwarning 1.1138 period Antidepressants Prewarning period Postwarning 0.3503 period Anticonvulsants Prewarning period Postwarning 0.4061 period
Standard Error
Odds Ratiob
P Value
Confidence Interval
.6578
0.366-1.885
.0195a
1.116-3.499
.0227a
1.169-7.939
.1619
0.869-2.319
.3260
0.667-3.375
1 0.4178
0.831
1 0.2916
1.976
1 0.4888
3.046
1 0.2504
1.419
1 0.4135
1.501
a
P < .05. Year effect estimated the odds ratio (OR) of service in prewarning (20042005) relative to postwarning (2006-2007) controlling for age, race, gender, marital status, education, family income, insurance status, geographical region, and metropolitan statistical area.
b
P ¼ .0227). An increase in the use of antidepressant medication was not significant in the postwarning period as compared to the prewarning period (OR ¼ 1.420, CI ¼ 0.887-2.274, P ¼ .1619). Similarly, an increase in the use of anticonvulsants was not significant in the postwarning period (OR ¼ 1.508, CI ¼ 0.683-3.332, P ¼ .3260) as compared to the prewarning period.
well as in noninstitutionalized elderly persons with dementia.22 A ‘‘predecline,’’ in the use of AAPs, might have lowered the utilization in the prewarning phase making it challenging to detect change. However, since 2007 was the most recent complete data available at the time this study was conducted, we needed to balance the postwarning period with the prewarning period. This predecline in use of AAPs might be associated to a series of events that occurred before the BBW was implemented. First, communication letters were published by the FDA, which might have sensitized the physicians against prescribing AAPs because of its association with cardiovascular events.4,23,24 Second, reports regarding the negative effects of off-label use of AAPs in elderly persons with dementia started garnering attention.25 Third, before the warnings went into effect, detailed guidelines were published by the Office of Inspector General, which prohibited the pharmaceutical companies from off-label marketing of drugs.26 Although, we highlight some of the most important events that might have led to this predecline, actual patient care is more dynamic and well out of the scope of our study. A few other events occurred that might have augmented the actual decline when the warning was in effect. In 2005, two major trials were conducted that questioned the efficacy and safety of AAPs in dementia population. The Clinical Antipsychotic Trial of Intervention Effectiveness (CATIE-AD), funded by the National Institute of Mental Health, reported that advantages of the treatment of AAPs were offset by the side effects of AAPs in elderly patients diagnosed with dementia.25 In addition, CATIE-AD trial further ratified the contention that AAPs lead to higher mortality in individuals suffering from dementia.27 Moreover, the Medicare part D went into effect in January 2006, which might have skewed the result in the postwarning period. Also, previously published literature states that nearly 50% to 80% of individuals diagnosed with dementia reside in nursing homes. However, the nursing home population is not represented in the MEPS database and we were not able to ascertain this possibility in our sample. Although there might be other factors that might have resulted in the observed result, it is highly unlikely to explain all the market characteristics.
Nonantipsychotic Psychotropic Drug Use Discussion AAP Use The primary objective of this study was to assess the impact of BBW on the utilization of AAPs and nonantipsychotic psychotropic alternatives like antidepressants, anticonvulsants, benzodiazepines, and antidementia agents. The bivariate and logistic regression analysis revealed that AAP utilization, although lower, was not significantly different between the prewarning and the postwarning periods. The results of the current study are similar to the previous studies that determined the impact of the antipsychotic BBW on the use of antipsychotic medications in institutionalized as
Antidementia medication (cholinesterase inhibitors and memantine) utilization was not significantly different between the prewarning and the postwarning periods. However, when a logistic regression model was used, respondents were more likely to take antidementia agents in the postwarning period as compared to the prewarning period.
Antidementia agents An increase in the likelihood of taking antidementia agents in the postwarning period could be due to rising safety concerns about the usage of AAPs in dementia population.27 Although some consensus guidelines still recommend usage of AAPs,
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new data have surfaced that supports the use of cholinesterase inhibitors and memantine in dementia population with comorbid behavioral disorders.28 Also in 2003, memantine was launched and highly promoted because of its effectiveness in the dementia population. However, it lacked strong evidence in the form of clinical trials or randomized control trials. Nevertheless, the promotion of this new drug in the market along with negative reports regarding AAPs might have resulted in a compensatory shift in the use of antidementia agents in patients diagnosed with dementia.
Benzodiazepines A bivariate analysis showed no significant increase in the use of benzodiazepines, however, when a logistic regression was performed, patients diagnosed with dementia were 200% more likely to take benzodiazepines in the postwarning period as compared to the prewarning period. This increase in use of benzodiazepines, in patients with dementia, could arise due to the need for managing neuropsychiatric symptoms of patients with dementia. According to published literature, nearly 60% to 90% of individuals with dementia suffer from neuropsychiatric disorders and symptoms.29,30 As a result, individuals with dementia often experience significant sleep/wake cycle disturbances called ‘‘sun downing’’ and the degree of disturbance parallels the severity of dementia.31 This altered circadian rhythm may not only trouble individuals with dementia but also can be a serious problem for caregivers, since persons’ sleep rhythm may not match the daily routine of the caregiver or the institution. This mismatch may culminate in the prescription of hypnotic medications such as benzodiazepines, since antidementia medications were ineffective and AAP medication use was being highly criticized. In such circumstances, the physician could consider benzodiazepines as a safe alternative because they show some protective effect on aging dementia population and can assure continued compliance. Chi-square tests and multivariate tests in anticonvulsants and antidepressants did not show any significant changes in the use of these medications between the pre- and postwarning periods. Several limitations should be noted for this study. The BBW period coincided with the implementation of Medicare Part D and could have skewed the medication utilization pattern in the postwarning period. Also, benzodiazepines were not covered by Medicare Part D during the period of the study, which might have led to the underestimation of benzodiazepine users in the study. The data used in the study were from
the MEPS, which is a secondary database. MEPS is a survey of noninstitutionalized population, so it leaves out patients from nursing homes, hospitals, and homeless population, who use antipsychotics more extensively and have a different pattern of use altogether. As MEPS is a self-reported database rather than physician reported, it may lack accuracy in terms of clinical diagnosis, insurance status, and medication use. Also because medication use is self-reported, recall and/or response biases may have occurred in reporting the use of medications. Other limitations of the study are its small sample size in atypical and benzodiazepine medication category. Small sample sizes may cause larger variations in standard errors and can result in lower statistical power. Also, the time frame for the pre- and postwarning period was just 2 years. However, this was the most recent complete data available when the study was being conducted. Similarly, small time frame only shows acute changes and makes it difficult to identify any gradual change in medication use. Also, the overlap between private insurance status and Medicare coverage cannot be accounted for. This might have led to the overestimation of the ‘‘Medicare sample.’’ Last but not the least, we could only utilize variables that were available in MEPS and therefore could not account for unmeasured confounders.
Conclusion In summary, the regulatory warnings and labeling changes regarding off-label use of AAPs in dementia treatment seem to have made little impact on their actual use in noninstitutionalized populations. However, a similar argument cannot be extended to institutionalized settings where the use of these drugs is more extensive and the effect of any labeling changes are likely to be more enduring because of tighter professional monitoring of their use. Further research is needed to observe the effect of labeling changes in nursing homes where treatment of dementia is more common. Also, changes in prescription patterns of antipsychotics over a long period could be evaluated to understand the long-term changes. With regard to spillover effects, there was a corresponding increase in the use of nonantipsychotic psychotropics. While the compensatory shift that occurred in this case may be clinically justified, it may also point toward a rising use of potentially unsafe and clinically untested and unproven therapeutic alternatives.
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Appendix A Table A1. List of Medications Included in Each Medication Class. Antidementia
Anticonvulsants
Benzodiazepines
Antidepressants
Antipsychotics
Cholinesterase inhibitors Reminyl Aricept Exelon Donepezil HCl Razadyne Aricept (film coated) Galantamine HBr Galantamine hydrobromide Razadyne (film coated) Razadyne ER Antidementia Memantine
Phenytoin sodium extended Clonazepam Depakote Lyrica Gabapentin Lorazepam Diazepam
Clonazepam Temazepam Alprazolam Xanax
Zoloft Mirtazapine Nortriptyline Wellbutrin xl Effexor-xr Effexor Amitriptyline Lexapro Paxil Prozac Mirtazapine (remeron) Trazodone Trazodone HCl Amitriptylin Citalopram Celexa Paroxetine Zoloft (unit-of-use) Sertraline hydrochloride (film coated) Remeron Fluoxetine HCl Effexor XR (unit-of-use) Sertraline Trazadone Sertraline HCl Citalopram hydrobromide (film coated)
Risperdal Seroquel Zyprexa Quetiapine fumarate Seroquel (film coated) Geodon Haloperidol Risperidone
Authors’ Note RS was involved in conceptualizing the study, analyzing the data, interpreting the results, and writing the manuscript. RN was also involved in conceptualization, in refining the idea, checking the accuracy of the interpretation of the results, guiding, proofreading, and critically evaluating the research and manuscript.
3.
4.
Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
5.
Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.
6.
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10. Straus SMJM, Sturkenboom MCJM, Bleumink GS, et al. Noncardiac QTc-prolonging drugs and the risk of sudden cardiac death. Eur Heart J. 2005;26(19):2007-2012. doi:10.1093/eurheartj/ ehi312. 11. Ray WA, Meador KG. Antipsychotics and sudden death: is thioridazine the only bad actor? Br J Psychiatry J Ment Sci. 2002;180: 483-484. 12. Warner J. Risk of choking in mental illness. Lancet. 2004; 363(9410):674. doi:10.1016/S0140-6736(04)15664-X. 13. Berzlanovich AM, Muhm M, Sim E, et al. Foreign body asphyxiation—an autopsy study. Am J Med. 1999;107(4):351-355. 14. Ruschena D, Mullen PE, Palmer S, et al. Choking deaths: the role of antipsychotic medication. Br J Psychiatry. 2003;183:446-450. 15. Liperoti R, Pedone C, Lapane KL, et al. Venous thromboembolism among elderly patients treated with atypical and conventional antipsychotic agents. Arch Intern Med. 2005;165(22): 2677-2682. doi:10.1001/archinte.165.22.2677. 16. Research Center for Drug Evaluation and Public Health Advisories (Drugs). Public Health Advisory: Deaths with Antipsychotics in Elderly Patients with Behavioral Disturbances. Web site. http://www.fda.gov/Drugs/DrugSafety/PostmarketDrugSafety InformationforPatientsandProviders/DrugSafetyInformationfor HeathcareProfessionals/PublicHealthAdvisories/ucm053171.htm. Accessed July 24, 2013. 17. Commissioner of the Safety Alerts for Human Medical Products. Antipsychotics, Conventional and Atypical. Web site. http://www. fda.gov/Safety/MedWatch/SafetyInformation/SafetyAlertsfor HumanMedicalProducts/ucm110212.htm. Accessed July 26, 2013. 18. Dorsey E, Rabbani A, Gallagher SA, et al. Impact of FDA black box advisory on antipsychotic medication use. Arch Intern Med. 2010;170(1):96-103. doi:10.1001/archinternmed.2009.456. 19. Kales HC, Zivin K, Kim HM, et al. Trends in antipsychotic use in dementia 1999-2007. Arch Gen Psychiatry. 2011;68(2):190-197. doi:10.1001/archgenpsychiatry.2010.200. 20. Medical Expenditure Panel Survey Home. Web site. http://meps. ahrq.gov/mepsweb/. Accessed July 26, 2013.
21. SAS|Business Analytics and Business Intelligence Software. Web site. http://www.sas.com/. Accessed July 24, 2013. 22. Valiyeva E, Herrmann N, Rochon PA, et al. Effect of regulatory warnings on antipsychotic prescription rates among elderly patients with dementia: a population-based time-series analysis. CMAJ. 2008;179(5):438-446. doi:10.1503/cmaj.071540. 23. Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol. 2005;58(4):323-337. doi:10.1016/j.jclinepi.2004.10.012. 24. Wang C-C, Farley JF. Patterns and predictors of antipsychotic medication use among the U.S. population: findings from the Medical Expenditure Panel Survey. Res Soc Adm Pharm. 2013; 9(3):263-275. doi:10.1016/j.sapharm.2009.07.001. 25. Jeste DV, Blazer D, Casey D, et al. ACNP White Paper: update on use of antipsychotic drugs in elderly persons with dementia. Neuropsychopharmacology. 2008;33(5):957-970. doi:10.1038/sj.npp. 1301492. 26. Greene S. False claims act liability for off-label promotion of pharmaceutical products. Penn State Law Rev. 2005;110:41. 27. Schneider LS, Tariot PN, Dagerman KS, et al. Effectiveness of atypical antipsychotic drugs in patients with Alzheimer’s disease. N Engl J Med. 2006;355(15):1525-1538. doi:10.1056/ NEJMoa061240. 28. Trinh N-H, Hoblyn J, Mohanty S, et al. Efficacy of cholinesterase inhibitors in the treatment of neuropsychiatric symptoms and functional impairment in Alzheimer disease: a meta-analysis. JAMA. 2003;289(2):210-216. 29. Lyketsos CG, Steinberg M, Tschanz JT, et al. Mental and behavioral disturbances in dementia: findings from the Cache County Study on Memory in Aging. Am J Psychiatry. 2000;157(5): 708-714. 30. Mega MS, Cummings JL, Fiorello T, et al. The spectrum of behavioral changes in Alzheimer’s disease. Neurology. 1996;46(1): 130-135. 31. Pollak CP, Perlick D, Linsner JP, et al. Sleep problems in the community elderly as predictors of death and nursing home placement. J Commun Health. 1990;15(2):123-135.
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Journal of Pharmacy Practice 1-8 ª The Author(s) 2015 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0897190015579451 jpp.sagepub.com
Rakesh R. Singh, MS1, and Rajesh Nayak, PhD2
Abstract Background: The study seeks to investigate the impact of Food and Drug Administration’s black box warning (BBW) on the use of atypical antipsychotics (AAP) and nonantipsychotic psychotropic alternatives in noninstitutionalized elderly population diagnosed with dementia. Method: The Medical Expenditure Panel Survey (2004 through 2007) was utilized as the data source. Medication use in elderly patients (65 years) was defined as taking at least 1 medication for dementia. We performed a statistical comparison of prewarning (2004-2005) and postwarning (2006-2007) periods with respect to AAP and nonantipsychotic psychotropic use to examine the impact of labeling changes. Results: A bivariate analysis did not yield statistically significant change in either the AAP or nonantipsychotic psychotropic use, pre- versus postwarning. However, multivariate logistic-regression analyses revealed greater odds for antidementia (odds ratio [OR] ¼ 1.976, P ¼ .0195) and benzodiazepine (OR ¼ 3.046, P ¼ .0227) medication use in postwarning period compared to the prewarning period. Conclusion: The regulatory warnings and labeling changes regarding offlabel use of AAPs in dementia treatment showed minimal impact on their actual use in noninstitutionalized populations. A corresponding increase in the use of nonantipsychotic psychotropics explains that BBW might have resulted in a compensatory shift in favor of benzodiazepines and antidementia medications. Additional research should be conducted to examine the longterm impact of BBW on antipsychotic prescribing changes. Keywords medication safety, neurology, pharmacy administration, drug information, social and administrative sciences
Background Antipsychotic medications were primarily approved for managing symptoms of schizophrenia and schizophrenia-related disorders. Utilization of antipsychotics (typical and atypical) has scaled steadily since its introduction in early 1970s, and atypical antipsychotics (AAPs) alone accounted for more than US$7 billion in annual expenditures in 2007.1 Besides the approved indications, antipsychotics are increasingly being prescribed off-label, in the elderly as well as children, for a range of mental health conditions.2 Previous reports suggested an increase in use of antipsychotics in the dementia population, particularly for managing behavioral and psychological disorders associated with the disease. Evidence from randomized clinical trials clearly suggests that the use of antipsychotics in the elderly dementia population is associated with fatal side effects.3 In a meta-analysis of community dwelling cohort, antipsychotic use was associated with statistically significant increase in mortality compared to the nonantipsychotic cohort.4 Although the exact mechanism of action is not known, few plausible causes have been outlined in the literature. AAPs affect
the cardiac system and increase the likelihood of arrhythmias and sudden cardiac death. Studies have also indicated association with aspiration pneumonia, venous thromboembolism, and cerebrovascular events.5-15 In response to rising safety concerns and mounting evidence against use of antipsychotic medications in dementia, the US Food and Drug Administration (FDA), in 2005, issued a black box warning (BBW) of excess mortality associated with the use of all 6 AAPs in dementia for persons aged 65 years and above.16 In June 2008, the US FDA extended the BBW to typical antipsychotics as well.17
1 Department of Health Outcomes and Pharmacy Practice, College of Pharmacy, The University of Texas at Austin, Austin, TX, USA 2 Department of Pharmacy Administration and Allied Health Sciences, College of Pharmacy and Health Sciences, St John’s University, Queens, NY, USA
Corresponding Author: Rakesh R. Singh, The University of Texas at Austin, 2409 University Ave., STOP A1930, Austin, TX, USA. Email: [email protected]
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Since the imposition of the BBW, numerous studies have investigated the impact of regulatory labeling changes on the utilization of antipsychotics in patients with dementia. A study by Dorsey et al evaluating the impact of the BBW among all individuals 18 years and older reported a 34% increase in the use of AAPs overall, and 16% among individuals with dementia.18 Another study by Kales et al that evaluated the impact of BBW on the use of AAPs in veterans 65 years and above who were diagnosed with dementia reported significant decline in the use of AAPs in the veteran population after the BBW was issued.19 However, both the studies are indicative of physicians practice rather than actual prescribing practice. The impact of the warning extended beyond the intended classes. Previous studies have also evaluated the impact of the BBW on the spillover or compensatory change in utilization of nonantipsychotic medications (antidepressants, anticonvulsants, and benzodiazepines) used in patients with dementia.18,19 In the absence of clinical evidence to support the use of AAPs in dementia, nonantipsychotics drugs might appear as the only viable alternative. To this end, the study by Dorsey et al provided some early evidence that spillover effects might have led to decreased prescribing of AAPs in younger population even though the BBW was clearly meant for the elderly population.18 Furthermore, a study by Kales et al, on a group of veterans 65 years and older diagnosed with dementia, also observed spillover effects, particularly in nonantipsychotic drug classes, providing further evidence that such effects could be a probable consequences of the regulations.19 Although previous studies focused on the impact of BBW on the use of AAPs in the physician reported surveys and/or veteran population prescribing, very few of them explored patient reported data from noninstitutionalized individuals 65 years of age and over and diagnosed with dementia.18,19 Exploring noninstitutionalized patients might be important because individuals suffering with dementia might get their first diagnosis from a primary care provider in an officebased setting. It is highly unlikely for a patient with dementia to be hospitalized during the initial phase of their illness. More importantly, patients being hospitalized might be at a more advance stage of their illness where antipsychotics might be the only treatment available given the lack of evidencebased trials for other nonantipsychotic medications. Furthermore, since AAPs are being prescribed off-label, they are less likely to be recorded in physicians surveys. Patient reported administrative data will provide a more wide ranging and accurate picture of the practice trends. The current study addressed this important research gap, as well as evaluated the utilization patterns and consequences of labeling changes for both AAP and nonantipsychotic use in the noninstitutionalized population.
Methods Data and Sample The Medical Expenditure Panel Survey (MEPS) is a complex national probability sample survey of the US civilian
noninstitutionalized population. MEPS database has 2 components for which the data are collected, that is, the Household Component (MEPS-HC) and the Insurance Component (MEPS-IC). MEPS-HC is a nationally representative data of households that includes demographic characteristics, health conditions, health status, use of medical services, charges and payments, access to care, satisfaction with care, health insurance coverage, income, and employment.20 The MEPS-HC is a sample of households subsampled from the previous year’s National Health Interview Survey. 20 Each new MEPS sample is referred to as a panel, and data for each panel are collected through 5 rounds of computer-assisted personal interviews spread over a 2.5-year period. 20 MEPS-IC is an annual survey of employers that collects data regarding the number and types of private health insurance plans offered, associated benefits, annual premiums, annual contribution by employees, eligibility requirements, and employer characteristics. MEPS-IC component comprises of MEPS-IC list sample and MEPS-IC household sample. MEPS-IC list component comprises of nationwide sample of state and local governments and other establishments. However, these data are not available for public use and can be accessed only through the census bureau’s research center. The MEPS-IC household component comprises of a sample of employers that were identified from the responses in the MEPS-HC survey component.20 We used publicly available household component files (MEPS-HC) from year 2004 through 2007.20 In our study, we selected individuals from the prescription file based on their medication use. Cases with associated dementia diagnosis were subsequently identified based on the clinical classification code (CCCODEX; CCCODEX-653), a coding system developed by MEPS.20 The initial sample consisted of 339 subjects (unweighted) 65 years of age who were being prescribed at least 1 medication of interest, that is, AAPs, antidepressant, anticonvulsants, antidementia (cholinesterase inhibitors and memantine) agents, and/or benzodiazepines for dementia. We excluded 23 subjects who were taking typical antipsychotics and 24 subjects who did not have a matching diagnosis of dementia in the medical file.
Outcome Measures AAP medications were identified by the Multum-Lexicon categories as described in the MEPS database. Antipsychotic medication use was dichotomized as 1 for ‘‘YES’’ and 0 for ‘‘NO.’’ Psychotropic medications, such as anticonvulsants, antidepressants, benzodiazepines, and/or antidementia medications (cholinesterase inhibitors or memantine), were also identified by the Multum-Lexicon categories. Because the patient could use more than 1 such medication, separate variables for each additional psychotropic medication use were also created.20 Dependent variables developed for the study were antipsychotic medication use and nonantipsychotic psychotropic medication use. The main independent variable in the model was
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the warning period. The warning period was split into 2 phases: prewarning period (years 2004-2005) and postwarning period (years 2006-2007).
Study Covariates Other covariates included in the model were race (black/white), education (0-15/>15 years), marital status (single/married), prescription drug coverage (yes/no), gender (male/female), family income (low/low to poor/middle to high income), insurance status (uninsured/private/public), region (northeast/midwest/west/south), usual source of care (yes/no), and metropolitan statistical area (MSA; urban/rural).
Statistical Analysis 2
The analysis reported includes chi-square (w ) tests stratified by each class of medication to analyze differences in medication use between the pre- and the postwarning periods with respect to sociodemographic and other variables. Further, multivariate logistic regression models explain the effect of BBW on each medication class. The regression models controlled for demographic confounders such as race, gender, marital status, education, family income, region, insurance status, prescription drug coverage, usual source of care, and MSA. All statistical analyses were performed using statistical package SAS version 9.1 (SAS Institute Inc, North Carolina).21
Results Figure 1 represents the number of persons taking medications in the study, stratified by survey years. The overall medication use declined in 2005, indicating a possible impact of the BBW on AAP medication use. Table 1 summarizes the demographic characteristics of all persons 65 years and above with a diagnosis of dementia. A majority of the medication users were whites (76%), females (56%), single (51%), attained lower educational status (77%), residing in the south (36%), had a prescription drug coverage (53%), middle to high income group (51%), had a public insurance coverage (47%), and a usual source of care (87%).
Bivariate Analysis of Medication Use Table 2 shows that proportions of persons diagnosed with dementia who were using medications (antipsychotics, antidepressants, anticonvulsants, benzodiazepines, or antidementia agents) were higher in the postwarning (53.09%) period as compared to the prewarning period (46.91%). Although the overall medication use increased, the percentage of people using AAPs in the postwarning period actually (46.88%) declined in comparison to the prewarning period (53.12%). However, the decrease in use of AAPs was not statistically significant. The use of anticonvulsants (pre [39.41%] vs post [60.59%]), benzodiazepine (pre [35.69%] vs post [64.31%]), antidepressants (pre [44.19%] vs post [55.81%)]), and antidementia (pre [46.52%] vs post
Number of patients in thousands
Singh and Nayak
60 50 40
53.64
30 26.35
30.05
20 10 10.26
0 2004
2005
2006
2007
Year
Figure 1. Number of respondents being prescribed atypical antipsychotics associated with dementia—stratified by each year.
[53.48%]) agents increased in the postwarning period as compared to the prewarning period. However, this increase was not statistically significant.
Sociodemographic Characteristics Differences for a Typical Antipsychotic Use and Nonantipsychotic Psychotropic Use A w2 test revealed significant differences in the proportion of respondents receiving AAP medications in the postwarning period, with respect to race (w2 ¼ 4.17, P ¼ .0412) and availability of prescription drug coverage (w2 ¼ 21.63, P < .0001). Significant differences in the proportion of respondents receiving medications (nonantipsychotic psychotropic) in the postwarning period, with respect to the availability of prescription drug coverage (w2 ¼ 56.67, P < .0001) and usual source of care (w2 ¼ 4.96, P ¼ .0259) were also observed.
Logistic Regression for Change in Medication Use A multivariate logistic regression (Table 3) analysis revealed a significant year-effect, after controlling for confounders such as age, race, gender, education, marital status, insurance status, family income, region, usual source of care, and MSA. Although insignificant, the regression analysis revealed that the individuals diagnosed with dementia were almost 17% less likely to be prescribed an AAP in the postwarning period as compared to the prewarning period (odds ratio [OR] ¼ 0.835, confidence interval [CI] ¼ 0.369-1.891, P ¼ .6578). In the case of nonantipsychotic psychotropic alternatives such as cholinesterase inhibitors or memantine (approved for the treatment of dementia), the individuals diagnosed with dementia were almost twice as likely to be prescribed antidementia agents (cholinesterase inhibitor or memantine) in the postwarning period as compared to the prewarning period (OR ¼ 1.979, CI ¼ 1.126-3.643, P ¼ .0195). The use of other nonantipsychotic psychotropic alternatives such as benzodiazepines also increased significantly in the postwarning period as compared to the prewarning period. Respondents diagnosed with dementia were 3 times more likely to receive benzodiazepines in the postwarning period as compared to the prewarning period (OR ¼ 3.070, CI ¼ 1.188-7.935,
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Table 1. Weighted and Un-Weighted Baseline Characteristics of Respondents with Dementia 65 Years and Above (N ¼ 339). Dementia Characteristics Age, mean Race Whites Nonwhites Gender Male Female Educationb 0-15 years >15 years Married Married Single Rx coverage Rx coverage No Rx coverage MSAc Rural Urban Regiond Northeast Midwest South West Family income Poor Low to near poor Middle to high Insurance Uninsured Private Public Usual source of caree No usual source of care Usual source of care
Dementia
Medication Users (N ¼ 292)
Weighted (N ¼ 773 995)
Medication Nonusers (N ¼ 39)
Weighted (N ¼ 81 917)
292 225 67 292 106 186 275 246 29 292 121 171 292 127 165 271 57 214 271 49 41 132 49 292 52 92 148 292 2 126 164 269 10 259
79.97 + 5.84 773 995 (90.43%) 654 968 (76.53%) 119 027 (13.90%) 774 995 (90.43%) 294 576 (34.42%) 479 419 (56.01%) 719 658 (89.78%) 620 926 (77.46%) 98 732 (12.32%) 773 995 (90.43%) 334 706 (39.11%) 439 289 (51.32%) 773 995 (90.43%) 451 161 (52.71%) 322 834 (37.72%) 676 447 (90.43%) 118 068 (15.79%) 558 379 (74.68%) 676 447 (90.43%) 147 910 (19.78%) 109 387 (14.63%) 267 303 (35.75%) 151 847 (20.31%) 773 995 (90.43%) 93 160 (10.88%) 244 395 (28.55%) 436 440 (50.99%) 773 995 (90.43%) 2530 (0.30%) 372 030 (43.47%) 399 435 (46.67%) 673 500 (90.43%) 23 544 (3.16%) 649 956 (87.27%)
39 27 12 39 10 29 39 39 0 39 10 29 35 19 20 35 7 28 35 7 5 18 5 39 11 17 11 39 0 10 29 35 1 34
79.36 + 4.64 81 917 (9.57%) 59 480 (6.95%) 22 437 (2.62%) 81 917 (9.57%) 62 271 (7.28%) 19 646 (2.29%) 81 917 (10.22%) 81 917 (10.22%) 0 81 917 (9.57%) 24 989 (2.92%) 56 928 (6.65%) 81 917 (9.57%) 38 678 (5.05%) 43 239 (4.52%) 71 281 (9.57%) 9750 (1.30%) 61 576 (8.24%) 71 281 (9.57%) 20 920 (2.80%) 12 051 (1.61%) 28 445 (3.80%) 9865 (1.32%) 81 917 (9.57%) 10 473 (1.22%) 41 921 (4.90% 29 523 (3.45%) 81 917 (9.57%) 0 30 294 (3.54%) 51 623 (6.03%) 71 281 (9.57%) 1916 (0.26%) 69 365 (9.31%)
Totala 331
331
314
331
331
306
306
331
331
304
Abbreviation: MSA, metropolitan statistical area. a There were 8 cases with nonpositive weights that were excluded from the study. b There were 17 unweighted and 28 456 weighted missing cases for education. c There were 25 unweighted and 39 422 weighted missing cases for metropolitan statistical area. d There were 25 unweighted and 39 422 weighted missing cases for region. e There were 27 unweighted and 40 770 weighted missing cases for usual source of care.
Table 2. Bivariate Analysis for Change in Utilization of Each Medication Class Between the Prewarning and Postwarning Periods. Medication Atypical antipsychotic Antidepressants Anticonvulsants Benzodiazepines Antidementiab At least 1 medication
Prewarning Weighted 63 905 140 570 47 376 28 263 303 033 363 078
(53.12%) (44.19%) (39.41%) (35.69%) (46.52%) (46.91%)
Postwarning Weighted 56 177 72 50 348 410
Chi-Square Value
df
P Valuea
0.81 1.13 1.91 2.54 2.25 2.76
1 1 1 1 1 1
.3668 .2883 .1674 .1110 .1332 .0967
395 (46.88%) 504 (55.81%) 827 (60.59%) 937 (64.31%) 363 (53.48%) 918 (53.09%)
a
P < .05. Antidementia medications comprise of cholinesterase inhibitors and memantine.
b
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Table 3. Logistic Regression to Determine the Year Effect of Atypical Antipsychotic Black Box Warning on Medication Use in the Dementia Population After Controlling for Possible Confounders. Variable
Estimate
Atypical antipsychotics Prewarning period Postwarning 0.1851 period Antidementia Prewarning period Postwarning 0.6810 period Benzodiazepines Prewarning period Postwarning 1.1138 period Antidepressants Prewarning period Postwarning 0.3503 period Anticonvulsants Prewarning period Postwarning 0.4061 period
Standard Error
Odds Ratiob
P Value
Confidence Interval
.6578
0.366-1.885
.0195a
1.116-3.499
.0227a
1.169-7.939
.1619
0.869-2.319
.3260
0.667-3.375
1 0.4178
0.831
1 0.2916
1.976
1 0.4888
3.046
1 0.2504
1.419
1 0.4135
1.501
a
P < .05. Year effect estimated the odds ratio (OR) of service in prewarning (20042005) relative to postwarning (2006-2007) controlling for age, race, gender, marital status, education, family income, insurance status, geographical region, and metropolitan statistical area.
b
P ¼ .0227). An increase in the use of antidepressant medication was not significant in the postwarning period as compared to the prewarning period (OR ¼ 1.420, CI ¼ 0.887-2.274, P ¼ .1619). Similarly, an increase in the use of anticonvulsants was not significant in the postwarning period (OR ¼ 1.508, CI ¼ 0.683-3.332, P ¼ .3260) as compared to the prewarning period.
well as in noninstitutionalized elderly persons with dementia.22 A ‘‘predecline,’’ in the use of AAPs, might have lowered the utilization in the prewarning phase making it challenging to detect change. However, since 2007 was the most recent complete data available at the time this study was conducted, we needed to balance the postwarning period with the prewarning period. This predecline in use of AAPs might be associated to a series of events that occurred before the BBW was implemented. First, communication letters were published by the FDA, which might have sensitized the physicians against prescribing AAPs because of its association with cardiovascular events.4,23,24 Second, reports regarding the negative effects of off-label use of AAPs in elderly persons with dementia started garnering attention.25 Third, before the warnings went into effect, detailed guidelines were published by the Office of Inspector General, which prohibited the pharmaceutical companies from off-label marketing of drugs.26 Although, we highlight some of the most important events that might have led to this predecline, actual patient care is more dynamic and well out of the scope of our study. A few other events occurred that might have augmented the actual decline when the warning was in effect. In 2005, two major trials were conducted that questioned the efficacy and safety of AAPs in dementia population. The Clinical Antipsychotic Trial of Intervention Effectiveness (CATIE-AD), funded by the National Institute of Mental Health, reported that advantages of the treatment of AAPs were offset by the side effects of AAPs in elderly patients diagnosed with dementia.25 In addition, CATIE-AD trial further ratified the contention that AAPs lead to higher mortality in individuals suffering from dementia.27 Moreover, the Medicare part D went into effect in January 2006, which might have skewed the result in the postwarning period. Also, previously published literature states that nearly 50% to 80% of individuals diagnosed with dementia reside in nursing homes. However, the nursing home population is not represented in the MEPS database and we were not able to ascertain this possibility in our sample. Although there might be other factors that might have resulted in the observed result, it is highly unlikely to explain all the market characteristics.
Nonantipsychotic Psychotropic Drug Use Discussion AAP Use The primary objective of this study was to assess the impact of BBW on the utilization of AAPs and nonantipsychotic psychotropic alternatives like antidepressants, anticonvulsants, benzodiazepines, and antidementia agents. The bivariate and logistic regression analysis revealed that AAP utilization, although lower, was not significantly different between the prewarning and the postwarning periods. The results of the current study are similar to the previous studies that determined the impact of the antipsychotic BBW on the use of antipsychotic medications in institutionalized as
Antidementia medication (cholinesterase inhibitors and memantine) utilization was not significantly different between the prewarning and the postwarning periods. However, when a logistic regression model was used, respondents were more likely to take antidementia agents in the postwarning period as compared to the prewarning period.
Antidementia agents An increase in the likelihood of taking antidementia agents in the postwarning period could be due to rising safety concerns about the usage of AAPs in dementia population.27 Although some consensus guidelines still recommend usage of AAPs,
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new data have surfaced that supports the use of cholinesterase inhibitors and memantine in dementia population with comorbid behavioral disorders.28 Also in 2003, memantine was launched and highly promoted because of its effectiveness in the dementia population. However, it lacked strong evidence in the form of clinical trials or randomized control trials. Nevertheless, the promotion of this new drug in the market along with negative reports regarding AAPs might have resulted in a compensatory shift in the use of antidementia agents in patients diagnosed with dementia.
Benzodiazepines A bivariate analysis showed no significant increase in the use of benzodiazepines, however, when a logistic regression was performed, patients diagnosed with dementia were 200% more likely to take benzodiazepines in the postwarning period as compared to the prewarning period. This increase in use of benzodiazepines, in patients with dementia, could arise due to the need for managing neuropsychiatric symptoms of patients with dementia. According to published literature, nearly 60% to 90% of individuals with dementia suffer from neuropsychiatric disorders and symptoms.29,30 As a result, individuals with dementia often experience significant sleep/wake cycle disturbances called ‘‘sun downing’’ and the degree of disturbance parallels the severity of dementia.31 This altered circadian rhythm may not only trouble individuals with dementia but also can be a serious problem for caregivers, since persons’ sleep rhythm may not match the daily routine of the caregiver or the institution. This mismatch may culminate in the prescription of hypnotic medications such as benzodiazepines, since antidementia medications were ineffective and AAP medication use was being highly criticized. In such circumstances, the physician could consider benzodiazepines as a safe alternative because they show some protective effect on aging dementia population and can assure continued compliance. Chi-square tests and multivariate tests in anticonvulsants and antidepressants did not show any significant changes in the use of these medications between the pre- and postwarning periods. Several limitations should be noted for this study. The BBW period coincided with the implementation of Medicare Part D and could have skewed the medication utilization pattern in the postwarning period. Also, benzodiazepines were not covered by Medicare Part D during the period of the study, which might have led to the underestimation of benzodiazepine users in the study. The data used in the study were from
the MEPS, which is a secondary database. MEPS is a survey of noninstitutionalized population, so it leaves out patients from nursing homes, hospitals, and homeless population, who use antipsychotics more extensively and have a different pattern of use altogether. As MEPS is a self-reported database rather than physician reported, it may lack accuracy in terms of clinical diagnosis, insurance status, and medication use. Also because medication use is self-reported, recall and/or response biases may have occurred in reporting the use of medications. Other limitations of the study are its small sample size in atypical and benzodiazepine medication category. Small sample sizes may cause larger variations in standard errors and can result in lower statistical power. Also, the time frame for the pre- and postwarning period was just 2 years. However, this was the most recent complete data available when the study was being conducted. Similarly, small time frame only shows acute changes and makes it difficult to identify any gradual change in medication use. Also, the overlap between private insurance status and Medicare coverage cannot be accounted for. This might have led to the overestimation of the ‘‘Medicare sample.’’ Last but not the least, we could only utilize variables that were available in MEPS and therefore could not account for unmeasured confounders.
Conclusion In summary, the regulatory warnings and labeling changes regarding off-label use of AAPs in dementia treatment seem to have made little impact on their actual use in noninstitutionalized populations. However, a similar argument cannot be extended to institutionalized settings where the use of these drugs is more extensive and the effect of any labeling changes are likely to be more enduring because of tighter professional monitoring of their use. Further research is needed to observe the effect of labeling changes in nursing homes where treatment of dementia is more common. Also, changes in prescription patterns of antipsychotics over a long period could be evaluated to understand the long-term changes. With regard to spillover effects, there was a corresponding increase in the use of nonantipsychotic psychotropics. While the compensatory shift that occurred in this case may be clinically justified, it may also point toward a rising use of potentially unsafe and clinically untested and unproven therapeutic alternatives.
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Appendix A Table A1. List of Medications Included in Each Medication Class. Antidementia
Anticonvulsants
Benzodiazepines
Antidepressants
Antipsychotics
Cholinesterase inhibitors Reminyl Aricept Exelon Donepezil HCl Razadyne Aricept (film coated) Galantamine HBr Galantamine hydrobromide Razadyne (film coated) Razadyne ER Antidementia Memantine
Phenytoin sodium extended Clonazepam Depakote Lyrica Gabapentin Lorazepam Diazepam
Clonazepam Temazepam Alprazolam Xanax
Zoloft Mirtazapine Nortriptyline Wellbutrin xl Effexor-xr Effexor Amitriptyline Lexapro Paxil Prozac Mirtazapine (remeron) Trazodone Trazodone HCl Amitriptylin Citalopram Celexa Paroxetine Zoloft (unit-of-use) Sertraline hydrochloride (film coated) Remeron Fluoxetine HCl Effexor XR (unit-of-use) Sertraline Trazadone Sertraline HCl Citalopram hydrobromide (film coated)
Risperdal Seroquel Zyprexa Quetiapine fumarate Seroquel (film coated) Geodon Haloperidol Risperidone
Authors’ Note RS was involved in conceptualizing the study, analyzing the data, interpreting the results, and writing the manuscript. RN was also involved in conceptualization, in refining the idea, checking the accuracy of the interpretation of the results, guiding, proofreading, and critically evaluating the research and manuscript.
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Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.
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