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Original Investigation |

Antipsychotics, Other Psychotropics, and the Risk of Death in Patients With Dementia Number Needed to Harm FREE

Donovan T. Maust, MD, MS1,2; Hyungjin Myra Kim, ScD2,3; Lisa S. Seyfried, MD, MS1; Claire Chiang, PhD1,2; Janet Kavanagh, MS1; Lon S. Schneider, MD, MS4; Helen C. Kales, MD1,2
[+] Author Affiliations
1Department of Psychiatry, University of Michigan, Ann Arbor
2Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
3Center for Statistical Consultation and Research, University of Michigan, Ann Arbor
4Department of Psychiatry, University of Southern California, Los Angeles
JAMA Psychiatry. 2015;72(5):438-445. doi:10.1001/jamapsychiatry.2014.3018.
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Published online

Importance  Antipsychotic medications are associated with increased mortality in older adults with dementia, yet their absolute effect on risk relative to no treatment or an alternative psychotropic is unclear.

Objective  To determine the absolute mortality risk increase and number needed to harm (NNH) (ie, number of patients who receive treatment that would be associated with 1 death) of antipsychotic, valproic acid and its derivatives, and antidepressant use in patients with dementia relative to either no treatment or antidepressant treatment.

Design, Setting, and Participants  A retrospective case-control study was conducted in the Veterans Health Administration from October 1, 1998, through September 30, 2009. Participants included 90 786 patients 65 years or older with a diagnosis of dementia. Final analyses were conducted in August 2014.

Exposures  A new prescription for an antipsychotic (haloperidol, olanzapine, quetiapine, and risperidone), valproic acid and its derivatives, or an antidepressant (46 008 medication users).

Main Outcomes and Measures  Absolute change in mortality risk and NNH over 180 days of follow-up in medication users compared with nonmedication users matched on several risk factors. Among patients in whom a treatment with medication was initiated, mortality risk associated with each agent was also compared using the antidepressant group as the reference, adjusting for age, sex, years with dementia, presence of delirium, and other clinical and demographic characteristics. Secondary analyses compared dose-adjusted absolute change in mortality risk for olanzapine, quetiapine, and risperidone.

Results  Compared with respective matched nonusers, individuals receiving haloperidol had an increased mortality risk of 3.8% (95% CI, 1.0%-6.6%; P < .01) with an NNH of 26 (95% CI, 15-99); followed by risperidone, 3.7% (95% CI, 2.2%-5.3%; P < .01) with an NNH of 27 (95% CI, 19-46); olanzapine, 2.5% (95% CI, 0.3%-4.7%; P = .02) with an NNH of 40 (95% CI, 21-312); and quetiapine, 2.0% (95% CI, 0.7%-3.3%; P < .01) with an NNH of 50 (95% CI, 30-150). Compared with antidepressant users, mortality risk ranged from 12.3% (95% CI, 8.6%-16.0%; P < .01) with an NNH of 8 (95% CI, 6-12) for haloperidol users to 3.2% (95% CI, 1.6%-4.9%; P < .01) with an NNH of 31 (95% CI, 21-62) for quetiapine users. As a group, the atypical antipsychotics (olanzapine, quetiapine, and risperidone) showed a dose-response increase in mortality risk, with 3.5% greater mortality (95% CI, 0.5%-6.5%; P = .02) in the high-dose subgroup relative to the low-dose group. When compared directly with quetiapine, dose-adjusted mortality risk was increased with both risperidone (1.7%; 95% CI, 0.6%-2.8%; P = .003) and olanzapine (1.5%; 95% CI, 0.02%-3.0%; P = .047).

Conclusions and Relevance  The absolute effect of antipsychotics on mortality in elderly patients with dementia may be higher than previously reported and increases with dose.

Individual clinical trials and meta-analyses have suggested modest benefit from some antipsychotic agents over placebo for the treatment of psychosis and aggression in patients with dementia13 and that these symptoms may return when a medication is discontinued.4 Potential harms anticipated with use of these medications include known adverse effects such as metabolic changes and extrapyramidal symptoms.1,5,6 However, evidence pooled across randomized, placebo-controlled trials (RCTs) of atypical antipsychotics, such as risperidone and olanzapine, demonstrated an increased risk of cerebrovascular adverse events for which the US Food and Drug Administration (FDA) issued a warning in 2003.7 Subsequent analyses of published and unpublished clinical trial data on atypical antipsychotics by the FDA and a meta-analysis of 15 RCTs by Schneider et al8 demonstrated an increased mortality risk. In April 2005, the FDA9 issued a black box warning that the use of atypical antipsychotics leads to increased all-cause mortality when used for behavioral disturbances in patients with dementia. Additional observational analyses10,11 have demonstrated that first-generation antipsychotic agents confer an even higher mortality risk than do the atypical agents, leading to another FDA12 black box warning in 2008. However, at the time the warnings were issued, the available evidence described class-wide effects on mortality without clear delineation of the risks associated with individual medications.

Using a large national registry of Veterans Affairs (VA) patients with dementia, Kales et al13 published the first analyses that provided estimates of the head-to-head mortality risk over 180 days, comparing individual antipsychotic agents and valproic acid and its derivatives (hereafter referred to as valproic acid), which are frequently used alternatives14 for behavioral disturbances in dementia. Subsequent analyses of elderly community-dwelling15 and nursing home16 patients have generally confirmed the initial findings that individual antipsychotic agents vary in their mortality risk, ranging from quetiapine (lowest) to haloperidol (highest).

The decision to use any intervention in medicine requires balancing potential benefits with potential harms, but it can be difficult for clinicians to interpret the clinical significance of absolute changes in risk or benefit. The number needed to harm (NNH) is a useful metric for clinicians to understand a treatment’s potential for harm, expressing the number of patients who have to receive treatment for a particular harmful outcome to occur with the intervention.17 The NNH is formally defined as the reciprocal of the change in absolute risk. Two sets of meta-analyses of atypical RCTs by Schneider et al1,8 provided key preliminary evidence for clinicians to help weigh the relative benefits and risks of using antipsychotics. First, this group demonstrated the increased mortality risk of atypical antipsychotics relative to placebo in patients with dementia,8 showing an absolute mortality risk increase of 1% over 8 to 12 weeks of treatment, or an NNH of 100 (1/.01). The authors suggested that this degree of risk may be similar to that of other types of medications used in frail, elderly patients, although subsequent work18 has demonstrated that the mortality risk associated with antipsychotic treatment is greater than that with other psychotropic medications. In a second set of analyses, Schneider et al1 examined the potential benefits of treatment with antipsychotics. Depending on the outcome measure and criterion for improvement, the number needed to treat ranged from 5 to 14, in contrast to the NNH of 100.

Over the past several years, investigators have consistently demonstrated both class- and agent-specific associations with increased mortality risk when these agents are used to treat dementia-related behavioral disturbances. However, when faced with the clinical decision of whether to prescribe a given medication for a given patient, physicians may have difficulty quantifying and comparing the risk. Here, we build on previous observational analyses of a cohort of patients with dementia newly treated with an antipsychotic (haloperidol, olanzapine, quetiapine, and risperidone) to estimate the increased absolute mortality risk and corresponding NNH during 180 days of follow-up relative to no treatment. Similar analyses are included for valproic acid and antidepressants since they are commonly used as alternatives to antipsychotics for aggression/agitation in dementia.14 Then, given the interest in antidepressant agents as more benign alternatives to antipsychotics19,20 and their increased use following the FDA warnings,14 we describe the mortality risk and NNH of antipsychotics and valproic acid relative to antidepressants. Finally, we provide estimates of the increased risk across atypical antipsychotics by agent and by dose.

Study Cohort

The data source and characteristics used here are similar to those previously published.13 In brief, deidentified data were provided by national VA registries maintained by the Serious Mental Illness Treatment Resource and Evaluation Center in Ann Arbor, Michigan, and the study was approved, with waiver of informed consent, by the VA Ann Arbor Healthcare System. Patients potentially included were aged 65 years or older and had a dementia diagnosis for at least 1 inpatient or outpatient encounter (International Classification of Diseases, Ninth Revision [ICD-9] codes 290.0, 290.1x, 290.2x, 290.3, 290.4x, 291.2, 294.10, 294.11, 331.0, 331.1, and 331.82) between October 1, 1998, and September 30, 2009. The cohort was then limited to patients who began outpatient treatment with a study medication following a period of at least 6 months without exposure to any antipsychotic, antidepressant, or anticonvulsant. Based on previous work demonstrating that 87% of VA patients with dementia received antipsychotic monotherapy,13 we limited this cohort to monotherapy. In the event that patients had more than 1 treatment episode during the 11-year study period, the first episode was used. The final treatment group included 46 008 medication users.

Medications

We included the antipsychotics haloperidol, olanzapine, risperidone, and quetiapine; the anticonvulsant valproic acid and its derivatives; and antidepressants, excluding tricyclic antidepressants or monoamine oxidase inhibitors. Patients taking valproic acid who had a diagnosis of a seizure disorder were excluded from the sample.

Outcomes

The primary study outcome was 180-day mortality, with mortality data obtained from the US National Death Index (National Center for Health Statistics).21 Secondary analyses compared dose-adjusted absolute change in mortality risk for olanzapine, quetiapine, and risperidone.

Clinical Characteristics

Variables included sex, age, race, marital status, active clinical diagnoses, and prescriptions for benzodiazepines and opioids during the 12 months before the index date when treatment began. Time since dementia diagnosis was used as a proxy for dementia severity. Because antipsychotics are frequently prescribed for treatment of delirium, and delirium itself is a risk factor for mortality, we used a coding scheme for acute confusional states developed for a previous study22 to capture the presence of delirium. This scheme included the following ICD-9 codes: 290.3, 291.0, 292.0, 292.1, 292.2, 292.9, 293.0, 293.1, 293.9, 294.8, 294.9, 348.3, 437.2, 572.2, 290.11, 290.41, 292.81, 293.31, 293.82, 293.83, 293.89, and 349.82. A Charlson Comorbidity Index score23 was calculated based on the presence of 18 medical comorbidities (excluding dementia) and then categorized as 0, 1, and greater than 1. We also included days in the hospital and in the nursing home during the 12 months before the index date, as well as urban vs rural location, academic affiliation, and size of the treating facility. The fiscal year of the prescription was also included as a variable to account for secular trends in the use of these medications.14,24

Study Design

Once the medication-user cohort was defined, to estimate the increased mortality risk difference and corresponding NNH relative to no treatment, we paired each medication user with a matching nonuser patient. First, we created a nonuser cohort of patients potentially eligible for matching: these individuals were aged 65 years or older, had a diagnosis of dementia (as described above), and had at least 6 months free of any antipsychotic, antidepressant, and anticonvulsant. For each medication-using patient, potential matching nonuser patients were first identified matching on the calendar year of the initial dementia diagnosis. Next, potential matching nonuser patients had a phantom fill date created that was the same number of days from the dementia diagnosis as for the corresponding medication-using patient. Using this phantom fill date, each medication-using patient was paired to an eligible nonuser patient selected randomly from the matching nonuser pool, and was matched further on additional patient characteristics at that time including age (±2.5 years), race, delirium diagnosis within the preceding 12 months, psychiatric hospitalization within the preceding 12 months, and 3-category Charlson Comorbidity Index score. Because medication users were limited to monotherapy, a potential nonuser was excluded if treatment with any antidepressant, antipsychotic, or anticonvulsant medication was started during the 180-day observation period.

Analytic Plan

The final study monotherapy cohort included 46 008 users; for the matched cohort, 45 393 of the monotherapy users were matched with nonusers. Descriptive statistics captured patient characteristics by medication prescribed (Table 1). A 180-day observation period was chosen based on previously published analyses.10,11,13 The outcome was death within the observation period following a new prescription (or phantom fill date for the nonuser cohort).

Table Graphic Jump LocationTable 1.  Characteristics of 46 008 Patientsa

Two primary analyses were done. First, we estimated the mortality risk difference for each medication relative to no treatment based on matched user and nonuser patients for each agent. We used a generalized linear model with logit link to fit a logistic regression model for the 180-day mortality risk associated with a given medication. We accounted for pairing between medication user and matched nonuser using a generalized estimating equation and adjusted for other clinical and demographic variables available in the administrative data (Table 2 footnote provides full list of covariates). Based on this model, we calculated the absolute difference in mortality risk and the corresponding NNH for patients in each medication group relative to each matched nonuser cohort. Next, to estimate the 180-day mortality risk difference and NNH for each medication compared with antidepressants, we used a logistic regression model with data from the full monotherapy cohort. Primary predictors in the model were dummy indicators for each study medication, with antidepressants as the referent medication group.

Table Graphic Jump LocationTable 2.  Crude Death Rates During a 180-Day Observation Period Among Patients With Dementia Starting Therapy With a New Medication

As a secondary analysis, we compared the mortality risk difference across the 3 atypical antipsychotics (olanzapine, quetiapine, and risperidone) controlling for medication dosage. Among these patients, 14.7% (n = 1929) had missing dosage data; thus, missing dosages were multiply imputed using a multivariate normal model that included all covariates and study medications as well as mortality. Imputation was done using SAS, version 9.3 (SAS Institute Inc). Given evidence suggesting that mortality is associated with medication dosage,15 we first grouped the 3 atypical antipsychotic users by haloperidol-equivalent dosage25 (low [<1.5 mg/d], medium [1.5 to <3.0 mg/d], and high [≥3.0 mg/d]) to calculate dose-based absolute mortality risk differences, using the low-dose group as the reference. Lastly, mortality risk differences were calculated for olanzapine and risperidone relative to quetiapine, adjusting for haloperidol-equivalent prescribed dose and clinical and demographic variables. The risk difference estimates were pooled across 5 multiply-imputed data sets with the Rubin method26 and were used to calculate the risk of death and NNH. As a sensitivity analysis, comparisons among the atypical antipsychotics by medication and by haloperidol-equivalent dosage were done only among medication users with valid dose information.

Table 1 presents the clinical and demographic characteristics of the study population stratified by medication group. Patients who were receiving haloperidol were significantly sicker than were those in the other medication groups, with a generally higher Charlson Comorbidity Index score, more days of hospitalization, and more nursing home days. This group was more likely to have received a delirium diagnosis within the prior 12 months and had the largest proportion also receiving benzodiazepines. The haloperidol group had a higher proportion of African American patients and a lower proportion of married patients than did the other medication groups. In addition, relative to the other groups, a larger proportion of patients receiving haloperidol were in facilities with fewer beds.

The valproic acid and antidepressant groups had the lowest proportions of African American patients, and the antidepressant group had the smallest proportion of patients who had received a benzodiazepine or a diagnosis of delirium within the prior 12 months. The antidepressant group had the highest proportion of patients with a comorbid diagnosis of depression, posttraumatic stress disorder, and other anxiety disorders; the valproic acid group included the highest proportion of patients with a comorbid bipolar disorder diagnosis. The olanzapine group had the smallest proportion of patients with a Charlson Comorbidity Index score greater than 1. Although the antidepressant group was second only to the haloperidol group for share of patients with Charlson Comorbidity Index score greater than 1, the antidepressant group had the largest proportions of patients with no hospital or nursing home days in the year before the index.

Table 2 presents the 180-day crude mortality for medication users and their matched nonuser counterparts. Haloperidol users had the highest mortality (20.7%) relative to nonusers, followed by risperidone (13.9%), olanzapine (13.9%), valproic acid (12.2%), quetiapine (11.8%), and antidepressants (8.3%). The crude mortality rates among matched nonusers ranged from 9.8% (matched nonusers for olanzapine) to 7.2% (matched nonusers for valproic acid).

The adjusted absolute mortality risk difference between medication users and matched nonusers is also presented in Table 2. The adjusted mortality risk was higher for haloperidol users relative to matched nonusers by 3.8% (95% CI, 1.0%-6.6%; P < .01). In terms of NNH, treatment with haloperidol was associated with 1 death for every 26 (1/.038; 95% CI, 15-99) patients who received treatment. Among the other antipsychotics, quetiapine had the lowest association with mortality relative to matched nonusers, with an adjusted risk difference of 2.0% (95% CI, 0.7%-3.3%; P < .01; NNH, 50; 95% CI, CI 30-150). The antidepressant group had only a slightly increased risk of death relative to matched nonusers; the risk difference for valproic acid and its derivatives was not significantly different from 0, providing no clear evidence for increased mortality. Including rurality and facility size as covariates did not impact the results.

Table 3 presents the adjusted mortality risk directly comparing the study psychotropic medications, using antidepressants as the reference group. Relative to other psychotropic monotherapy agents, haloperidol was associated with the greatest mortality risk, with an absolute risk of 12.3% higher (95% CI, 8.6%-16.0%; P < .01) than antidepressants, yielding an NNH of 8 (95% CI, 6-12) compared with antidepressant treatment. Quetiapine use had the lowest effect on mortality, with a 3.2% (95% CI, 1.6%-4.9%; P < .01) higher mortality risk relative to antidepressants (NNH, 31; 95% CI, 21-62).

Table Graphic Jump LocationTable 3.  Adjusted Mortality Risk Differences in Death Rates During the 180-Day Observation Period Between Medication Users and Antidepressant Usersa
Secondary Analyses

Dosage information for olanzapine, quetiapine, and risperidone is presented in Table 4. Compared with the low-dose haloperidol-equivalent group, mortality for the medium-dose group was nonsignificantly higher (1.3%; 95% CI, −0.1% to 2.7%; P = .07), but the high-dose group had significantly increased mortality (3.5%; 95% CI, 0.5% to 6.5%; P = .02; NNH, 29; 95% CI, 15-200). Controlling for dose, the 3 second-generation antipsychotics differed in mortality risk when compared directly. Relative to quetiapine, olanzapine increased the risk by 1.5% (95% CI, 0.02% to 3.0%; P = .047; NNH, 67; 95% CI, 33 to 5000) and risperidone increased the risk by 1.7% (0.6% to 2.8%, P = .003; NNH, 59; 95% CI, 36 to 167). Sensitivity analyses evaluating only medication users with valid dose information also demonstrated increased mortality risk among the high-dose group and the risperidone group. However, the increased risk associated with olanzapine relative to quetiapine was no longer statistically significant.

Table Graphic Jump LocationTable 4.  Initially Prescribed Mean Daily Dose and Haloperidol-Equivalent Dosage Groups of Atypical Antipsychotic Medications

Building on previous work in this large national sample of outpatients with dementia, we examined the mortality risk associated with newly prescribed antipsychotics, valproic acid, and antidepressants. Compared with the matched cohort of medication nonusers, the mortality risk associated with haloperidol was the highest overall among the study medications, and risperidone was the highest among the atypical antipsychotics. Antidepressant use was associated with a small, but statistically significant, increase in mortality. This finding is of note in light of the recent RCT20 suggesting that citalopram significantly reduced agitation but may also carry adverse cognitive and cardiac effects. Our findings suggest that, during a 180-day period, starting haloperidol therapy for a patient with dementia may be associated with 1 additional death for every 26 patients receiving treatment. For the atypical antipsychotics, the NNH ranged from 27 to 50 relative to the NNH in matched nonusers. When directly comparing other medication users with patients receiving antidepressants, haloperidol had the largest associated mortality risk and quetiapine had the least risk. Comparing the atypical antipsychotics directly and controlling for dose, both risperidone and olanzapine increased mortality relative to quetiapine, although the increased risk with olanzapine was no longer significant in the sensitivity analysis limited to nonimputed data. Lastly, the analyses suggested a dose-response relationship between atypical antipsychotics and risk of mortality.

The increased risk of mortality is higher than that previously reported, although prior estimates were from RCTs, which are less subject to confounding by indication. In 2005, Schneider et al8 originally reported an NNH for death of 100 for the second-generation agents from clinical trials of 10 to 12 weeks. A more recent Agency for Healthcare Research and Quality Comparative Effectiveness Review found a slightly lower NNH for a mortality of 87 for patients with dementia.27 The results of the present study confirm previous findings that have demonstrated that haloperidol has the highest associated mortality risk, followed by atypical antipsychotics and valproic acid.10,13,15,16,18 Even quetiapine, which was consistently found to be less harmful than other antipsychotics, had an increased mortality risk of 2.0% (95% CI, 0.7-3.3; P < .01) relative to matched nonusers, yielding an NNH of 50 (95% CI, 30-150). Although quetiapine appears to have the least association with mortality, it also has less evidence of benefit than olanzapine or risperidone.1,3

Our findings suggest that the mortality risk for the least harmful antipsychotic studied (quetiapine) is double that of the initial estimate of Schneider et al8; for risperidone the mortality risk is nearly 4-fold higher. In addition, our secondary analyses demonstrated a mortality dose response, suggesting that a strategy using a high dose rather than a low dose (eg, risperidone, 3.0 mg rather than 0.5 mg) may be associated with additional mortality. Although the prior estimates were based on RCTs completed during 6 to 12 weeks,3,8 the longer period of analysis in the present study is likely a more accurate reflection of how these medications are used in the community and therefore may more fully capture the association with mortality.

The primary limitations of this study stem from the use of an administrative, claims-based database lacking information on dementia severity and behavioral or psychiatric symptoms. Although the analyses were adjusted for a wide range of clinical characteristics, the clinical complexity of these patients, who were not randomly assigned to treatment, may not have been captured. Some analyses2830 have found an association between certain neuropsychiatric symptoms and mortality, so it is conceivable that a portion of the increased mortality risk seen in medication users relative to nonusers or among the medication users could be related to the symptom or behavior that prompted the prescription. In addition, our analyses were limited to episodes of medication monotherapy during the first treatment episode, which potentially limits the generalizability.

The balance of benefit to risk of antipsychotic treatment in dementia continues to shift, as our findings suggest that use of these medications may be associated with increased mortality of a greater magnitude than previously described. The present analyses provide critical information that can help physicians minimize potential harms at multiple decision points. If an antipsychotic or alternative psychotropic is prescribed, how much may this increase the patient’s risk of mortality? If a second-generation antipsychotic is prescribed, which agent is most associated with increased mortality? Is dose of an antipsychotic associated with mortality? The decision to use these medications is generally in response to profoundly distressing and potentially dangerous behaviors of patients. Prescribing a medication that increases mortality risk seems contrary to the tenet “first, do no harm,” yet for patients who pose a danger to themselves and others and are in profound distress, use of such medications may still be appropriate.31,32 These new data can help physicians minimize the potential harm associated with antipsychotic treatment.

Submitted for Publication: April 7, 2014; final revision received August 25, 2014; accepted November 8, 2014.

Corresponding Author: Donovan T. Maust, MD, MS, Department of Psychiatry, University of Michigan, North Campus Research Complex, 2800 Plymouth Rd, Bldg 16, Room 217W, Ann Arbor, MI 48109 (maustd@umich.edu).

Published Online: March 18, 2015. doi:10.1001/jamapsychiatry.2014.3018.

Author Contributions: Dr Kales had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Kim, Seyfried, Schneider, Kales.

Acquisition, analysis, or interpretation of data: Maust, Kim, Chiang, Kavanagh, Kales.

Drafting of the manuscript: Maust, Kales.

Critical revision of the manuscript for important intellectual content: Maust, Kim, Seyfried, Chiang, Kavanagh, Schneider, Kales.

Statistical analysis: Kim, Chiang.

Obtained funding: Kim, Kavanagh, Kales.

Administrative, technical, or material support: Seyfried, Kavanagh, Kales.

Study supervision: Schneider, Kales.

Conflict of Interest Disclosures: Dr Schneider has received grants from the National Institute on Aging, the State of California, the Alzheimer’s Association, and grants or research support from Johnson & Johnson, Eli Lilly, Novartis, and Pfizer. He has served as a consultant for and received consulting fees from Abbott Laboratories, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Forest Laboratories, GlaxoSmithKline, Johnson & Johnson, Lundbeck, Merck, Novartis, Pfizer, Takeda, and the State of California Department of Justice. Dr Kim has received grants from the National Institute of Mental Health, National Institute of Nursing Research, and the Department of Veterans Affairs. In addition to the funding noted above, Dr Kales reports receipt of grants from the National Institute of Nursing Research and the Department of Veterans Affairs. No other disclosures are reported.

Funding/Support: This work was supported by National Institute of Mental Health grant R01MH08107-01 and the Beeson Career Development Award Program (K08AG048321; funded through the National Institute on Aging, the American Federation for Aging Research, The John A. Hartford Foundation, and The Atlantic Philanthropies; Dr Maust, principal investigator).

Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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Kales  HC, Kamholz  BA, Visnic  SG, Blow  FC.  Recorded delirium in a national sample of elderly inpatients: potential implications for recognition. J Geriatr Psychiatry Neurol. 2003;16(1):32-38.
PubMed   |  Link to Article
Charlson  ME, Pompei  P, Ales  KL, MacKenzie  CR.  A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383.
PubMed   |  Link to Article
Olfson  M, Blanco  C, Liu  SM, Wang  S, Correll  CU.  National trends in the office-based treatment of children, adolescents, and adults with antipsychotics. Arch Gen Psychiatry. 2012;69(12):1247-1256.
PubMed   |  Link to Article
Andreasen  NC, Pressler  M, Nopoulos  P, Miller  D, Ho  B-C.  Antipsychotic dose equivalents and dose-years: a standardized method for comparing exposure to different drugs. Biol Psychiatry. 2010;67(3):255-262.
PubMed   |  Link to Article
Rubin  DB, Schenker  N.  Multiple imputation in health-care databases: an overview and some applications. Stat Med. 1991;10(4):585-598.
PubMed   |  Link to Article
Maglione  M, Maher  AR, Hu  J,  et al. Off-Label Use of Atypical Antipsychotics: An Update. Rockville, MD: Agency for Healthcare Research & Quality; 2011.
Okura  T, Plassman  BL, Steffens  DC, Llewellyn  DJ, Potter  GG, Langa  KM.  Neuropsychiatric symptoms and the risk of institutionalization and death: the aging, demographics, and memory study. J Am Geriatr Soc. 2011;59(3):473-481.
PubMed   |  Link to Article
Lopez  OL, Becker  JT, Chang  Y-F,  et al.  The long-term effects of conventional and atypical antipsychotics in patients with probable Alzheimer’s disease. Am J Psychiatry. 2013;170(9):1051-1058.
PubMed   |  Link to Article
Tun  S-M, Murman  DL, Long  HL, Colenda  CC, von Eye  A.  Predictive validity of neuropsychiatric subgroups on nursing home placement and survival in patients with Alzheimer disease. Am J Geriatr Psychiatry. 2007;15(4):314-327.
PubMed   |  Link to Article
Rabins  PV, Lyketsos  CG.  Antipsychotic drugs in dementia: what should be made of the risks? JAMA. 2005;294(15):1963-1965.
PubMed   |  Link to Article
Treloar  A, Crugel  M, Prasanna  A,  et al.  Ethical dilemmas: should antipsychotics ever be prescribed for people with dementia? Br J Psychiatry. 2010;197(2):88-90.
PubMed   |  Link to Article

Figures

Tables

Table Graphic Jump LocationTable 1.  Characteristics of 46 008 Patientsa
Table Graphic Jump LocationTable 2.  Crude Death Rates During a 180-Day Observation Period Among Patients With Dementia Starting Therapy With a New Medication
Table Graphic Jump LocationTable 3.  Adjusted Mortality Risk Differences in Death Rates During the 180-Day Observation Period Between Medication Users and Antidepressant Usersa
Table Graphic Jump LocationTable 4.  Initially Prescribed Mean Daily Dose and Haloperidol-Equivalent Dosage Groups of Atypical Antipsychotic Medications

References

Schneider  LS, Dagerman  K, Insel  PS.  Efficacy and adverse effects of atypical antipsychotics for dementia: meta-analysis of randomized, placebo-controlled trials. Am J Geriatr Psychiatry. 2006;14(3):191-210.
PubMed   |  Link to Article
Sultzer  DL, Davis  SM, Tariot  PN,  et al; CATIE-AD Study Group.  Clinical symptom responses to atypical antipsychotic medications in Alzheimer’s disease: phase 1 outcomes from the CATIE-AD effectiveness trial. Am J Psychiatry. 2008;165(7):844-854.
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Maher  AR, Maglione  M, Bagley  S,  et al.  Efficacy and comparative effectiveness of atypical antipsychotic medications for off-label uses in adults: a systematic review and meta-analysis. JAMA. 2011;306(12):1359-1369.
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Devanand  DP, Mintzer  J, Schultz  SK,  et al.  Relapse risk after discontinuation of risperidone in Alzheimer’s disease. N Engl J Med. 2012;367(16):1497-1507.
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Schneider  LS, Tariot  PN, Dagerman  KS,  et al; CATIE-AD Study Group.  Effectiveness of atypical antipsychotic drugs in patients with Alzheimer’s disease. N Engl J Med. 2006;355(15):1525-1538.
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Jeste  DV.  Tardive dyskinesia rates with atypical antipsychotics in older adults. J Clin Psychiatry. 2004;65(suppl 9):21-24.
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US Food and Drug Administration. Risperdal (risperidone) dear healthcare professional letter Apr 2003.http://www.fda.gov/safety/medwatch/safetyinformation/safetyalertsforhumanmedicalproducts/ucm168933.htm. Published April 16, 2003. Accessed February 2, 2014.
Schneider  LS, Dagerman  KS, Insel  P.  Risk of death with atypical antipsychotic drug treatment for dementia: meta-analysis of randomized placebo-controlled trials. JAMA. 2005;294(15):1934-1943.
PubMed   |  Link to Article
US Food and Drug Administration. Public health advisory: deaths with antipsychotics in elderly patients with behavioral disturbances. US Department of Health and Human Services. http://www.fda.gov/Drugs/DrugSafety/ucm053171.htm. Accessed February 2, 2014.
Wang  PS, Schneeweiss  S, Avorn  J,  et al.  Risk of death in elderly users of conventional vs. atypical antipsychotic medications. N Engl J Med. 2005;353(22):2335-2341.
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Schneeweiss  S, Setoguchi  S, Brookhart  A, Dormuth  C, Wang  PS.  Risk of death associated with the use of conventional versus atypical antipsychotic drugs among elderly patients. CMAJ. 2007;176(5):627-632.
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US Food and Drug Administration. Information for healthcare professionals: information on conventional antipsychotics. US Department of Health and Human Services. http://www.fda.gov/Drugs/DrugSafety/ucm124830.htm. Accessed February 2, 2014
Kales  HC, Kim  HM, Zivin  K,  et al.  Risk of mortality among individual antipsychotics in patients with dementia. Am J Psychiatry. 2012;169(1):71-79.
PubMed   |  Link to Article
Kales  HC, Zivin  K, Kim  HM,  et al.  Trends in antipsychotic use in dementia 1999-2007. Arch Gen Psychiatry. 2011;68(2):190-197.
PubMed   |  Link to Article
Gerhard  T, Huybrechts  K, Olfson  M,  et al.  Comparative mortality risks of antipsychotic medications in community-dwelling older adults. Br J Psychiatry. 2014;205(1):44-51.
PubMed   |  Link to Article
Huybrechts  KF, Gerhard  T, Crystal  S,  et al.  Differential risk of death in older residents in nursing homes prescribed specific antipsychotic drugs: population based cohort study. BMJ. 2012;344:e977.
PubMed   |  Link to Article
Cook  RJ, Sackett  DL.  The number needed to treat: a clinically useful measure of treatment effect. BMJ. 1995;310(6977):452-454.
PubMed   |  Link to Article
Kales  HC, Valenstein  M, Kim  HM,  et al.  Mortality risk in patients with dementia treated with antipsychotics versus other psychiatric medications. Am J Psychiatry. 2007;164(10):1568-1576.
PubMed   |  Link to Article
Sink  KM, Holden  KF, Yaffe  K.  Pharmacological treatment of neuropsychiatric symptoms of dementia: a review of the evidence. JAMA. 2005;293(5):596-608.
PubMed   |  Link to Article
Porsteinsson  AP, Drye  LT, Pollock  BG,  et al; CitAD Research Group.  Effect of citalopram on agitation in Alzheimer disease: the CitAD randomized clinical trial. JAMA. 2014;311(7):682-691.
PubMed   |  Link to Article
Fillenbaum  GG, Burchett  BM, Blazer  DG.  Identifying a National Death Index match. Am J Epidemiol. 2009;170(4):515-518.
PubMed   |  Link to Article
Kales  HC, Kamholz  BA, Visnic  SG, Blow  FC.  Recorded delirium in a national sample of elderly inpatients: potential implications for recognition. J Geriatr Psychiatry Neurol. 2003;16(1):32-38.
PubMed   |  Link to Article
Charlson  ME, Pompei  P, Ales  KL, MacKenzie  CR.  A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383.
PubMed   |  Link to Article
Olfson  M, Blanco  C, Liu  SM, Wang  S, Correll  CU.  National trends in the office-based treatment of children, adolescents, and adults with antipsychotics. Arch Gen Psychiatry. 2012;69(12):1247-1256.
PubMed   |  Link to Article
Andreasen  NC, Pressler  M, Nopoulos  P, Miller  D, Ho  B-C.  Antipsychotic dose equivalents and dose-years: a standardized method for comparing exposure to different drugs. Biol Psychiatry. 2010;67(3):255-262.
PubMed   |  Link to Article
Rubin  DB, Schenker  N.  Multiple imputation in health-care databases: an overview and some applications. Stat Med. 1991;10(4):585-598.
PubMed   |  Link to Article
Maglione  M, Maher  AR, Hu  J,  et al. Off-Label Use of Atypical Antipsychotics: An Update. Rockville, MD: Agency for Healthcare Research & Quality; 2011.
Okura  T, Plassman  BL, Steffens  DC, Llewellyn  DJ, Potter  GG, Langa  KM.  Neuropsychiatric symptoms and the risk of institutionalization and death: the aging, demographics, and memory study. J Am Geriatr Soc. 2011;59(3):473-481.
PubMed   |  Link to Article
Lopez  OL, Becker  JT, Chang  Y-F,  et al.  The long-term effects of conventional and atypical antipsychotics in patients with probable Alzheimer’s disease. Am J Psychiatry. 2013;170(9):1051-1058.
PubMed   |  Link to Article
Tun  S-M, Murman  DL, Long  HL, Colenda  CC, von Eye  A.  Predictive validity of neuropsychiatric subgroups on nursing home placement and survival in patients with Alzheimer disease. Am J Geriatr Psychiatry. 2007;15(4):314-327.
PubMed   |  Link to Article
Rabins  PV, Lyketsos  CG.  Antipsychotic drugs in dementia: what should be made of the risks? JAMA. 2005;294(15):1963-1965.
PubMed   |  Link to Article
Treloar  A, Crugel  M, Prasanna  A,  et al.  Ethical dilemmas: should antipsychotics ever be prescribed for people with dementia? Br J Psychiatry. 2010;197(2):88-90.
PubMed   |  Link to Article

Correspondence

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Submit a Comment
Population clinical characteristics are critical.
Posted on April 1, 2015
Scott Mendelson
VA
Conflict of Interest: None
It is stated by the authors that \"it is conceivable that a portion of the increased mortality risk seen in medication users relative to nonusers or among the medication users could be related to the symptom or behavior that prompted the prescription.\" In my mind this is not a trivial concern, but a confound that completely voids the significance of the data. To draw the conclusion that antipsychotics, valproate and antidepressants are themselves increasing mortality, then the authors needed to have more clearly determined that the non-users with whom they are comparing drug-treated groups are of the same population as those treated. They didn't; and I don't believe they can--as they are very likely not.
Many Questions Remain Related to Antipsychotics and Dementia
Posted on April 14, 2015
Virginia Dato MD MPH
Department of Biomedical Informatics, University of Pittsburgh, School of Medicine
Conflict of Interest: I am funded by NLM Pittsburgh Biomedical Informatics Training Grant 5T15 LM007059-28

I read the article “Antipsychotics, Other Psychotropics, and the Risk of Death in Patients With Dementia: Number Needed to Harm” [1] having reviewed literature in response to a black box warning for an antipsychotic prescribed for a beloved family member.This publication provides important data on over 45,000 individuals with dementia who were placed on anti-psychotics. Unfortunately, the types of dementia are not differentiated and no information is available on symptoms, quality of life or non-palliative treatments. A number needed to harm (with harm defined as death) of 50 would not be acceptable for treatment of a non-fatal self-resolving illness. However, dementia is often a fatal progressive illness with a very poor quality of life at advanced stages [2,3]. Number needed to treat is necessary to determine a likelihood to be helped or harmed4. A number needed to harm of 26 but with a substantial improvement in quality of life would have a higher likelihood of helping than a number needed to harm of 50 with little or no improvement. This paper speaks of “do no harm”; however in the late stages of dementia harm may be unavoidable. Although non-pharmacologic options are available, there is no “one size fits all solution” [5]. Let us not forget the Golden Rule “do unto others as you would have them do unto you.” As a society, we must be careful not to take options away from patients, caregivers and clinicians until better ones for their specific situation are available. This dataset is an excellent start to improving life for the individuals with this difficult diagnosis. Perhaps human/natural language technologies [6,7] can be used to help answer the many questions that remain.

1. Maust DT, Kim H, Seyfried LS, et al. Antipsychotics, other psychotropics, and the risk of death in patients with dementia: Number needed to harm. JAMA Psychiatry. 2015.

2. Passmore MJ. Neuropsychiatric Symptoms of Dementia: Consent, Quality of Life, and Dignity. BioMed Research International. 2013;2013:4.

3. Mitchell SL, Teno JM, Kiely DK, et al. The Clinical Course of Advanced Dementia. New England Journal of Medicine. 2009;361(16):1529-1538.

4. Citrome L, Ketter TA. When does a difference make a difference? Interpretation of number needed to treat, number needed to harm, and likelihood to be helped or harmed. International Journal of Clinical Practice. 2013;67(5):407-411.

5. Kales HC, Gitlin LN, Lyketsos CG. Assessment and management of behavioral and psychological symptoms of dementia. Vol 3502015.

6. Suominen H. Text mining and information analysis of health documents. Artificial Intelligence in Medicine. 2014;61(3):127-130.

7. Hazlehurst BL, Lawrence JM, Donahoo WT, et al. Automating assessment of lifestyle counseling in electronic health records. Am J Prev Med. 2014;46(5):457-464.

Response to Dr Dato
Posted on April 27, 2015
Donovan Maust, Lon Schneider, Helen Kales
University of Michigan, University of Southern California
Conflict of Interest: This work was supported by NIMH grant R01MH08107-01 and the Beeson Career Development Award Program (NIA K08AG048321, the American Federation for Aging Research, The John A. Hartford Foundation, and The Atlantic Philanthropies).In addition to the funding noted above, Dr. Kales reports receipt of grants from NINR and the Department of Veterans Affairs. Dr. Schneider has received grants from the NIA, the State of California, the Alzheimer’s Association, and grants or research support from Johnson & Johnson, Eli Lilly, Novartis and Pfizer. He has served as a consultant for and received consulting fees from Abbott Laboratories, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Forest Laboratories, GlaxoSmithKline, Johnson & Johnson, Lundbeck, Merck, Novartis, Pfizer, Takeda, and the State of California Department of Justice. Dr. Kim has received grants from NIMH, NINR, and the Department of Veterans Affairs. The other authors have no disclosures to note.

We agree with Dr. Dato that there is no “one size fits all solution” for either pharmacological or non-pharmacological treatment. We agree as well that antipsychotics should not be taken away as a treatment option. Their use, however, should be targeted and in conjunction with an understanding of risk and benefit (see Kales et al. [1]). The number needed to treat (NNT) is important to consider and, as we note in the paper, 5 to 14 patients need to be treated in order for one to show benefit [2], The benefits, however, are modest at best (i.e., one or two points on a scale), as demonstrated in the small effect sizes seen across a substantial number of randomized clinical trials. When one weighs the NNT with an estimate of the NNH (using death as the harm), we can assess the likelihood of help versus harm (i.e., LHH = (1/NNT)/(1/NNH)). Using Dr. Dato’s comment that antipsychotics show a NNH = 50 (i.e., number needed to harm for quetiapine, which had the lowest mortality risk in our analysis), we find that for every 4 to 10 patients who benefit from antipsychotics, one will die as a result of treatment. To us, this seems a high price to pay for modest benefit when other options are available. Weighing the potential benefits of treatment (e.g.: What is the symptom being treated? What is the degree of associated distress and/or dangerousness?) with potential harms should be done on a case-by-case basis. We are sure Dr. Dato would agree, however, that a physician’s duty to not cause harm is not to be taken lightly. We feel that discussions between providers, patients, and caregivers should be informed by the most accurate evidence available and hope that our work can help inform these discussions.

[1] Kales HC, Gitlin LN, Lyketsos CG. Assessment and management of behavioral and psychological symptoms of dementia. BMJ. Apr 02 2015;350(mar02 7):h369-h369.

[2] Schneider LS, Dagerman K, Insel PS. Efficacy and adverse effects of atypical antipsychotics for dementia: meta-analysis of randomized, placebo-controlled trials. Am J Geriatr Psychiatry. 2006;14(3):191–210.

Response to Dr Mendelson
Posted on April 27, 2015
Donovan Maust, Lon Schneider, Helen Kales
University of Michigan, University of Southern California
Conflict of Interest: This work was supported by NIMH grant R01MH08107-01 and the Beeson Career Development Award Program (NIA K08AG048321, the American Federation for Aging Research, The John A. Hartford Foundation, and The Atlantic Philanthropies).In addition to the funding noted above, Dr. Kales reports receipt of grants from NINR and the Department of Veterans Affairs. Dr. Schneider has received grants from the NIA, the State of California, the Alzheimer’s Association, and grants or research support from Johnson & Johnson, Eli Lilly, Novartis and Pfizer. He has served as a consultant for and received consulting fees from Abbott Laboratories, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Forest Laboratories, GlaxoSmithKline, Johnson & Johnson, Lundbeck, Merck, Novartis, Pfizer, Takeda, and the State of California Department of Justice. Dr. Kim has received grants from NIMH, NINR, and the Department of Veterans Affairs. The other authors have no disclosures to note.

Dr. Mendelson raises an important point about the comparability of our patient groups that we addressed through a variety of methods. First, we matched pairs on specific criteria and excluded from analysis any medication users for whom we could not find a match. Second, our mortality models included a range of patient-level clinical information (>30 variables listed in Tables 2 and 3) to account for the potential influence of these characteristics on mortality. Perhaps what Dr. Mendelson is suggesting, however, is that we do not have information about the burden of neuropsychiatric symptoms in the patient population—in this way, the users and non-users are most likely not the same. The association of specific neuropsychiatric symptoms themselves with mortality is important to consider. However, the studies that have demonstrated an association between symptoms and mortality have not controlled for the use of psychotropic medication [1,2]. This is critical, as the symptoms that are associated with mortality (depression, psychosis, agitation) are those that are also most likely to be associated with medication use. The studies that suggest an association of neuropsychiatric symptoms with mortality have done so over more than 5 years of follow-up, which is a very different timeframe than we examined for medication-associated mortality. A prior study by Kales et al. found that the greatest mortality risk associated with antipsychotics occurred within the first four months after a new start [3]. While our study is subject to the limitations of observational analyses, our findings build in a consistent manner upon prior analyses of both randomized trial and observational data. It was pooled analyses of randomized, placebo-controlled trials of atypical antipsychotics—where medication users and non-users are from the same population—that first demonstrated increased mortality with atypical antipsychotics [4]. Subsequent observational analyses, using a variety methods to limit potential confounding, as did ours, have consistently demonstrated that conventional antipsychotics are associated with higher mortality than the atypical antipsychotics [5,6]. Third, prior analyses comparing medications head-to-head that included valproic acid found a mortality increase comparable to the atypical antipsychotics [5], as we also found. In clinical practice, medications used to treat the neuropsychiatric symptoms of dementia are frequently used in a manner and time-frame that has not been studied in clinical trials. Careful analysis of observational data such as ours is the best option to inform clinical practice. 

[1] Okura T, Plassman BL, Steffens DC, Llewellyn DJ, Potter GG, Langa KM. Neuropsychiatric symptoms and the risk of institutionalization and death: the aging, demographics, and memory study. J Am Geriatr Soc. 2011;59(3):473–481.

[2] Peters ME, Schwartz S, Han D, et al. Neuropsychiatric Symptoms as Predictors of Progression to Severe Alzheimer’s Dementia and Death: The Cache County Dementia Progression Study. Am J Psychiatr. 2015. Epub ahead of print. doi:10.1176/appi.ajp.2014.14040480.

[3] Kales HC, Kim HM, Zivin K, et al. Risk of mortality among individual antipsychotics in patients with dementia. Am J Psychiatr. Feb 2012;169(1):71-79.

[4] Schneider LS, Dagerman KS, Insel P. Risk of death with atypical antipsychotic drug treatment for dementia: meta-analysis of randomized placebo-controlled trials. JAMA 2005;294(15):1934–1943. 

[5] Kales HC, Kim HM, Zivin K, et al. Risk of mortality among individual antipsychotics in patients with dementia. Am J Psychiatr. 2012;169(1):71–79.

[6] Huybrechts KF, Gerhard T, Crystal S, et al. Differential risk of death in older residents in nursing homes prescribed specific antipsychotic drugs: population based cohort study. MJj. 2012;344:e977.

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