This study compared the risk of hospitalization among adults with schizophrenia being treated with equivalent dose ranges of lurasidone versus aripiprazole, olanzapine, quetiapine, or risperidone. Administrative claims data for this analysis came from the IBM MarketScan Commercial, Medicare Supplemental, and Multi-State Medicaid databases between January 2011 and June 2017. The study included adults with schizophrenia who initiated treatment with an antipsychotic and were continuously enrolled for 360 days prior to and following the date of the initial antipsychotic prescription. Risk of all-cause and schizophrenia-related hospitalization among patients who received lurasidone monotherapy versus aripiprazole, olanzapine, quetiapine, or risperidone in equivalent dose ranges were assessed. Marginal structural models that accounted for preindex characteristics, changes in antipsychotic treatment, and time-varying covariates assessed differences between lurasidone and other second-generation antipsychotics on all-cause and schizophrenia-related hospitalizations. A sensitivity analysis was conducted without the dose-equivalence requirement. A total of 20,212 patients met the study inclusion criteria. Compared with those treated with lurasidone monotherapy, the adjusted risk of all-cause hospitalization was significantly higher among patients treated with olanzapine (adjusted rate ratio [aRR], 1.49;
This study compared the risk of hospitalization among adults with schizophrenia being treated with equivalent dose ranges of lurasidone versus aripiprazole, olanzapine, quetiapine, or risperidone. Administrative claims data for this analysis came from the IBM MarketScan Commercial, Medicare Supplemental, and Multi-State Medicaid databases between January 2011 and June 2017. The study included adults with schizophrenia who initiated treatment with an antipsychotic and were continuously enrolled for 360 days prior to and following the date of the initial antipsychotic prescription. Risk of all-cause and schizophrenia-related hospitalization among patients who received lurasidone monotherapy versus aripiprazole, olanzapine, quetiapine, or risperidone in equivalent dose ranges were assessed. Marginal structural models that accounted for preindex characteristics, changes in antipsychotic treatment, and time-varying covariates assessed differences between lurasidone and other second-generation antipsychotics on all-cause and schizophrenia-related hospitalizations. A sensitivity analysis was conducted without the dose-equivalence requirement. A total of 20,212 patients met the study inclusion criteria. Compared with those treated with lurasidone monotherapy, the adjusted risk of all-cause hospitalization was significantly higher among patients treated with olanzapine (adjusted rate ratio [aRR], 1.49; P = .04), quetiapine (aRR, 1.64; P = .01), or risperidone (aRR, 1.47; P = .04), but not aripiprazole (aRR, 1.24; P = .28). A similar, non-statistically significant pattern of adjusted risks of schizophrenia-related hospitalizations was observed. A sensitivity analysis without the dose-equivalence requirement produced consistent results. As hospitalization is a major cost driver of direct healthcare cost, lurasidone may be a cost-saving treatment option for patients with schizophrenia.
Am J Manag Care. 2019;25:-S0
Schizophrenia is a debilitating, chronic mental illness that affects approximately 0.3% to 1.0% of the US population.1,2 Symptoms can be divided into “positive,” such as delusions and hallucinations, and “negative,” such as lack of emotion and social withdrawal.1 Because of the severity of the symptoms, most individuals with schizophrenia are unable to engage in paid employment, maintain marriage/partner relationships, or live independently.3
In the United States, the economic burden of schizophrenia in 2013 was estimated at $155.7 billion, including $37.7 billion in direct healthcare costs.4 Inpatient costs were the largest driver of direct healthcare costs, accounting for $15.2 billion (40.3%) of the direct costs.4 Different types of healthcare expenditures have different clinical implications in schizophrenia.5 Inpatient and emergency department (ED) use may reflect symptomatic relapses, while higher rates of outpatient visits and greater use of antipsychotic medications may reflect greater engagement in treatment.5 Increased adherence with antipsychotics has been linked with reduced inpatient costs6,7 and improved long-term functioning.8
Antipsychotics are the primary treatment for acute schizophrenia9,10 and are recommended in the stable phase because they substantially reduce the risk of relapse.10 Second-generation antipsychotics (SGAs) are preferred over first-generation antipsychotics (FGAs) for acute schizophrenia because of a reduced risk of developing extrapyramidal symptoms.9 Meta-analyses summarizing the results of randomized controlled trials of patients who are taking antipsychotics have reported substantial variations in extrapyramidal symptoms, prolactin elevation, sedation, and weight gain.11,12 The metabolic burden associated with commonly used SGAs has been classified as substantial for olanzapine and clozapine, intermediate for quetiapine and risperidone, and neutral to low for aripiprazole, lurasidone, and ziprasidone.13 A patient’s past experience with antipsychotics, particularly tolerability issues, should be considered before prescribing a particular treatment.9 Study results have shown that patients prefer efficacious antipsychotics with less risk of weight gain and hyperglycemia.14
Comparative Effectiveness Study Challenges
Patient preferences, adherence, real-world dosing, and other factors can affect the efficacy of treatment in usual clinical care and potentially limit the generalizability of clinical trial results to real-world effectiveness.
When designing comparative effectiveness studies using real-world data, the Agency for Healthcare Research and Quality (AHRQ) recommends, “When appropriate and possible, comparisons should be made for exposure and comparison groups at various clinically equivalent dose levels.”15 Studying medication effects across different dosage strengths is an important consideration when designing head-to-head clinical trials16-18; however, it is often ignored in studies using real-world data where treatment effects are studied without considering the consequences of dosage strength. Comparisons between medications used at different doses could make a lower-dosed medication appear more tolerable and a higher-dosed medication appear more efficacious. In addition, comparisons among different dose levels could result in confounding by severity, as higher doses are more likely to be given to patients with greater disease severity.15
An additional challenge for comparative effectiveness research in schizophrenia is the high frequency of antipsychotic treatment switching. As such, an intent-to-treat (ITT) analysis of antipsychotic treatment in real-world clinical practice is often inappropriate. Many comparative effectiveness studies using administrative claims have used an ITT approach,19-23 in which patients are classified according to their first prescribed antipsychotic, and outcomes are observed regardless of whether patients discontinue or switch to a different antipsychotic treatment. However, in clinical trials using ITT, adherence to the treatment protocol is closely monitored and data are no longer collected from a patient if treatment is discontinued.
To address these challenges in real-world studies, some investigators have used treatment episodes, rather than patients, as the unit of analysis.24-26 Recent studies have gone a step further and used marginal structural models (MSMs),27-29 which account for treatment switching, incorporate time-varying covariates, and appear to more accurately estimate causal treatment effects.30 Marginal structural modeling is a multistep analytic procedure which uses weighted repeated measures and takes into consideration time-varying treatment effects. To accomplish this, weights are calculated and assigned to each observation to balance background characteristics across treatment groups. Consistent estimates of treatment effects can be generated.31
The objective of this study was to compare the risk of hospitalization among patients with schizophrenia treated with equivalent doses of lurasidone versus aripiprazole, olanzapine, quetiapine, or risperidone using an MSM that accounted for changes in treatment and covariates over time.
Study Design and Database
This retrospective database study used administrative claims data from the IBM MarketScan Commercial Claims and Encounters Database, MarketScan Medicare Supplemental and Coordination of Benefits Database, and Multi-State Medicaid Database.32 The databases contained adjudicated inpatient, outpatient, and pharmacy claims data that were deidentified per the Health Insurance Portability and Accountability Act of 1996.32,33 For this study, all the administrative claims were dated between January 1, 2011, and June 30, 2017.
Patient Inclusion/Exclusion Criteria
All patients were required to have at least 1 diagnosis of schizophrenia (International Classification of Disease, 9th Revision, Clinical Modification [ICD-9-CM]: 295.x; or ICD-10-CM: F20.x; for both, x can be any value). Patients were also required to initiate an oral SGA (lurasidone, aripiprazole, asenapine, brexpiprazole, cariprazine, clozapine, iloperidone, paliperidone, olanzapine, quetiapine, risperidone, or ziprasidone) or an oral FGA (chlorpromazine, fluphenazine, haloperidol, loxapine, prochlorperazine, perphenazine, pimozide, thioridazine, thiothixene, or trifluoperazine) following their first diagnosis for schizophrenia. Patients were required to be at least 18 years of age on the index date, defined as the date of the first antipsychotic prescription. Continuous enrollment in a health plan with medical and pharmacy benefits was required for 360 days before (preindex period) and after (postindex period) the index date. Finally, patients could not have been treated with any antipsychotics during the preindex period.
This study compared hospitalization rates among patients treated with monotherapy lurasidone versus aripiprazole, olanzapine, quetiapine, or risperidone. These 5 SGAs were the focus because they were the most commonly used, accounting for more than 75% of all antipsychotic monotherapy use in our dataset. The daily dose associated with each antipsychotic claim was estimated by multiplying the dose strength (in milligrams) with the quantity of tablets or capsules supplied, then dividing by the estimated number of days the quantity should last (days supplied). In the primary analysis, dosing was restricted to a maximum daily dose equivalent to 80 mg of lurasidone.34 The dose of each medication equivalent to 80 mg of lurasidone was determined using published estimates of doses equivalent to 100 mg of chlorpromazine.34 The rationale for using lurasidone 80 mg per day as a threshold of dose equivalence was based on its inclusion in the initially approved dose range for schizophrenia and as the most common dose used in real-world settings. Lurasidone was initially approved in 2010 with a recommended dose range of 40 mg to 80 mg in adult patients with schizophrenia; this dose was updated to 40 mg to 160 mg in 2013.35 In clinical practice, the majority of adult patients with schizophrenia are treated with 40 mg to 80 mg of lurasidone.26,36 The median daily dose is reported for each antipsychotic with and without this dose-equivalence requirement in Table 1.
The 360-day postindex period was divided into twelve 30-day intervals (“months”), such that each patient contributed 12 patient-months to our dataset. Monotherapy was defined as treatment for at least 75% of days (≥22 days) with a single antipsychotic during a 30-day interval. The comparison groups included monotherapy lurasidone, aripiprazole, olanzapine, quetiapine, or risperidone, at a dose equivalent to 80 mg per day or less of lurasidone. Patient-months that did not meet these criteria were classified as “other.” The “other” group was included because the statistical model (described below) required all patient-months to be classified and could include combination therapy, monotherapy with FGAs or SGAs other than those listed above, monotherapy with equivalent doses above 80 mg per day of lurasidone, and no antipsychotic treatment.
A sensitivity analysis that did not involve dose-equivalence comparison was conducted. In this analysis, lurasidone, aripiprazole, olanzapine, quetiapine, and risperidone monotherapy patient-months were classified as such, regardless of the daily dose. Patient-months classified as “other” in this analysis included the same treatments as in the primary analysis, with the exception of monotherapy doses above 80 mg per day of lurasidone.
All-cause hospitalizations were identified using any hospital claim, regardless of associated diagnostic codes. Schizophrenia-related hospitalizations were those in which the hospital claim contained a diagnosis of schizophrenia (ICD-9-CM: 295.x or ICD-10-CM: F20.x) in any position. Rates of all-cause and schizophrenia-related hospitalization associated with lurasidone monotherapy patient-months were compared with rates of all-cause and schizophrenia-related hospitalization associated with aripiprazole, olanzapine, quetiapine, and risperidone monotherapy patient-months.
Patient preindex characteristics were calculated across the 360-day preindex period. These included age, gender, insurance type (Medicaid or commercial/Medicare Supplemental), and Charlson Comorbidity Index (CCI) score37; the proportions of patients who had at least 1 claim with a diagnosis of substance/alcohol/nicotine use, anxiety disorder, depression, bipolar disorder, diabetes, hypertension, or obesity (Appendix 1); the proportions of patients with at least 1 prescription for an antidepressant, anxiolytic, or mood stabilizer (lithium, divalproex, lamotrigine, carbamazepine, oxcarbazepine, and topiramate); and numbers of all-cause hospitalizations, schizophrenia-related hospitalizations, and all-cause ED visits.
MSMs were used to examine the effects of antipsychotic treatment on hospitalization. MSMs can estimate causal treatment effects when treatment and other covariates change over the course of follow-up.30 This is accomplished by weighting the data with the probability of receiving each of the various treatments in each time period (using stabilized inverse probability weights). Time-dependent confounding variables can be controlled when outcomes of interest are modeled.38
Stabilized inverse probability weights were calculated for each patient-month in the postindex period.39 A multinomial logistic regression model was used to predict assignment to each treatment category using preindex (time-independent) as well as postindex (time-dependent) covariates. The time-independent covariates consisted of an indicator of whether the patient was above or below the mean age at index; gender; preindex CCI score; and diagnosis of substance/alcohol/nicotine use, anxiety disorder, bipolar disorder, depression, diabetes, hypertension, and obesity. The time-dependent covariates included treatment in the prior month, any hospitalization in the prior month, and any ED visit during the prior month.
Because there was no preindex antipsychotic treatment, stabilized inverse probability weights could not be calculated for month 1. Therefore, outcomes were modeled over month 2 through month 12, although treatment and resource utilization in month 1 were used to predict treatment category and outcomes in subsequent months. Counts of inpatient admissions during month 2 through month 12 were modeled using generalized estimating equations (GEEs) with an exchangeable correlation matrix, negative binomial distribution, and log link function. Covariates in these GEE models included the treatment category for the current patient-month and all the previously mentioned time-independent variables. All GEE models were weighted using the stabilized inverse probability weights. All statistical analyses were completed using SAS version 9.4 (SAS Institute; Cary, NC) with a prespecified 2-tailed alpha of P <.05.
A total of 20,212 patients with schizophrenia who initiated antipsychotic therapy met all inclusion criteria (Appendix 2). Of these, 10,644 patients received initial monotherapy with lurasidone (2.7%), aripiprazole (8.2%), olanzapine (9.4%), quetiapine (12.7%), or risperidone (19.7%) at a dose equivalent to 80 mg or less per day of lurasidone. Over the postindex period, daily doses were low and mostly below the dose-equivalence threshold. Daily doses were similar before and after dose-equivalence restriction (Table 1).
The average age of the patients in the sample was 41.3 years, and 50.8% were female. Nearly half of the patients had a history of substance, alcohol, or nicotine use (46.9%) or depression (42.5%). Comorbidities such as diabetes (16.6%), hypertension (36.7%), and obesity (13.8%) were common. Most patients had Medicaid insurance (67.0%). Relative to patients initiating the other SGAs, patients initiating lurasidone were younger, more likely to be female, and more likely to have a history of depression, obesity, and treatment with antidepressants, anxiolytics, and mood stabilizers (Table 2). In the preindex period, the rate of all-cause hospitalizations was approximately 0.06 per patient-month (ie, 6 hospitalizations per 100 patient-months).
The numbers of patients classified into each treatment group over follow-up are presented in Table 3. Use of each index monotherapy declined over time, with the greatest drop occurring between month 1 and month 2. The percentage of patients treated with each antipsychotic at month 12 relative to month 1 was descriptively highest for lurasidone (36.0% [194/539]), followed by aripiprazole (35.9%), olanzapine (33.5%), quetiapine (28.9%), and risperidone (24.5%).
Rate of Hospitalization Over Follow-Up Period
The unadjusted rate of all-cause hospitalization per 100 patient-months associated with lurasidone (3.42 [91 hospitalizations/2659 patient-months]) was lower than that of olanzapine (5.04 [493/9788]; P = .002), quetiapine (6.24 [750/12,015]; P <.001), and risperidone (4.63 [798/17,233]; P = .01), but was not different from that of aripiprazole (3.26 [308/9436]; P = .71) (Figure 1). After adjustment for preindex and time-dependent characteristics, the predicted rate of all-cause hospitalization associated with lurasidone was 2.78 per 100 patient-months, which was lower than that of olanzapine (4.15; P = .04), quetiapine (4.55; P = .01), risperidone (4.09; P = .04), and aripiprazole (3.44; P = .28) (Figure 1). Adjusted rates of schizophrenia-related hospitalizations displayed a similar relationship.
Relative Rate of Hospitalization
Compared with lurasidone, the MSM-adjusted relative rates of all-cause hospitalization associated with olanzapine (adjusted rate ratio [aRR], 1.49; P = .04), quetiapine (aRR, 1.64; P = .01), and risperidone (aRR, 1.47; P = .04) were significantly higher (Figure 2). Adjusted relative rates of schizophrenia-related hospitalizations were consistent with these estimates. Several preindex characteristics were significant predictors of hospitalizations. Male patients were 13% more likely to be hospitalized than female patients. History of anxiety, bipolar disorder, and depression was associated with 65%, 37%, and 48% increases in all-cause hospitalizations, respectively. History of substance, alcohol, or nicotine use was associated with a 61% increased risk of hospitalization, and hypertension was associated with an 18% increased risk (Figure 2).
Results of the sensitivity analysis without dose-equivalence restriction, presented in Appendix 3, consistently supported the findings of the primary analysis. After MSM adjustment, lurasidone monotherapy was associated with the lowest rate of all-cause hospitalizations. Differences in the rates of all-cause hospitalization reached statistical significance when lurasidone was compared against olanzapine, quetiapine, and risperidone, but not aripiprazole.
In this observational claims database study of patients with schizophrenia treated with equivalent doses of SGAs, lurasidone was associated with significantly fewer all-cause hospitalizations than were olanzapine, quetiapine, and risperidone. Lurasidone was also associated with a numerically lower rate of schizophrenia-related hospitalizations than other SGAs. We note that schizophrenia-related hospitalizations were less common than all-cause hospitalizations, resulting in lower statistical power.
The results from this study are consistent with those of 2 previous studies that compared hospitalization rates between lurasidone and other SGAs in patients with schizophrenia in real-world settings. The first study, conducted by an academic research group, used an ITT approach, did not control for dose, and used aripiprazole as the reference treatment.23 Relative to initiating treatment with aripiprazole, initiating treatment with lurasidone was associated with significantly fewer hospitalizations over 12 months (—5.98 hospitalizations per patient; 95% CI, –6.61 to –5.35]), followed by risperidone (–0.26; 95% CI, –0.34 to –0.17), and olanzapine (–0.16; 95% CI, –0.26 to –0.07). Quetiapine was associated with significantly more hospitalizations than aripiprazole (0.40; 95% CI, 0.32-0.49).23 Lurasidone was also associated with significantly fewer ED visits, lower hospital costs, and lower total costs compared with aripiprazole.23
A second study that used a treatment-episode approach to compare patients with schizophrenia who switched from other SGAs to either quetiapine or lurasidone reported that patients who switched to quetiapine had significantly higher odds of all-cause (adjusted odds ratio [aOR], 1.64) and mental health-related hospitalizations (aOR, 1.74), but not schizophrenia-related hospitalizations (aOR, 1.35), compared with patients who switched to lurasidone.26 Therefore, the limited literature that has compared hospitalization risk associated with lurasidone and other SGAs in patients with schizophrenia has used different methods, but they consistently reported lower risk of hospitalization among patients treated with lurasidone.
In this study, persistence with SGAs was low. Assuming all patients using antipsychotic monotherapy in month 12 used the same antipsychotic consistently over follow-up, the ratio of patients treated with the study antipsychotic at month 12/month 1 may reflect an upper limit on persistence. This ratio ranged from 24.5% to 36.0%, and lurasidone had the highest value, suggesting greater persistence compared with other antipsychotic agents. Antipsychotic adherence and persistence have been linked to reduced hospitalization rates6,7 and better long-term outcomes.8
Because changes in antipsychotic treatment are common, if an ITT approach had been utilized, the treatment patients were receiving may not have matched the treatment group to which they were assigned. The MSM approach appeared to better capture the effects of medication on hospitalization risk than an ITT approach because the ITT approach implicitly assumes high persistence.30,38,39
An important aspect of this study was the use of equivalent doses. In usual clinical care, antipsychotics may be used at doses outside of the recommended dose range.40-42 However, in the primary analysis, comparison was limited to doses equivalent to 80 mg or less per day of lurasidone. Equivalent doses of antipsychotics have been estimated using multiple methods.18 One leading method used data from double-blind clinical trials to estimate a dose that had efficacy equivalent to 100 mg per day of chlorpromazine.18,43 The current study used chlorpromazine dose equivalents summarized from multiple studies and published by the College of Psychiatric and Neurologic Pharmacists.34 Therefore, the current study utilized an approach that is consistent with the AHRQ’s recommendation for dose equivalent comparison of treatment effects.15
In the current study, dosing of antipsychotics was generally low based on recommended dose ranges for adult schizophrenia. Use of low doses was most common for risperidone and quetiapine. However, the low doses observed were generally consistent with previously documented doses in real-world clinical practice.44
The results of the current study indicated that monotherapy lurasidone was associated with fewer all-cause hospitalizations than other SGAs at doses equivalent to 80 mg or less per day of lurasidone. A sensitivity analysis without dose-equivalence restrictions reached similar conclusions. Notably, in 2006, the cost of a single schizophrenia hospitalization in the United States was estimated to be $8334 for a patient with Medicaid and $7802 for a patient with private insurance.45 A more recent estimate from the National Inpatient Sample Database showed the average cost of hospitalization for a person with schizophrenia was $9793 in 2016.46 For a large patient population, the cost savings associated with using lurasidone instead of these more commonly used antipsychotics could be substantial.
The administrative claims data were collected for administrative purposes rather than research purposes. Although the data reflected usual clinical care and provided excellent measures of healthcare resource use, the data were subject to potential coding errors, and important measures such as symptom severity were not available. Furthermore, although the MSMs adjusted for multiple preindex and time-varying covariates, unmeasured confounding variables could still exist. Statistical adjustments for multiple comparisons were not made. Finally, patients without health insurance could not be included and the results may not be generalizable to this population.
In this claims database analysis of patients with schizophrenia treated with equivalent doses of SGAs, those treated with lurasidone monotherapy had a lower risk of hospitalization than patients treated with olanzapine, quetiapine, or risperidone monotherapy. As hospitalization is a major cost driver of direct healthcare cost for individuals with schizophrenia, lurasidone may be a cost-saving treatment option. Authors’ Affiliations: Sunovion Pharmaceuticals; STATinMED Research.
Funding Source: Financial support for this work was provided by Sunovion Pharmaceuticals Inc.
Author Disclosure: Drs Ng-Mak, Messali, and Loebel are full-time employees of Sunovion Pharmaceuticals Inc. Ms Huang and Dr Wang are full-time employees of STATinMED Research.
Author Acknowledgments: The authors would like to thank Alex Liu from STATinMED Research for data analytical support, and Michael Stensland from Agile Outcomes Research, Inc, for medical writing support.
Authorship Information: Concept and design (DNM, AM, AH, LW, AL); analysis and interpretation of data (DNM, AM, AH, LW, AL); and critical revision of the manuscript for important intellectual content (DNM, AM, AH, LW, AL).
Address correspondence to: Daisy Ng-Mak, PhD, Sunovion Pharmaceuticals Inc, 84 Waterford Dr, Marlborough, MA 01752. Email: daisy.ng-mak@