Real-world predictors of relapse in patients with schizophrenia and schizoaffective disorder in a large health system

Schizophrenia is often characterized by recurring relapses, which are associated with a substantial clinical and economic burden. Early identification of individuals at the highest risk for relapse in real-world treatment settings could help improve outcomes and reduce healthcare costs. Prior work has identified a few consistent predictors of relapse in schizophrenia, however, studies to date have been limited to insurance claims data or small patient populations. Thus, this study used a large sample of health systems electronic health record (EHR) data to analyze relationships between patient-level factors and relapse and model a set of factors that can be used to identify the increased prevalence of relapse, a severe and preventable reality of schizophrenia. This retrospective, observational cohort study utilized EHR data extracted from the largest Midwestern U.S. non-profit healthcare system to identify predictors of relapse. The study included patients with a diagnosis of schizophrenia (ICD-10 F20) or schizoaffective disorder (ICD-10 F25) who were treated within the system between October 15, 2016, and December 31, 2021, and received care for at least 12 months. A relapse episode was defined as an emergency room or inpatient encounter with a pre-determined behavioral health-related ICD code. Patients' baseline characteristics, comorbidities and healthcare utilization were described. Modified log-Poisson regression (i.e. log Poisson regression with a robust variance estimation) analyses were utilized to estimate the prevalence of relapse across patient characteristics, comorbidities and healthcare utilization and to ultimately identify an adjusted model predicting relapse. Among the 8119 unique patients included in the study, 2478 (30.52%) experienced relapse and 5641 (69.48%) experienced no relapse. Patients were primarily male (54.72%), White Non-Hispanic or Latino (54.23%), with Medicare insurance (51.40%), and had baseline diagnoses of substance use (19.24%), overweight/obesity/weight gain (13.06%), extrapyramidal symptoms (48.00%), lipid metabolism disorder (30.66%), hypertension (26.85%), and diabetes (19.08%). Many differences in patient characteristics, baseline comorbidities, and utilization were revealed between patients who relapsed and patients who did not relapse. Through model building, the final adjusted model with all significant predictors of relapse included the following variables: insurance, age, race/ethnicity, substance use diagnosis, extrapyramidal symptoms, number of emergency room encounters, behavioral health inpatient encounters, prior relapses episodes, and long-acting injectable prescriptions written. Prevention of relapse is a priority in schizophrenia care. Challenges related to historical health record data have limited the knowledge of real-world predictors of relapse. This study offers a set of variables that could conceivably be used to construct algorithms or models to proactively monitor demographic, comorbidity, medication, and healthcare utilization parameters which place patients at risk for relapse and to modify approaches to care to avoid future relapse.

Impact of lurasidone on health-related quality of life in adults with bipolar depression: a post-hoc analysis

OBJECTIVE

The objective of this post-hoc analysis was to assess the impact of lurasidone monotherapy on health-related quality of life (HRQoL) in adults with bipolar depression.

METHODS

Data were analyzed from a 6-week randomized, double-blind (DB), placebo-controlled trial of lurasidone monotherapy (NCT00868699) and a 6-month open label extension (OLE; NCT00868959). Patients who received lurasidone monotherapy or placebo during the DB trial were eligible to continue or switch to lurasidone monotherapy during the OLE. The 16-item Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form (Q-LES-Q-SF) was collected at DB baseline, DB week 6/OLE baseline, OLE month 3, and OLE month 6. Effect size (ES) and mean changes from baseline were reported for Q-LES-Q-SF total and item scores during the DB trial and OLE, respectively.

RESULTS

Of 485 patients in the DB trial (lurasidone monotherapy: n = 323; placebo: n = 162), 316 patients continued or switched to lurasidone monotherapy during the OLE. Significant improvements in Q-LES-Q-SF scores in lurasidone vs. placebo were reported for 13 of 16 items (all p < .05) at DB week 6. The greatest improvements were overall life satisfaction (ES = 0.57), social relationships (0.55), medication satisfaction (0.48), family relationships (0.46), and ability to function in daily life (0.45, all p < .001). Improvements in Q-LES-Q-SF total and item scores were sustained at OLE month 6.

CONCLUSIONS

Treatment with lurasidone provided a significant improvement across HRQoL items including overall life satisfaction, social and family relationships, medication satisfaction, and ability to function in daily life. Improvements were sustained during the 6-month OLE.

Hospitalization risk among adults with bipolar I disorder treated with lurasidone versus other oral atypical antipsychotics: a retrospective analysis of Medicaid claims data

OBJECTIVE

To compare the risk of hospitalization for adult Medicaid beneficiaries with bipolar I disorder treated with lurasidone vs. other oral atypical antipsychotics (AAPs) as monotherapy.

METHODS

A retrospective cohort study of the IBM MarketScan Multi-State Medicaid Claims database identified adults with bipolar I disorder who initiated an AAP (index date) between 1 January 2014 and 30 June 2019. Patients were continuously enrolled 12 months pre- and 24 months post-index date. Each month during the post-index period was categorized as monotherapy with lurasidone, aripiprazole, olanzapine, quetiapine or risperidone, no/minimal treatment, or other. Marginal structural models were performed to estimate hospitalization risk and length of stay (LOS) (all-cause and bipolar I disorder-related) compared to lurasidone.

RESULTS

The analysis included 8262 adults. Compared to lurasidone, the adjusted odds ratios (aORs) of all-cause hospitalization were significantly higher for olanzapine (aOR = 1.60, 95% CI = 1.09-2.10) and quetiapine (aOR = 1.54, 95% CI = 1.18-1.89). The risk was significantly higher for bipolar I disorder-related hospitalization for quetiapine (aOR = 1.57, 95% CI = 1.10-2.04) and risperidone (aOR = 1.80, 95% CI = 1.04-2.56) compared to lurasidone. The bipolar I disorder-related LOS per 100 patient-months was more than twice as long for quetiapine (8.42 days) compared to lurasidone (3.97 days, p < .01).

CONCLUSIONS

Lurasidone-treated adult Medicaid patients with bipolar I disorder had significantly lower risk of all-cause hospitalization than those treated with olanzapine and quetiapine and lower risk of bipolar I disorder-related hospitalization than quetiapine and risperidone. Bipolar I disorder-related hospital LOS was significantly shorter for patients treated with lurasidone compared to quetiapine.

Hospitalization Risk for Adults with Bipolar I Disorder Treated with Oral Atypical Antipsychotics as Adjunctive Therapy with Mood Stabilizers: A Retrospective Analysis of Medicaid Claims Data

Background: Atypical antipsychotics (AAPs) with mood stabilizers are recommended as a first-line treatment for patients with bipolar disorder. No studies have compared the inpatient health care resource utilization for patients with bipolar disorder treated with lurasidone as adjunctive therapy with mood stabilizers compared with other oral AAPs. Objective: To compare the risk of hospitalization for adult Medicaid beneficiaries with bipolar I disorder when treated with lurasidone compared with other oral AAPs as adjunctive therapy with mood stabilizers. Methods: This retrospective cohort study used the MarketScan Research Databases Multi-State Medicaid Database (IBM, Armonk, NY) claims data to assess patients with bipolar I disorder between January 1, 2014, and June 30, 2019. Adult patients who initiated oral AAP treatment with mood stabilizers (index date) and who were continuously enrolled 12 months before (pre-index) and 24 months after (post-index) the index date were included. Treatment categories assigned by patient-month included lurasidone, aripiprazole, olanzapine, quetiapine, risperidone, or ziprasidone with mood stabilizers; no/minimal treatment; AAP monotherapy; and other. Marginal structural models were performed to estimate the all-cause and psychiatric hospitalization rates and hospital length of stay associated with each adjunctive AAP therapy by controlling for both time-invariant and time-varying confounders. Results: Adults with bipolar I disorder (N = 11,426; mean age = 39.4 years; female=73%) treated with an adjunctive oral AAP with mood stabilizers during the index month were categorized into lurasidone (12%), aripiprazole (17%), olanzapine (7%), quetiapine (32%), risperidone (11%), ziprasidone (7%), or other (15%) treatment groups. The adjusted odds of all-cause and psychiatric hospitalization were significantly higher for olanzapine (all causes: adjusted odds ratio [aOR] = 1.59; 95% CI, 1.13-2.25; psychiatric: aOR = 1.61, 95% CI, 1.12-2.32), quetiapine (all-causes: aOR = 1.27, 95% CI, 1.01-1.58; psychiatric: aOR = 1.28, 95% CI, 1.02-1.59), and ziprasidone (all-causes: aOR = 1.68, 95% CI, 1.05-2.66; psychiatric: aOR = 1.55, 95% CI, 1.02-2.35) compared with lurasidone with mood stabilizers. The adjusted odds of all-cause and psychiatric hospitalizations were numerically lower for lurasidone compared with aripiprazole. The all-cause hospital length of stay per 100 patient-months was significantly higher for olanzapine (20.3 days) and quetiapine (16.0 days) compared with lurasidone (12.2 days, both P values < 0.05). Conclusions: In a Medicaid population, adults with bipolar I disorder treated with lurasidone as adjunctive therapy with mood stabilizers had significantly lower all-cause and psychiatric hospitalization rates compared with olanzapine, quetiapine, and ziprasidone. Fewer hospitalizations may reduce the economic burden associated with bipolar disorder. (Curr Ther Res Clin Exp. 2021; 82:XXX-XXX).

Formulary restrictions on atypical antipsychotics: impact on costs for patients with schizophrenia and bipolar disorder in Medicaid

OBJECTIVES

To measure the impact of state Medicaid formulary policies on costs for patients with schizophrenia and bipolar disorder.

STUDY DESIGN

Retrospective analysis of medical and pharmacy claims for patients diagnosed with schizophrenia or bipolar disorder in 24 state Medicaid programs.

METHODS

We combined information on formulary restrictions in Medicaid with the medical and pharmacy claims of 117,908 patients with schizophrenia and 170,596 patients with bipolar disorder in Medicaid who were single-eligible, and newly prescribed a second-generation antipsychotic from 2001 to 2008. We tested the impact of formulary restrictions on the medical costs and utilization of patients in the 12 months after the index prescription. To capture social costs in addition to medical expenditures in Medicaid, we estimated the incremental costs of incarcerating patients with schizophrenia and bipolar disorder associated with formulary restrictions.

RESULTS

Patients with schizophrenia subject to formulary restrictions were more likely to be hospitalized (odds ratio 1.13, P <.001), had 23% higher inpatient costs (P <.001), and 16% higher total costs (P <.001). Similar effects were observed for patients with bipolar disorder. Our estimates suggest restrictive formulary policies in Medicaid increased the number of prisoners by 9920 and incarceration costs by $362 million nationwide in 2008.

CONCLUSIONS

Applying formulary restrictions to atypical antipsychotics is associated with higher total medical expenditures for patients with schizophrenia and bipolar disorder in Medicaid. Combined with the other social costs such as an increase in incarceration rates, these formulary restrictions could increase state costs by $1 billion annually, enough to offset any savings in pharmacy costs.