Effect of diabetes on caregiver burden in an observational study of individuals with Alzheimer's disease.

BACKGROUND: The burden on caregivers of patients with Alzheimer's disease (AD) is associated with the patient's functional status and may also be influenced by chronic comorbid medical conditions, such as diabetes. This post-hoc exploratory analysis assessed whether comorbid diabetes in patients with AD affects caregiver burden, and whether caregivers with diabetes experience greater burden than caregivers without diabetes. Caregiver and patient healthcare resource use (HCRU) were also assessed. METHODS: Baseline data from the GERAS observational study of patients with AD and their caregivers (both n = 1495) in France, Germany and the UK were analyzed. Caregiver burden was assessed using the Zarit Burden Interview (ZBI). Caregiver time on activities of daily living (ADL: basic ADL; instrumental ADL, iADL) and supervision (hours/month), and caregiver and patient HCRU (outpatient visits, emergency room visits, nights hospitalized) were assessed using the Resource Utilization in Dementia instrument for the month before the baseline visit. Regression analyses were adjusted for relevant covariates. Time on supervision and basic ADL was analyzed using zero-inflated negative binomial regression. RESULTS: Caregivers of patients with diabetes (n = 188) were younger and more likely to be female (both p < 0.05), compared with caregivers of patients without diabetes (n = 1307). Analyses showed caregivers of patients with diabetes spent significantly more time on iADL (+16 %; p = 0.03; increases were also observed for basic ADL and total caregiver time but did not reach statistical significance) and had a trend towards increased ZBI score. Patients with diabetes had a 63 % increase in the odds of requiring supervision versus those without diabetes (p = 0.01). Caregiver and patient HCRU did not differ according to patient diabetes. Caregivers with diabetes (n = 127) did not differ from those without diabetes (n = 1367) regarding burden/time, but caregivers with diabetes had a 91 % increase in the odds of having outpatient visits (p = 0.01). CONCLUSIONS: This cross-sectional analysis found caregiver time on iADL and supervision was higher for caregivers of patients with AD and diabetes versus without diabetes, while HCRU was unaffected by patient diabetes. Longitudinal analyses assessing change in caregiver burden over time by patient diabetes status may help clarify the cumulative impact of diabetes and AD dementia on caregiver burden.

Predictors of Change in Adherence Status from 1 Year to the Next Among Patients with Type 2 Diabetes Mellitus on Oral Antidiabetes Drugs.

BACKGROUND: Diabetes is a leading cause of morbidity, mortality, and medical resource utilization in the United States and worldwide. Treatment is aimed at keeping blood glucose levels close to normal and preventing or delaying medical complications. It has been estimated that only 50% of patients with diabetes in the United States achieve glycosylated hemoglobin A1c level < 7%. Nonadherence to antidiabetic medications has been identified as a major factor related to poor glycemic control. OBJECTIVES: To (a) assess adult patients with type 2 diabetes mellitus (T2DM) whose adherence status to oral antidiabetic drugs (OADs) changed from 1 year to the next and (b) identify predictors of change in adherence status. METHODS: This retrospective study of the Humana Medicare Advantage Database included patients with T2DM and continuous enrollment between 2010 and 2012. Proportion of days covered (PDC) by OADs was calculated for each of the 3 study years (2010, 2011, 2012). Patients were classified as adherent (PDC ≥ 80%) or nonadherent (PDC < 80%) during each year. Patient characteristics from the baseline period (2010) were used as covariates, and adherence status changes from baseline to follow-up year (2011) were used as response variables. Data from the subsequent study periods (2011 as baseline, 2012 as follow-up) were used to validate the model (final model). RESULTS: A total of 238,402 patients met inclusion criteria. Among them, 144,216 (60.5%) were adherent, and 94,186 (39.5%) were nonadherent during the baseline period. Change in adherence status from baseline to follow-up year was observed in 31,320 (21.7%) patients that were adherent and 39,284 (41.7%) patients that were nonadherent during the baseline year. The final model for baseline adherent patients had a receiver-operating characteristic (ROC) index of 73% and a misclassification rate of 39%. The predictors of highest importance were identified as total number of prescriptions filled with 90-day supply, diabetes-related pill burden, longest gap in OADs, total number of antidiabetic classes filled, and copay for the last OAD filled. The final model had a sensitivity value of 76.4%. The final model for baseline nonadherent patients had a ROC index of 68%, a misclassification rate of 36.4%, and sensitivity value of 52.9%. The predictors of highest importance were diabetes-related pill burden, longest gap in OADs, month-wise patient oscillation from adherent to nonadherent during baseline year, total number of prescriptions filled with a 90-day supply, and total pill burden during the baseline year. CONCLUSIONS: One third of the T2DM patients changed adherence status from 1 year to the next, and factors associated with adherence status changes were identified. Predictive models such as those used in this study can serve as useful and cost-effective tools for payers, helping to identify members that should be targeted for adherence enhancement programs and, ultimately, to improve patients' long-term outcomes. DISCLOSURES: Funding for this research was provided by Eli Lilly and Company. Comprehensive Health Insights, owned by Humana, completed this study. Peng, Fu, Ascher-Svanum, Ali, and Rodriguez are employees of Eli Lilly and Company. Saundankar and Louder are employed by Comprehensive Health Insights, and Slabaugh and Young are employed by Humana. Study concept and design were contributed by Peng, Ascher-Svanum, and Young. Saundankar and Louder took the lead in data collection, while Saundankar, Peng, Fu, and Louder interpreted the data. The manuscript was written by Saundankar, Peng, Fu, and Louder and revised by Saundankar, Rodriguez, Ali, and Louder.

Early Glycemic Response Predicts Achievement of Subsequent Treatment Targets in the Treatment of Type 2 Diabetes: A Post hoc Analysis.

INTRODUCTION: American Diabetes Association consensus guidelines emphasize individualized treatment in the management of type 2 diabetes mellitus (T2DM). Early glycemic response is a clinical marker that may predict longer term efficacy for individual patients and provide a clinical tool to enhance personalized treatment. This analysis evaluated whether glycemic response measured at week 12 ("early") could serve as a reliable predictor of glycemic control at weeks 24 and 52 of therapy in patients with T2DM. METHODS: We used data from 3 randomized, controlled clinical trials that evaluated patients with T2DM treated with 3 commonly prescribed glucose-lowering medications: metformin (n = 597), sulfonylurea (n = 626), and insulin glargine (n = 1046). The gradient boosting method was used to identify predictors of subsequent response; predictive accuracy was represented by sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Treatment success at weeks 24 and 52 was assessed for each patient and defined as achieving a glycated hemoglobin (HbA1c) level of <7.0% or a reduction from baseline of ≥1.0%. RESULTS: The predictive parameters (sensitivity, specificity, PPV, and NPV) for improvements in HbA1c at week 24 for metformin were 0.83, 0.81, 0.44, and 0.96; for sulfonylurea, 0.79, 0.94, 0.71, and 0.96; and for insulin glargine, 0.67, 0.89, 0.65, and 0.90. The predictive parameters for improvements in HbA1c at week 52 for metformin were 0.73, 0.84, 0.56, and 0.92 and for sulfonylurea, 0.45, 0.94, 0.74, and 0.82. CONCLUSION: High predictive values identified in this analysis support "early" response as an appropriate tool for predicting treatment success at weeks 24 and 52. The high NPV (lack of early glycemic response) appears to be an effective indicator of the likely need for change in (or intensification of) therapy. These data support the current guideline recommendations that clinicians evaluate therapeutic responses to pharmacologic interventions with metformin, sulfonylureas, or insulin glargine as early as week 12.

Associations Between Glycemic Control, Depressed Mood, Clinical Depression, and Diabetes Distress Before and After Insulin Initiation: An Exploratory, Post Hoc Analysis.

INTRODUCTION: Although depression is often associated with poor glycemic control in patients with type 2 diabetes mellitus (T2DM), this observation has been inconsistent. This exploratory, post hoc analysis investigated associations between depression parameters and glycemic control using data from a 24-month, prospective, observational, non-interventional study evaluating glycemic response following insulin initiation for T2DM. METHODS: We analyzed data from a 24-month, prospective, observational study that evaluated glycemic response in patients with T2DM who initiated insulin therapy (N = 985) in 5 European countries. Secondary measures included patient-reported diagnosis of depression at baseline, severity of depressed/anxious mood (EuroQol (EQ)-5D item) and diabetes-related distress (Psychological Distress domain of the Diabetes Health Profile, DHP-18). The latter two measures were assessed at baseline and 5 time points throughout the study. Glycemic control was measured by glycated hemoglobin (HbA1c) at these same time points. Analyses employed t tests to assess the unadjusted baseline difference in HbA1c between patients with and without the respective depression parameter. The potential effect of demographic and clinical confounding variables was controlled through a linear model structure. Patient HbA1c levels were analyzed by presence/absence of a history of diagnosed depression, depressed mood, and diabetes-related distress. RESULTS: Patients with higher depression parameters or distress at baseline had significantly higher rates of microvascular complications at baseline. Patients with a history of diagnosed depression or high diabetes-related distress had higher HbA1c than patients without. HbA1c of patients with or without depressed mood was not significantly different at baseline. The proportion of patients with depressed mood declined after insulin initiation, whereas the proportion of patients with high diabetes-related distress did not significantly change. HbA1c improved following insulin initiation, regardless of presence/absence of studied depression/distress parameters at baseline. CONCLUSION: History of diagnosed depression, diabetes-related distress, and depressed mood were associated with a higher rate of microvascular complications. Diagnosed depression and diabetes-related distress also showed higher HbA1c at baseline when insulin was initiated. Insulin therapy improved glycemic control, while preexisting depressed mood declined and diabetes-related distress remained unchanged.

Cognitive and Functional Decline in Patients With Mild Alzheimer Dementia With or Without Comorbid Diabetes.

PURPOSE: Although diabetes is recognized as a risk factor for the development of cognitive impairment and for accelerated progression to Alzheimer disease (AD), it is unclear whether patients with diabetes who have already progressed to AD have a different rate of cognitive and functional decline compared with that in those without diabetes. This post hoc exploratory analysis compared cognitive and functional decline over an 18-month period in patients with mild AD dementia with and without comorbid diabetes. Decline in quality of life was assessed as a secondary objective. METHODS: In a post hoc exploratory analysis, we analyzed data from the placebo groups of three 18-month, randomized, placebo-controlled trials of solanezumab and semagacestat in patients with AD. Data from patients with mild AD dementia (Mini-Mental State Examination [MMSE] score, 20-26) and comorbid diabetes at baseline were compared with data from patients with mild AD dementia without diabetes at baseline. Cognition was assessed using the 14-item AD Assessment Scale-Cognitive Subscale (ADAS-Cog14) and the MMSE. Functioning was assessed with the AD Cooperative Study-Activities of Daily Living Inventory (instrumental subset) (ADCS-iADL). Quality of life was assessed using the European Quality of Life-5 Dimensions scale, proxy version (proxy utility score and visual analog scale score), and the Quality of Life in AD scale, self-report and proxy (caregiver) versions. Group comparisons of changes from baseline to 18 months in cognitive, functional, and quality-of-life measures employed a repeated-measures model adjusted for propensity score, study, baseline cognition score (functional or quality of life), age, sex, level of education, genotype of the apolipoprotein E gene, and concurrent use of an acetylcholinesterase inhibitor or memantine. FINDINGS: At baseline, patients with mild AD dementia with and without diabetes did not significantly differ on the cognitive measures, but those without diabetes were functioning at a significantly higher level. At 18 months, compared with patients without diabetes, those with diabetes showed a numerically but statistically nonsignificantly lesser cognitive decline (least squares mean between-group differences: ADAS-Cog14 score, 1.61 [P = 0.21]; MMSE score, -0.40 [P = 0.49]) and a statistically significantly lesser functional decline (least squares mean between-group difference in ADCS-iADL score, -3.07; P = 0.01). The 2 groups did not differ on declines in the quality-of-life measures. IMPLICATIONS: The present findings suggest that diabetes may influence the rate of functional decline among patients with mild AD dementia. These results require replication in studies that address the limitations of the present post hoc exploratory analysis and that explore the potential causes of the observed differences.

Does participation in a weight control program also improve clinical and functional outcomes for Chinese patients with schizophrenia treated with olanzapine?

OBJECTIVES: This study examined whether participation in a weight control program (WCP) by patients with schizophrenia treated with olanzapine was also associated with improvements in clinical and functional outcomes. METHODS: A post-hoc analysis was conducted using data from the Chinese subgroup (n=330) of a multi-country, 6-month, prospective, observational study of outpatients with schizophrenia who initiated or switched to oral olanzapine. At study entry and monthly visits, participants were assessed with the Clinical Global Impression of Severity, and measures of patient insight, social activities, and work impairment. The primary comparison was between the 153 patients who participated in a WCP at study entry (n=93) or during the study (n=60) and the 177 patients who did not participate in a weight control program (non-WCP). Mixed Models for Repeated Measures with baseline covariates were used to compare outcomes over time. Kaplan-Meier survival analysis was used to assess time to response. RESULTS: Participants had a mean age of 29.0 years and 29.3 years, and 51.0% and 57.6% were female for WCP and non-WCP groups, respectively. Average initiated daily dose for olanzapine was 9.5±5.4 mg. WCP participants gained less weight than non-participants (3.9 kg vs 4.9 kg, P=0.03) and showed statistically significant better clinical and functional outcomes: greater improvement in illness severity (-2.8 vs -2.1, P<0.001), higher treatment response rates (94.1% vs 80.9%, P<0.001), shorter time to response (P<0.001), and greater improvement in patients' insight (P<0.001). Patients who enrolled in a WCP during the study had greater initial weight gain than those who enrolled at baseline (P<0.05), but similar total weight gain. CONCLUSION: Participation in a WCP may not only lower the risk of clinically significant weight gain in olanzapine-treated patients, but may also be associated with additional clinical and functional benefits.

Long-term functional improvements in the 2-year treatment of schizophrenia outpatients with olanzapine long-acting injection.

BACKGROUND: Little is known about the long-term changes in the functioning of schizophrenia patients receiving maintenance therapy with olanzapine long-acting injection (LAI), and whether observed changes differ from those seen with oral olanzapine. METHODS: This study describes changes in the levels of functioning among outpatients with schizophrenia treated with olanzapine-LAI compared with oral olanzapine over 2 years. This was a secondary analysis of data from a multicenter, randomized, open-label, 2-year study comparing the long-term treatment effectiveness of monthly olanzapine-LAI (405 mg/4 weeks; n=264) with daily oral olanzapine (10 mg/day; n=260). Levels of functioning were assessed with the Heinrichs-Carpenter Quality of Life Scale. Functional status was also classified as "good", "moderate", or "poor", using a previous data-driven approach. Changes in functional levels were assessed with McNemar's test and comparisons between olanzapine-LAI and oral olanzapine employed the Student's t-test. RESULTS: Over the 2-year study, the patients treated with olanzapine-LAI improved their level of functioning (per Quality of Life total score) from 64.0-70.8 (P<0.001). Patients on oral olanzapine also increased their level of functioning from 62.1-70.1 (P<0.001). At baseline, 19.2% of the olanzapine-LAI-treated patients had a "good" level of functioning, which increased to 27.5% (P<0.05). The figures for oral olanzapine were 14.2% and 24.5%, respectively (P<0.001). Results did not significantly differ between olanzapine-LAI and oral olanzapine. CONCLUSION: In this 2-year, open-label, randomized study of olanzapine-LAI, outpatients with schizophrenia maintained or improved their favorable baseline level of functioning over time. Results did not significantly differ between olanzapine-LAI and oral olanzapine.

Early discontinuation and restart of insulin in the treatment of type 2 diabetes mellitus.

INTRODUCTION: Although the largest improvement in glycemic control occurs within the first 90 days of insulin therapy, little is known about early persistence on insulin therapy. This research aimed to identify predictors of early discontinuation and of subsequent restart of basal or mixture insulin among patients with type 2 diabetes mellitus (T2DM) and to assess the economic cost associated with such behaviors over a 1-year period. METHODS: Truven's Health Analytics Commercial Claims and Encounters database was utilized for the study. Logistic regressions were used to examine factors associated with early discontinuation of insulin (basal or mixture) and, among patients who discontinued early, the factors associated with restarting. Cost regressions were estimated using generalized linear models with a gamma distribution and logistic link. Kaplan-Meier survival curves were used to examine time to discontinuation and time to restart among those who discontinued. RESULTS: Multivariate analyses revealed that patient characteristics, prior healthcare resource utilization, comorbid diagnoses, and type of initiated insulin were associated with early discontinuation of insulin and of restarting among patients who discontinued early. Acute care (hospitalization and emergency room) costs were 9.6% higher among patients who discontinued early (P < 0.001), although outpatient, drug, and total costs were significantly lower among individuals who discontinued early. Among the early discontinuation subgroup, restarting insulin was associated with higher costs. Specifically: 11.3% higher acute care costs (P < 0.001), 24.0% higher outpatient costs (P < 0.001), 80.2% higher drug costs (P < 0.001), and 30.3% higher total costs (P < 0.001), compared to patients who discontinued early but did not restart insulin therapy in the 1-year post-period. CONCLUSION: Among patients with T2DM who were initiated on insulin therapy, early discontinuation of insulin and its subsequent restart were associated with significantly higher acute care costs, which may signal a more complex and challenging subgroup of patients who tend to be less engaged in outpatient care and may have poorer long-term outcomes.

Comparison of olanzapine long-acting injection and oral olanzapine: a 2-year, randomized, open-label study in outpatients with schizophrenia.

We compared long-term treatment effectiveness of monthly olanzapine long-acting injection (LAI) with that of oral olanzapine. Outpatients with 2 or more episodes of psychotic worsening in the past 24 months with Positive and Negative Syndrome Scale total score of lower than 70 were randomized to 405 mg/4 weeks of olanzapine LAI (n = 264) or 10 mg/d of oral olanzapine (n = 260) for 2 years of open-label treatment. Dosing thereafter was flexible (150-405 mg/4 weeks of LAI vs 5-20 mg/d of oral). Primary outcome was time to all-cause discontinuation. At baseline, patients were clinically stable (mean Positive and Negative Syndrome Scale total score of 57). Seventeen percent of patients had been psychiatrically hospitalized in the previous 6 months, and 4.6% were rated nonadherent in the month before study entry. The groups did not differ significantly in median time to all-cause discontinuation (645 days for LAI, 678 days for oral; P = 0.61), discontinuation rate (53.8% for LAI, 51.2% for oral; P = 0.60), or relapse rate (20.1% for LAI, 18.5% for oral; P = 0.66). Postbaseline psychiatric hospitalization rate was low for both groups (7.6% for LAI, 9.2% for oral), but mean hospitalization duration was significantly longer for oral patients (1.80 days [20 for those hospitalized] vs 0.43 days [6 for those hospitalized], P = 0.02). There were no clinically significant group differences in adverse events or safety measures. No post-injection delirium/sedation syndrome events occurred. In conclusion, olanzapine LAI and oral olanzapine were similarly effective and well tolerated for up to 2 years of treatment in patients with schizophrenia. Treatment discontinuation for olanzapine LAI was similar to that of oral olanzapine, despite the 3-hour post-injection observation period and other precautionary procedures related to risk of post-injection delirium/sedation syndrome.

Early perception of medication benefit predicts subsequent antipsychotic response in schizophrenia: "the consumer has a point" revisited.

BACKGROUND: An easy-to-administer tool for predicting response to antipsychotic treatment could improve the acute management of patients with schizophrenia. We assessed whether a patient's perception of medication benefit early in treatment could predict subsequent response or nonresponse to continued use of the same treatment. METHOD: This post hoc analysis used data from a randomized, open-label trial of antipsychotics for treatment of schizophrenia in which attitudes about medication adherence were assessed after two weeks of antipsychotic treatment using the Rating of Medication Influences (ROMI) scale. The analysis included 439 patients who had Positive and Negative Syndrome Scale (PANSS) and ROMI scale data at Weeks 2 and 8. Scores on the ROMI subscale Perceived Medication Benefit factor were used to predict subsequent antipsychotic response at Week 8, defined as a .20% reduction from baseline on the PANSS. Logistic regression was used to identify a cut-off score for the Perceived Medication Benefit factor that could accurately identify antipsychotic responders vs. nonresponders at Week 8. RESULTS: A score of .2.75 (equal to a mean subscale score of .11.00) on the ROMI scale Perceived Medication Benefit factor at Week 2 predicted response at Week 8 with high specificity (72%) and negative predictive value (70%), moderate sensitivity (44%) and positive predictive value (47%), and with a 38% misclassification rate. CONCLUSIONS: A brief assessment of the patient's perception of medication benefit at two weeks into treatment appears to be a good predictor of subsequent response and nonresponse after eight weeks of treatment with the same antipsychotic.

Characteristics of patients misdiagnosed with Alzheimer's disease and their medication use: an analysis of the NACC-UDS database.

BACKGROUND: This study compared individuals whose clinical diagnosis of Alzheimer's disease (AD) matched or did not match neuropathologic results at autopsy on clinical and functional outcomes (cognitive impairment, functional status and neuropsychiatric symptoms). The study also assessed the extent of potentially inappropriate medication use (using potentially unnecessary medications or potentially inappropriate prescribing) among misdiagnosed patients. METHODS: Longitudinal data from the National Alzheimer's Coordinating Center Uniform Data Set (NACC-UDS, 2005-2010) and corresponding NACC neuropathological data were utilized to compare 88 misdiagnosed and 438 accurately diagnosed patients. RESULTS: Following adjustment of sociodemographic characteristics, the misdiagnosed were found to have less severe cognitive and functional impairment. However, after statistical adjustment for sociodemographics, dementia severity level, time since onset of cognitive decline and probable AD diagnosis at baseline, the groups significantly differed on only one outcome: the misdiagnosed were less likely to be depressed/dysphoric. Among the misdiagnosed, 18.18% were treated with potentially inappropriate medication. An additional analysis noted this rate could be as high as 67.10%. CONCLUSIONS: Findings highlight the importance of making an accurate AD diagnosis to help reduce unnecessary treatment and increase appropriate therapy. Additional research is needed to demonstrate the link between potentially inappropriate treatment and adverse health outcomes in misdiagnosed AD patients.

The longitudinal interplay between negative and positive symptom trajectories in patients under antipsychotic treatment: a post hoc analysis of data from a randomized, 1-year pragmatic trial.

BACKGROUND: Schizophrenia is a highly heterogeneous disorder with positive and negative symptoms being characteristic manifestations of the disease. While these two symptom domains are usually construed as distinct and orthogonal, little is known about the longitudinal pattern of negative symptoms and their linkage with the positive symptoms. This study assessed the temporal interplay between these two symptom domains and evaluated whether the improvements in these symptoms were inversely correlated or independent with each other. METHODS: This post hoc analysis used data from a multicenter, randomized, open-label, 1-year pragmatic trial of patients with schizophrenia spectrum disorder who were treated with first- and second-generation antipsychotics in the usual clinical settings. Data from all treatment groups were pooled resulting in 399 patients with complete data on both the negative and positive subscale scores from the Positive and Negative Syndrome Scale (PANSS). Individual-based growth mixture modeling combined with interplay matrix was used to identify the latent trajectory patterns in terms of both the negative and positive symptoms. Pearson correlation coefficients were calculated to examine the relationship between the changes of these two symptom domains within each combined trajectory pattern. RESULTS: We identified four distinct negative symptom trajectories and three positive symptom trajectories. The trajectory matrix formed 11 combined trajectory patterns, which evidenced that negative and positive symptom trajectories moved generally in parallel. Correlation coefficients for changes in negative and positive symptom subscale scores were positive and statistically significant (P < 0.05). Overall, the combined trajectories indicated three major distinct patterns: (1) dramatic and sustained early improvement in both negative and positive symptoms (n = 70, 18%), (2) mild and sustained improvement in negative and positive symptoms (n = 237, 59%), and (3) no improvement in either negative or positive symptoms (n = 82, 21%). CONCLUSIONS: This study of symptom trajectories over 1 year shows that changes in negative and positive symptoms were neither inversely nor independently related with each other. The positive association between these two symptom domains supports the notion that different symptom domains in schizophrenia may depend on each other through a unified upstream pathological disease process.

Predictors of psychiatric hospitalization during 6 months of maintenance treatment with olanzapine long-acting injection: post hoc analysis of a randomized, double-blind study.

BACKGROUND: Hospitalization is a costly and distressing event associated with relapse during schizophrenia treatment. No information is available on the predictors of psychiatric hospitalization during maintenance treatment with olanzapine long-acting injection (olanzapine-LAI) or how the risk of hospitalization differs between olanzapine-LAI and oral olanzapine. This study aimed to identify the predictors of psychiatric hospitalization during maintenance treatment with olanzapine-LAI and assessed four parameters: hospitalization prevalence, incidence rate, duration, and the time to first hospitalization. Olanzapine-LAI was also compared with a sub-therapeutic dose of olanzapine-LAI and with oral olanzapine. METHODS: This was a post hoc exploratory analysis of data from a randomized, double-blind study comparing the safety and efficacy of olanzapine-LAI (pooled active depot groups: 405 mg/4 weeks, 300 mg/2 weeks, and 150 mg/2 weeks) with oral olanzapine and sub-therapeutic olanzapine-LAI (45 mg/4 weeks) during 6 months' maintenance treatment of clinically stable schizophrenia outpatients (n=1064). The four psychiatric hospitalization parameters were analyzed for each treatment group. Within the olanzapine-LAI group, patients with and without hospitalization were compared on baseline characteristics. Logistic regression and Cox's proportional hazards models were used to identify the best predictors of hospitalization. Comparisons between the treatment groups employed descriptive statistics, the Kaplan-Meier estimator and Cox's proportional hazards models. RESULTS: Psychiatric hospitalization was best predicted by suicide threats in the 12 months before baseline and by prior hospitalization. Compared with sub-therapeutic olanzapine-LAI, olanzapine-LAI was associated with a significantly lower hospitalization rate (5.2% versus 11.1%, p < 0.01), a lower mean number of hospitalizations (0.1 versus 0.2, p = 0.01), a shorter mean duration of hospitalization (1.5 days versus 2.9 days, p < 0.01), and a similar median time to first hospitalization (35 versus 60 days, p = 0.48). Olanzapine-LAI did not differ significantly from oral olanzapine on the studied hospitalization parameters. CONCLUSIONS: In clinically stable schizophrenia outpatients receiving olanzapine-LAI maintenance treatment, psychiatric hospitalization was best predicted by a history of suicide threats and prior psychiatric hospitalization. Olanzapine-LAI was associated with a significantly lower incidence of psychiatric hospitalization and shorter duration of hospitalization compared with sub-therapeutic olanzapine-LAI. Olanzapine-LAI did not differ significantly from oral olanzapine on hospitalization parameters. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00088491.

The personal, societal, and economic burden of schizophrenia in the People's Republic of China: implications for antipsychotic therapy.

BACKGROUND: This article describes the personal, societal, and economic burden attributable to schizophrenia in the People's Republic of China and highlights the potential for effective outpatient treatment to reduce this burden given recent changes in the Chinese health care system. The importance of effective antipsychotic therapy in reducing the burden of schizophrenia is also examined. METHODS: Published research on the burden, disability, management, and economic costs of schizophrenia in the People's Republic of China was examined in the context of the larger body of global research. Research written in English or Chinese and published before June 2012 was identified using PubMed, CNKI, and Wanfang Med database searches. The contribution of effective antipsychotic therapy in reducing the risk for relapse and hospitalization and improving patients' functioning is described. RESULTS: Schizophrenia imposes a substantial burden on Chinese society, with indirect costs accounting for the majority of the total cost. Functional impairment is high, leading to lost wages and work impairment. In the People's Republic of China, schizophrenia is the most common diagnosis among hospitalized psychiatric patients. Ongoing changes in the Chinese health care system may reduce some barriers to effective relapse prevention in schizophrenia and potentially reduce hospitalizations. The use of antipsychotics for acute episodes and maintenance treatment has been shown to decrease symptom severity and reduce the risk for relapse and hospitalization. However, discontinuing antipsychotic medication appears common and is a strong predictor of relapse. Cost-effectiveness research in the People's Republic of China is needed to examine the potential gains from improved outpatient antipsychotic treatment. CONCLUSION: Schizophrenia is a very costly mental illness in terms of personal, economic, and societal burden, both in the People's Republic of China and globally. When treated effectively, patients tend to persist longer with antipsychotic treatment, have fewer costly relapses, and have improved functioning. Further research examining the long-term effects of reducing barriers to effective treatments on the societal burden of schizophrenia in the People's Republic of China is needed.

Movement disorder profile and treatment outcomes in a one-year study of patients with schizophrenia.

BACKGROUND: This study identified subgroups of patients with schizophrenia who differed on their movement disorder profile and compared their treatment outcomes. METHODS: Data from a randomized, open-label, one-year study of patients with schizophrenia who were treated with antipsychotics in usual clinical care settings were analyzed (n = 640). Five measures of movement disorder were incorporated into a single Movement Disorder Index (MDI). Subgroups that differed in their movement disorder profile over the one-year study period were compared on clinical and functional outcomes. RESULTS: THREE SUBGROUPS WERE IDENTIFIED: a worsening of MDI in 15% of patients, an improvement in 33%, and no change in 53%. Compared with the other two subgroups, the MDI-worsened subgroup had poorer symptom improvement measured by the Positive and Negative Syndrome Scale (PANSS) total score (mean changes of -11.0, -18.4, and -16.8 for the patients who had a worsening of MDI, no change, and an improvement, respectively), poorer symptom improvement on the PANSS positive and anxiety/depression subscale scores, worsening on the 36-Item Short Form Health Survey (SF-36) physical component summary score, and a higher rate of hospitalization (P < 0.05). CONCLUSION: Patients with schizophrenia who experience worsening of their MDI score appear to have poorer clinical and functional outcomes, suggesting that such worsening may be a marker of poorer prognosis.

Time to all-cause treatment discontinuation of olanzapine compared to other antipsychotics in the treatment of schizophrenia: a systematic review and meta-analysis.

OBJECTIVE: This comprehensive review and meta-analysis compared the effectiveness of olanzapine and other antipsychotics in schizophrenia treatment, defining effectiveness as time to all-cause medication discontinuation (primary) and as all-cause treatment discontinuation rates. This study examined randomized clinical trials (RCTs) and observational non-interventional studies. EXPERIMENTAL PROCEDURES: Schizophrenia studies that compared olanzapine with individual first- (FGAs) and/or second-generation antipsychotics (SGAs) were included in the meta-analyses. Hazard ratios (HR), risk ratios (RR), and their associated 95% confidence intervals were extracted for RCTs and observational studies. Sensitivity analyses assessed the impact of sources of funding, dose of olanzapine, and allocation concealment method on final results. RESULTS: There were 60 RCTs (N=33,360) and 27 observational studies (N=202,591) included. On time to all-cause medication discontinuation, olanzapine was significantly better than aripiprazole, quetiapine, risperidone, ziprasidone and perphenazine for RCTs and better than amisulpride, risperidone, haloperidol, and perphenazine for observational studies. There were no significant differences between olanzapine and clozapine in RCTs or observational studies. All-cause discontinuation rates in RCTs were significantly lower for olanzapine compared to all comparators except amisulpride and clozapine. In observational studies, olanzapine was less effective than clozapine. Industry-sponsored studies favored olanzapine when compared to haloperidol and perphenazine; higher dose of olanzapine favored quetiapine and perphenazine when compared to olanzapine; method of allocation concealment did not generally affect the results. CONCLUSION: Using a global measure of medication effectiveness (time to all-cause medication discontinuation), olanzapine appears to be more effective - in both RCTs and observational studies - than most SGAs and FGAs, except for clozapine.

Empirically driven definitions of "good," "moderate," and "poor" levels of functioning in the treatment of schizophrenia.

PURPOSE: This study used an empirical approach to identify and validate the classification of patients with schizophrenia in "good," "moderate," or "poor" functioning groups based on the assessment of functional measures. METHODS: Using data from a study of schizophrenia outpatients, patients were classified into functional groups using cluster analysis based on the Heinrich-Carpenter Quality of Life Scale (QLS), the 36-item Short-Form Health Survey (SF-36) Mental Component Summary Score, and a productivity measure. A three-cluster solution was chosen. Concurrent, convergent, and discriminant validity were assessed. Criteria for classifying patient functioning as "good," "moderate," or "poor" were established using classification and regression tree analysis. RESULTS: The three clusters consistently differentiated patients on the QLS, SF-36 Mental Component Summary Score, and productivity measure. The clusters also differed on other functional measures and were concordant with previous functional classifications. Concurrent, convergent, and discriminant validity were good. "Good" functioning was identified as a QLS total score ≥ 84.5; "moderate" and "poor" functioning were separated by a cutoff score of 15.5 on the QLS intrapsychic foundation domain. Sensitivity ranged from 86 to 93 % and specificity from 89 to 99 %. CONCLUSIONS: The heterogeneity in functioning of schizophrenia patients can be classified reliably in an empirical manner using specific cutoff scores on commonly used functional measures.