Treatment patterns in Medicaid patients with schizophrenia initiated on a first- or second-generation long-acting injectable versus oral antipsychotic

Dominic Pilon,1 Kruti Joshi,2 Neeta Tandon,2 Marie-Hélène Lafeuille,1 Rhiannon L Kamstra,1 Bruno Emond,1 Patrick Lefebvre2 1Groupe d’analyse, Ltée, Montréal, QC, Canada; 2Janssen Scientific Affairs, LLC, Titusville, NJ, USA Background: Poor antipsychotic (AP) adherence is a key issue in patients with schizophrenia. First-generation antipsychotic (FGA) and second-generation antipsychotic (SGA) long-acting injectable therapies (LAI) may improve adherence compared to oral antipsychotics (OAP). The objective of the study was to compare treatment adherence and persistence in Medicaid patients with schizophrenia initiated on first-generation long-acting injectable therapies (FGA-LAI) or second-generation long-acting injectable therapies (SGA-LAI) versus OAP.Methods: Adults with schizophrenia initiated on FGA-LAI, SGA-LAI, or OAP on or after January 2010 were identified using a six-state Medicaid database (January 2009– March 2015). Outcomes were assessed during the 12 months following treatment initiation. Index medication adherence was assessed using the proportion of days covered ≥80%, while persistence was assessed as no gap of ≥30, ≥60, or ≥90 days between days of supply. Outcomes were compared between FGA/SGA-LAI and OAP cohorts using chi-squared tests and adjusted odds ratios (OR).Results: During follow-up, AP polypharmacy was more common in FGA-LAI patients (N=1,089; 36%; P=0.029) and less common in SGA-LAI patients (N=2,209; 27%; P<0.001) versus OAP patients (N=20,478; 33%). After adjustment, SGA-LAI patients had 24% higher odds of adherence at 12 months (OR: 1.24; P<0.001), in contrast to FGA-LAI patients who had 48% lower odds of adherence (OR: 0.52; P<0.001) relative to OAP patients. SGA-LAI patients were more likely to be persistent (no gap ≥60 days) at 12 months than OAP patients (37% vs 30%; P<0.001), but not FGA-LAI patients (31% vs 30%; P=0.776). In comparison to OAP patients, SGA-LAI patients had 46% higher adjusted odds of persistence (no gap ≥60 days; OR: 1.46; P<0.001), while FGA-LAI patients were not significantly different (OR: 0.95; P=0.501).Conclusion: Medicaid patients initiated on SGA-LAI demonstrated better treatment adherence and persistence compared to OAP patients, while those initiated on FGA-LAI did not show significant improvement in adherence or persistence and had more AP polypharmacy relative to OAP patients. These findings suggest the potential value of SGA-LAI in the treatment of schizophrenia. Keywords: schizophrenia, long-acting injectable therapy, adherence, persistence, first generation, second generatio

Health characteristics of patients with asthma, COPD and asthma–COPD overlap in the NHANES database

Jean-Pierre Llanos,1 Hector Ortega,2 Guillaume Germain,3 Mei Sheng Duh,4 Marie-Helene Lafeuille,3 Sean Tiggelaar,3 Christopher F Bell1, Beth Hahn1 1US Medical Affairs, GSK, Research Triangle Park, NC, USA; 2US Medical Affairs, GSK, La Jolla, CA, USA; 3Groupe d’Analyse, Ltée, Montréal, QC, Canada; 4Analysis Group, Inc., Boston, MA, USA Introduction: Asthma and COPD have overlapping characteristics. As there are limited data on whether asthma–COPD overlap (ACO) represents a distinct condition, this study aimed to determine the similarities and differences of ACO with asthma and COPD.Methods: US population-based, cross-sectional study using National Health and Nutrition Examination Survey data (2009–2012) compared participants with ACO vs those with asthma or COPD, each as mutually exclusive disease states. Demographics, health status, disability/limitations, health care resource utilization, clinical characteristics, and peripheral blood eosinophil counts were analyzed.Results: A total of 1,609, 479, and 299 participants with asthma, COPD, and ACO, respectively, were included. An age-matched asthma subgroup included 299 participants from the asthma group. Compared with asthma and COPD, participants with ACO had worse health status, increased disease burden, and more comorbid conditions. The ACO, vs age-matched asthma subgroup, had lower percent predicted prebronchodilator forced expiratory volume in 1 second (82.1% vs 88.0%; P=0.017). The ACO group had significantly more asthma attacks in the past year than the age-matched asthma subgroup (49.8% vs 38.4%; P<0.001). The ACO group had more participants with postbronchodilator forced expiratory volume in 1 second <80% predicted (52.1%) vs COPD (30.8%; P=0.003) and more participants with blood eosinophil counts ≥400 cells/µL (16.9%) vs COPD (9.5%; P=0.007) and the asthma subgroup (6.7%; P=0.014).Conclusion: The ACO group represents an important subset of patients with chronic respiratory disease with an increased burden of disease over asthma and COPD individually. Early identification of this population will enable appropriate therapeutic interventions in a timely manner. Keywords: lung function, health status, eosinophils, asthma attack, respiratory diseas

Development of predictive risk models for major adverse cardiovascular events among patients with type 2 diabetes mellitus using health insurance claims data

Abstract Background There exist several predictive risk models for cardiovascular disease (CVD), including some developed specifically for patients with type 2 diabetes mellitus (T2DM). However, the models developed for a diabetic population are based on information derived from medical records or laboratory results, which are not typically available to entities like payers or quality of care organizations. The objective of this study is to develop and validate models predicting the risk of cardiovascular events in patients with T2DM based on medical insurance claims data. Methods Patients with T2DM aged 50 years or older were identified from the Optum™ Integrated Real World Evidence Electronic Health Records and Claims de-identified database (10/01/2006–09/30/2016). Risk factors were assessed over a 12-month baseline period and cardiovascular events were monitored from the end of the baseline period until end of data availability, continuous enrollment, or death. Risk models were developed using logistic regressions separately for patients with and without prior CVD, and for each outcome: (1) major adverse cardiovascular events (MACE; i.e., non-fatal myocardial infarction, non-fatal stroke, CVD-related death); (2) any MACE, hospitalization for unstable angina, or hospitalization for congestive heart failure; (3) CVD-related death. Models were developed and validated on 70% and 30% of the sample, respectively. Model performance was assessed using C-statistics. Results A total of 181,619 patients were identified, including 136,544 (75.2%) without prior CVD and 45,075 (24.8%) with a history of CVD. Age, diabetes-related hospitalizations, prior CVD diagnoses and chronic pulmonary disease were the most important predictors across all models. C-statistics ranged from 0.70 to 0.81, indicating that the models performed well. The additional inclusion of risk factors derived from pharmacy claims (e.g., use of antihypertensive, and use of antihyperglycemic) or from medical records and laboratory measures (e.g., hemoglobin A1c, urine albumin to creatinine ratio) only marginally improved the performance of the models. Conclusion The claims-based models developed could reliably predict the risk of cardiovascular events in T2DM patients, without requiring pharmacy claims or laboratory measures. These models could be relevant for providers and payers and help implement approaches to prevent cardiovascular events in high-risk diabetic patients