Switching patterns of immediate-release forms of generic mixed amphetamine salts products among privately and publicly insured individuals aged 15-64 years in the United States, 2013-2019.

PURPOSE: Immediate-release forms of generic mixed amphetamine salts (MAS) have been the subject of passive surveillance reports signaling lack of effectiveness. We examined switching patterns that might suggest whether long-term users of specific MAS are more likely to switch away or switch back after use of the MAS of interest in the FDA's Sentinel Distributed Database. METHODS: We required at least 60-day continuous supply of selected MAS grouped by Abbreviated New Drug Application (ANDA) to describe patterns of switching away from and to generics approved under the ANDAs of interest among individuals ages 15-64 years with attention deficit hyperactivity disorder or narcolepsy during 2013-2019. RESULTS: We observed the greatest number of treatment episodes for ANDA 040422 (n = 525 771), followed by ANDA 202424 (n = 181 693), ANDA 040439 (n = 62 363), ANDA 040440 (n = 21 143), and ANDA 040480 (n = 8792). Of those with switches away from their original ANDA, episodes initiated on generic products under ANDA 040422 (48.6%) and ANDA 202424 (43.0%) were most likely to switch back, while those initiated on generic product under ANDA 040480 were least likely (24.1%). Of those episodes with switches to a generic under an ANDA of interest, about one-third (range 27.1% to 37.0%) switched back to the same product. These switches back had a median time to switch of about 30 days. CONCLUSIONS: These descriptive analyses, although subject to limitations, did not suggest increased switching away or switching back after use of the generics of interest. Continued post-marketing surveillance is warranted.

Incidence of Opioid Overdose Among Patients Using ER/LA Opioid Analgesics Before and After Implementation of the Class-Wide Opioid Risk Evaluation and Mitigation Strategy.

INTRODUCTION: The United States (US) Food and Drug Administration (FDA) required a Risk Evaluation and Mitigation Strategy (REMS) for extended-release and long-acting (ER/LA) opioid analgesics on 09 July 2012. METHODS: This study compared the incidence of opioid overdose before (July 2010-June 2012) and after (July 2013-September 2016) the initiation of the Risk Evaluation and Mitigation Strategy (REMS) for extended-release and long-acting (ER/LA) opioid analgesics. We identified patients with ≥1 ER/LA opioid dispensing in either time period in national data from the HealthCore Integrated Research DatabaseSM (HIRD) and in United States (US) Medicaid claims data from four states. We described each population, calculated the incidence rate (IR) of opioid overdose, and assessed crude and propensity score adjusted incidence rate ratios (IRR) comparing the overdose rate after vs before implementation of the REMS. RESULTS: A total of 121,229 commercially insured and 11,488 Medicaid patients were included in the analysis. Rates of overdose were substantially higher in Medicaid patients than in the commercially insured patients (IR 192.0, 95% confidence interval [CI] 162.60-225.18 versus 102.60, 95% CI 93.0-112.93 in the active period). The IRRs for opioid overdose were 1.01 (95% CI 0.87-1.17) in the commercially insured population and 0.70 (95% CI 0.52-0.93) in Medicaid. CONCLUSION: This leveling off of overdose rates among commercially insured patients and decline among Medicaid patients is encouraging, but it is difficult to disentangle the specific impact of the REMS from many other ongoing initiatives with similar goals.

Development of predictive models to identify advanced-stage cancer patients in a US healthcare claims database.

BACKGROUND: Although healthcare databases are a valuable source for real-world oncology data, cancer stage is often lacking. We developed predictive models using claims data to identify metastatic/advanced-stage patients with ovarian cancer, urothelial carcinoma, gastric adenocarcinoma, Merkel cell carcinoma (MCC), and non-small cell lung cancer (NSCLC). METHODS: Patients with ≥1 diagnosis of a cancer of interest were identified in the HealthCore Integrated Research Database (HIRD), a United States (US) healthcare database (2010-2016). Data were linked to three US state cancer registries and the HealthCore Integrated Research Environment Oncology database to identify cancer stage. Predictive models were constructed to estimate the probability of metastatic/advanced stage. Predictors available in the HIRD were identified and coefficients estimated by Least Absolute Shrinkage and Selection Operator (LASSO) regression with cross-validation to control overfitting. Classification error rates and receiver operating characteristic curves were used to select probability thresholds for classifying patients as cases of metastatic/advanced cancer. RESULTS: We used 2723 ovarian cancer, 6522 urothelial carcinoma, 1441 gastric adenocarcinoma, 109 MCC, and 12,373 NSCLC cases of early and metastatic/advanced cancer to develop predictive models. All models had high discrimination (C > 0.85). At thresholds selected for each model, PPVs were all >0.75: ovarian cancer = 0.95 (95% confidence interval [95% CI]: 0.94-0.96), urothelial carcinoma = 0.78 (95% CI: 0.70-0.86), gastric adenocarcinoma = 0.86 (95% CI: 0.83-0.88), MCC = 0.77 (95% CI 0.68-0.89), and NSCLC = 0.91 (95% CI 0.90 - 0.92). CONCLUSION: Predictive modeling was used to identify five types of metastatic/advanced cancer in a healthcare claims database with greater accuracy than previous methods.

Patient and prescriber characteristics among patients with type 2 diabetes mellitus continuing or discontinuing sulfonylureas following insulin initiation: data from a large commercial database.

OBJECTIVE: To describe patient and provider characteristics for patients with type 2 diabetes (T2DM) initiating basal insulin and describe basal insulin's impact on sulfonylurea (SU) discontinuation. METHODS: A retrospective cohort study was conducted using the HealthCore Integrated Research Database. Patients had ≥12 months of continuous coverage prior to initiating insulin, and were utilizing at least one anti-hyperglycemic drug at the time of insulin initiation. Predictors for SU discontinuation were evaluated utilizing Cox proportional hazards models. RESULTS: Among the 74,334 individuals aged ≥18 years with T2DM who initiated basal insulin from 2006-2015, 30% were taking metformin (MET) and SU when initiating insulin. Among the 22,418 MET/SU patients, 31% discontinued SU within 3 months of insulin initiation and, by 12 months, 55% had discontinued SU. Sulfonylurea discontinuation was similar among many patient and provider characteristics, while being modestly positively associated (p < .05; HRs <1.5) with female gender, more co-morbidities, cardiac revascularization, chronic liver disease, hospitalizations with a T2DM diagnosis, and hypoglycemia prior to insulin initiation. SU discontinuation was modestly inversely associated with receiving an insulin prescription from an endocrinologist (HR = 0.90, 95% CI = 0.85-0.95). CONCLUSIONS: Roughly half of commercially-insured T2DM patients discontinued SU within 1 year after insulin initiation, and SU discontinuation was not strongly associated with a range of patient and provider characteristics.

Slow Gait Speed and Risk of Long-Term Nursing Home Residence in Older Women, Adjusting for Competing Risk of Mortality: Results from the Study of Osteoporotic Fractures.

OBJECTIVES: To determine whether slow gait speed increases the risk of costly long-term nursing home residence when accounting for death as a competing risk remains unknown. DESIGN: Longitudinal cohort study using proportional hazards models to predict long-term nursing home residence and subdistribution models with death as a competing risk. SETTING: Community-based prospective cohort study. PARTICIPANTS: Older women (mean age 76.3) participating in the Study of Osteoporotic Fractures who were also enrolled in Medicare fee-for-service plans (N = 3,755). MEASUREMENTS: Gait speed was measured on a straight 6-m course and averaged over two trials. Long-term nursing home residence was defined using a validated algorithm based on Medicare Part B claims for nursing home-related care. RESULTS: Participants were followed until long-term nursing home residence, disenrollment from Medicare plan, death, or December 31, 2010. Over the follow-up period (median 11 years), 881 participants (23%) experienced long-term nursing home residence, and 1,013 (27%) died before experiencing this outcome. Slow walkers (55% of participants with gait speed <1 m/s) were significantly more likely than fast walkers to reside in a nursing home long-term (adjusted hazards ratio (aHR) = 1.79, 95% confidence interval (CI) = 1.54-2.09). Associations were attenuated in subdistribution models (aHR = 1.52, 95% CI = 1.30-1.77) but remained statistically significant. CONCLUSION: Older community-dwelling women with slow gait speed are more likely to experience long-term nursing home residence, as well as mortality without long-term residence. Ignoring the competing mortality risk may overestimate long-term care needs and costs.