Introduction:The aim of this work is to evaluate baricitinib safety with respect to venous thromboembolism (VTE), major adverse cardiovascular events (MACE), and serious infection relative to tumor necrosis factor inhibitors (TNFi) in patients with rheumatoid arthritis (RA). Methods: Patients with RA from 14 real-world data sources (three disease registries, eight commercial and three government health insurance claims databases) in the United States (n = 9), Europe (n = 3), and Japan (n = 2) were analyzed using a new user active comparator design. Propensity score matching (1:1) controlled for potential confounding. Meta-analysis

Purpose: Large numbers of multiple myeloma patients can be studied in real-world clinical settings using administrative databases. The validity of these studies is contingent upon accurate case identification. Our objective was to develop and evaluate algorithms to use with administrative data to identify multiple myeloma cases.Methods: Patients aged ≥18 years with ≥1 International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code for multiple myeloma (203.0x) were identified at two study sites. At site 1, several algorithms were developed and validated by comparing results to tumor registry cases.An algorithm with a reasonable positive predictive value (PPV) (0.81) and sensitivity (0.73) was selected and then validated at site 2 where results were compared with medical chart data. The algorithm required that ICD-9-CM codes 203.0x occur before and after the diagnostic procedure codes for multiple myeloma.Results: At site 1, we identified 1432 patients. The PPVs of algorithms tested ranged from 0.54 to 0.88. Sensitivities ranged from 0.30 to 0.88. At site 2, a random sample (n = 400) was selected from 3866 patients, and medical charts were reviewed by a clinician for 105 patients. Algorithm PPV was 0.86 (95% CI, 0.79-0.92). Conclusions:We identified cases of multiple myeloma with adequate validity for claims database analyses. At least two ICD-9-CM diagnosis codes 203.0x preceding diagnostic procedure codes for multiple myeloma followed by ICD-9-CM codes within a specific time window after diagnostic procedure codes were required to achieve reasonable algorithm performance. KEYWORDS administrative data, algorithm, ICD-9 codes, multiple myeloma, pharmacoepidemiology, positive predictive value, sensitivity Nancy A. Brandenburg is not currently employed at Celgene. Her role in the study involved conceptualization of the study design and analysis and manuscript development, writing, and review.

In this large, multi-site study, compared with other SGA combined, aripiprazole is not associated with an increased risk of suicide events in an inception cohort of patients with ICD-9/ICD-10 codes indicative of schizophrenia or bipolar disorder.

Objective Refilling an opioid prescription early is an important risk factor of prescription opioid abuse and misuse; we aimed to understand the scope of this behavior. This study was conducted to quantify the prevalence and distribution of early refills among patients prescribed opioids. Methods We conducted a retrospective cohort study utilizing dispensed prescription records. Patients filling one or more prescription opioids were identified and followed for one year. Early refills were defined as having a second prescription filled ≥15% early relative to the days’ supply of the previous prescription for the same opioid (according to the National Drug Code [NDC]). The distribution of the number of early refills and patient characteristics were assessed. Results A total of 60.6 million patients met the study criteria; 28.8% had two or more opioid prescriptions for the same opioid during follow-up. Less than 3% of all patients receiving an opioid had an early refill. Approximately 10% of those with two or more opioid prescriptions for the same drug had an early refill. For patients with multiple fills (N = 1.5 million with extended-release long-acting [ER/LA] opioids; N = 17.1 million with immediate-release short-acting [IR/SA] opioids), early refills were more common among patients with an ER/LA opioid (18.5%) compared with an IR/SA opioid (8.7%). Three-quarters of patients with an early refill had only one (70.9% and 78.4% for ER/LA and IR/SA, respectively). Conclusion Refilling an opioid prescription with the same opioid early is an infrequent behavior within all opioid users, but more common in ER/LA users. Patients who refilled early tended to do so just once.

4424 Background: Understanding adherence in oral CML therapy is an important part of selecting and managing long-term CML treatment. Literature indicates that imatinib adherence ranges widely (14–98%), and data for other BCR-ABL inhibitors (dasatinib and nilotinib) are currently sparse. Imatinib was approved as first-line therapy in the USA in 2001. Dasatinib and nilotinib were approved as first-line therapy at the end of 2010, leading to limited adherence data for this indication. Both dasatinib and nilotinib were approved for second-line therapy earlier in time (dasatinib approved in 2006, nilotinib approved in 2007). As survival rates improve for patients with CML and as multiple frontline therapeutic options exist, it is important to understand medication adherence patterns as part of long-term therapy. Methods: Using the HealthCore Integrated Research Database (HIRD™), we identified patients with ≥1 International Classification of Diseases (9th edition) code for CML (205.1x) and ≥1 prescription for a BCR-ABL inhibitor dispensed 1/1/2001–6/30/2010. We used medication possession ratio (MPR; number of days supply of current prescription divided by total days between current and next prescription) to calculate adherence to treatment. Cox proportional hazard models were used to quantify rates of poor adherence (MPR <85%) comparing nilotinib to dasatinib. Models were adjusted for baseline characteristics, previous imatinib exposure, concomitant medications, and comorbidities. Results: We identified 2,145 patients with a CML diagnosis exposed to a BCR-ABL inhibitor from 2001 to 2010. Among these 2,145 patients, 2,064 received imatinib as first-line therapy, 65 received dasatinib first-line and 16 received nilotinib first-line during this time period. Among the 2,064 first-line imatinib users, 197 received dasatinib and 53 received nilotinib as second-line therapy. Sample size was too small to evaluate adherence in first-line dasatinib and nilotinib users in the current dataset. Among second-line users, mean exposure to dasatinib was 276 days (≤100 mg/day, 275 days; ≥140 mg/day, 276 days) and 170 days for nilotinib. Adjusted Cox proportional hazard ratios comparing poor adherence in nilotinib vs. dasatinib were 1.6 (95% confidence interval [CI] 1.0–2.4) overall, 1.9 (95% CI 1.2–3.0) for nilotinib vs. dasatinib ≤100 mg/day, and 1.2 (95% CI 0.7–2.0) for nilotinib vs. dasatinib ≥140 mg/day. Conclusion: When comparing treatment adherence for second-line CML therapy, overall, patients treated with nilotinb were 60% more likely to have poor adherence than patients receiving dasatinib. Sample size was too small to adequately examine adherence among first-line users. However, the cohort is being extended beyond 2010 and analyses are underway to assess adherence in first-line therapies. Disclosures: Off Label Use: Although dasatinib and nilotinib are now approved for first-line therapy, some patients in our study were prescribed dasatinib or nilotinib before they were approved as first line therapy. In our abstract, we report the number of users who may have been prescribed dasatinib or nilotinib as first-line therapy prior to approval of dasatinib or nilotinib as first-line therapy. Additional analyses may be reported. Hirji:BMS: Employment. Davis:BMS: Employment.