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Aim When selecting treatments for type 2 diabetes (T2D), it is important to consider not only efficacy and safety, but also other treatment attributes that have an impact on patient preference. The objective of this study was to examine preference between injection devices used for two weekly GLP‐1 receptor agonists. Materials and Methods The PREFER study was an open‐label, multicentre, randomized, crossover study assessing patient preference for dulaglutide and semaglutide injection devices among injection‐naïve patients receiving oral medication for type 2 diabetes. After being trained to use each device, participants performed all steps of injection preparation and administered mock injections into an injection pad. Time‐to‐train (TTT) for each device was assessed in a subset. Results There were 310 evaluable participants (48.4% female; mean age, 60.0 years; 78 participants in the TTT subgroup). More participants preferred the dulaglutide device than the semaglutide device (84.2% vs. 12.3%; P

Nancy K Leidy,1 Fernando J Martinez,2 Karen G Malley,1 David M Mannino,3 MeiLan K Han,4 Elizabeth D Bacci,5 Randall W Brown,6 Julia F Houfek,7 Wassim W Labaki,4 Barry J Make,8 Catherine A Meldrum,4 Wilson Quezada,9 Stephen Rennard,10 Byron Thomashow,9 Barbara P Yawn11 1Evidera, Patient-Centered Research, Bethesda, MD, USA; 2Weill Cornell Medicine, Joan & Sanford Weill Department of Medicine, New York, NY, USA; 3University of Kentucky, Preventive Medicine & Environmental Health, Lexington, KY, USA; 4University of Michigan, Division of Pulmonary & Critical Care Medicine, Ann Arbor, MI, USA; 5Evidera, Patient-Centered Research, Seattle, WA, USA; 6University of Michigan, Department of Health Behavior & Health Education, School of Public Health, Ann Arbor, MI, USA; 7University of Nebraska Medical Center College of Nursing, Omaha, NE, USA; 8National Jewish Health, Department of Medicine, Division of Pulmonary, Critical Care & Sleep Medicine, Denver, CO, USA; 9Columbia University Medical Center, Division of Pulmonary, Allergy, & Critical Care, New York, NY, USA; 10AstraZeneca, IMED Biotech Unit, Cambridge, UK & University of Nebraska Medical Center, Department of Medicine, Omaha, NE, USA; 11University of Minnesota, Department of Family & Community Health, Minneapolis, MN & COPD Foundation, Miami, FL, USA Background: COPD Assessment in Primary Care To Identify Undiagnosed Respiratory Disease and Exacerbation Risk (CAPTURE™) uses five questions and peak expiratory flow (PEF) thresholds (males ≤350 L/min; females ≤250 L/min) to identify patients with a forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC) 2: 37% vs 5%, p10: 86% vs 57%, p

Rationale This study is part of a larger, multi-method project to develop a questionnaire for identifying undiagnosed cases of chronic obstructive pulmonary disease (COPD) in primary care settings, with specific interest in the detection of patients with moderate to severe airway obstruction or risk of exacerbation. Objectives To examine 3 existing datasets for insight into key features of COPD that could be useful in the identification of undiagnosed COPD. Methods Random forests analyses were applied to the following databases: COPD Foundation Peak Flow Study Cohort (N=5761), Burden of Obstructive Lung Disease (BOLD) Kentucky site (N=508), and COPDGene® (N=10,214). Four scenarios were examined to find the best, smallest sets of variables that distinguished cases and controls:(1) moderate to severe COPD (forced expiratory volume in 1 second [FEV1] Results From 4 to 8 variables were able to differentiate cases from controls, with sensitivity ≥73 (range: 73-90) and specificity >68 (range: 68-93). Across scenarios, the best models included age, smoking status or history, symptoms (cough, wheeze, phlegm), general or breathing-related activity limitation, episodes of acute bronchitis, and/or missed work days and non-work activities due to breathing or health. Conclusions Results provide insight into variables that should be considered during the development of candidate items for a new questionnaire to identify undiagnosed cases of clinically significant COPD.

Rationale: Chronic obstructive pulmonary disease (COPD) is often unrecognized and untreated.Objectives: To develop a method for identifying undiagnosed COPD requiring treatment with currently available therapies (FEV1

Background: Validated algorithms for identifying progression to metastatic cancer could permit the use of administrative claims databases for research in this area. Objective: To identify simple algorithms that could accurately detect cancer progression to metastatic breast, non-small cell lung, and colorectal cancer using medical and pharmacy claims data. Methods: Adults with stage I–III breast, non-small cell lung cancer (NSCLC), or colorectal cancer (CRC) in the Geisinger Health System from 2004–2011 were selected. Evidence of progression was extracted via manual chart review as the reference standard. In addition to secondary malignancy diagnosis (ICD-9 code for metastases), diagnoses, procedures, and treatments were selected with clinician input as indicators of cancer progression. Random forests models provided variable importance scores. In addition to codes for secondary malignancy, several more complex algorithms were constructed and performance measures calculated. Results: Among those with breast cancer (17/502 [3.4%] progressed), the performance of a secondary malignancy code was suboptimal (sensitivity: 64.7%; specificity: 86.0%; positive predictive value [PPV]: 13.9; negative predictive value [NPV]: 98.6%); requiring malignancy at another site or initiation of immunotherapy increased PPV and specificity but decreased sensitivity. For NSCLC (61/236 [25.8%] progressed) codes for secondary malignancy alone (PPV: 47.4%; NPV: 84.8%; sensitivity: 60.7%; specificity: 76.6%) performed similarly or better than more complex algorithms. For CRC (33/276 [12.0%] progressed), secondary malignancy codes had good specificity (92.7%) and NPV (92.3%) but low sensitivity (42.4%) and PPV (43.8%); an algorithm with change in chemotherapy increased sensitivity but decreased other metrics. Conclusions: Selected algorithms performed similarly to the presence of a secondary tumor diagnosis code, with low sensitivity/PPV and higher specificity/NPV. Accurate identification of cancer progression likely requires verification through chart review.

This study (1) used patient-reported outcome measures to assess and compare the health status of type 2 diabetes patients with and without obesity and (2) assessed the value of weight change among obese and non-obese subgroups, using standard gamble (SG) utility methodology.Among a sample with type 2 diabetes in the United Kingdom, individuals with obesity (BMIor = 30 kg/m2) were identified and compared to non-obese patients. Patients completed the EQ-5D, Psychological General Well-Being Index, Appraisal of Diabetes Symptoms, and Diabetes Symptom Checklist-Revised (DSC-R). SG interviews assessed the utility of the 'basic' type 2 diabetes health state anchored to respondents' body weight, as well as health states with altered weight.A total of 129 patients (74 obese; 55 non-obese) completed interviews (mean age 55.9 years; 64.3% male). Obese patients reported lower health status (EQ-5D VAS; between-group difference: p0.001) and greater symptom impact (several DSC-R scales, p0.05). Utilities of the basic health state were 0.86 (obese) and 0.91 (non-obese; p = 0.02). Hypothetical health states with higher weight received lower utilities, whereas reduced weight was associated with increased utility. There was a between-group difference in the disutility associated with 5% higher weight (obese 0.068; non-obese 0.051; p = 0.03).Compared with non-obese patients, the obese group reported lower health status and greater symptom impact. SG interviews found an inverse relationship between weight and utility. Furthermore, obese patients with type 2 diabetes may value weight change differently than non-obese patients. Study limitations include the sample size and the use of a patient sample, rather than a sample selected from the general population. Overall, the results demonstrate that utilities can differ by patient subgroups, even among patients with the same diagnosis.

Background: COPD is underdiagnosed, often uncovered during exacerbations or after significant loss of lung function. We are developing a new method (simple questionnaire + peak expiratory flow [PEF]) for identifying patients needing spirometric evaluation for clinically significant COPD (FEV1 Purpose: This study used random forests (RF) to identify the best, smallest set of questions (with and without PEF) capable of case identification. Methods: Prospective, cross-sectional, multi-site, case-control study. Subjects: ≥40 years from US pulmonary and primary care clinics. Cases (clinically significant COPD): ≥1 AECOPD past 12 months or FEV1 60% pred) and AECOPD-free ≥12 months or no COPD. Subjects completed questionnaires, PEF, spirometry (if not on record). Results: N=346; 186 Cases (184 with PEF), 160 Controls. Mean (SD) age=62.7 (10.1) years; 55% female; 86% white; 41% ≤high school; 16% never smoked. Cases: mean (SD) FEV1% pred=42.5(14.2); Controls=82.5(15.7). RF case-control sensitivity/specificity estimates for the final 5-item questionnaire: 83.5/69.7; questionnaire followed by score-driven use of PEF: 90.2/78.8%. Case-no COPD with score-driven PEF: 90.2/92.0. Questions ask about exposure, breathing, tire easily, and acute respiratory illness, and do not ask about smoking, cough, or sputum. Conclusions: These 5 questions + selective use of PEF may be an effective and efficient approach for identifying patients needing diagnostic evaluation for COPD.

Objective To determine whether patients in whom myositis develops after they receive silicone breast implants have distinct clinical, serologic, and/or immunogenetic features compared with patients with myositis who do not have silicone implants. Methods A preliminary case series study was followed by a larger, independent, matched case–control study to evaluate women in whom myositis developed after they received silicone implants (MASI patients) compared with healthy women with silicone implants and women with myositis but without silicone implants (idiopathic inflammatory myopathy; IIM patients). Results In a preliminary study, 11 MASI patients differed from 76 IIM patients in having an increased frequency of HLA–DQA1*0102 (odds ratio [OR] 9.8, 95% confidence interval [95% CI] 1.77–96.79) and decreased frequencies of the myositis-associated risk factor DRB1*0301 (OR 0.1 [95% CI 0.002–0.63]) and its linked allele DQA1*0501 (OR 0.2 [95% CI 0.02–0.87]). A subsequent independent, matched case–control study revealed that although clinical features and autoantibodies did not differ significantly between the MASI and IIM groups, MASI patients again had decreased frequencies of DRB1*0301 (OR 0.2 [95% CI 0.07–0.72]) and DQA1*0501 (OR 0.2 [95% CI 0.08–0.84]) compared with IIM patients. Additional comparisons between MASI patients from both studies combined (n = 37) and a larger population of IIM patients (n = 453) suggested that HLA–DQA1*0102 may be uniquely associated with MASI (OR 2.6 [95% CI 1.25–5.46]). Conclusion Women in whom inflammatory myopathy develops after they receive silicone implants constitute an immunogenetically distinct group of patients with myositis. These and other data suggest that autoimmune diseases as now defined may consist of multiple distinct entities, each of which is characterized by different genes and environmental exposures.

Background/Purpose: The myositis syndromes are rare systemic autoimmune diseases with poorly understood etiologies. We present the demographics, illness features and treatments of patients with juvenile dermatomyositis (JDM) who enrolled in a newly created national registry. Methods: Using a patient database from The Myositis Association and supplemental advertisements, a national registry of myositis patients was established. Between December 2010 and July 2012 questionnaires were mailed to 8847 myositis patients in the US and Canada. The questionnaire queried demographics, clinical features, environmental exposures, and quality of life. Descriptive statistics and multivariable logistic regression analysis were computed using GraphPad Prysm and SAS. Results: 1956 patients (22%) returned the questionnaire and consented to participate; 1806 who met probable or definite Bohan and Peter criteria for myositis were included (708 DM, 483 PM, 466 IBM, 139 JDM, 10 JPM); juvenile patients were diagnosed before age 18 years. Of the 139 JDM patients, the median age at diagnosis was 6.9 years and median disease duration at enrollment was 10.3 years. Most JDM patients were female (78%) and Non-Hispanic Caucasian (88%), and the remainder were Hispanic (6.5%), Asian (2.9%), multiple races (2.2%), and Black (0.7%). Patients or their parents often completed a graduate degree (23%) or college degree (29%). JDM patients were primarily diagnosed by a pediatric rheumatologist (48%), with adult and pediatric dermatologists (22%), pediatric neurologists and primary care physicians (11% each) diagnosing most of the remaining patients; 67% were under the care of a pediatric rheumatologist. JDM patients frequently had skin rashes as a major manifestation (86%); arthritis (35%) and dysphagia (32%) were also common, whereas lung disease (12%) was less frequent. An additional autoimmune disease was present in 18% of JDM patients, with JIA (8%) and SLE and celiac disease (3% each) the most frequent. There were no recorded associated malignancies. 98% of JDM patients received prednisone therapy. Methotrexate was the most common steroid-sparing agent (84%), followed by hydroxychloroquine (60%), IV pulse solumedrol (54%), IVIG (48%), cyclosporine (19%), rituximab and anti-TNFs (10% each). Predictors of which agents were received varied among medications, but included age, year of JDM diagnosis, gender, and region of country. Pulse solumedrol and cyclosporine were more likely to be used in JDM patients with dysphagia, hydroxychloroquine in patients with skin rashes and less likely in those with fevers, and azathioprine was less likely in patients with arthritis. Of medications utilized, 45% of JDM patients reported responding best to IVIG, 39% responded best to prednisone, 33% to anti-TNFs, and 29% to cyclophosphamide. Conclusion: A nationwide myositis registry has been established and includes a subsample of JDM patients that appears demographically and clinically representative of other US populations. This registry may help identify environmental exposures associated with myositis, elucidate factors associated with quality of life, and serve as an important resource for future clinical investigations.

Background Patient-reported measures can be used to examine whether drug differences other than clinical efficacy have an impact on outcomes that may be important to patients. Although exenatide and insulin glargine appear to have similar efficacy for treatment of type 2 diabetes, there are several differences between the two treatments that could influence outcomes from the patient's perspective. The purpose of the current study was to examine whether the two drugs were comparable as assessed by patient-reported outcomes using data from a clinical trial in which these injectable medications were added to pre-existing oral treatment regimens. Methods Patients were randomized to either twice daily exenatide or once daily insulin glargine during a 26-week international trial. At baseline and endpoint, five patient-reported outcome measures were administered: the Vitality Scale of the SF-36, The Diabetes Symptom Checklist – Revised (DSC-R), the EuroQol EQ-5D, the Treatment Flexibility Scale (TFS), and the Diabetes Treatment Satisfaction Questionnaire (DTSQ). Change from baseline to endpoint was analyzed within each treatment group. Group differences were examined with General linear models (GLMs), controlling for country and baseline scores. Results A total of 549 patients with type 2 diabetes were enrolled in the trial, and current analyses were conducted with data from the 455 per protocol patients (228 exenatide and 227 insulin glargine). The sample was primarily Caucasian (79.6%), with slightly more men (55.2%) than women, and with a mean age of 58.5 years. Paired t-tests found that both treatment groups demonstrated statistically significant baseline to endpoint change on several of the health outcomes instruments including the DSC-R, DTSQ, and the SF-36 Vitality subscale. GLMs found no statistically significant differences between groups in change on the health outcomes instruments. Conclusion This analysis found that both exenatide and insulin glargine were associated with significant improvements in patient-reported outcomes when added to oral medications among patients with type 2 diabetes. Despite an additional daily injection and a higher rate of gastrointestinal adverse events, treatment satisfaction in the exenatide group was comparable to that of the glargine group, possibly because of weight reduction observed in patients treated with exenatide.