Transthyretin amyloid cardiomyopathy among patients hospitalized for heart failure and performance of an adapted wild-type ATTR-CM machine learning model: Findings from GWTG-HF.

BACKGROUND: An 11-factor random forest model has been developed among ambulatory heart failure (HF) patients for identifying potential wild-type amyloidogenic TTR cardiomyopathy (wtATTR-CM). The model has not been evaluated in a large sample of patients hospitalized for HF. METHODS: This study included Medicare beneficiaries aged ≥65 years hospitalized for HF in the Get With The Guidelines-HF® Registry from 2008-2019. Patients with and without a diagnosis of ATTR-CM were compared, as defined by inpatient and outpatient claims data within 6 months pre- or post-index hospitalization. Within a cohort matched 1:1 by age and sex, univariable logistic regression was used to evaluate relationships between ATTR-CM and each of the 11 factors of the established model. Discrimination and calibration of the 11-factor model were assessed. RESULTS: Among 205,545 patients (median age 81 years) hospitalized for HF across 608 hospitals, 627 patients (0.31%) had a diagnosis code for ATTR-CM. Univariable analysis within the 1:1 matched cohort of each of the 11-factors in the ATTR-CM model found pericardial effusion, carpal tunnel syndrome, lumbar spinal stenosis, and elevated serum enzymes (e.g., troponin elevation) to be strongly associated with ATTR-CM. The 11-factor model showed modest discrimination (c-statistic 0.65) and good calibration within the matched cohort. CONCLUSIONS: Among US patients hospitalized for HF, the number of patients with ATTR-CM defined by diagnosis codes on an inpatient/outpatient claim within 6 months of admission was low. Most factors within the prior 11-factor model were associated with greater odds of ATTR-CM diagnosis. In this population, the ATTR-CM model demonstrated modest discrimination.

EstimATTR: A Simplified, Machine-Learning-Based Tool to Predict the Risk of Wild-Type Transthyretin Amyloid Cardiomyopathy.

BACKGROUND: Wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM), an increasingly recognized cause of heart failure (HF), often remains undiagnosed until later stages of the disease. METHODS AND RESULTS: A previously developed machine learning algorithm was simplified to create a random forest model based on 11 selected phenotypes predictive of ATTRwt-CM to estimate ATTRwt-CM risk in hypothetical patient scenarios. Using U.S. medical claims datasets (IQVIA), International Classification of Diseases codes were extracted to identify a training cohort of patients with ATTRwt-CM (cases) or nonamyloid HF (controls). After assessment in a 20% test sample of the training cohort, model performance was validated in cohorts of patients with International Classification of Diseases codes for ATTRwt-CM or cardiac amyloidosis vs nonamyloid HF derived from medical claims (IQVIA) or electronic health records (Optum). The simplified model performed well in identifying patients with ATTRwt-CM vs nonamyloid HF in the test sample, with an accuracy of 74%, sensitivity of 77%, specificity of 72%, and area under the curve of 0.82; robust performance was also observed in the validation cohorts. CONCLUSIONS: This simplified machine learning model accurately estimated the empirical probability of ATTRwt-CM in administrative datasets, suggesting it may serve as an easily implementable tool for clinical assessment of patient risk for ATTRwt-CM in the clinical setting. BRIEF LAY SUMMARY: Wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM for short) is a frequently overlooked cause of heart failure. Finding ATTRwt-CM early is important because the disease can worsen rapidly without treatment. Researchers developed a computer program that predicts the risk of ATTRwt-CM in patients with heart failure. In this study, the program was used to check for 11 medical conditions linked to ATTRwt-CM in the medical claims records of patients with heart failure. The program was 74% accurate in identifying ATTRwt-CM in patients with heart failure and was then used to develop an educational online tool for doctors (the wtATTR-CM estimATTR).

Transthyretin amyloid cardiomyopathy in women: frequency, characteristics, and diagnostic challenges.

Transthyretin amyloid cardiomyopathy (ATTR-CM) is a progressive, life-threatening disease characterized by deposition of insoluble amyloid fibrils in the myocardium, resulting in cardiac structural and functional abnormalities and ultimately heart failure. Disease frequency is reportedly lower in women than men, but sex-related differences have not been well established. We conducted a systematic literature review (SLR), based on PRISMA-P guidelines and registered with PROSPERO, to assess whether the epidemiology and clinical presentation of ATTR-CM differ between women and men. MEDLINE, Embase, and Cochrane databases and selected conference proceedings were searched (August 16, 2019) to identify observational and clinical studies reporting sex-specific data for patients with wild-type or hereditary ATTR-CM. Of 193 publications satisfying final eligibility criteria, 69 studies were included in our pooled analysis. Among the 4669 patients with ATTR-CM analyzed, 791 (17%) were women, including 174 (9%), 366 (29%), and 251 (18%) in studies of wild-type, hereditary, and undefined ATTR-CM, respectively. Data available on disease characteristics were limited and very heterogeneous, but trends suggested some cardiac structural/functional differences, i.e., lower interventricular septal and posterior wall thickness and left ventricular (LV) end diastolic diameter, and higher LV ejection fractions, in women versus men across ATTR-CM subtypes. Because LV wall thickness > 12 mm is generally the suggested threshold for ATTR-CM diagnosis in both sexes, smaller cardiac anatomy in women with the disease may lead to underdiagnosis. Additional research and studies are needed to elucidate potential disparities between sexes in ATTR-CM frequency, clinical characteristics, and underlying biological mechanisms. This study was registered within the International Prospective Register of Systematic Reviews (PROSPERO) database of the University of York (CRD42019146995).

Benefits of quitting smoking on work productivity and activity impairment in the United States, the European Union and China.

BACKGROUND: Smoking has important health and economic consequences for individuals and society. This study expands the understanding of work-related burden associated with smoking and benefit of smoking cessation across the US, European Union (EU) and China using large-scale, representative survey methodology. METHODS: Data utilised the 2013 National Health and Wellness Survey in United States (US), EU5 (UK, France, Germany, Italy, and Spain) and China. Working-aged respondents 18-64 were used in the analyses (US N=58 500; EU5 N=50 417; China N=17 987) and were categorised into: current smokers, trying to quit, former smokers and never smokers. Generalised linear models controlling for demographics and health characteristics examined the relationship of smoking status with work productivity and activity impairment (WPAI-GH). The WPAI-GH measures were: absenteeism, presenteeism, overall work impairment, and activity impairment. Separately, current smokers were compared with those who quit 0-4, 5-10 and 11 or more years ago on WPAI-GH end-points. RESULTS: Current smokers reported greater absenteeism in the US and China and greater presenteeism, overall work impairment, and activity impairment than former and never smokers across the three regions. Those who quit even 0-4 years ago demonstrated lower absenteeism, presenteeism, and activity impairment in China and lower presenteeism, overall work impairment, and activity impairment in the US and EU5. CONCLUSIONS: Smoking was associated with significant work productivity loss in the US, EU5 and China. The results suggest that quitting benefits extend to work productivity rapidly after cessation, serving to further encourage and promote the implementation of workplace cessation programs.

Clinical characteristics and health care resource use of patients at risk for wild-type transthyretin amyloid cardiomyopathy identified by machine learning model.

BACKGROUND: Transthyretin amyloid cardiomyopathy (ATTR-CM) is a progressive, life-threatening systemic disorder that is an underrecognized cause of heart failure (HF). When the diagnosis of wild-type ATTR-CM (ATTRwt-CM) is delayed, patients often undergo additional assessments, deferring appropriate management as symptoms potentially worsen. Prompt recognition of patients at risk for ATTRwt-CM is essential to facilitate earlier diagnosis and disease-modifying treatment. A previously developed machine learning model performed well in identifying ATTRwt-CM in patients with HF vs controls with nonamyloid HF using medical claims/electronic health records, providing a systematic framework to raise disease suspicion. OBJECTIVE: To further evaluate this model's performance in identifying ATTRwt-CM using a large claims database of older adults with HF and confirmed ATTRwt-CM or nonamyloid HF; and to explore the characteristics and health care resource utilization (HCRU) of patients with confirmed and suspected ATTRwt-CM. METHODS: In this retrospective study, the prior model was applied using Humana administrative claims for patients diagnosed with ATTRwt-CM (cases) and nonamyloid HF (controls [1:1]). Patients were aged 65-89 years, had at least 2 claims for HF diagnosis (2015-2020), and were continuously enrolled in a Medicare Advantage prescription drug plan for at least 12 months before and at least 6 months after HF diagnosis. For the assessment of characteristics and HCRU, the suspected risk level was categorized based on the predicted probability (PP) from model output (high, moderate, and low risk: PP≥0.70; ≥0.50 and < 0.70; and < 0.50, respectively). RESULTS: Of 267,025 eligible patients, 119 (0.04%) had confirmed ATTRwt-CM; of 266,906 patients with nonamyloid HF, 10,997 (4.1%), 68,174 (25.5%), and 187,735 (70.3%) were categorized as high, moderate, and low risk for ATTRwt-CM, respectively. The model demonstrated sensitivity/specificity/accuracy/receiver operating characteristic area under the concentration-time curve of 88%/65%/77%/0.89, respectively, in differentiating ATTRwt-CM from nonamyloid HF. In patients with confirmed ATTRwt-CM, the mean (SD) time between HF and ATTRwt-CM diagnoses was 751 (528) days; 65% and 48% were hospitalized before and after ATTRwt-CM diagnosis, respectively. Atrial fibrillation was more common in patients with confirmed ATTRwt-CM and high risk (39% and 55%) vs low risk (27%). Hospitalization and emergency department visits after HF diagnosis were reported in 57% and 46% of patients with high ATTRwt-CM risk, respectively. CONCLUSIONS: The ATTRwt-CM predictive model performed well in identifying disease risk in the Humana Research Database. Patients at high risk for ATTRwt-CM had high HCRU and may benefit from the earlier suspicion of ATTRwt-CM. The model may be used as a tool to identify patients with a suspected high risk for the disease to facilitate earlier detection and treatment. DISCLOSURES: This study was sponsored by Pfizer. Medical writing support was provided by Donna McGuire of Engage Scientific Solutions and funded by Pfizer. Drs Bruno and Schepart and Mr Casey are currently employees of Pfizer and equity holders in this publicly traded company. Dr Reed was an employee of Pfizer at the time that this analysis was planned and conducted. Mr Sheer and Dr Simmons are currently employees of Humana, which received research funding from Pfizer. Dr Nair was an employee of Humana at the time that this analysis was planned and conducted.

Real-World Characteristics of Patients with Wild-Type Transthyretin Amyloid Cardiomyopathy: An Analysis of Electronic Healthcare Records in the United States.

BACKGROUND: Tafamidis was approved for the treatment of hereditary and wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM) in May 2019, based on findings from the Tafamidis in Transthyretin Cardiomyopathy Clinical Trial (ATTR-ACT). METHODS: This retrospective cohort study evaluated the factors associated with tafamidis prescription after diagnosis of ATTRwt-CM in the real world. Between May 2019 and December 2020, 430 patients with 6 months' database activity were indexed from the de-identified US Optum electronic healthcare records at first diagnosis of ATTRwt-CM or prescription of tafamidis, then followed until last activity or death. Of these, 209 patients were prescribed tafamidis during follow-up, 167 (80%) within 1 month, 98% by 6 months, and 100% by 9 months. Median time from index to tafamidis prescription, calculated using the Kaplan-Meier method, was 5.8 months (95% confidence interval [CI] 2.4-not evaluable). RESULTS: Factors associated with tafamidis prescription in a multivariable Cox proportional hazards regression (hazard ratio [95% CI]) included age ≥ 65 years (2.1 [1.07-4.05]), male sex (1.6 [1.07-2.28]), having heart failure/cardiomyopathy (2.4 [1.54-3.82]), and having had technetium-99m pyrophosphate myocardial scintigraphy (1.7 [1.28-2.28]). CONCLUSIONS: The clinical characteristics of patients with ATTRwt-CM who were prescribed tafamidis in the real world were broadly comparable with those who took part in ATTR-ACT. Further studies are needed to evaluate hereditary and ATTRwt-CM patient populations in the real world and assess the long-term outcomes associated with disease management pathways. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov identifier: NCT01994889.

Implementing a Machine-Learning-Adapted Algorithm to Identify Possible Transthyretin Amyloid Cardiomyopathy at an Academic Medical Center.

Background: Wild-type transthyretin amyloid cardiomyopathy (ATTR-CM) is a frequently under-recognized cause of heart failure (HF) in older patients. To improve identification of patients at risk for the disease, we initiated a pilot program in which 9 cardiac/non-cardiac phenotypes and 20 high-performing phenotype combinations predictive of wild-type ATTR-CM were operationalized in electronic health record (EHR) configurations at a large academic medical center. Methods: Inclusion criteria were age >50 years and HF; exclusion criteria were end-stage renal disease and prior amyloidosis diagnoses. The different Epic EHR configurations investigated were a clinical decision support tool (Best Practice Advisory) and operational/analytical reports (Clarity™, Reporting Workbench™, and SlicerDicer); the different data sources employed were problem list, visit diagnosis, medical history, and billing transactions. Results: With Clarity, among 45 051 patients with HF, 4006 patients (8.9%) had ⩾1 phenotype combination associated with increased risk of wild-type ATTR-CM. Across all data sources, 2 phenotypes (cardiomegaly; osteoarthrosis) and 2 combinations (carpal tunnel syndrome + HF; atrial fibrillation + heart block + cardiomegaly + osteoarthrosis) generated the highest proportions of patients for wild-type ATTR-CM screening. Conclusion: All EHR configurations tested were capable of operationalizing phenotypes or phenotype combinations to identify at-risk patients; the Clarity report was the most comprehensive.

Applying diagnosis support systems in electronic health records to identify wild-type transthyretin amyloid cardiomyopathy risk.

Aim: Wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM) is frequently misdiagnosed, and delayed diagnosis is associated with substantial morbidity and mortality. At three large academic medical centers, combinations of phenotypic features were implemented in electronic health record (EHR) systems to identify patients with heart failure at risk for ATTRwt-CM. Methods: Phenotypes/phenotype combinations were selected based on strength of correlation with ATTRwt-CM versus non-amyloid heart failure; different clinical decision support and reporting approaches and data sources were evaluated on Cerner and Epic EHR platforms. Results: Multiple approaches/sources showed potential usefulness for incorporating predictive analytics into the EHR to identify at-risk patients. Conclusion: These preliminary findings may guide other medical centers in building and implementing similar systems to improve recognition of ATTRwt-CM in patients with heart failure.

Drug Discovery and Development in Rare Diseases: Taking a Closer Look at the Tafamidis Story.

Rare diseases are increasingly recognized as a global public health priority. Governments worldwide currently provide important incentives to stimulate the discovery and development of orphan drugs for the treatment of these conditions, but substantial scientific, clinical, and regulatory challenges remain. Tafamidis is a first-in-class, disease-modifying transthyretin (TTR) kinetic stabilizer that represents a major breakthrough in the treatment of transthyretin amyloidosis (ATTR amyloidosis). ATTR amyloidosis is a rare, progressive, and fatal systemic disorder caused by aggregation of misfolded TTR and extracellular deposition of amyloid fibrils in various tissues and organs, including the heart and nervous systems. In this review, we present the successful development of tafamidis spanning 3 decades, marked by meticulous laboratory research into disease mechanisms and natural history, and innovative clinical study design and implementation. These efforts established the safety and efficacy profile of tafamidis, leading to its regulatory approval, and enabled post-approval initiatives that further support patients with ATTR amyloidosis.

A machine learning model for identifying patients at risk for wild-type transthyretin amyloid cardiomyopathy.

Transthyretin amyloid cardiomyopathy, an often unrecognized cause of heart failure, is now treatable with a transthyretin stabilizer. It is therefore important to identify at-risk patients who can undergo targeted testing for earlier diagnosis and treatment, prior to the development of irreversible heart failure. Here we show that a random forest machine learning model can identify potential wild-type transthyretin amyloid cardiomyopathy using medical claims data. We derive a machine learning model in 1071 cases and 1071 non-amyloid heart failure controls and validate the model in three nationally representative cohorts (9412 cases, 9412 matched controls), and a large, single-center electronic health record-based cohort (261 cases, 39393 controls). We show that the machine learning model performs well in identifying patients with cardiac amyloidosis in the derivation cohort and all four validation cohorts, thereby providing a systematic framework to increase the suspicion of transthyretin cardiac amyloidosis in patients with heart failure.

Healthcare Costs of Smokers Using Varenicline Versus Nicotine-Replacement Therapy Patch in the United States: Evidence from Real-World Practice.

INTRODUCTION: Varenicline (VAR) is an effective smoking-cessation therapy compared to the commonly used nicotine-replacement therapy patch (NRT-P). However, comparative real-world evidence on smoking-cessation therapies is limited, especially for economic outcomes. METHODS: Using national claims databases (2012-2016) in the United States (US), adults initiating VAR or NRT-P without use of any other smoking-cessation products were followed for up to 1 year on a quarterly basis. Outcomes included smoking-attributable (SA) (cardiovascular, diabetes, pulmonary diseases, and smoking cessation) and all-cause costs (2017 US dollars). Adjusted mean costs were estimated from multivariable regressions, with baseline characteristics and propensity scores as covariates. Annual adjusted costs were calculated from quarterly averages. RESULTS: The VAR cohort (n = 209,284) was younger (mean age 46.7 vs. 49.0 years) and had fewer comorbidities [mean Charlson Comorbidity Index (CCI): 0.8 vs. 1.6] than the NRT-P cohort (n = 34,593). After adjustment, VAR cohort had lower SA and all-cause medical costs than NRT-P cohort in Quarters 1-4 (Q1-Q4) of follow-up, and had lower SA and all-cause total costs in Q2-Q4. Annually, VAR cohort had higher SA total costs ($307) and lower all-cause costs (- $2089) than NRT-P cohort. Annual medical costs were lower in VAR cohort (- $640 for SA and - $2876 for all-cause), and pharmacy costs were higher ($762 for SA and $777 for all-cause). In adherent patients (VAR: n = 38,744; NRT-P: n = 2702), VAR patients had lower annual medical costs (- $794 for SA and - $1636 for all-cause) and higher pharmacy costs ($1175 for SA and $1269 for all-cause); differences in SA and all-cause total costs were not statistically significant between treatment groups. CONCLUSIONS: Lower SA and all-cause medical costs associated with the use of VAR versus NRT-P resulted in savings in all-cause total costs and, among adherent patients, potentially offset the high pharmacy costs of VAR. FUNDING: Pfizer, Inc.

Smoking Cessation Is Associated With Lower Indirect Costs.

OBJECTIVE: This study quantified differences in indirect costs due to decreased work productivity between current and former smokers. Former smokers were further categorized by number of years since quitting to assess corresponding differences. METHODS: Data on employed individuals were obtained from the 2013 US National Health and Wellness Survey (NHWS; N = 75,000). Indirect costs were calculated for current smokers and former smokers from weekly wages based on age and sex. RESULTS: The annual total indirect costs for current smokers were $1327.53, $1560.18, and $1839.87 higher than for those who quit 0 to 4 years, 5 to 10 years, and more than or equal to 11 years prior, respectively. There were no significant differences in mean total indirect costs between the former smoker groups. CONCLUSIONS: Current smokers showed significantly higher total annual indirect costs compared with former smokers, independently of the number of years since quitting smoking.

Mobile App Usage Patterns of Patients Prescribed a Smoking Cessation Medicine: Prospective Observational Study.

BACKGROUND: Cigarette smoking is the leading preventable cause of death and is responsible for more than 480,000 deaths per year in the United States. Smoking cessation is challenging for many patients. Regardless of available treatment options, most quit attempts are unaided, and it takes multiple attempts before a patient is successful. With the ever-increasing use of smartphones, mobile apps hold promise in supporting cessation efforts. This study evaluates the ease of use and user satisfaction with the Pfizer Meds app to support smoking cessation among patients prescribed varenicline (Chantix). OBJECTIVE: Study participants included varenicline users who downloaded and used the app on their personal smartphone. The main objectives were to report mobile app download frequency and usage details and to describe the participant-reported satisfaction with and usefulness of the app over the 14-week follow-up study period. METHODS: Adults aged 18 years or older who had been prescribed varenicline were identified from the Express Scripts Incorporated pharmacy claims database. After meeting privacy restrictions, subjects were sent an invitation letter and second reminder letter with instructions on how to download the Pfizer Meds mobile app. Participants received a push notification to complete a smartphone-enabled survey regarding the utility of the app 12 weeks after downloading the app. Descriptive statistics summarized sociodemographics, use of varenicline, and details of use and satisfaction with the mobile app. RESULTS: Of the 38,129 varenicline users who were sent invitation letters, 1281 participants (3.35%) downloaded the Pfizer Meds app. Of the 1032 users with demographic and other data, 585 (56.68%) were females, and 446 (43.22%) were males; mean age was 46.4 years (SD 10.8). The mean number of app sessions per participant was 4.0 (SD 6.8). The end-of-study survey was completed by 131 survey respondents (10.23%, 131/1281); a large number of participants (117/131, 89.3%) reported being extremely, very, or moderately satisfied with the app. A total of 97 survey respondents (97/131, 74.0%) reported setting up a quit date in the app. Of those, 74 (74/97, 76%) reported quitting on their quit date. CONCLUSIONS: Positive patient engagement was observed in this study based on app download and usage. This study quantified how the Pfizer Meds app performed in an observational real-world data setting. The findings demonstrate the willingness of participants to set a quit date and use the app for support in medication adherence, refill reminders, and information regarding how to take the medication. This study provides real-world evidence of the contribution apps can make to the continued encouragement of smokers to improve their health by smoking cessation.

Estimated Budget Impact of Adopting the Affordable Care Act's Required Smoking Cessation Coverage on United States Healthcare Payers.

INTRODUCTION: Despite abundant information on the negative impacts of smoking, more than 40 million adult Americans continue to smoke. The Affordable Care Act (ACA) requires tobacco cessation as a preventive service with no patient cost share for all FDA-approved cessation medications. Health plans have a vital role in supporting smoking cessation by managing medication access, but uncertainty remains on the gaps between smoking cessation requirements and what is actually occurring in practice. This study presents current cessation patterns, real-world drug costs and plan benefit design data, and estimates the 1- to 5-year pharmacy budget impact of providing ACA-required coverage for smoking cessation products to understand the fiscal impact to a US healthcare plan. METHODS: A closed cohort budget impact model was developed in Microsoft Excel® to estimate current and projected costs for US payers (commercial, Medicare, Medicaid) covering smoking cessation medicines, with assumptions for coverage and smoking cessation product utilization based on current, real-world national and state-level trends for hypothetical commercial, Medicare, and Medicaid plans with 1 million covered lives. A Markov methodology with five health states captures quit attempt and relapse patterns. Results include the number of smokers attempting to quit, number of successful quitters, annual costs, and cost per-member per-month (PMPM). RESULTS: The projected PMPM cost of providing coverage for smoking cessation medications is $0.10 for commercial, $0.06 for Medicare, and $0.07 for Medicaid plans, reflecting a low incremental PMPM impact of covering two attempts ranging from $0.01 for Medicaid to $0.02 for commercial and Medicare payers. CONCLUSION: The projected PMPM impact of covering two quit attempts with access to all seven cessation medications at no patient cost share remains low. Results of this study reinforce that the impact of adopting the ACA requirements for smoking cessation coverage will have a limited near-term impact on health plan's budgets. FUNDING: Pfizer Inc.

Content Validity of a Willingness to Quit Tool for Use with Current Smokers in Clinical Practice.

INTRODUCTION: Despite reductions in rates of smoking in the past decade, smoking remains one of the most significant public health concerns. Quitting smoking can result in reductions in a number of serious health conditions. The brief Willingness to Quit (WTQ) tool can be used in routine clinical practice to assess current willingness to quit and engage a patient-physician dialogue regarding smoking cessation. The overall aim of this study was to validate the content of a WTQ tool for use with current smokers in clinical practice. METHODS: In-depth, qualitative interviews were conducted with 12 current smokers and five physicians. The interview was divided into two sections: concept elicitation (CE) followed by cognitive debriefing (CD). During CE, participants were asked questions exploring the different factors that can impact an individual's willingness to quit smoking. During CD, participants were given a copy of the WTQ tool and asked to comment on their level of understanding and interpretability of the items and the feasibility of completing the tool in clinical practice. RESULTS: All of the current smokers (n = 12) and physicians (n = 5) interviewed indicated that the items were understandable and relevant to assess willingness to quit. The tool was considered simple and suitable for use in clinical practice. CONCLUSION: The WTQ tool is a brief tool to assess willingness to quit and to engage communication between patients and physicians. All smokers should be offered smoking cessation support and facilitating a discussion on willingness to quit further supports a personalized quit plan. FUNDING: Pfizer Inc.

A Pragmatic Randomized Trial Comparing Telephone-Based Enhanced Pharmacy Care and Usual Care to Support Smoking Cessation.

BACKGROUND: Smoking is the leading preventable cause of death, and tobacco control professionals continue to make progress in cessation efforts. Pharmacists can assist smokers seeking to quit by offering counseling on smoking cessation pharmacotherapies. Pragmatic randomized trials are useful for investigating practical questions about an intervention's risks, benefits, and costs in routine clinical practice. OBJECTIVE: To evaluate an enhanced pharmacy care (EPC) program involving personalized pharmacist-provided telephone counseling for supporting prescription smoking cessation medications compared with usual care (UC). METHODS: Cigarette smokers filling a newly prescribed smoking cessation pharmacotherapy and with pharmacy benefits managed by Express Scripts were recruited. Qualified subjects were randomized 1:1 to EPC and UC. Subjects in EPC received 3 telephone-counseling sessions from specialist pharmacists during the early course of the study, while subjects in UC did not receive any counseling sessions. Study outcomes were collected through telephone contact and using the Express Scripts prescription database. The primary outcome assessed the 1-week point prevalence (PP) of smoking abstinence at the end of the trial (week 12). Secondary outcomes included 4-week PP at week 12 and adherence, evaluated by proportion of days covered (PDC), to prescribed smoking cessation pharmacotherapies. RESULTS: There were 1,017 randomized subjects. Among them, 1,002 subjects were included in the analysis, and 513 were randomized into EPC and 489 into UC. Baseline demographics, smoking history, and prescribed smoking cessation pharmacotherapies were comparable. Varenicline and nicotine replacement therapy (NRT) were most frequently prescribed for smoking cessation. In EPC, 46.0% received all 3 counseling sessions; 29.4% received 2 sessions; and 14.6% received 1 session. Overall, 353 subjects in EPC and 383 subjects in UC completed the week 12 assessment. In the analysis for 1-week PP of smoking abstinence at week 12, the percentage of abstainers in EPC was numerically higher than in UC (42.3% vs. 38.2%) with OR = 1.24, 95% CI = 0.96-1.61. It was not statistically significant. Adherence to prescription smoking cessation medication was significantly higher in EPC versus UC (49.7% vs. 45.6%; P = 0.033). CONCLUSIONS: This study evaluated whether a telephone-based pharmacy care program, provided by pharmacists and designed to support attempted quitters, improved quitting and increased adherence over usual care. The findings suggest that an enhanced program may benefit smokers by increasing prescription smoking cessation medication adherence. Future research should explore this program's effect on smokers who are compliant, based on insights on quitting provided by the post hoc analyses and limitations of the current study design. DISCLOSURES: This study was sponsored by Pfizer. Gong, Baker, Zou, Bruno, Jumadilova, and Lawrence are employees and stockholders of Pfizer. Wilson and Ewel are employees of United BioSource Corporation, which received funding from Pfizer for conducting this study and for the development of this manuscript. Study concept and design were contributed by Gong, Bruno, and Ewel, with assistance from Jumadilova, Lawrence, and Zou. Gong, Jumadilova, Lawrence, and Ewel collected the data. Data interpretation was performed by Baker, Zou, and Wilson, assisted by Gong, Lawrence, and Ewel. The manuscript was written by Baker, Ewel, and Gong, with assistance from the other authors, and revised by Baker, Wilson, Zou, and Gong, with assistance from Bruno and Jumadilova.

BE EMPOWERED, a specialty pharmacy education program for hemophilia B patients, impacts adult joint bleeds and pediatric use of RICE.

BACKGROUND: Traditional education about hemophilia B in hemophilia treatment centers (HTCs) and episodic contact with HTCs limit the amount of education patients and their caregivers receive. Specialty care providers have frequent, continuing contact with patients. Each contact with a specialty care provider (e.g., coordinating a refill or addressing a patient inquiry) is another opportunity to support patient self-management of the disease and to give counsel on appropriate medication administration. The role of specialty pharmacy in improving patient self-management and supporting medication management and adherence is well established and reported with rheumatoid arthritis, multiple sclerosis, and renal transplant. With hemophilia, specialty pharmacies can support educational reinforcement of HTCs as well as support patient self-management and education of medication therapy. Utilization of patient education materials and programs can facilitate such a role. BE EMPOWERED, a specialty pharmacy education program for hemophilia B patients, is a multimodule education program coupled with frequent telephonic outreach.   OBJECTIVE: To provide education about hemophilia B, based upon discrete curriculum modules, facilitated by a specialty pharmacy-based nurse educator.   METHODS: Patients with hemophilia B (or, for children, their caregivers) were enrolled in the BE EMPOWERED program, and data were prospectively collected regarding bleeding and hemophilia-specific quality of life (QoL) outcomes (n = 21 caregivers, n = 17 adults).  RESULTS: BE EMPOWERED was associated with a statistically significant impact on the use of RICE (rest, ice, compression, and elevation) by caregivers whose utilization increased from 81% to 95% (P = 0.05). Adults in the BE EMPOWERED program experienced a statistically significant drop in the annualized bleeding rate (ABR), decreasing from 4.7 to 2.5 for total bleeds and decreasing from 3.5 to 1.7 for joint bleeds (P ≤ 0.02). For children with hemophilia B, bleeds were less common overall, as reported by their caregivers, with a mean ABR of 1.1 before and 1.2 following the program. Regarding QoL scores, adults had lower scores compared with children enrolled in the program.  CONCLUSIONS: Completion of the BE EMPOWERED program was associated with a decrease in total bleeds and in joint bleeds in adults and with increased RICE utilization in children, as reported by caregivers. QoL scores were lower in adults compared with children, and further research is warranted to understand this difference. Future studies may focus on the effect of specialty pharmacy as an educational vehicle with potential cost benefits. 

Characterization of the first adult de novo case of 46,X,der(Y)t(X;Y)(p22.3;q11.2).

Herein, we describe a case of an infertile man detected in postnatal diagnosis with FISH characterization and array-CGH used for genome-wide screening which allowed the identification of a complex rearrangement involving sex chromosomes, apparently without severe phenotypic consequences. The deletion detected in our patient has been compared with previously reported cases leading us to propose a hypothetical diagnostic algorithm that would be useful in similar clinical situations, with imperative multi disciplinary approach integrated with genetic counseling. Our patient, uniquely of reproductive age, is one of six reported cases of duplication of Xp22.3 (~8.4Mb) segment and contemporary deletion of Yq (~42.9Mb) with final karyotype as follows: 46,X,der(Y),t(X;Y)(Ypter→Yq11.221::Xp22.33→Xpter).ish der(Y) (Yptel+,Ycen+,RP11-529I21+,RP11-506M9-Yqtel−,Xptel+). arrXp22.33p22.31(702­8,395,963, 8,408,289x1), Yq11.221q12 (14,569,317x1, 14,587,321­57,440,839x0).