Ospemifene versus local estrogen: adherence and costs in postmenopausal dyspareunia

2019 ◽  
Vol 8 (13) ◽  
pp. 1111-1123 ◽  
Author(s):  
Brooke M Faught ◽  
Graziella Soulban ◽  
Jason Yeaw ◽  
Christiane Maroun ◽  
Katharine Coyle ◽  
...  
Keyword(s):  
Real World ◽  
Healthcare Costs ◽  
Claims Data ◽  
The Other ◽  
Real World Data ◽  
Database Study ◽  
World Data ◽  
Pharmacy Claims ◽  
Direct Healthcare Costs ◽  
Retrospective Database

Aim: Objective was to compare adherence and persistence, as well as direct healthcare costs and utilization, of ospemifene to available local estrogen therapies (LETs). Patients & methods: This retrospective database study used integrated medical and pharmacy claims data from the IQVIA Real-World Data Adjudicated Claims – US Database. Results: Ospemifene patients had significantly greater adherence and persistence compared with the other nonring LETs. Ospemifene had the lowest mean outpatient costs of any of the LET cohorts, including the estradiol vaginal ring. Total all-cause healthcare costs were also significantly less for ospemifene patients compared with all other LETs.

Treatment patterns and characteristics of acute promyelocytic leukemia (APL) patients receiving arsenic trioxide (ATO) therapy in a real-world setting.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18522-e18522
Author(s):  
Boxiong Tang ◽  
Susan Gabriel ◽  
Jifang Zhou ◽  
Ashutosh K. Pathak ◽  
Debra Irwin ◽  
...  
Keyword(s):  
Real World ◽  
Index Date ◽  
Claims Data ◽  
Treatment Patterns ◽  
Chronic Obstructive ◽  
Administrative Claims ◽  
First Line ◽  
Real World Data ◽  
World Data

e18522 Background: Clinical trials have shown that low-risk APL patients had significantly better outcomes when receiving first-line all-trans retinoic acid (ATRA) + ATO compared with standard ATRA + chemotherapy. Few published studies have used real-world data to describe patients using ATO and their current treatment patterns. This study used United States (US) administrative claims data to describe treatment patterns and characteristics of patients receiving first-line ATO. Methods: This retrospective, observational cohort study used claims data from the MarketScan databases. As there is no ICD-9-CM diagnosis code for APL, ATO treatment was used as a surrogate for the diagnosis of APL since ATO is typically used only in APL patients. Patients were selected if they had ≥1 claims for ATO between January 1, 2000, and June 30, 2015. Date of first use was designated the index date. To identify first-line ATO initiation, patients with ATRA or other APL-indicated chemotherapy claims any time before the index date were excluded. Variable baseline and follow-up periods consisting of ≥3 months of pre-index and ≥30 days of post-index continuous enrollment in medical and pharmacy benefit were used. Results: In total, 331 patients were identified with a subset (n = 265) having ≥2 claims for ATO. The analysis focused on these 265 patients, 54% of whom were male. Mean age was 60.6 years; 45% were covered by Medicare. The most common comorbid conditions measured were diabetes (6%), chronic obstructive pulmonary disease (5%), and congestive heart failure (4%). The most commonly selected APL treatments administered during follow-up were ATRA (17%) and daunorubicin (9%) with the use of idarubicin, cytarabine, and mitoxantrone at less than 3%. Maintenance therapy with methotrexate or 6-mercaptopurine was observed in 7% and 6% of patients, respectively. Conclusions: This is one of the first studies to examine patient characteristics and treatment patterns for first-line ATO using real-world data. Further research is needed to evaluate outcomes for patients receiving ATO as first-line therapy and to re-evaluate treatment guidelines in light of these outcomes.

Abstract P341: Development of Predictive Models for Cardiovascular Health to Support Its Use in Real-world Data

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Hui Hu ◽  
Jiang Bian ◽  
Thomas A Pearson ◽  
Heather S Lipkind ◽  
Yi Zheng ◽  
...  
Keyword(s):  
Physical Activity ◽  
Total Cholesterol ◽  
Real World ◽  
Predictive Models ◽  
Cardiovascular Health ◽  
The United States ◽  
The Other ◽  
Gradient Boosting ◽  
Real World Data ◽  
World Data

Life’s Simple 7 (LS7) developed by the American Heart Association (AHA) is a new index of cardiovascular health (CVH). LS7 is comprised of 7 metrics, including 3 health factors (blood pressure [BP], total cholesterol, and glucose) and 4 health behaviors (body mass index [BMI], cigarette smoking, diet, and physical activity). To date, CVH estimates are mainly obtained from national surveys, clinical trials, and cohort studies. Real-world data (RWD) such as electronic health records (EHRs) and claims data and real-world evidence generated from these data are playing an increasing role. However, the lack of information on all 7 CVH metrics in RWD limits the use of the CVH concept in research and preventions based on RWD. Using data from the 1999-2016 National Health and Nutrition Examination Survey (NHANES), we developed predictive models for CVH among adults using 3 metrics (i.e. BP, BMI, and smoking) and sociodemographic factors (i.e. age, gender, race/ethnicity, education, and marital status) which are widely available in RWD. Each CVH metric was categorized into ideal (2 points), intermediate (1 point), or poor (0 point), and then weighted accordingly following LS7 to generate an overall CVH score (0-14 points) with a higher score indicating better CVH. Individuals with more than 4 ideal CVH metrics were determined as having ideal CVH. In addition, we also developed models using 4 CVH metrics (i.e. BP, BMI, and smoking + one of the other 4 metrics). The data were randomly divided into training (80%) and testing (20%) sets. Gradient boosting decision trees models were trained using the CatBoost library with hyper-parameters tuned by a grid search based on 5-fold cross validations. A total of 45,614 individuals aged 18 years and older in 1999-2016 NHANES were included. The models with 3 CVH metrics (i.e. BP, BMI, and smoking) as predictors achieved a test-AUC of 0.95 and a test-RMSE of 1.39. Including one of the other 4 CVH metrics (i.e. total cholesterol, glucose, diet, or physical activity) as a predictor in the models along with the previous 3 metrics (i.e. BP, BMI, and smoking) further improved the predictive performance (test-AUC>0.96 and test-RMSE<1.38). These findings suggested that the 3 CVH metrics (i.e. BP, BMI, and smoking) that are widely available in RWD can be used to accurately estimate CVH among adults in the United States.

scholarly journals Analysis of user Awareness for Saudi State Mobile Applications

2020 ◽  
Vol 9 (4) ◽  
pp. 314-321
Keyword(s):  
Real World ◽  
Mobile Applications ◽  
The State ◽  
The Other ◽  
Real World Data ◽  
World Data ◽  
Extra Effort ◽  
Other Hand ◽  
Security Practices ◽  
Extensive Effort

In this article, we analyze the perception of Saudi state application users about password selection from real-world data. A total of 1,082 participants provided information about their behavior on state applications. The study extracts useful information related to the users’ weak practices. The findings include useful information representing thousands of minds and individual behaviors in using state applications. As a contribution to the area, it is found that the state applications were developed properly regarding security practices. However, users still represent the weakest party, and they are not aware of the proper practices they should follow. Thus, extensive effort is required to be spent on user education. On the other hand, the diversity of state applications may represent an extra effort to users in the way that they have separate passwords for each application, which makes a unified login portal for all the state applications the appropriate solution.

scholarly journals Mechanisms for Online Organ Matching

2017 ◽  
Author(s):  
Nicholas Mattei ◽  
Abdallah Saffidine ◽  
Toby Walsh
Keyword(s):  
Real World ◽  
Waiting List ◽  
The Other ◽  
Kidney Transplants ◽  
Real World Data ◽  
World Data ◽  
Simple Mechanism ◽  
Complex Algorithm

Matching donations from deceased patients to patients on the waiting list account for over 85\% of all kidney transplants performed in Australia. We propose a simple mechanisms to perform this matching and compare this new mechanism with the more complex algorithm currently under consideration by the Organ and Tissue Authority in Australia. We perform a number of experiments using real world data provided by the Organ and Tissue Authority of Australia. We find that our simple mechanism is more efficient and fairer in practice compared to the other mechanism currently under consideration.

scholarly journals Cost of Type 2 Diabetes Patients with Chronic Kidney Disease Based on Real-World Data: An Observational Population-Based Study in Spain

2021 ◽  
Vol 18 (18) ◽  
pp. 9853
Author(s):  
Ruth Usó-Talamantes ◽  
Silvia González-de-Julián ◽  
Javier Díaz-Carnicero ◽  
Inmaculada Saurí-Ferrer ◽  
José Luis Trillo-Mata ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
High Risk ◽  
Kidney Disease ◽  
Economic Impact ◽  
Real World ◽  
Healthcare Costs ◽  
Risk Groups ◽  
Health District ◽  
Real World Data ◽  
World Data

This study analyzed the prevalence, costs and economic impact of chronic kidney disease CKD in patients with T2D in a Spanish Health District using real-world data. Observational cross-sectional study in adult patients with T2D was through data extracted from the information systems of the Valencia Clínico–La Malvarrosa Health District in the year 2015. Patients were stratified with the KDIGO classification for CKD. Additionally, patients were assigned to Clinical Risk Groups (CRGs) according to multimorbidity. Direct costs of primary and specialized care, and medication were estimated. The prevalence of T2D in the database population (n = 28,345) was 10.8% (mean age (SD) = 67.8 years (13.9); 51.5% male). Up to 14.935 patients (52.6%) had data on kidney function. According to the KDIGO classification, 66.2% of the patients were at low risk of CKD, 20.6% at moderately increased risk, 7.9% at high risk, and 5.2% at very high risk. The average healthcare costs associated with these four risk groups were EUR 3437, EUR 4936, EUR 5899 and EUR 7389, respectively. The large number of T2D patients with CKD in the early stages of the disease generated a significant increase in direct healthcare costs. The economic impact could be mitigated by early and comprehensive therapeutic approaches.

Sign in / Sign up

Export Citation Format

Share Document