scholarly journals Physicians’ Experience and Willingness to Participate in Non-Interventional Trials in Bulgaria

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Emil S. Kostov ◽  
Evgeni E. Grigorov ◽  
Hristina V. Lebanova
Keyword(s):  
Real World ◽  
National Level ◽  
Willingness To Participate ◽  
Real World Data ◽  
Healthcare Resources ◽  
Additional Information ◽  
Anonymous Questionnaire ◽  
Usual Manner ◽  
Proper Training ◽  
Outpatient Settings

Summary Non-interventional studies (NIS) are conducted to obtain additional information about a medicinal product prescribed in the usual manner in compliance with the conditions determined in the marketing authorization. They are a valuable source of real-world data for the effectiveness and safety of medicines. This study aims to assess physicians‘ knowledge of non-interventional studies in Bulgaria and identify the primary factors and barriers hindering the NIS at a national level. An individual anonymous questionnaire with 16 items was distributed among physicians in inpatient and outpatient settings. The results showed that 81.3% (n=147) of the respondents have no experience with non-interventional studies. Physicians‘ willingness to participate in NIS in the future is high and independent of their previous experience. The main barriers hindering conducting NIS in Bulgaria are related to organization, the conduct and the design of the trials, and, sometimes, the investigators‘ concerns. There is a need for proper training of the researchers and expanding healthcare resources to grow the NIS sector in Bulgaria in line with the tendencies in Europe.

Network Data Characteristics

2011 ◽  
pp. 104-122
Author(s):  
Yu Wang
Keyword(s):  
Real World ◽  
Random Variables ◽  
Network Data ◽  
Traffic Data ◽  
Real World Data ◽  
Additional Information ◽  
Data Points ◽  
Key Features ◽  
Basic Concepts ◽  
Data Elements

Data represents the natural phenomena of our real world. Data is constructed by rows and columns; usually rows represent the observations and columns represent the variables. Observations, also called subjects, records, or data points, represent a phenomenon in the real world and variables, as also known as data elements or data fields, represent the characteristics of observations in data. Variables take different values for different observations, which can make observations independent of each other. Figure 4.1 illustrates a section of TCP/IP traffic data, in which the rows are individual network traffics, and the columns, separated by a space, are characteristics of the traffics. In this example, the first column is a session index of each connection and the second column is the date when the connection occurred. In this chapter, we will discuss some fundamental key features of variables and network data. We will present detailed discussions on variable characteristics and distributions in Sections Random Variables and Variables Distributions, and describe network data modules in Section Network Data Modules. The material covered in this chapter will help readers who do not have a solid background in this area gain an understanding of the basic concepts of variables and data. Additional information can be found from Introduction to the Practice of Statistics by Moore and McCabe (1998).

Probabilistic Models for Social Media Mining

2014 ◽  
pp. 95-105
Author(s):  
Flora S. Tsai
Keyword(s):  
Social Media ◽  
Real World ◽  
Probabilistic Models ◽  
The Other ◽  
Media Content ◽  
Real World Data ◽  
Social Media Mining ◽  
Additional Information ◽  
Classification Framework ◽  
Media Mining

This paper proposes probabilistic models for social media mining based on the multiple attributes of social media content, bloggers, and links. The authors present a unique social media classification framework that computes the normalized document-topic matrix. After comparing the results for social media classification on real-world data, the authors find that the model outperforms the other techniques in terms of overall precision and recall. The results demonstrate that additional information contained in social media attributes can improve classification and retrieval results.

scholarly journals Locational privacy-preserving distance computations with intersecting sets of randomly labeled grid points

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Rainer Schnell ◽  
Jonas Klingwort ◽  
James M. Farrow
Keyword(s):  
Programming Languages ◽  
Real World ◽  
Spatial Data ◽  
Large Scale ◽  
Privacy Preserving ◽  
Real World Data ◽  
Data Set ◽  
Additional Information ◽  
Grid Points ◽  
High Level

Abstract Background We introduce and study a recently proposed method for privacy-preserving distance computations which has received little attention in the scientific literature so far. The method, which is based on intersecting sets of randomly labeled grid points, is henceforth denoted as ISGP allows calculating the approximate distances between masked spatial data. Coordinates are replaced by sets of hash values. The method allows the computation of distances between locations L when the locations at different points in time t are not known simultaneously. The distance between $$L_1$$ L 1 and $$L_2$$ L 2 could be computed even when $$L_2$$ L 2 does not exist at $$t_1$$ t 1 and $$L_1$$ L 1 has been deleted at $$t_2$$ t 2 . An example would be patients from a medical data set and locations of later hospitalizations. ISGP is a new tool for privacy-preserving data handling of geo-referenced data sets in general. Furthermore, this technique can be used to include geographical identifiers as additional information for privacy-preserving record-linkage. To show that the technique can be implemented in most high-level programming languages with a few lines of code, a complete implementation within the statistical programming language R is given. The properties of the method are explored using simulations based on large-scale real-world data of hospitals ($$n=850$$ n = 850 ) and residential locations ($$n=13,000$$ n = 13 , 000 ). The method has already been used in a real-world application. Results ISGP yields very accurate results. Our simulation study showed that—with appropriately chosen parameters – 99 % accuracy in the approximated distances is achieved. Conclusion We discussed a new method for privacy-preserving distance computations in microdata. The method is highly accurate, fast, has low computational burden, and does not require excessive storage.

Probabilistic Models for Social Media Mining

2011 ◽  
Vol 6 (1) ◽  
pp. 13-24 ◽  
Author(s):  
Flora S. Tsai
Keyword(s):  
Social Media ◽  
Real World ◽  
Probabilistic Models ◽  
The Other ◽  
Media Content ◽  
Real World Data ◽  
Social Media Mining ◽  
Additional Information ◽  
Classification Framework ◽  
Media Mining

This paper proposes probabilistic models for social media mining based on the multiple attributes of social media content, bloggers, and links. The authors present a unique social media classification framework that computes the normalized document-topic matrix. After comparing the results for social media classification on real-world data, the authors find that the model outperforms the other techniques in terms of overall precision and recall. The results demonstrate that additional information contained in social media attributes can improve classification and retrieval results.

scholarly journals Real-World Evidence Should Be Used in Regulatory Decisions About New Pharmaceutical and Medical Device Products for Diabetes

2019 ◽  
Vol 13 (6) ◽  
pp. 995-1000 ◽  
Author(s):  
David C. Klonoff ◽  
Alberto Gutierrez ◽  
Alexander Fleming ◽  
David Kerr
Keyword(s):  
Real World ◽  
Randomized Clinical Trials ◽  
Sole Source ◽  
Real World Data ◽  
Pharmacy Records ◽  
Health Records ◽  
Additional Information ◽  
Real World Evidence ◽  
Combining Data ◽  
Regulatory Decisions

Randomized clinical trials (RCTs) are no longer the sole source of data to inform guidelines, regulatory, and policy decisions. Real-world data (RWD), collected from registries, electronic health records, insurance claims, pharmacy records, social media, and sensor outputs from devices form real-world evidence (RWE), which can supplement evidence from RCTs. Benefits of using RWE include less time and cost to produce meaningful data; the ability to capture additional information, including social determinants of health that can impact health outcomes; detection of uncommon adverse events; and the potential to apply machine learning and artificial intelligence to the delivery of health care. Overall, combining data from RCTs and RWE would allow regulators to make ongoing and more evidence-based decisions in approving and monitoring products for diabetes.

VP116 Comparison Between Time To Off Treatment And Italian Medicines Agency Registries Treatment Duration

2017 ◽  
Vol 33 (S1) ◽  
pp. 203-204
Author(s):  
Gabriele Vittoria ◽  
Antonio Fascì ◽  
Matteo Ferrario ◽  
Giovanni Giuliani
Keyword(s):  
Clinical Trials ◽  
Real World ◽  
Treatment Duration ◽  
National Level ◽  
Real Life ◽  
Evidence Base ◽  
Phase Iii ◽  
Real World Data ◽  
The Mean ◽  
High Level

INTRODUCTION:The Italian Medicines Agency Registry represents a tool that could be a precious source of information regarding the mean treatment duration of a drug in a real world context. Monitoring registries are applied at the national level after market authorization and are designed not only to apply the Managed Entry Agreements (MEAs) but also to collect Real World Data on drugs safety, effectiveness and real life utilization. The purpose of this analysis was to compare the treatment duration from clinical trials and the mean treatment duration calculated using data from monitoring registries (1).METHODS:For each drug included in the analysis it was collected the treatment duration from Time To Off Treatment curves for the experimental drug (eTTOT) from Phase III clinical trials and the mean treatment duration data calculated by using the number of cycles (converted in months of treatment) of all treated patients extracted from AIFA registries (TTAR). The mean ratios between the Time of Treatment of Italian Medicines Agency and Experimental arm time to off treatment were calculated to identify potential correlations. High level of correlation was expected if Time to Payment By Result /Time To Off Treatment ratio was close to 1 (±.2).RESULTS:Six Roche products or different indications of the same product were identified as candidates for the analysis from 2013 to 2016. The mean TTAR/eTTOT ratio observed in patients treated from 2013 to 2016 was .97 (±.10), meaning that the mean treatment duration calculated from AIFA Registries is strongly comparable with the treatment duration observed in clinical trials. In one case the TTAR is even more major than eTTOT.CONCLUSIONS:A high level of correlation between TTAR and eTTOT was found. Additional analyses considering different cohorts of patients over time could be useful to have a more precise estimate of real world drug utilization. Even though RCTs remain the gold standard for demonstrating clinical efficacy in restricted trial setting, Real World Evidence from AIFA registries can contribute to the evidence base needed for healthcare decisions.

Abstract #946: Assessment of Acromegaly Patients with and Without Diabetes Treated with Lanreotide Depot: 2-Year Real World Data

2016 ◽  
Vol 22 ◽  
pp. 219
Author(s):  
Roberto Salvatori ◽  
Olga Gambetti ◽  
Whitney Woodmansee ◽  
David Cox ◽  
Beloo Mirakhur ◽  
...  
Keyword(s):  
Real World ◽  
Real World Data ◽  
World Data

Safety and efficacy of direct acting oral anticoagulants and vitamin K antagonists in nonvalvular atrial fibrillation – a network meta-analysis of real-world data

VASA ◽  
2019 ◽  
Vol 48 (2) ◽  
pp. 134-147 ◽  
Author(s):  
Mirko Hirschl ◽  
Michael Kundi
Keyword(s):  
Real World ◽  
Meta Analysis ◽  
Vitamin K Antagonists ◽  
Oral Anticoagulants ◽  
Efficacy And Safety ◽  
Nonvalvular Atrial Fibrillation ◽  
Real World Data ◽  
Hazard Ratios ◽  
Direct Acting ◽  
Event Rates

Abstract. Background: In randomized controlled trials (RCTs) direct acting oral anticoagulants (DOACs) showed a superior risk-benefit profile in comparison to vitamin K antagonists (VKAs) for patients with nonvalvular atrial fibrillation. Patients enrolled in such studies do not necessarily reflect the whole target population treated in real-world practice. Materials and methods: By a systematic literature search, 88 studies including 3,351,628 patients providing over 2.9 million patient-years of follow-up were identified. Hazard ratios and event-rates for the main efficacy and safety outcomes were extracted and the results for DOACs and VKAs combined by network meta-analysis. In addition, meta-regression was performed to identify factors responsible for heterogeneity across studies. Results: For stroke and systemic embolism as well as for major bleeding and intracranial bleeding real-world studies gave virtually the same result as RCTs with higher efficacy and lower major bleeding risk (for dabigatran and apixaban) and lower risk of intracranial bleeding (all DOACs) compared to VKAs. Results for gastrointestinal bleeding were consistently better for DOACs and hazard ratios of myocardial infarction were significantly lower in real-world for dabigatran and apixaban compared to RCTs. By a ranking analysis we found that apixaban is the safest anticoagulant drug, while rivaroxaban closely followed by dabigatran are the most efficacious. Risk of bias and heterogeneity was assessed and had little impact on the overall results. Analysis of effect modification could guide the clinical decision as no single DOAC was superior/inferior to the others under all conditions. Conclusions: DOACs were at least as efficacious as VKAs. In terms of safety endpoints, DOACs performed better under real-world conditions than in RCTs. The current real-world data showed that differences in efficacy and safety, despite generally low event rates, exist between DOACs. Knowledge about these differences in performance can contribute to a more personalized medicine.

Sign in / Sign up

Export Citation Format

Share Document