Welcome!

News Feed Item

Diabetic Macular Edema Market (BRVO & CRVO) Epidemiology Forecast to 2023 New Report Available at MarketOptimizer.org

MarketOptimizer.org adds new report "Epicast Report: Diabetic Macular Edema - Epidemiology Forecast to 2023" to its store.

DALLAS, Sept. 3, 2014 /PRNewswire-iReach/ -- Macular edema (ME) occurs due to the thickening and swelling (edema) of the macula, which is the area of the retina that is responsible for central vision. In ME, fluid and protein deposits collect on or under the macula of the eye, due to a breakdown in the blood-retinal barrier. The occurrence of ME is highly frequent in diabetics and usually manifests itself as diabetic macular edema (DME). DME is often a complication of diabetic retinopathy, and is the most common cause of vision loss in individuals with diabetes, especially if left untreated. The risk for ME is high in patients with retinal vein occlusion (RVO), which consists of two types: branch retinal vein occlusion (BRVO) and central retinal vein occlusion (CRVO).

Photo - http://photos.prnewswire.com/prnh/20140903/142483

Epidemiologists forecast that the diagnosed prevalent cases of DME in the diagnosed diabetic retinopathy population in the 7MM will increase by 34.2% during the forecast period, from 922,492 cases in 2013 to 1,238,301 cases in 2023. The total prevalent cases of ME following BRVO in the 7MM will increase by 13.7% during the forecast period, from 294,862 cases in 2013 to 335,346 cases in 2023. The total prevalent cases of ME following CRVO in the 7MM will increase by 19.6% during the forecast period, from 114,571 cases in 2013 to 136,973 cases in 2023.

Order a Purchase Copy @ http://www.marketoptimizer.org/contacts/purchase?rname=10264 .

Epidemiological analysis is supported by the use of country-specific prevalence data from epidemiological studies published in peer-reviewed journals. GlobalData epidemiologists used uniform methodology across the markets to forecast the diagnosed prevalent cases of DME in the diagnosed diabetic retinopathy population and the total prevalent cases of ME following BRVO and CRVO, to allow for a meaningful comparison of the disease populations across markets.

Scope

  • The Diabetic Macular Edema (DME) EpiCast Report and EpiCast Model provide an overview of the risk factors, comorbidities, and the global and historical trends for DME in the seven major markets (7MM) (US, France, Germany, Italy, Spain, UK, and Japan). It includes a 10-year epidemiological forecast for the diagnosed prevalent cases of DME in the diagnosed diabetic retinopathy population and the total prevalent cases of ME following branch retinal vein occlusion (BRVO) and central retinal vein occlusion (CRVO) segmented by sex and age (20–39 years, 40–59 years, 60–79 years, and =80 years) in these markets.
  • The DME epidemiology report and model were written and developed by Masters- and PhD-level epidemiologists.
  • The EpiCast Report is in-depth, high quality, transparent and market-driven, providing expert analysis of disease trends in the 7MM.
  • The EpiCast Model is easy to navigate, interactive with dashboards, and epidemiology-based with transparent and consistent methodologies. Moreover, the model supports data presented in the report and showcases disease trends over a 10-year forecast period using reputable sources.

Complete Report Details @ http://www.marketoptimizer.org/epicast-report-diabetic-macular-edema-epidemiology-forecast-to-2023.html .

Reasons to Buy

  • Develop business strategies by understanding the trends shaping and driving the global DME market.
  • Quantify patient populations in the global DME market to improve product design, pricing, and launch plans.
  • Organize sales and marketing efforts by identifying the sex and age groups that present the best opportunities for DME therapeutics in each of the markets covered.
  • Identify the number of ME cases following BRVO and CRVO.

Major Points in Table of Content

1 Table of Contents

2 Executive Summary

3 Introduction

4 Epidemiology

4.1 Disease Background

4.2 Risk Factors and Comorbidities

4.3 Global Trends

4.3.1 US

4.3.2 5EU

4.3.3 Japan

4.4 Forecast Methodology

4.4.1 Sources Used

4.4.2 Sources Not Used

4.4.3 Forecast Assumptions and Methods — Diagnosed Prevalent Cases of Diabetes

4.4.4 Forecast Assumptions and Methods — Diagnosed Prevalent Cases of Diabetic Retinopathy

4.4.5 Forecast Assumptions and Methods – Diagnosed Prevalent Cases of DME in the Diagnosed Diabetic Retinopathy Population

4.4.6 Forecast Assumptions and Methods – Total Prevalent Cases of ME following BRVO and CRVO

4.5 Epidemiological Forecast for Macular Edema (2013–2023)

4.5.1 Diagnosed Prevalent Cases of DME in the Diagnosed Diabetic Retinopathy Population

4.5.2 Age-Specific Diagnosed Prevalent Cases of DME in the Diagnosed Diabetic Retinopathy Population

4.5.3 Sex-Specific Diagnosed Prevalent Cases of DME in the Diagnosed Diabetic Retinopathy Population

4.5.4 Total Prevalent Cases of ME following BRVO

4.5.5 Age-Specific Total Prevalent Cases of ME following BRVO

4.5.6 Sex-Specific Total Prevalent Cases of ME following BRVO

4.5.7 Total Prevalent Cases of ME following CRVO

4.5.8 Age-Specific Total Prevalent Cases of ME following CRVO

4.5.9 Sex-Specific Total Prevalent Cases of ME following CRVO

4.6 Discussion

4.6.1 Epidemiological Forecast Insight

4.6.2 Limitations of the Analysis

4.6.3 Strengths of the Analysis

Inquire Before Buying @ http://www.marketoptimizer.org/contacts/inquire-before-buying?rname=10264 .

(This is a premium report priced at US$3995 for a single user License)

List of Tables

Table 1: Risk Factors for DME

Table 2: Comorbidities for DME

Table 3: 7MM, Sources of Diagnosed Prevalence of DME in the Diagnosed Diabetic Retinopathy Population

Table 4: 7MM, Sources of Total Prevalence of ME following BRVO and CRVO

Table 5: 7MM, Sources Not Used in Epidemiological Analysis of DME

Table 6: 7MM, Diagnosed Prevalent Cases of DME in the Diagnosed Diabetic Retinopathy Population, Ages =20 Years, Both Sexes, N, 2013–2023

Table 7: 7MM, Diagnosed Prevalent Cases of DME in the Diagnosed Diabetic Retinopathy Population, by Age, Both Sexes, N, (Row %), 2013

Table 8: 7MM, Diagnosed Prevalent Cases of DME in the Diagnosed Diabetic Retinopathy Population, by Sex, Ages =20 Years, N (Row %), 2013

Table 9: 7MM, Total Prevalent Cases of ME following BRVO, Ages =20 Years, Both Sexes, N, 2013–2023

Table 10: 7MM, Total Prevalent Cases of ME following BRVO, by Age, Both Sexes, N, (Row %), 2013

Table 11: 7MM, Total Prevalent Cases of ME following BRVO, by Sex, Ages =20 Years, N (Row %), 2013

Explore more reports on Pharmaceuticals industry at http://www.marketoptimizer.org/category/life-sciences/pharmaceuticals .

About Us:

MarketOptimizer.org is an online database of market research reports offer in-depth analysis of over 5000 market segments. The library has syndicated reports by leading market research publishers across the globe and also offer customized market research reports for multiple industries.

Media Contact: Ritesh Tiwari, MarketOptimizer, +18883915441, [email protected]

News distributed by PR Newswire iReach: https://ireach.prnewswire.com

SOURCE MarketOptimizer

More Stories By PR Newswire

Copyright © 2007 PR Newswire. All rights reserved. Republication or redistribution of PRNewswire content is expressly prohibited without the prior written consent of PRNewswire. PRNewswire shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon.

Latest Stories
Big Data, cloud, analytics, contextual information, wearable tech, sensors, mobility, and WebRTC: together, these advances have created a perfect storm of technologies that are disrupting and transforming classic communications models and ecosystems. In his session at @ThingsExpo, Erik Perotti, Senior Manager of New Ventures on Plantronics’ Innovation team, provided an overview of this technological shift, including associated business and consumer communications impacts, and opportunities it ...
Redis is not only the fastest database, but it is the most popular among the new wave of databases running in containers. Redis speeds up just about every data interaction between your users or operational systems. In his session at 19th Cloud Expo, Dave Nielsen, Developer Advocate, Redis Labs, will share the functions and data structures used to solve everyday use cases that are driving Redis' popularity.
A critical component of any IoT project is what to do with all the data being generated. This data needs to be captured, processed, structured, and stored in a way to facilitate different kinds of queries. Traditional data warehouse and analytical systems are mature technologies that can be used to handle certain kinds of queries, but they are not always well suited to many problems, particularly when there is a need for real-time insights.
To leverage Continuous Delivery, enterprises must consider impacts that span functional silos, as well as applications that touch older, slower moving components. Managing the many dependencies can cause slowdowns. See how to achieve continuous delivery in the enterprise.
You think you know what’s in your data. But do you? Most organizations are now aware of the business intelligence represented by their data. Data science stands to take this to a level you never thought of – literally. The techniques of data science, when used with the capabilities of Big Data technologies, can make connections you had not yet imagined, helping you discover new insights and ask new questions of your data. In his session at @ThingsExpo, Sarbjit Sarkaria, data science team lead ...
Is your aging software platform suffering from technical debt while the market changes and demands new solutions at a faster clip? It’s a bold move, but you might consider walking away from your core platform and starting fresh. ReadyTalk did exactly that. In his General Session at 19th Cloud Expo, Michael Chambliss, Head of Engineering at ReadyTalk, will discuss why and how ReadyTalk diverted from healthy revenue and over a decade of audio conferencing product development to start an innovati...
"Software-defined storage is a big problem in this industry because so many people have different definitions as they see fit to use it," stated Peter McCallum, VP of Datacenter Solutions at FalconStor Software, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Extracting business value from Internet of Things (IoT) data doesn’t happen overnight. There are several requirements that must be satisfied, including IoT device enablement, data analysis, real-time detection of complex events and automated orchestration of actions. Unfortunately, too many companies fall short in achieving their business goals by implementing incomplete solutions or not focusing on tangible use cases. In his general session at @ThingsExpo, Dave McCarthy, Director of Products...
WebRTC is bringing significant change to the communications landscape that will bridge the worlds of web and telephony, making the Internet the new standard for communications. Cloud9 took the road less traveled and used WebRTC to create a downloadable enterprise-grade communications platform that is changing the communication dynamic in the financial sector. In his session at @ThingsExpo, Leo Papadopoulos, CTO of Cloud9, discussed the importance of WebRTC and how it enables companies to focus...
StackIQ has announced the release of Stacki 3.2. Stacki is an easy-to-use Linux server provisioning tool. Stacki 3.2 delivers new capabilities that simplify the automation and integration of site-specific requirements. StackIQ is the commercial entity behind this open source bare metal provisioning tool. Since the release of Stacki in June of 2015, the Stacki core team has been focused on making the Community Edition meet the needs of members of the community, adding features and value, while ...
Deploying applications in hybrid cloud environments is hard work. Your team spends most of the time maintaining your infrastructure, configuring dev/test and production environments, and deploying applications across environments – which can be both time consuming and error prone. But what if you could automate provisioning and deployment to deliver error free environments faster? What could you do with your free time?
Using new techniques of information modeling, indexing, and processing, new cloud-based systems can support cloud-based workloads previously not possible for high-throughput insurance, banking, and case-based applications. In his session at 18th Cloud Expo, John Newton, CTO, Founder and Chairman of Alfresco, described how to scale cloud-based content management repositories to store, manage, and retrieve billions of documents and related information with fast and linear scalability. He addres...
SYS-CON Events announced today the Kubernetes and Google Container Engine Workshop, being held November 3, 2016, in conjunction with @DevOpsSummit at 19th Cloud Expo at the Santa Clara Convention Center in Santa Clara, CA. This workshop led by Sebastian Scheele introduces participants to Kubernetes and Google Container Engine (GKE). Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn the key concepts and practices for deploying and maintainin...
Cloud analytics is dramatically altering business intelligence. Some businesses will capitalize on these promising new technologies and gain key insights that’ll help them gain competitive advantage. And others won’t. Whether you’re a business leader, an IT manager, or an analyst, we want to help you and the people you need to influence with a free copy of “Cloud Analytics for Dummies,” the essential guide to this explosive new space for business intelligence.
The competitive landscape of the global cloud computing market in the healthcare industry is crowded due to the presence of a large number of players. The large number of participants has led to the fragmented nature of the market. Some of the major players operating in the global cloud computing market in the healthcare industry are Cisco Systems Inc., Carestream Health Inc., Carecloud Corp., AGFA Healthcare, IBM Corp., Cleardata Networks, Merge Healthcare Inc., Microsoft Corp., Intel Corp., an...