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Lewis Sheiner


2019
Stockholm, Sweden



2018
Montreux, Switzerland

2017
Budapest, Hungary

2016
Lisboa, Portugal

2015
Hersonissos, Crete, Greece

2014
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2013
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2012
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2011
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2010
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2009
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2008
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2007
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2006
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2005
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2004
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2003
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2002
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2001
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2000
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1999
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1998
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1997
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1996
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1995
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1994
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1993
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1992
Basel, Switzerland



Printable version

PAGE. Abstracts of the Annual Meeting of the Population Approach Group in Europe.
ISSN 1871-6032

Reference:
PAGE 25 (2016) Abstr 5818 [www.page-meeting.org/?abstract=5818]


Poster: Drug/Disease modeling - Other topics


IV-77 Kirill Zhudenkov A Markov Chain model to characterize cataract progression and disease burden in the Russian Federation

Kirill Zhudenkov (1), Olga Orlova (2), Blair Ireland, Vladimir Trubilin (2)

(1) – M&S Decisions, Moscow, Russia; (2) - The Institute of Improvement of Professional Skill of the Federal Medico-Biological Agency of Russia

Objectives: Cataract - clouding of the eye lens, resulting in blurred vision - is a slowly but irreversibly progressing disease; it may result in complete blindness. The ophthalmic market in Russia is rapidly growing. However, among patients, ophthalmologists, and health authorities, there is  broad heterogeneity in knowledge of cataract treatment options and in opinions on the utilization of modern treatment techniques. The aim of this work was to provide a model-based analysis that represents cataract progression and disease burden in Russia, in order to compare costs of (i) conservative and non-effective treatment (eye drops) vs. (ii) surgical and more effective treatments.

Methods: The disease progression model implied a Markov Chain, with 4 states of vision quality, from normal vision to severe cataract and transition probabilities fitted against the epidemiology study data [1, 2] and official Russian statistics [3-5]. The model estimates disease progression, quality-of-life changes, direct and indirect treatment costs, in 50- to 80-year old patients. Cataract surgery outcomes and complications were also taken into account.

Results: The model allowed us to estimate disease progression rate, as related to the continuous loss of vision observed at different stages of cataract development. For example, the model suggested that, at around 50 years of age, about 15% of individuals within the considered cohort would be diagnosed with cataract; at age 60, this fraction would raise up to 50%. From a cost effectiveness standpoint, model-based results indicate that direct and indirect costs of conservative treatment, which are initially much smaller vs. surgery cost, exceed direct costs related to surgical treatment, 4 to 8 years post diagnosis.

Conclusions: We provide here a new, quantitative, model-based paradigm for cataract burden & treatment option assessments, through the implementation of a qualified disease progression model and a cost / quality-of-life analysis. Costs of conservative (and rather non-efficacious) treatment, while initially modest, do exceed surgery cost within a relatively short period of time following diagnosis and while individuals are still part of the active work force, thus favoring the more efficacious, and ultimately more cost-effective treatment (surgery). These results are expected to provide a rational support for the wider use of cataract surgery in Russia, both in the private market as well as in state-funded medical care.



References:
[1] J Epidemiol Biostat. 1999;4(4):337-44;
[2] Eur J Ophthalmol. 2010 Sep-Oct;20(5):892-901;
[3] The data from the Moscow Federal fund for OMS 2015. http://www.mgfoms.ru;
[4] The data from the General OMS Tariff agreement 2013;
[5] The data from the Federal Statistics Service in Russia 2015. http://www.gks.ru