Literature DB >> 9498634

Costs of predicting IDDM.

J Hahl1, T Simell, J Ilonen, M Knip, O Simell.   

Abstract

Programmes aiming at prediction and prevention of insulin-dependent diabetes mellitus (IDDM), a multifactorial autoimmune disease, have been launched or are in the planning phase in several countries. We hypothesized that the costs of finding the correct target subjects for preventive interventions are likely to vary markedly according to the prediction strategy chosen. Average direct costs accruing in the Finnish IDDM Prediction and Prevention Project (DIPP) were analysed from the health care provider's viewpoint. The genetically targeted strategy included costs of assessing genetic IDDM susceptibility followed by measurement of marker(s) of islet autoimmunity in the susceptibility restricted population at 3 to 6-month intervals. In the pure immunological strategy markers of autoimmunity were repeatedly analysed in the entire population. The data were finally exposed to sensitivity analysis. The genetically targeted prediction strategy is cost-saving in the first year if autoimmune markers are analysed as frequently as under the DIPP project, and in all circumstances later. The 10-year direct costs per child are US$ 245 (present value $ 217, 5% discount rate) if the genetically targeted approach is used and $ 733 (present value $ 619) if the pure immunological strategy is chosen. In sensitivity analysis the 10-year costs (present value) per child of the genetically targeted strategy and of the pure immunological strategy varied from $ 152 to $ 241 and from $ 430 to $ 788, respectively. The genetically targeted IDDM prediction strategy is remarkably cost-saving as compared with the pure immunological strategy mainly because fewer subjects will need retesting during the follow-up.

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Year:  1998        PMID: 9498634     DOI: 10.1007/s001250050870

Source DB:  PubMed          Journal:  Diabetologia        ISSN: 0012-186X            Impact factor:   10.122


  6 in total

1.  Health-related quality of life in type 1 diabetes without or with symptoms of long-term complications.

Authors:  J Hahl; H Hämäläinen; H Sintonen; T Simell; S Arinen; O Simell
Journal:  Qual Life Res       Date:  2002-08       Impact factor: 4.147

Review 2.  Genetic testing and common disorders in a public health framework: how to assess relevance and possibilities. Background Document to the ESHG recommendations on genetic testing and common disorders.

Authors:  Frauke Becker; Carla G van El; Dolores Ibarreta; Eleni Zika; Stuart Hogarth; Pascal Borry; Anne Cambon-Thomsen; Jean Jacques Cassiman; Gerry Evers-Kiebooms; Shirley Hodgson; A Cécile J W Janssens; Helena Kaariainen; Michael Krawczak; Ulf Kristoffersson; Jan Lubinski; Christine Patch; Victor B Penchaszadeh; Andrew Read; Wolf Rogowski; Jorge Sequeiros; Lisbeth Tranebjaerg; Irene M van Langen; Helen Wallace; Ron Zimmern; Jörg Schmidtke; Martina C Cornel
Journal:  Eur J Hum Genet       Date:  2011-04       Impact factor: 4.246

3.  A simulation model for estimating direct costs of type 1 diabetes prevention.

Authors:  Jarmo Hahl; Tuula Simell; Antti Kupila; Päivi Keskinen; Mikael Knip; Jorma Ilonen; Olli Simell
Journal:  Pharmacoeconomics       Date:  2003       Impact factor: 4.981

Review 4.  Prediabetes in children: natural history, diagnosis, and preventive strategies.

Authors:  Petri Kulmala
Journal:  Paediatr Drugs       Date:  2003       Impact factor: 3.022

5.  Rotavirus infections and development of diabetes-associated autoantibodies during the first 2 years of life.

Authors:  M Blomqvist; S Juhela; S Erkkila; S Korhonen; T Simell; A Kupila; O Vaarala; O Simell; M Knip; J Ilonen
Journal:  Clin Exp Immunol       Date:  2002-06       Impact factor: 4.330

6.  Development of autoantibodies in the TrialNet Natural History Study.

Authors:  Kendra Vehik; Craig A Beam; Jeffrey L Mahon; Desmond A Schatz; Michael J Haller; Jay M Sosenko; Jay S Skyler; Jeffrey P Krischer
Journal:  Diabetes Care       Date:  2011-07-12       Impact factor: 19.112

  6 in total

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