PS 1-7 SYSTEMATIC OVERVIEW OF DECISION-ANALYTIC MODELING STUDIES IN IODINE DEFICIENCY RELATED DISEASES

Sunday, October 23, 2016
Bayshore Ballroom ABC, Lobby Level (Westin Bayshore Vancouver)
Poster Board # PS 1-7

Ursula Rochau, MD, MSc, UMIT, Dept. of Public Health, Health Services Research & HTA / ONCOTYROL - Center for Personalized Cancer Medicine, Area 4 HTA and Bioinformatics, Hall i. T./Innsbruck, Austria, Marie Schoenhensch, BSc, Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i. T., Austria, Vjollca Qerimi, MPharm, Institute of Public Health, Medical Decision Making and HTA, Department of Public Health, Health Services Research and HTA, UMIT - University for Health Sciences, Medical Informatics and Technology / Faculty of Pharmacy, University of Skopje, Macedonia, Hall in Tyrol, Austria, Igor Stojkov, MPharm, UMIT - University for Health Sciences, Medical Informatics and Technology, Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, Hall i. T., Austria, Robin Peeters, MD, PhD, Thyroid Center, Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, Netherlands, Rodrigo Moreno-Reyes, MD, PhD, Department of Nuclear Medicine, Hospital Erasme, Université Libre de Bruxelles, Belgium, Brussels, Belgium, Henry Völzke, MD, Institute for Community Medicine, University Medicine Greifswald, Germany, Greifswald, Germany, Uwe Siebert, MD, MPH, MSc, ScD, UMIT, Dept. of Public Health, Health Services Research & HTA / Harvard Univ., Dept. Health Policy & Management, Institute for Technology Assessment / Oncotyrol - Center for Personalized Cancer Medicine, Hall in Tirol (Austria) / Boston (USA), Austria and Beate Jahn, PhD, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria, Hall in Tyrol, Austria
Purpose:

Iodine deficiency related disease prevention and treatment remain an important public health problem. Iodine deficiency can have severe health consequences, such as cretinism, goiter, hypothyroidism or thyroid nodules as well as economic implications. Our aim was to give an overview on studies applying a decision-analytic model to evaluate the effectiveness and/or cost-effectiveness of iodine deficiency related treatments, prevention strategies or diagnostic procedures.

Method:

We performed a comprehensive systematic literature search in Pubmed/Medline, Tuft’s CEA Registry, NHS EED and Embase to identify published studies comparing different treatment, prevention or diagnostic strategies with a mathematical decision-analytic model. Studies were required to evaluate patient-relevant health outcomes (e.g., remaining life years, quality-adjusted life years). All studies were screened by at least two independent reviewers and a third person (modeling or clinical expert) decided on inclusion if there was disagreement. We completed a comprehensive evidence table providing an overview on study characteristics (e.g., research question, target population, time horizon, health outcomes, analytic approach, perspective).

Result:

Overall, we found 2241 studies. After removal of duplicates, abstract and title screening, as well as fulltext screening, 16 studies remained included. Ten studies evaluated screening programs (mainly newborns and pregnant women), five studies focused on treatment approaches (Graves’ disease, thyroid nodules) and one study was about a primary prevention (consequences of iodine supplementation on offspring) related to iodine deficiency. Most of the studies were conducted within the U.S. health-care context (n=7), two for Iran and France, and one study for the Czech Republic, Germany, the Netherlands and the U.K. In six studies, a Markov state-transition model was applied and in eight studies a decision tree. The remaining studies did not explicitly state their modeling approach. The analytical time horizon ranged from one year to lifetime. 75% of the studies evaluated quality-adjusted life years as health outcome measure. In all studies, a cost-effectiveness analysis was performed. None of the models compared the same research question for the same health care context; therefore, no comparison of the models was possible. None of the models reported a formal model validation.

Conclusion:

Overall, we mostly found decision-analytic modeling studies evaluating specific screening programs or treatment approaches; however, there was no model evaluating primary prevention programs on a population basis.

See more of: POSTER SESSION I & WELCOME RECEPTION

See more of: 38th Annual North American Meeting of the Society for Medical Decision Making