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Mapping the obesity problems scale to the SF-6D: results based on the Scandinavian Obesity Surgery Registry (SOReg)
Department of Epidemiology and Global Health, Umeå University, Umeå, Sweden; Research Group Health Outcomes and Economic Evaluation, Department of Learning, Informatics, Management and Ethics, Karolinska Instiutet, Solna, Sweden.
Örebro University, School of Medical Sciences. Örebro University Hospital. Department of Surgery.ORCID iD: 0000-0003-4958-1611
Örebro University, School of Medical Sciences. Örebro University Hospital. (Clinical Epidemiology and Biostatistics)ORCID iD: 0000-0002-3552-9153
Department of Epidemiology and Global Health, Umeå University, Umeå, Sweden.
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2023 (English)In: European Journal of Health Economics, ISSN 1618-7598, E-ISSN 1618-7601, Vol. 24, no 2, p. 279-292Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Obesity Problem Scale (OP) is a widely applied instrument for obesity, however currently calculation of health utility based on OP is not feasible as it is not a preference-based measure. Using data from the Scandinavian Obesity Surgery Registry (SOReg), we sought to develop a mapping algorithm to estimate SF-6D utility from OP. Furthermore, to test whether the mapping algorithm is robust to the effect of surgery.

METHOD: The source data SOReg (n = 36 706) contains both OP and SF-36, collected at pre-surgery and at 1, 2 and 5 years post-surgery. The Ordinary Least Square (OLS), beta-regression and Tobit regression were used to predict the SF-6D utility for different time points respectively. Besides the main effect model, different combinations of patient characteristics (age, sex, Body Mass Index, obesity-related comorbidities) were tested. Both internal validation (split-sample validation) and validation with testing the mapping algorithm on a dataset from other time points were carried out. A multi-stage model selection process was used, accessing model consistency, parsimony, goodness-of-fit and predictive accuracy. Models with the best performance were selected as the final mapping algorithms.

RESULTS: The final mapping algorithms were based on OP summary score using OLS models, for pre- and post-surgery respectively. Mapping algorithms with different combinations of patients' characteristics were presented, to satisfy the user with a different need.

CONCLUSION: This study makes available algorithms enabling crosswalk from the Obesity Problem Scale to the SF-6D utility. Different mapping algorithms are recommended for the mapping of pre- and post-operative data.

Place, publisher, year, edition, pages
Springer, 2023. Vol. 24, no 2, p. 279-292
Keywords [en]
Cross-walk, Health utility, Mapping, Obesity, Obesity-problem scale (OP), Quality of life (QOL), SF-6D
National Category
Surgery Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:oru:diva-99106DOI: 10.1007/s10198-022-01473-7ISI: 000798119000001PubMedID: 35596099Scopus ID: 2-s2.0-85130222208OAI: oai:DiVA.org:oru-99106DiVA, id: diva2:1659879
Funder
Umeå UniversityForte, Swedish Research Council for Health, Working Life and Welfare, 2018-00896Available from: 2022-05-23 Created: 2022-05-23 Last updated: 2023-12-08Bibliographically approved

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Stenberg, ErikCao, Yang

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