Sun Sun1,2, Erik Stenberg3, Yang Cao4, Lars Lindholm5, Klas-Göran Salén5, Karl A Franklin6, Nan Luo7. 1. Department of Epidemiology and Global Health, Umeå University, 90185, Umeå, Sweden. sun.sun@umu.se. 2. Research Group Health Outcomes and Economic Evaluation, Department of Learning, Informatics, Management and Ethics, Karolinska Instiutet, Solna, Sweden. sun.sun@umu.se. 3. Department of Surgery, Faculty of Medicine and Health, Örebro University, Örebro, Sweden. 4. Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden. 5. Department of Epidemiology and Global Health, Umeå University, 90185, Umeå, Sweden. 6. Department of Surgical and Perioperative Sciences, Surgery, Umeå University, Umeå, Sweden. 7. NUS Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Abstract
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.
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.
Authors: J L Hedenbro; E Näslund; L Boman; G Lundegårdh; A Bylund; M Ekelund; A Laurenius; P Möller; T Olbers; M Sundbom; J Ottosson; I Näslund Journal: Obes Surg Date: 2015-10 Impact factor: 4.129
Authors: Clara Mukuria; Donna Rowen; Sue Harnan; Andrew Rawdin; Ruth Wong; Roberta Ara; John Brazier Journal: Appl Health Econ Health Policy Date: 2019-06 Impact factor: 2.561