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PharmacoEconomics
09, 2022;40 (9): 901-915.

Does the Structure Matter? An External Validation and Health Economic Results Comparison of Event Simulation Approaches in Severe Obesity.

Björn Schwander, Klaus Kaier, Mickaël Hiligsmann, Silvia Evers, Mark Nuijten
Author Information
  1. Björn Schwander: Department of Health Services Research, CAPHRI-Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands. bjoern.schwander@ahead-net.de. ORCID
  2. Klaus Kaier: Institute of Medical Biometry and Statistics (IMBI), University of Freiburg, Freiburg im Breisgau, Germany. ORCID
  3. Mickaël Hiligsmann: Department of Health Services Research, CAPHRI-Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands. ORCID
  4. Silvia Evers: Department of Health Services Research, CAPHRI-Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands. ORCID
  5. Mark Nuijten: a2m-Ars Accessus Medica, Amsterdam, the Netherlands.
PMID: 35771486 DOI: 10.1007/s40273-022-01162-6

Abstract

OBJECTIVES: As obesity-associated events impact long-term survival, health economic (HE) modelling is commonly applied, but modelling approaches are diverse. This research aimed to compare the events simulation and the HE outcomes produced by different obesity modelling approaches.
METHODS: An external validation, using the Swedish obesity subjects (SOS) study, of three main structural event modelling approaches was performed: (1) continuous body mass index (BMI) approach; (2) risk equation approach; and (3) categorical BMI-related approach. Outcomes evaluated were mortality, cardiovascular events, and type 2 diabetes (T2D) for both the surgery and the control arms. Concordance between modelling results and the SOS study were investigated by different state-of-the-art measurements, and categorized by the grade of deviation observed (grades 1-4 expressing mild, moderate, severe, and very severe deviations). Furthermore, the costs per quality-adjusted life-year (QALY) gained of surgery versus controls were compared.
RESULTS: Overall and by study arm, the risk equation approach presented the lowest average grade of deviation (overall grade 2.50; control arm 2.25; surgery arm 2.75), followed by the continuous BMI approach (overall 3.25; control 3.50; surgery 3.00) and by the categorial BMI approach (overall 3.63; control 3.50; surgery 3.75). Considering different confidence interval limits, the costs per QALY gained were fairly comparable between all structural approaches (ranging from £2,055 to £6,206 simulating a lifetime horizon).
CONCLUSION: None of the structural approaches provided perfect external event validation, although the risk equation approach showed the lowest overall deviations. The economic outcomes resulting from the three approaches were fairly comparable.

References

  1. World Health Organization. Fact Sheet on Obesity. 2003. https://www.who.int/dietphysicalactivity/media/en/gsfs_obesity.pdf . Accessed 09 Feb 2019.
  2. Wharton S, Lau DCW, Vallis M, Sharma AM, Biertho L, Campbell-Scherer D, et al. Obesity in adults: a clinical practice guideline. Can Med Assoc J. 2020;192(31):E875–91. https://doi.org/10.1503/cmaj.191707 . [DOI: 10.1503/cmaj.191707]
  3. Yumuk V, Tsigos C, Fried M, Schindler K, Busetto L, Micic D, et al. European Guidelines for Obesity Management in Adults. Obes Facts. 2015;8(6):402–24. https://doi.org/10.1159/000442721 . [DOI: 10.1159/000442721]
  4. World Health Organization. Updated Fact Sheet on Obesity. 2018. https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight . Accessed 09 Feb 2019.
  5. Schwander B, Hiligsmann M, Nuijten M, Evers S. Systematic review and overview of health economic evaluation models in obesity prevention and therapy. Expert Rev Pharmacoecon Outcomes Res. 2016;16(5):561–70. https://doi.org/10.1080/14737167.2016.1230497 . [DOI: 10.1080/14737167.2016.1230497]
  6. Philips Z, Bojke L, Sculpher M, Claxton K, Golder S. Good practice guidelines for decision-analytic modelling in health technology assessment: a review and consolidation of quality assessment. Pharmacoeconomics. 2006;24(4):355–71. https://doi.org/10.2165/00019053-200624040-00006 . [DOI: 10.2165/00019053-200624040-00006]
  7. Eddy DM, Hollingworth W, Caro JJ, Tsevat J, McDonald KM, Wong JB. Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force–7. Value Health. 2012;15(6):843–50. https://doi.org/10.1016/j.jval.2012.04.012 . [DOI: 10.1016/j.jval.2012.04.012]
  8. Schwander B, Nuijten M, Hiligsmann M, Evers S. Event simulation and external validation applied in published health economic models for obesity: a systematic review. Expert Rev Pharmacoecon Outcomes Res. 2018;18(5):529–41. https://doi.org/10.1080/14737167.2018.1501680 . [DOI: 10.1080/14737167.2018.1501680]
  9. Au N, Marsden G, Mortimer D, Lorgelly PK. The cost-effectiveness of shopping to a predetermined grocery list to reduce overweight and obesity. Nutr Diabetes. 2013;3(6): e77. https://doi.org/10.1038/nutd.2013.18 . [DOI: 10.1038/nutd.2013.18]
  10. Caro J, Stillman O, Danel A, Getsios D, McEwan P. Cost effectiveness of rimonabant use in patients at increased cardiometabolic risk: estimates from a Markov model. J Med Econ. 2007;10(3):239–54. https://doi.org/10.3111/13696990701438629 . [DOI: 10.3111/13696990701438629]
  11. Meads DM, Hulme CT, Hall P, Hill AJ. The cost-effectiveness of primary care referral to a UK commercial weight loss programme. Clin Obes. 2014;4(6):324–32. https://doi.org/10.1111/cob.12077 . [DOI: 10.1111/cob.12077]
  12. Schwander B, Nuijten M, Hiligsmann M, Queally M, Leidl R, Joore M, et al. Identification and expert panel rating of key structural approaches applied in health economic obesity models. Health Policy Technol. 2020;9(3):314–22. https://doi.org/10.1016/j.hlpt.2020.03.005 . [DOI: 10.1016/j.hlpt.2020.03.005]
  13. Schwander B, Nuijten M, Evers S, Hiligsmann M. Replication of published health economic obesity models: assessment of facilitators, hurdles and reproduction success. Pharmacoeconomics. 2021;39(4):433–46. https://doi.org/10.1007/s40273-021-01008-7 . [DOI: 10.1007/s40273-021-01008-7]
  14. Sjöström L, Lindroos AK, Peltonen M, Torgerson J, Bouchard C, Carlsson B, et al. Lifestyle, diabetes, and cardiovascular risk factors 10 years after bariatric surgery. N Engl J Med. 2004;351(26):2683–93. https://doi.org/10.1056/NEJMoa035622 . [DOI: 10.1056/NEJMoa035622]
  15. Sjöström L. Review of the key results from the Swedish Obese Subjects (SOS) trial - a prospective controlled intervention study of bariatric surgery. J Intern Med. 2013;273(3):219–34. https://doi.org/10.1111/joim.12012 . [DOI: 10.1111/joim.12012]
  16. National Institute for Health and Care Excellence. Single Technology Appraisal—Liraglutide for managing overweight and obesity [ID740]. 2020. https://www.nice.org.uk/guidance/ta664/evidence/appraisal-consultation-committee-papers-pdf-8952596893 . Accessed 19 Jan 2022.
  17. McManus E, Turner D, Sach T. Can You Repeat That? Exploring the definition of a successful model replication in health economics. Pharmacoeconomics. 2019;37(11):1371–81. https://doi.org/10.1007/s40273-019-00836-y . [DOI: 10.1007/s40273-019-00836-y]
  18. Briggs ADM, Wolstenholme J, Blakely T, Scarborough P. Choosing an epidemiological model structure for the economic evaluation of non-communicable disease public health interventions. Popul Health Metrics. 2016;14(1):17. https://doi.org/10.1186/s12963-016-0085-1 . [DOI: 10.1186/s12963-016-0085-1]
  19. Sutcliffe SJ, Fox KF, Wood DA, Sutcliffe A, Stock K, Wright M, et al. Incidence of coronary heart disease in a health authority in London: review of a community register. BMJ. 2003;326(7379):20. https://doi.org/10.1136/bmj.326.7379.20 . [DOI: 10.1136/bmj.326.7379.20]
  20. Gibbs RG, Newson R, Lawrenson R, Greenhalgh RM, Davies AH. Diagnosis and initial management of stroke and transient ischemic attack across UK health regions from 1992 to 1996: experience of a national primary care database. Stroke. 2001;32(5):1085–90. https://doi.org/10.1161/01.str.32.5.1085 . [DOI: 10.1161/01.str.32.5.1085]
  21. González EL, Johansson S, Wallander MA, Rodríguez LA. Trends in the prevalence and incidence of diabetes in the UK: 1996–2005. J Epidemiol Community Health. 2009;63(4):332–6. https://doi.org/10.1136/jech.2008.080382 . [DOI: 10.1136/jech.2008.080382]
  22. Mulnier HE, Seaman HE, Raleigh VS, Soedamah-Muthu SS, Colhoun HM, Lawrenson RA, et al. Risk of stroke in people with type 2 diabetes in the UK: a study using the General Practice Research Database. Diabetologia. 2006;49(12):2859–65. https://doi.org/10.1007/s00125-006-0493-z . [DOI: 10.1007/s00125-006-0493-z]
  23. Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA. 1999;282(16):1523–9. https://doi.org/10.1001/jama.282.16.1523 . [DOI: 10.1001/jama.282.16.1523]
  24. Ni Mhurchu C, Parag V, Nakamura M, Patel A, Rodgers A, Lam TH. Body mass index and risk of diabetes mellitus in the Asia-Pacific region. Asia Pac J Clin Nutr. 2006;15(2):127–33. [PMID: 16672195]
  25. Anderson KM, Odell PM, Wilson PW, Kannel WB. Cardiovascular disease risk profiles. Am Heart J. 1991;121(1 Pt 2):293–8. https://doi.org/10.1016/0002-8703(91)90861-b . [DOI: 10.1016/0002-8703(91)90861-b]
  26. Anderson KM, Wilson PW, Odell PM, Kannel WB. An updated coronary risk profile. A statement for health professionals. Circulation. 1991;83(1):356–62. https://doi.org/10.1161/01.cir.83.1.356 . [DOI: 10.1161/01.cir.83.1.356]
  27. D’Agostino RB, Russell MW, Huse DM, Ellison RC, Silbershatz H, Wilson PW, et al. Primary and subsequent coronary risk appraisal: new results from the Framingham study. Am Heart J. 2000;139(2 Pt 1):272–81. https://doi.org/10.1067/mhj.2000.96469 . [DOI: 10.1067/mhj.2000.96469]
  28. Wolf PA, D’Agostino RB, Belanger AJ, Kannel WB. Probability of stroke: a risk profile from the Framingham Study. Stroke. 1991;22(3):312–8. https://doi.org/10.1161/01.str.22.3.312 . [DOI: 10.1161/01.str.22.3.312]
  29. Clarke PM, Gray AM, Briggs A, Farmer AJ, Fenn P, Stevens RJ, et al. A model to estimate the lifetime health outcomes of patients with type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS no. 68). Diabetologia. 2004;47(10):1747–59. https://doi.org/10.1007/s00125-004-1527-z . [DOI: 10.1007/s00125-004-1527-z]
  30. Kothari V, Stevens RJ, Adler AI, Stratton IM, Manley SE, Neil HA, et al. UKPDS 60: risk of stroke in type 2 diabetes estimated by the UK Prospective Diabetes Study risk engine. Stroke. 2002;33(7):1776–81. https://doi.org/10.1161/01.str.0000020091.07144.c7 . [DOI: 10.1161/01.str.0000020091.07144.c7]
  31. Stevens RJ, Kothari V, Adler AI, Stratton IM. The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56). Clin Sci (Lond). 2001;101(6):671–9. [DOI: 10.1042/CS20000335]
  32. Stern MP, Williams K, Haffner SM. Identification of persons at high risk for type 2 diabetes mellitus: do we need the oral glucose tolerance test? Ann Intern Med. 2002;136(8):575–81. https://doi.org/10.7326/0003-4819-136-8-200204160-00006 . [DOI: 10.7326/0003-4819-136-8-200204160-00006]
  33. Myint PK, Luben RN, Wareham NJ, Bingham SA, Khaw KT. Combined effect of health behaviours and risk of first ever stroke in 20,040 men and women over 11 years’ follow-up in Norfolk cohort of European Prospective Investigation of Cancer (EPIC Norfolk): prospective population study. BMJ. 2009;338: b349. https://doi.org/10.1136/bmj.b349 . [DOI: 10.1136/bmj.b349]
  34. Mohan KM, Wolfe CD, Rudd AG, Heuschmann PU, Kolominsky-Rabas PL, Grieve AP. Risk and cumulative risk of stroke recurrence: a systematic review and meta-analysis. Stroke. 2011;42(5):1489–94. https://doi.org/10.1161/strokeaha.110.602615 . [DOI: 10.1161/strokeaha.110.602615]
  35. Labounty TM, Gomez MJ, Achenbach S, Al-Mallah M, Berman DS, Budoff MJ, et al. Body mass index and the prevalence, severity, and risk of coronary artery disease: an international multicentre study of 13,874 patients. Eur Heart J Cardiovasc Imaging. 2013;14(5):456–63. https://doi.org/10.1093/ehjci/jes179 . [DOI: 10.1093/ehjci/jes179]
  36. Smolina K, Wright FL, Rayner M, Goldacre MJ. Long-term survival and recurrence after acute myocardial infarction in England, 2004 to 2010. Circ Cardiovasc Qual Outcomes. 2012;5(4):532–40. https://doi.org/10.1161/circoutcomes.111.964700 . [DOI: 10.1161/circoutcomes.111.964700]
  37. Warren E, Brennan A, Akehurst R. Cost-effectiveness of sibutramine in the treatment of obesity. Med Decision Making. 2004;24(1):9–19. https://doi.org/10.1177/0272989x03261565 . [DOI: 10.1177/0272989x03261565]
  38. UK Office for National Statistics. National Life Tables, United Kingdom, 1980-1982 to 2018-2020. 2021. https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/lifeexpectancies/datasets/nationallifetablesunitedkingdomreferencetables . Accessed 17 May 2022.
  39. Willis M, Johansen P, Nilsson A, Asseburg C. Validation of the economic and health outcomes model of type 2 diabetes mellitus (ECHO-T2DM). Pharmacoeconomics. 2017;35(3):375–96. https://doi.org/10.1007/s40273-016-0471-3 . [DOI: 10.1007/s40273-016-0471-3]
  40. Lopes S, Johansen P, Lamotte M, McEwan P, Olivieri A-V, Foos V. External validation of the core obesity model to assess the cost-effectiveness of weight management interventions. Pharmacoeconomics. 2020;38(10):1123–33. https://doi.org/10.1007/s40273-020-00941-3 . [DOI: 10.1007/s40273-020-00941-3]
  41. Hippisley-Cox J, Coupland C. Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study. BMJ. 2017;359: j5019. https://doi.org/10.1136/bmj.j5019 . [DOI: 10.1136/bmj.j5019]
  42. Nuttall FQ. Body mass index: obesity, BMI, and health: a critical review. Nutr Today. 2015;50(3):117–28. https://doi.org/10.1097/nt.0000000000000092 . [DOI: 10.1097/nt.0000000000000092]
  43. Gutin I, In BMI. We trust: reframing the body mass index as a measure of health. Soc Theory Health. 2018;16(3):256–71. https://doi.org/10.1057/s41285-017-0055-0 . [DOI: 10.1057/s41285-017-0055-0]
  44. Look Ahead Research Group. Eight-year weight losses with an intensive lifestyle intervention: the look AHEAD study. Obesity (Silver Spring). 2014;22(1):5–13. https://doi.org/10.1002/oby.20662 . [DOI: 10.1002/oby.20662]

MeSH Term

Cost-Benefit Analysis
Diabetes Mellitus, Type 2
Humans
Obesity
Obesity, Morbid
Quality-Adjusted Life Years
Journal Article
Article has an altmetric score of 5

Word Cloud

Created with Highcharts 10.0.0approach3approachesmodelling2surgerycontroloveralleventsdifferentstudystructuralBMIriskequationgradearm50economicHEoutcomesobesityexternalvalidationSOSthreeeventcontinuousdeviationseveredeviationscostsperQALYgainedlowest2575fairlycomparableOBJECTIVES:obesity-associatedimpactlong-termsurvivalhealthcommonlyapplieddiverseresearchaimedcomparesimulationproducedMETHODS:usingSwedishsubjectsmainperformed:1bodymassindexcategoricalBMI-relatedOutcomesevaluatedmortalitycardiovasculartypediabetesT2DarmsConcordanceresultsinvestigatedstate-of-the-artmeasurementscategorizedobservedgrades1-4expressingmildmoderateFurthermorequality-adjustedlife-yearversuscontrolscomparedRESULTS:Overallpresentedaveragefollowed00categorial63Consideringconfidenceintervallimitsranging£2055£6206simulatinglifetimehorizonCONCLUSION:NoneprovidedperfectalthoughshowedresultingStructureMatter?ExternalValidationHealthEconomicResultsComparisonEventSimulationApproachesSevereObesity

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