Advertisement

PharmacoEconomics

, Volume 29, Issue 3, pp 225–237 | Cite as

Value of Information in the Osteoarthritis Setting

Cost Effectiveness of COX-2 Selective Inhibitors, Traditional NSAIDs and Proton Pump Inhibitors
  • Nicholas Latimer
  • Joanne Lord
  • Robert L. Grant
  • Rachel O’Mahony
  • John Dickson
  • Philip G. Conaghan
Original Research Article Value of Information in the Osteoarthritis Setting

Abstract

Background: Recent National Institute for Health and Clinical Excellence (NICE) guidance recommended that when traditional NSAIDs or cyclooxygenase (COX)-2 selective inhibitors are used by people with osteoarthritis (OA), they should be prescribed along with a proton pump inhibitor (PPI). However, specific recommendations about the type ofNSAID orCOX-2 could not be made due to high levels of uncertainty in the economic evaluation.

Objective: To investigate the value of obtaining further evidence to inform the economic evaluation of NSAIDs, COX-2s and PPIs for people with OA.

Methods: An economic evaluation with an expected value of perfect information (EVPI) analysis was conducted, using a Markov model with data identified from a systematic review. The base-case model used adverse event data from the three largest randomized trials of COX-2 inhibitors, and we repeated the analysis using observational adverse event data. The model was run for a hypothetical population of people with OA, and subgroup analyses were conducted for people with raised gastrointestinal (GI) and cardiovascular (CV) risk. The EVPI was based upon the OA population in England — approximately 2.8 million people. Of these, 50% were assumed to use NSAIDs or COX-2 selective inhibitors for 3 months per year and 56% of these were assumed to be patients with raised GI and CV risk.

Results: The value of further information for this decision problem was very high. Population-level EVPI was £85.1 million in the low-risk group and £179.5 million in the high-risk group (2007–8 values). Expected value of partial perfect information (EVPPI) analysis showed that the groups of parameters for which further evidence was likely to be of most value were CV adverse event risks and all adverse event rates associated with the specific drugs celecoxib and ibuprofen. The value of perfect information remained high even when observational adverse event data were used.

Conclusions: There is a very high value associated with obtaining further information on uncertain parameters for the economic evaluation of NSAIDs, COX-2 selective inhibitors and PPIs for people with OA. Obtaining further randomized or observational information on CV risks is likely to be particularly cost effective.

Keywords

Celecoxib Proton Pump Inhibitor Utility Score Etoricoxib Adverse Event Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors gratefully acknowledge the advice and input of other members of the Osteoarthritis Guideline Development Group and other experts who advised the group regarding the original economic model: Dr Fraser Birrell, Dr Michael Burke, Ms Jo Cumming, Professor Paul Dieppe, Professor Mike Doherty, Dr Krysia Dziedzic, Professor Roger Francis, Mrs Christine Kell, Professor Alex MacGregor, Ms Carolyn Naisby, Mrs Susan Oliver, Mrs Alison Richards, Dr Martin Underwood, Dr Garry Barton, Dr Bernard Higgins.

All authors were members of the Guideline Development Group (PGC chaired the Group, JD was the clinical advisor, RLG was NCC-CC project manager, NL was the NCC-CC health economist, JL was the NICE technical advisor and RO was the NCC-CC research fellow). During the guidelines process, PGC received travel grants to educational meetings from Merck Sharp & Dohme (MSD), honoraria for joint injection tutorials (MSD) and has been advisor to Novartis and Bristol Myers Squibb on imaging studies in rheumatoid arthritis. JD has received travel grants from Pfizer, Wyeth, Novartis and Napp, and honoraria for tutorials from Pfizer and Novartis; he has been on advisory boards for pharmaceutical companies, including GSK, Wyeth and Novartis. After completing the guideline analysis but prior to its publication, NL joined Roche Products Ltd and has since moved to the University of Sheffield. RLG, JL and RO have no competing interests.

The NCC-CC was commissioned and funded by NICE to complete the Osteoarthritis Clinical Guideline; however, this supplementary analysis was undertaken subsequent to the guideline process and no further funding was received.

References

  1. 1.
    National Collaborating Centre for Chronic Conditions (NCC-CC) on behalf of the National Institute for Health and Clinical Excellence. Osteoarthritis: national clinical guideline for care and management in adults. London: Royal College of Physicians, 2008 Feb [online]. Available from URL: http://www.nice.org.uk/nicemedia/pdf/CG059FullGuideline.pdf [Accessed 2010 Sep 28]Google Scholar
  2. 2.
    Maetzel A, Krahn M, Naglie G, et al. The cost-effectiveness of celecoxib and rofecoxib in patients with osteoarthritis or rheumatoid arthritis. Ottawa (ON): Canadian Coordinating Office for Health Technology Assessment, 2001. Technology report no. 23Google Scholar
  3. 3.
    Schaefer M, De Lattre M, Gao X, et al. Assessing the cost-effectiveness of COX-2 specific inhibitors for arthritis in the Veterans Health Administration. Curr Med Res Opin 2005; 21 (1): 47–60PubMedCrossRefGoogle Scholar
  4. 4.
    Spiegel BM, Targownik L, Dulai GS, et al. The cost-effectiveness of cyclooxygenase-2 selective inhibitors in the management of chronic arthritis. Ann Int Med 2003; 138 (10): 795–806PubMedGoogle Scholar
  5. 5.
    Segal L, Day SE, Chapman AB, et al. Can we reduce disease burden from osteoarthritis? Med J Aust 2004; 180 (5 Suppl.): 1–7Google Scholar
  6. 6.
    National Collaborating Centre for Chronic Conditions (NCC-CC) on behalf of the National Institute for Health and Clinical Excellence. Osteoarthritis: national clinical guideline for care and management in adults: appendix D. Details of the NSAID/COX-2 inhibitor health economic model. London: Royal College of Physicians, 2008 Feb [online]. Available from URL: http://bookshop.rcplondon.ac.uk/contents/pub242-f185bcd7-8506-422c-8159-b755dd335a3b.pdf [Accessed 2010 Sep 28]Google Scholar
  7. 7.
    National Institute for Health and Clinical Excellence. Guidance on the use of cyclo-oxygenase (COX) II selective inhibitors, celecoxib, rofecoxib, meloxicam and etodolac for osteoarthritis and rheumatoid arthritis. Technology appraisal guidance no. 27. London: NICE, 2001 JulGoogle Scholar
  8. 8.
    Latimer N, Lord J, Grant RL, et al. Cost effectiveness of COX 2 selective inhibitors and traditional NSAIDs alone or in combination with a proton pump inhibitor for people with osteoarthritis. BMJ 2009; 339: b2538CrossRefGoogle Scholar
  9. 9.
    Silverstein FE, Faich G. Gastrointestinal toxicity with celecoxib vs nonsteroidal anti-inflammatory drugs for osteoarthritis and rheumatoid arthritis: the CLASS study. A randomized controlled trial. JAMA 2000; 284 (10): 1247–55Google Scholar
  10. 10.
    Laine L, Curtis SP, Cryer B, et al. Assessment of upper gastrointestinal safety of etoricoxib and diclofenac in patients with osteoarthritis and rheumatoid arthritis in the Multinational Etoricoxib and Diclofenac Arthritis Longterm (MEDAL) programme: a randomised comparison. Lancet 2007; 369 (9560): 465–73PubMedCrossRefGoogle Scholar
  11. 11.
    Farkouh ME, Kirschner H. Comparison of lumiracoxib with naproxen and ibuprofen in the Therapeutic Arthritis Research and Gastrointestinal Event Trial (TARGET), cardiovascular outcomes: randomised controlled trial. Lancet 2004; 364 (9435): 675–84PubMedCrossRefGoogle Scholar
  12. 12.
    Schnitzer TJ, Burmester GR, Mysler E. Comparison of lumiracoxib with naproxen and ibuprofen in the Therapeutic Arthritis Research and Gastrointestinal Event Trial (TARGET), reduction in ulcer complications: randomised controlled trial. Lancet 2004; 364 (9435): 665–74PubMedCrossRefGoogle Scholar
  13. 13.
    National Health Service National Prescribing Centre. Cardiovascular and gastrointestinal safety of NSAIDs. Liverpool: National Prescribing Centre, 2007 Nov [online]. Available from URL: http://www.npc.co.uk/ebt/merec/cardio/cdrisk/resources/merec_extra_no30.pdf [Accessed 2010 Jan 20]Google Scholar
  14. 14.
    Mamdani M, Juurlink DN, Lee DS, et al. Cyclo-oxygenase-2 inhibitors versus nonselective non-steroidal anti-inflammatory drugs and congestive heart failure outcomes in elderly patients: a population-based cohort study. Lancet 2004 May 29; 363 (9423): 1751–6PubMedCrossRefGoogle Scholar
  15. 15.
    Hippisley-Cox J, Coupland C, Logan R. Risk of adverse gastrointestinal outcomes in patients taking cyclo-oxygenase-2 inhibitors or conventional non-steroidal antiinflammatory drugs: population based nested case-control analysis. BMJ 2005; 331 (7528): 1310–6PubMedCrossRefGoogle Scholar
  16. 16.
    Andersohn F, Schade R, Suissa S, et al. Cyclo-oxygenase-2 selective nonsteroidal anti-inflammatory drugs and the risk of ischemic stroke: a nested case-control study. Stroke 2006; 37 (7): 1725–30PubMedCrossRefGoogle Scholar
  17. 17.
    Medicines and Healthcare products Regulatory Agency (MHRA), Pharmacovigilence Working Party (PhVWP). Assessment report: diclofenac, ibuprofen, naproxen. London: MHRA, 2006Google Scholar
  18. 18.
    Hernandez-Diaz S, Varas-Lorenzo C, Garcia Rodriguez LA. Non-steroidal antiinflammatory drugs and the risk of acute myocardial infarction. Basic Clin Pharmacol Toxicol 2006; 98 (3): 266–74PubMedCrossRefGoogle Scholar
  19. 19.
    Bloor K, Maynard A. Is there scope for improving the cost-effective prescribing of nonsteroidal anti-inflammatory drugs? Pharmacoeconomics 1996; 9 (6): 484–96PubMedCrossRefGoogle Scholar
  20. 20.
    National Institute for Health and Clinical Excellence. Guide to the methods of technology appraisal. London: NICE, 2008 Jun [online]. Available from URL: http://www.nice.org.uk/media/B52/A7/TAMethodsGuideUpdatedJune2008.pdf [Accessed 2010 Sep 28]Google Scholar
  21. 21.
    Curtis L, Netten A. Unit costs of health and health social care. Kent: PSSRU, University of Kent, 2006Google Scholar
  22. 22.
    UK Department of Health. NHS reference costs 2005–06 (278472). London: Department of Health, 2006 Dec 7Google Scholar
  23. 23.
    British National Formulary. 53rd ed. London: BMJ Publishing, 2007Google Scholar
  24. 24.
    National Institute for Health and Clinical Excellence. Hypertension: management in adults in primary care. Pharmacological update. London: NICE, 2006 [online]. Available from URL: http://www.nice.org.uk/nicemedia/live/10986/30111/30111.pdf [Accessed 2010 Sep 28]Google Scholar
  25. 25.
    Pickard A, Johnson J, Feeny D. EQ-5D: responsiveness of generic health-related quality of life measures in stroke. Quality Life Res 2005; 14: 207–19CrossRefGoogle Scholar
  26. 26.
    Tufts Medical Center; Institute for Clinical Research and Health Policy Studies; The Center for the Evaluation of Value and Risk in Health. Cost-effectiveness analysis registry. Preference weights 1998–2001 [online]. Available from URL: http://www.tufts-nemc.org/cearegistry/ [Accessed 2008 Apr 29]Google Scholar
  27. 27.
    Bellamy NW, Buchanan W, Goldsmith C, et al. Validation study of WOMAC: a health status instrument for measuring clinically important patient relevant outcomes to antirheumatic drug therapy in patients with osteoarthritis of the hip or knee. J Rheumatology 1988; 15: 1833–40Google Scholar
  28. 28.
    Barton GR, Sach T, Jenkinson C, et al. Do estimates of costutility based on the EQ-5D differ from those based on the mapping of utility scores? Health Qual Life Outcomes 2008; 6: 51PubMedCrossRefGoogle Scholar
  29. 29.
    Department of Health. Health survey for England (HS no. 6). London: Department of Health, 1998 Feb 26Google Scholar
  30. 30.
    Brown TJ, Hooper L, Elliott RA, et al. A comparison of the cost-effectiveness of five strategies for the prevention of nonsteroidal anti-inflammatory drug-induced gastrointestinal toxicity: a systematic review with economic modelling. Health Technol Assess 2006; 10 (38): iii-xiii, 1–183Google Scholar
  31. 31.
    Scheiman JM, Yeomans ND, Talley NJ, et al. Prevention of ulcers by esomeprazole in at-risk patients using non-selective NSAIDs and COX 2 inhibitors. Am J Gastroenterol 2006; 101 (4): 701–10PubMedCrossRefGoogle Scholar
  32. 32.
    Briggs A. Economics notes: handling uncertainty in economic evaluation. BMJ 1999 Jul 10; 319 (7202): 120PubMedCrossRefGoogle Scholar
  33. 33.
    Griffin S, Welton NJ, Claxton K. Exploring the research decision space: the expected value of information for sequential research designs. Med Decis Making 2010 Mar; 30 (2): 155–62PubMedCrossRefGoogle Scholar
  34. 34.
    Ades AE, Lu G, Claxton K. Expected value of sample information in medical decision modelling. Med Decis Making 2004; 24: 207–27PubMedCrossRefGoogle Scholar
  35. 35.
    Briggs A, Sculpher M, Claxton K. Decision modelling for health economic evaluation. Oxford: Oxford University Press, 2006Google Scholar
  36. 36.
    Claxton KP, Sculpher MJ. Using value of information analysis to prioritise health research: some lessons from recent UK experience. Pharmacoeconomics 2006; 24 (11): 1055–68PubMedCrossRefGoogle Scholar
  37. 37.
    National Institute for Health and Clinical Excellence. Osteoarthritis: costing report. Implementing NICE guidance. London: NICE, 2008 Feb [online]. Available from URL: http://www.nice.org.uk/nicemedia/pdf/OsteoarthritisCostingReport.pdf [Accessed 2010 Jan 1]Google Scholar
  38. 38.
    Office for National Statistics. Quarterly population estimates (experimental) [online]. Available from URL: http://www.statistics.gov.uk/StatBase/Product.asp?vlnk=13523&Pos=&ColRank=1&Rank=272 [Accessed 2010 Jan 20]Google Scholar
  39. 39.
    Office for National Statistics. Morbidity: arthritis more common in women [online]. Available from URL: http://www.statistics.gov.uk/CCI/nugget.asp?ID=1331&Pos=&ColRank=2&Rank=448 [Accessed 2010 Jan 20]Google Scholar
  40. 40.
    Woolf AD, Pfleger B. Burden of major musculoskeletal conditions. Bull World Health Organ 2003; 81: 9 [online]. Available from URL: http://whqlibdoc.who.int/bulletin/2003/Vol81-No9/bulletin_2003_81(9)_646-656.pdf [Accessed 2010 Feb 8]Google Scholar
  41. 41.
    Prescription Pricing Authority. imPACT 2005 Mar: 2–4 [online]. Available from URL: http://www.nhsbsa.nhs.uk/PrescriptionServices/Documents/PPDImpact/imPACT_March_2005.pdf [Accessed 2010 Feb 8]Google Scholar
  42. 42.
    Brennan A, Kharroubi S, O’Hagan A, et al. Calculating partial expected value of perfect information via Monte Carlo sampling algorithms. Med Dec Making 2007; 27: 448CrossRefGoogle Scholar
  43. 43.
    Cantor SB. Cost-effectiveness analysis, extended dominance, and ethics: a quantitative assessment. Med Decis Making 1994; 14: 259PubMedCrossRefGoogle Scholar
  44. 44.
    Bojke L, Claxton K, Sculpher MJ, et al. Identifying research priorities: the value of information associated with repeat screening for age-related macular degeneration. Med Decis Making 2008; 28: 33–43PubMedCrossRefGoogle Scholar
  45. 45.
    Bravo Vergel Y, Hawkins NS, Claxton K, et al. The cost-effectiveness of etanercept and infliximab for the treatment of patients with psoriatic arthritis. Rheumatology 2007; 46: 1729–35PubMedCrossRefGoogle Scholar
  46. 46.
    Philips Z, Claxton KP, Palmer S, et al. Priority setting for research in health care: an application of value of information analysis to glycoprotein IIb/IIIa antagonists in non-ST elevation acute coronary syndrome. Int J Technol Assess Health Care 2006; 22 (3): 379–87PubMedCrossRefGoogle Scholar
  47. 47.
    Dong H, Coyle D, Buxton M. Value of information analysis for a new technology: computer-assisted total knee replacement. Int J Technol Assess Health Care 2007; 23 (3): 337–42PubMedCrossRefGoogle Scholar
  48. 48.
    Population Division, US Census Bureau. Table 2: annual estimates of the resident population by sex and selected age groups for the United States. April 1, 2000 to July 1, 2008 (NC-EST2008-02) [online]. Available from URL: http://www.census.gov/popest/national/asrh/NC-EST2008/NCEST2008-02.xls [Accessed 2010 Feb 8]Google Scholar

Copyright information

© Springer International Publishing AG 2011

Authors and Affiliations

  • Nicholas Latimer
    • 1
  • Joanne Lord
    • 2
  • Robert L. Grant
    • 3
  • Rachel O’Mahony
    • 4
  • John Dickson
    • 5
  • Philip G. Conaghan
    • 6
  1. 1.Health Economics and Decision Science, School of Health and Related ResearchUniversity of SheffieldSheffieldUK
  2. 2.Health Economics Research Group, Brunel UniversityUxbridgeUK
  3. 3.Royal College of Physicians of London, Regent’s ParkLondonUK
  4. 4.The National Collaborating Centre for Chronic Conditions (NCC-CC), Royal College of Physicians of London, Regent’s ParkLondonUK
  5. 5.Redcar and Cleveland Primary Care Trust, Guisborough Primary Care HospitalGuisboroughUK
  6. 6.Section of Musculoskeletal Disease, University of Leeds and NIHR Leeds Musculoskeletal Biomedical Research UnitLeedsUK

Personalised recommendations