Adjusting survival time estimates to account for treatment switching in randomized controlled trials - An economic evaluation context: Methods, limitations, and recommendations

Medical Decision Making

Volumn 34, Issue 3, 2014, Pages 387-402

  Latimer, Nicholas R ^a   Abrams, Keith R ^b   Lambert, Paul C ^b,c   Crowther, Michael J ^b   Wailoo, Allan J ^a   Morden, James P ^d   Akehurst, Ron L ^a   Campbell, Michael J ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

^b UNIVERSITY OF LEICESTER   (United Kingdom)

^c KAROLINSKA INSTITUTE   (Sweden)

^d INSTITUTE OF CANCER RESEARCH   (United Kingdom)

Author keywords

economic evaluation; modeling; prediction; statistical methods; survival analysis; technology assessment; treatment crossover; treatment switching

Indexed keywords

COST; MEDICAL TECHNOLOGY; RANDOMIZED CONTROLLED TRIAL (TOPIC); SURVIVAL;

BIOMEDICAL TECHNOLOGY; COSTS AND COST ANALYSIS; RANDOMIZED CONTROLLED TRIALS AS TOPIC; SURVIVAL ANALYSIS;

EID: 84898816391     PISSN: 0272989X     EISSN: 1552681X     Source Type: Journal    
DOI: 10.1177/0272989X13520192     Document Type: Article

References (44)

1. Guidance for Industry: Clinical Trial Endpoints for the Approval of Cancer Drugs and Biologics. Silver Spring (MD): US Department of Health and Human Services, Food and Drug Administration ; 2007 :
2. Committee for Medicinal Products for Human Use. Appendix 1 to the Guideline on the Evaluation of Anticancer Medicinal Products in Man (CHMP/EWP/205/95 REV.3): Methodological Considerations for Using Progression-Free Survival (PFS) as Primary Endpoint in Confirmatory Trials for Registration. London: European Medicines Agency; 2006. Available from: http://www.ema.europa.eu/docs/en-GB/document-library/Scientific-guideline/2009/ 12/WC500017736.pdf.
3. National Institute for Health and Care Excellence (NICE). Guide to the Methods of Technology Appraisal. London: NICE; 2008. Available from: http://www.nice.org.uk/media/B52/A7/TAMethodsGuideUpdatedJune2008.pdf.
4. Briggs A, Claxton K, Sculpher M Decision Modelling for Health Economic Evaluation. New York: Oxford University Press Inc. ; 2006:
5. Gold MR, Siegel JE, Russell LB, Weinstein MC Cost-Effectiveness in Health and Medicine. New York: Oxford University Press Inc. ; 1996:
6. Guidelines for the Economic Evaluation of Health Technologies. 3 rd ed.Ottawa: CADTH; 2006. Ottawa: CADTH ; 2006:
7. Morden JP, Lambert PC, Latimer NR, Abrams KR, Wailoo AJ. Assessing methods for dealing with treatment switching in randomised controlled trials: a simulation study. BMC Med Res Methodol. 2011 ; 11: 4
8. Lee Y, Ellenberg J, Hirtz D, Nelson K. Analysis of clinical trials by treatment actually received: is it really an option?. Stat Med. 1991 ; 10: 1595-605
9. Horwitz R, Horwitz S. Adherence to treatment and health outcomes. Arch Intern Med. 1993 ; 153: 1863-8
10. Pazopanib for the First-Line Treatment of Metastatic Renal Cell Carcinoma: TA 215. London: NICE ; 2011:
11. Everolimus for the Second-Line Treatment of Advanced Renal Cell Carcinoma: TA 219. London: NICE ; 2011 :
12. Robins JM, Finkelstein DM. Correcting for noncompliance and dependent censoring in an AIDS clinical trial with inverse probability of censoring weighted (IPCW) log-rank tests. Biometrics. 2000 ; 56 (3). 779-88
13. Robins JM, Greenland S. Adjusting for differential rates of prophylaxis therapy for PCP in high-dose versus low-dose AZT treatment arms in an AIDS randomized trial. J Am Statist Assoc. 1994 ; 89 (427). 737-49
14. Yamaguchi T, Ohashi Y. Adjusting for differential proportions of second-line treatment in cancer clinical trials, part I: structural nested models and marginal structural models to test and estimate treatment arm effects. Stat Med. 2004 ; 23 (13). 1991-2003
15. Hernan MA, Brumback B, Robins JM. Marginal structural models to estimate the joint causal effect of nonrandomized treatments. J Am Statist Assoc. 2001 ; 96 (454). 440-8
16. Robins JM Statistical Models in Epidemiology: The Environment and Clinical Trials. Halloran ME Berry D, ed. New York: Springer-Verlag ; 1999: 95-134.
17. BondMHoyleMMoxhamTNapierMAndersonR. The Clinical and Cost-Effectiveness of Sunitinib for the Treatment of Gastrointestinal Stromal Tumours: A Critique of the Submission from Pfizer. Peninsula Technology Assessment Group, Universities of Exeter and Plymouth, commissioned by the NHS R&D HTA Programme on behalf of the National Institute for Clinical Excellence. 2009. Available from: http://www.nice.org.uk/nicemedia/live/12040/43430/43430.pdf.
18. Robins JM, Tsiatis AA. Correcting for noncompliance in randomized trials using rank preserving structural failure time models. Commun Stat Theory Methods. 1991 ; 20 (8). 2609-31
19. Hernan MA, Robins JM. Instruments for causal inference: an epidemiologist's dream?. Epidemiology. 2006 ; 17: 360-72
20. Senn SJ. Covariate imbalance and random allocation in clinical trials. Stat Med. 1989 ; 8 (4). 467-75
21. Hampson LV, Metcalfe C. Incorporating prognostic factors into causal estimators: a comparison of methods for randomised controlled trials with a time-to-event outcome. Stat Med. 2012 ; 31 (26). 3073-88
22. Branson M, Whitehead J. Estimating a treatment effect in survival studies in which patients switch treatment. Stat Med. 2002 ; 21 (17). 2449-63
23. Latimer NR. Survival analysis for economic evaluations alongside clinical trials - extrapolation with patient-level data: inconsistencies, limitations and a practical guide. Med Decis Making. 2013 ; 33 (6). 743-54
24. White IR, Babiker AG, Walker S, Darbyshire JH. Randomization-based methods for correcting for treatment changes: examples from the Concorde trial. Stat Med. 1999 ; 18 (19). 2617-34
25. Yamaguchi T, Ohashi Y. Adjusting for differential proportions of second-line treatment in cancer clinical trials, part II: an application in a clinical trial of unresectable non-small-cell lung cancer. Stat Med. 2004 ; 23 (13). 2005-22
26. Guyot P, Welton NJ, Ouwens MJ, Ades AE. Survival time outcomes in randomized, controlled trials and meta-analyses: the parallel universes of efficacy and cost-effectiveness. Value Health. 2011 ; 14: 640-6
27. Guyot P, Ades AE, Ouwens MJNM, Welton NJ. Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves. BMC Med Res Methodol. 2012 ; 12: 9
28. LatimerNAbramsKRLambertPC. Adjusting for treatment switching in randomised controlled trials: a simulation study. University of Sheffield Health Economics and Decision Science Discussion Paper. 2013. No. 13/06. Available from: http://www.shef.ac.uk/polopoly-fs/1.259501!/file/HEDSDP1306.pdf.
29. Howe CJ, Cole SR, Chmiel JS, Munoz A. Limitation of inverse probability-of-censoring weights in estimating survival in the presence of strong selection bias. Am J Epidemiol. 2011 ; 173 (5). 569-77
30. Goetghebeur E, Lapp K. The effect of treatment compliance in a placebo- controlled trial: regression with unpaired data. Appl Statist. 1997 ; 46: 351-64
31. Fischer-Lapp K, Goetghebeur E. Practical properties of some structural mean analyses of the effect of compliance in randomized trials. Control Clin Trials. 1999 ; 20: 531-46
32. Robins JM. Correcting for non-compliance in randomized trials using structural nested mean models. Commun Stat Theory Methods. 1994 ; 23: 2379-412
33. White IR. Uses and limitations of randomization-based efficacy estimators. Stat Methods Med Res. 2005 ; 14 (4). 327-47
34. Vermorken JB, Mesia R, Rivera F, et al. Platinum-based chemotherapy plus cetuximab in head and neck cancer. N Engl J Med. 2008 ; 359: 1116-27
35. Achieving Clinical Excellence in the Treatment of Relapsed Non-Small Cell Lung Cancer: Tarceva (Erlotinib) NICE STA Submission. Welwyn Garden City (UK): Roche Products Ltd. ; 2006 :
36. LewisRBagnallAMForbesC. A Rapid and Systematic Review of the Clinical Effectiveness and Cost Effectiveness of Trastuzumab for Breast Cancer. NHS Centre for Reviews and Dissemination Report commissioned by the NHS R&D HTA Programme on behalf of the National Institute for Clinical Excellence. 2001. Available from: http://www.nice.org.uk/nicemedia/live/11445/32317/32317.pdf.
37. Final Appraisal Determination: Imatinib for the Treatment of Unresectable and/or Metastatic Gastro-intestinal Stromal Tumours: TA 86. London: NICE ; 2004 :
38. STA Submission to NICE: Velcade (Bortezomib) for the Treatment of Multiple Myeloma Patients at First Relapse. High Wycombe (UK): Janssen-Cilag Ltd. ; 2006 :
39. HoyleMRogersGGarsideRMoxhamTSteinK. The Clinical and Cost Effectiveness of Lenalidomide for Multiple Myeloma in People Who Have Received at Least One Prior Therapy: An Evidence Review of the Submission from Celgene. Peninsula Technology Assessment Group, Universities of Exeter and Plymouth, commissioned by the NHS R&D HTA Programme on behalf of the National Institute for Clinical Excellence. 2008. Available from: http://www.hta.ac.uk/erg/reports/ 1746.pdf.
40. HindDTappendenPTumurIEggingtonSSutcliffePRyanA. The Use of Irinotecan, Oxaliplatin and Raltitrexed for the Treatment of Advanced Colorectal Cancer: Systematic Review and Economic Evaluation (Review of Guidance No. 33). Addendum: Economic Evaluation of Irinotecan and Oxaliplatin for the Treatment of Advanced Colorectal Cancer. School of Health and Related Research, University of Sheffield, commissioned by the NHS R&D HTA Programme on behalf of the National Institute for Clinical Excellence. 2005. Available from: http://www.nice.org.uk/nicemedia/live/11561/33130/33130.pdf.
41. Single Technology Appraisal Submission: Erbitux (Cetuximab) for the First-Line Treatment of Metastatic Colorectal Cancer. London: Merck Serono Ltd. ; 2008 :
42. Guidance on the Use of Trastuzumab for the Treatment of Advanced Breast Cancer: NICE Technology Appraisal Guidance No. 34. London: NICE ; 2002 :
43. Robins JM The Encyclopedia of Biostatistics. Andersen PK Keiding N Armitage P Colton T, ed. Chichester (UK): John Wiley and Sons ; 1998: 4372-89.
44. Mark SD, Robins JM. A method for the analysis of randomized trials with compliance information: an application to the multiple risk factor intervention trial. Control Clin Trials. 1993 ; 14 (2). 79-97