publication . Other literature type . Book . Article . 2018

Causal inference for long-term survival in randomised trials with treatment switching: Should re-censoring be applied when estimating counterfactual survival times?

NR Latimer; IR White; KR Abrams; U Siebert;
  • Published: 25 Jun 2018
  • Publisher: SAGE Publications
  • Country: United Kingdom
Abstract
<jats:p> Treatment switching often has a crucial impact on estimates of effectiveness and cost-effectiveness of new oncology treatments. Rank preserving structural failure time models (RPSFTM) and two-stage estimation (TSE) methods estimate ‘counterfactual’ (i.e. had there been no switching) survival times and incorporate re-censoring to guard against informative censoring in the counterfactual dataset. However, re-censoring causes a loss of longer term survival information which is problematic when estimates of long-term survival effects are required, as is often the case for health technology assessment decision making. We present a simulation study designed t...
Subjects
free text keywords: Treatment switching, treatment crossover, survival analysis, overall survival, oncology, health technology assessment, time-to-event outcomes, prediction, re-censoring, Articles, Treatment switching, treatment crossover, survival analysis, overall survival, oncology, health technology assessment, time-to-event outcomes, prediction, re-censoring, Statistics and Probability, Health Information Management, Epidemiology, Econometrics, Statistics, Causal inference, Structural failure, Counterfactual thinking, Censoring (statistics), Mathematics
38 references, page 1 of 3

1. Latimer NR, Abrams KR, Lambert PC, et al. Adjusting survival time estimates to account for treatment switching in randomised controlled trials - an economic evaluation context: methods, limitations and recommendations. Med Decis Making 2014; 34: 387-402.

2. Jonsson L, Sandin R, Ekman M, et al. Analyzing overall survival in randomized controlled trials with crossover and implications for economic evaluation. Value Health 2014; 17: 707-713. [OpenAIRE]

3. Ishak KJ, Proskorovsky I, Korytowsky B, et al. Methods for adjusting for bias due to crossover in oncology trials. Pharmacoeconomics 2014; 32: 533-546. [OpenAIRE]

4. Watkins C, Huang X, Latimer N, et al. Adjusting overall survival for treatment switches: commonly used methods and practical application. Pharm Stat 2013; 12: 348-357.

5. Latimer NR, Henshall C, Siebert U, et al. Treatment Switching: statistical and decision making challenges and approaches. Int J Technol Assess Health Care 2016; 32: 160-166. [OpenAIRE]

6. Henshall C, Latimer NR, Sansom L, et al. Treatment switching in cancer trials: issues and proposals. Int J Technol Assess Health Care 2016; 32: 167-174. [OpenAIRE]

7. Robins JM. The analysis of randomized and non-randomized AIDS treatment trials using a new approach to causal inference in longitudinal studies. In: Sechrest L, Freeman H and Mulley A (eds) Health service research methodology: a focus on AIDS. Washington, DC: U.S. Public Health Service, National Center for Health Services Research, 1989, pp.113-159.

8. Robins JM. Analytic methods for estimating HIV treatment and cofactor effects. In: Ostrow DG and Kessler R (eds) Methodological issues of AIDS mental health research. New York, NY: Plenum Publishing, 1993, pp.213-290.

9. Branson M and Whitehead J. Estimating a treatment effect in survival studies in which patients switch treatment. Stat Med 2002; 21: 2449-2463. [OpenAIRE]

10. White IR. Estimating treatment effects in randomized trials with treatment switching. Stat Med 2006; 25: 1619-1622.

11. Latimer NR, Bell H, Abrams KR, et al. Adjusting for treatment switching in the METRIC study shows further improved overall survival with trametinib compared with chemotherapy. Cancer Med 2016; 5: 806-815. [OpenAIRE]

12. Tappenden P, Chilcott J, Ward S, et al. Methodological issues in the economic analysis of cancer treatments. Eur J Cancer 2006; 42: 2867-2875. [OpenAIRE]

13. National Institute for Health and Care Excellence. Guide to the methods of technology appraisal. London: NICE, 2013nice.org.uk/process/pmg9 (accessed 2 June 2017).

14. Briggs A, Claxton K and Sculpher M. Decision modelling for health economic evaluation. New York, NY: Oxford University Press Inc., 2006.

15. Sanders GD, Neumann PJ, Basu A, et al. Recommendations for conduct, methodological practices, and reporting of costeffectiveness analyses: second panel on cost-effectiveness in health and medicine. JAMA 2016; 316: 1093-1103. [OpenAIRE]

38 references, page 1 of 3
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publication . Other literature type . Book . Article . 2018

Causal inference for long-term survival in randomised trials with treatment switching: Should re-censoring be applied when estimating counterfactual survival times?

NR Latimer; IR White; KR Abrams; U Siebert;