Modeling Covariate-Adjusted Survival for Economic Evaluations in Oncology
Background and Objectives
In economic evaluations in oncology, adjusted survival should be generated if imbalances in prognostic/predictive factors across treatment arms are present. To date, no formal guidance has been developed regarding how such adjustments should be made. We compared various covariate-adjusted survival modeling approaches, as applied to the ENDEAVOR trial in multiple myeloma that assessed carfilzomib plus dexamethasone (Cd) versus bortezomib plus dexamethasone (Vd).
Overall survival (OS) data and baseline characteristics were used for a subgroup (bortezomib-naïve/one prior therapy). Four adjusted survival modeling approaches were compared: propensity score weighting followed by fitting a Weibull model to the two arms of the balanced data (weighted data approach); fitting a multiple Weibull regression model including prognostic/predictive covariates to the two arms to predict survival using the mean value of each covariate and using the average of patient-specific survival predictions; and applying an adjusted hazard ratio (HR) derived from a Cox proportional hazard model to the baseline risk estimated for Vd.
The mean OS estimated by the weighted data approach was 6.85 years (95% confidence interval [CI] 4.62–10.70) for Cd, 4.68 years (95% CI 3.46–6.74) for Vd, and 2.17 years (95% CI 0.18–5.06) for the difference. Although other approaches estimated similar differences, using the mean value of covariates appeared to yield skewed survival estimates (mean OS was 7.65 years for Cd and 5.40 years for Vd), using the average of individual predictions had limited external validity (implausible long-term OS predictions with > 10% of the Vd population alive after 30 years), and using the adjusted HR approach overestimated uncertainty (difference in mean OS was 2.03, 95% CI − 0.17 to 6.19).
Adjusted survival modeling based on weighted or matched data approaches provides a flexible and robust method to correct for covariate imbalances in economic evaluations. The conclusions of our study may be generalizable to other settings.
ClinicalTrials.gov identifier NCT01568866 (ENDEAVOR trial).
We would like to thank the two reviewers and the journal editor for the insightful comments that helped improve the manuscript.
IM and MC designed the study. IM performed the analyses. All authors analyzed the data. All authors contributed to writing the paper by providing guidance and comments on its content.
Compliance with Ethical Standards
This study was supported by Amgen.
Conflict of interest
I Majer, J.G. Castaigne, L. DeCosta, and M. Campioni are employees of Amgen and hold Amgen stock. S. Palmer was a paid consultant to Amgen with regard to advising on this research. S. Palmer has no conflict of interest to report. We, the authors, attest that we have herein disclosed any and all financial or other relationships that could be construed as a conflict of interest and that all sources of financial support for this study have been disclosed and are indicated in the Funding section.
- 1.Latimer N. NICE DSU Technical Support Document 14: Undertaking survival analysis for economic evaluations alongside clinical trials–extrapolation with patient-level data. 2011. http://www.nicedsu.org.uk
- 2.Committee for Medicinal Products for Human Use (CHMP). Guideline on adjustment for baseline covariates in clinical trials. London: European Medicines Agency; 2015.Google Scholar
- 5.Ghali WA, Quan H, Brant R, van Melle G, Norris CM, Faris PD, et al. APPROACH (Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease) Investigators. Comparison of 2 methods for calculating adjusted survival curves from proportional hazards models. JAMA. 2001;286(12):1494–7.CrossRefGoogle Scholar
- 9.Faria R, Hernandez Alava M, Manca A, Wailoo AJ. The use of observational data to inform estimates of treatment effectiveness in technology appraisal: methods for comparative individual patient data. NICE DSU technical support document 17. London: NICE; 2015.Google Scholar
- 10.Dimopoulos MA, Moreau P, Palumbo A, Joshua D, Pour L, Hájek R, et al. Carfilzomib and dexamethasone versus bortezomib and dexamethasone for patients with relapsed or refractory multiple myeloma (ENDEAVOR): a randomised, phase 3, open-label, multicentre study. Lancet Oncol. 2016;17(1):27–38.CrossRefGoogle Scholar
- 11.Dimopoulos M, Goldschmidt H, Niesvizky R, Joshua D, Chng W-J, Oriol A, et al. Overall survival of patients with relapsed or refractory multiple myeloma treated with carfilzomib and dexamethasone versus bortezomib and dexamethasone: interim analysis from the randomized phase 3 ENDEAVOR trial [abstract]. In: 16th International Myeloma Workshop; 1–4 Mar 2017; New Delhi.Google Scholar
- 12.National Institute for Health and Care Excellence (NICE). Bortezomib monotherapy for relapsed multiple myeloma (TA129). 2007. http://www.nice.org.uk/TA129. Accessed May 2016.
- 13.Data on file. Clinical study report: ENDEAVOR. Amgen: 9 May 2017.Google Scholar
- 24.National Institute for Health and Care Excellence (NICE). Carfilzomib for treated multiple myeloma in people who have received at least one prior therapy (ID 934). Evidence Review Group report. https://www.nice.org.uk/guidance/GID-TA10005/documents/committee-papers. Accessed Nov 2016.
- 30.Orlowski RZ, Nagler A, Sonneveld P, Bladé J, Hajek R, Spencer A, et al. Final overall survival results of a randomized trial comparing bortezomib plus pegylated liposomal doxorubicin with bortezomib alone in patients with relapsed or refractory multiple myeloma. Cancer. 2016;122(13):2050–6.CrossRefGoogle Scholar
- 31.National Institute for Health and Care Excellence (NICE). Single Technology Appraisal. Carfilzomib for previously treated multiple myeloma [ID934] Committee Papers. 2017. https://www.nice.org.uk/guidance/ta457/documents/committee-papers. Accessed Jul 2017.
- 32.Jakubowiak A, Majer IM, Houisse I, Benedict A, Campioni M, Panjabi S, et al. Economic evaluation of carfilzomib + dexamethasone (Kd) vs bortezomib + dexamethasone (Vd) in relapsed or refractory multiple myeloma (R/RMM) [abstract]. Blood. 2016;128(22):3582.Google Scholar
- 34.R Development Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2010.Google Scholar
- 36.National Institute for Health and Care Excellence (NICE), Multiple myeloma—lenalidomide (post bortezomib) (part rev TA171) [ID667]. Evidence review group report. https://www.nice.org.uk/guidance/GID-TAG452/documents/multiple-myeloma-lenalidomide-post-bortezomib-part-rev-ta171-evaluation-report2. Accessed Nov 2016.
- 40.National Institute for Health and Care Excellence (NICE). Single Technology Appraisal. Blinatumomab for treating Philadelphiachromosome-negative relapsed or refractory acute lymphoblastic leukaemia [ID804] Committee Papers. 2017. https://www.nice.org.uk/guidance/ta450/documents/committee-papers. Accessed Jul 2017.
- 41.National Institute for Health and Care Excellence (NICE). Single Technology Appraisal. Osimertinib for treating metastatic EGFR and T790M mutation-positive non-small-cell lung cancer [ID874]. Committee Papers. 2016. https://www.nice.org.uk/guidance/ta416/documents/committee-papers-2. Accessed Jul 2017.