Feasibility of Measuring Preferences for Chemotherapy Among Early-Stage Breast Cancer Survivors Using a Direct Rank Ordering Multicriteria Decision Analysis Versus a Time Trade-Off

A Letter to the Editor to this article was published on 10 November 2020

Abstract

Objectives

Chemotherapy is increasingly a preference-based choice among women diagnosed with early-stage breast cancer. Multicriteria decision analysis (MCDA) is a promising but underutilized method to facilitate shared decision making. We explored the feasibility of conducting an MCDA using direct rank ordering versus a time trade-off (TTO) to assess chemotherapy choice in a large population-based sample.

Methods

We surveyed 904 early-stage breast cancer survivors who were within 5 years of diagnosis and reported to the Western Washington State Cancer System and Kaiser Permanente Northern California registries. Direct rank ordering of 11 criteria and TTO surveys were conducted from September 2015 to July 2016; clinical data were obtained from registries or medical records. Multivariable regressions estimated post hoc associations between the MCDA, TTO, and self-reported chemotherapy receipt, considering covariates.

Results

Survivors ranged in age from 25 to 74 years and 73.9% had stage I tumors. The response rate for the rank ordering was 81.0%; TTO score was 94.2%. A one-standard deviation increase in the difference between the chemotherapy and no chemotherapy MCDA scores was associated with a 75.1% (95% confidence interval 43.9–109.7%; p < 0.001) increase in the adjusted odds of having received chemotherapy; no association was found between the TTO score and chemotherapy receipt.

Conclusions

A rank-order-based MCDA was feasible and was associated with chemotherapy choice. Future research should consider developing and testing this MCDA for use in clinical encounters. Additional research is required to develop a TTO-based model and test its properties against a pragmatic MCDA to inform future shared decision-making tools.

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Data Availability

The datasets generated and analyzed during the current study are not publicly available due to Institutional Review Board protocol, but may be available from the corresponding author upon reasonable request.

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Acknowledgements

The authors are grateful to Tom Ray, MBA, Stephanie Prausnitz, MS, Pete Bogdanos, Laurel Habel, Ph.D., and Yan Li, MD, Ph.D., of Kaiser Permanente for their contributions to this project.

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Affiliations

Authors

Contributions

LP, CP, and SR contributed to the conception and design of this work, data analysis and interpretation, and drafted the article; LP, TL, and SR contributed to the data collection; TL, SA, and SN contributed to manuscript writing; and JM contributed to the critical revision of the manuscript.

Corresponding author

Correspondence to Scott D. Ramsey.

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Conflict of interest

Laura Panattoni, Charles Phelps, Tracy A. Lieu, Stacey Alexeeff, Suzanne O’Neill, Jeanne Mandelblatt, and Scott D. Ramsey declare they have no conflicts of interest.

Funding

This research was supported by National Cancer Institute Grant #UO1 CA183081 (to JM, TL, and SR), And was also supported, in part, by Grant #U01 CA152958 from the National Cancer Institute, as part of the Cancer Intervention and Surveillance Modeling Network (CISNET), Grant #R35CA197289 (to JM) from the National Cancer Institute, and a supplement to Grant #UO1 CA183081 from the National Cancer Institute (SCO). The content is solely the responsibility of the authors and does not represent the official views of the National Cancer Institute at the National Institutes of Health.

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Panattoni, L., Phelps, C.E., Lieu, T.A. et al. Feasibility of Measuring Preferences for Chemotherapy Among Early-Stage Breast Cancer Survivors Using a Direct Rank Ordering Multicriteria Decision Analysis Versus a Time Trade-Off. Patient 13, 557–566 (2020). https://doi.org/10.1007/s40271-020-00423-w

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