Line of therapy and patient preferences regarding lung cancer treatment: a discrete-choice experiment

References

• Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70(1):7–30.
   PubMed Web of Science ®Google Scholar
• Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.
   PubMed Web of Science ®Google Scholar
• Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. 2019;69(1):7–34.
   PubMed Web of Science ®Google Scholar
• National Institutes of Health, National Cancer Institute. Surveillance, Epidemiology and End Results (SEER) Program. Cancer stat facts: lung and bronchus cancer; 2018 [cited 2019 Sep 29]. Available from: https://seer.cancer.gov/statfacts/html/lungb.html.
   Google Scholar
• Molina JR, Yang P, Cassivi SD, et al. Non-small cell lung cancer: epidemiology, risk factors, treatment, and survivorship, Mayo Clinic Proceedings. Philadelphia (PA): Elsevier; 2008, pp. 584–594.
   Google Scholar
• Schmidt K, Damm K, Vogel A, et al. Therapy preferences of patients with lung and colon cancer: a discrete choice experiment. PPA. 2017;11:1647–1656.
   Web of Science ®Google Scholar
• Pacchiana MV, Capelletto E, Carnio S, et al. Patients' attitudes and physicians' perceptions toward maintenance therapy for advanced non-small-cell lung cancer: a multicenter Italian survey . Clin Lung Cancer. 2017;18(4):381–387.
   PubMed Web of Science ®Google Scholar
• Aumann I, Kreis K, Damm K, et al. Treatment-related experiences and preferences of patients with lung cancer: a qualitative analysis. Health Expect. 2016;19(6):1226–1236.
   PubMed Web of Science ®Google Scholar
• Soria J-C, Ohe Y, Vansteenkiste J, et al. Osimertinib in untreated EGFR-mutated advanced non–small-cell lung cancer. N Engl J Med. 2018;378(2):113–125.
   PubMed Web of Science ®Google Scholar
• Peters S, Camidge DR, Shaw AT, et al. Alectinib versus crizotinib in untreated ALK-positive non–small-cell lung cancer. N Engl J Med. 2017;377(9):829–838.
   PubMed Web of Science ®Google Scholar
• Bridges JF, Mohamed AF, Finnern HW, et al. Patients' preferences for treatment outcomes for advanced non-small cell lung cancer: a conjoint analysis . Lung Cancer. 2012;77(1):224–231.
   PubMed Web of Science ®Google Scholar
• Schmidt K, Damm K, Prenzler A, et al. Preferences of lung cancer patients for treatment and decision-making: a systematic literature review. Eur J Cancer Care. 2016;25(4):580–591.
   PubMed Web of Science ®Google Scholar
• Gironés R, Torregrosa D, Gómez-Codina J, et al. Lung cancer chemotherapy decisions in older patients: the role of patient preference and interactions with physicians. Clin Transl Oncol. 2012;14(3):183–189.
   PubMed Web of Science ®Google Scholar
• Mühlbacher AC, Bethge S. Patients' preferences: a discrete-choice experiment for treatment of non-small-cell lung cancer. Eur J Health Econ. 2015;16(6):657–670.
   PubMed Web of Science ®Google Scholar
• Leighl NB, Tsao WS, Zawisza DL, et al. A willingness-to-pay study of oral epidermal growth factor tyrosine kinase inhibitors in advanced non-small cell lung cancer. Lung Cancer. 2006;51(1):115–121.
   PubMed Web of Science ®Google Scholar
• FDA. 21st Century Cures Act; 2016 [cited 2019 Sep 29]. Available from: https://www.congress.gov/114/plaws/publ255/PLAW-114publ255.pdf.
   Google Scholar
• National Comprehensive Cancer Network. NCCN categories of preference; 2017 [cited 2019 Sep 29]. Available from: https://www.nccn.org/professionals/physician_gls/categories_of_consensus.aspx.
   Google Scholar
• FDA, patient preference information – voluntary submission, review in premarket approval applications, humanitarian device exemption applications, and de Novo requests, and inclusion in decision summaries and device labeling: guidance for industry, Food and Drug Administration staff, and other stakeholders; 2016 [cited 2019 Jan 14]. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/patient-preference-information-voluntary-submission-review-premarket-approval-applications.
   Google Scholar
• Seo J, Smith BD, Estey EH, et al. Assessing patient preferences for the benefits and risks of treating for acute myeloid leukemia (AML): a pilot study. Washington, DC: American Society of Hematology; 2016.
   Google Scholar
• Dy SM, Janssen EM, Ferris A, et al. Live, learn, pass it on: a patient advocacy engagement project on the lived experience of lung cancer survivors. J Patient Exp. 2017;4(4):162–168.
   PubMedGoogle Scholar
• Bridges JF, Janssen EM, Ferris A, et al. Project Transform: engaging patient advocates to share their perspectives on improving research, treatment and policy. Curr Med Res Opin. 2018;34(10):1755–1762.
   PubMed Web of Science ®Google Scholar
• Janssen EM, Dy SM, Meara AS, et al. Analysis of patient preferences in lung cancer - estimating acceptable tradeoffs between treatment benefit and side effects. Patient Prefer Adherence. 2020;14:927–937.
   PubMed Web of Science ®Google Scholar
• Janssen EM, Segal JB, Bridges JF. A framework for instrument development of a choice experiment: an application to type 2 diabetes. Patient. 2016;9(5):465–479.
   PubMedGoogle Scholar
• Janssen EM, Benz HL, Tsai J-H, et al. Identifying and prioritizing concerns associated with prosthetic devices for use in a benefit-risk assessment: a mixed-methods approach. Expert Rev Med Devices. 2018;15(5):385–398.
   PubMed Web of Science ®Google Scholar
• Coast J, Al‐Janabi H, Sutton EJ, et al. Using qualitative methods for attribute development for discrete choice experiments: issues and recommendations. Health Econ. 2012;21(6):730–741.
   PubMed Web of Science ®Google Scholar
• Janssen EM, Bridges JF. Art and science of instrument development for stated-preference methods. Patient. 2017;10:377–379.
   Google Scholar
• Bridges JF, la Cruz Md, Pavilack M, et al. Patient preferences for attributes of tyrosine kinase inhibitor treatments for EGFR mutation-positive non-small-cell lung cancer. Future Oncol. 2019;15(34):3895–3907.
   PubMed Web of Science ®Google Scholar
• Johnson FR, Lancsar E, Marshall D, et al. Constructing experimental designs for discrete-choice experiments: report of the ISPOR conjoint analysis experimental design good research practices task force. Value Health. 2013;16(1):3–13.
   PubMed Web of Science ®Google Scholar
• Richardson DR, Seo J, Smith BD, et al. Quantifying patient preferences for treatment outcomes in AML: a discrete-choice experiment. Blood. 2018;132(Supplement 1):718–718.
   Web of Science ®Google Scholar
• Janssen EM, Marshall DA, Hauber AB, et al. Improving the quality of discrete-choice experiments in health: how can we assess validity and reliability? Expert Rev Pharmacoecon Outcomes Res. 2017;17(6):531–542.
   PubMed Web of Science ®Google Scholar
• Bridges JF, Kinter ET, Schmeding A, et al. Can patients diagnosed with schizophrenia complete choice-based conjoint analysis tasks? Patient. 2011;4(4):267–275.
   PubMedGoogle Scholar
• Lancsar E, Louviere J. Conducting discrete choice experiments to inform healthcare decision making: a user's guide. Pharmacoeconomics. 2008;26(8):661–677.
   PubMed Web of Science ®Google Scholar
• de Bekker‐Grob EW, Ryan M, Gerard K. Discrete choice experiments in health economics: a review of the literature. Health Econ. 2012;21(2):145–172.
   PubMed Web of Science ®Google Scholar
• Veldwijk J, Lambooij MS, de Bekker-Grob EW, et al. The effect of including an opt-out option in discrete choice experiments. PLoS One. 2014;9(11):e111805
   PubMed Web of Science ®Google Scholar
• Mühlbacher A, Johnson FR. Choice experiments to quantify preferences for health and healthcare: state of the practice. Appl Health Econ Health Policy. 2016;14(3):253–266.
   PubMed Web of Science ®Google Scholar
• Bridges JF, Hauber AB, Marshall D, et al. Conjoint analysis applications in health-a checklist: a report of the ISPOR good research practices for Conjoint Analysis Task Force. Value Health. 2011;14(4):403–413.
   PubMed Web of Science ®Google Scholar
• Bridges JF, Tsai J-H, Janssen E, et al. How do members of the Duchenne and Becker muscular dystrophy community perceive a discrete-choice experiment incorporating uncertain treatment benefit? An application of research as an event. Patient. 2019;12(2):247–257.
   PubMedGoogle Scholar
• Janssen EM, Longo DR, Bardsley JK, et al. Education and patient preferences for treating type 2 diabetes: a stratified discrete-choice experiment. Patient Prefer Adherence. 2017;11:1729–1736.
   PubMed Web of Science ®Google Scholar
• Janssen EM, Hauber AB, Bridges JF. Conducting a discrete-choice experiment study following recommendations for good research practices: an application for eliciting patient preferences for diabetes treatments. Value Health. 2018;21(1):59–68.
   PubMed Web of Science ®Google Scholar
• Hauber AB, González JM, Groothuis-Oudshoorn CG, et al. Statistical methods for the analysis of discrete choice experiments: a report of the ISPOR Conjoint Analysis Good Research Practices Task Force. Value Health. 2016;19(4):300–315.
   PubMed Web of Science ®Google Scholar
• Hausman J, McFadden D. Specification tests for the multinomial logit model. Econometrica. 1984;52(5):1219–1240.
   Web of Science ®Google Scholar
• Scarpa R, Thiene M, Train K. Utility in willingness to pay space: a tool to address confounding random scale effects in destination choice to the Alps. Am J Agric Econ. 2008;90(4):994–1010.
   Web of Science ®Google Scholar
• Train K, Weeks M. Discrete choice models in preference space and willingness-to-pay space. Applications of simulation methods in environmental and resource economics. Dordrecht: Springer; 2005. p.1–16.
   Google Scholar
• Hole AR, Kolstad JR. Mixed logit estimation of willingness to pay distributions: a comparison of models in preference and WTP space using data from a health-related choice experiment. Empir Econ. 2012;42(2):445–469.
   Web of Science ®Google Scholar
• Hauber AB, Itzler R, Johnson FR, et al. Healthy-days time equivalents for outcomes of acute rotavirus infections. Vaccine. 2011;29(45):8086–8093.
   PubMed Web of Science ®Google Scholar
• Johnson FR, Hauber AB, Özdemir S. Using conjoint analysis to estimate healthy-year equivalents for acute conditions: an application to vasomotor symptoms. Value Health. 2009;12(1):146–152.
   PubMed Web of Science ®Google Scholar
• Mehrez A, Gafni A. Quality-adjusted life years, utility theory, and healthy-years equivalents. Med Decis Making. 1989;9(2):142–149.
   PubMed Web of Science ®Google Scholar
• Hauber AB. Healthy-years equivalent: wounded but not yet dead. Expert Rev Pharmacoecon Outcomes Res. 2009;9(3):265–269.
   PubMedGoogle Scholar
• Train KE. Discrete choice methods with simulation. Cambridge (UK): Cambridge University Press; 2009.
   Google Scholar
• De Bekker‐Grob EW, Hol L, Donkers B, et al. Labeled versus unlabeled discrete choice experiments in health economics: an application to colorectal cancer screening. Value Health. 2010;13(2):315–323.
   PubMed Web of Science ®Google Scholar
• Ryan M, Bate A, Eastmond CJ, et al. Use of discrete choice experiments to elicit preferences. BMJ Quality & Safety. 2001;10(Supplement 1):i55–i60.
   Google Scholar
• Subramanian J, Regenbogen T, Nagaraj G, et al. Review of ongoing clinical trials in non–small-cell lung cancer: a status report for 2012 from the ClinicalTrials. gov website. J Thorac Oncol. 2013;8(7):860–865.
   PubMed Web of Science ®Google Scholar
• Janse SA, Dumanis SB, Huwig T, et al. Patient and caregiver preferences for the potential benefits and risks of a seizure forecasting device: a best–worst scaling. Epilepsy Behav. 2019;96:183–191.
   PubMed Web of Science ®Google Scholar
• Peay HL, Hollin I, Fischer R, et al. A community-engaged approach to quantifying caregiver preferences for the benefits and risks of emerging therapies for Duchenne muscular dystrophy. Clin Ther. 2014;36(5):624–637.
   PubMed Web of Science ®Google Scholar
• Richardson DR, Crossnohere NL, Seo J, et al. Age at diagnosis and patient preferences for treatment outcomes in AML: a discrete choice experiment to explore meaningful benefits. Cancer Epidemiol Biomarkers Prev. 2020;29(5):942–948.
   PubMed Web of Science ®Google Scholar