Literature DB >> 31559581

Increased survival time or better quality of life? Trade-off between benefits and adverse events in the systemic treatment of cancer.

V Valentí1, J Ramos2, C Pérez3, L Capdevila2, I Ruiz3, L Tikhomirova2, M Sánchez4, I Juez5, M Llobera6, E Sopena2, J Rubió7, R Salazar8.   

Abstract

INTRODUCTION: Primary objective of the study was to assess the relative weighting between benefit in survival time (SV), benefit in quality of life (QoL) and willingness to experience adverse events (AEs), in patient preferences for chemotherapy treatment.
MATERIALS AND METHODS: We included cancer patients with current or past systemic treatment of cancer (STC) as well as physicians placed as hypothetical patients. Participants filled a choice-based conjoint analysis questionnaire with 19 choices among three STC scenarios with variable amounts of benefit in SV or QoL and different types AEs.
RESULTS: One hundred patients (50 on curative and 50 on palliative intention treatment) and 114 physicians (61 oncologists and 53 non-oncologists) were included and asked about their preferred chemotherapy treatment. The relative weighting (sum 100%) of SV-QoL-AEs for making the choice in the 100 patients was SV35%-CV33%-AEs31% what was not significantly different from a random distribution (Goodness of fit Chi square P = 0.91) just as it was not for both subgroups, palliative (SV37%-QoL29%-AEs34%; GoF Chi square P = 0.55) and curative (SV34%-QoL36%-AEs30%; GoF Chi square P = 0.73) treatment. The observed distribution in the group of 114 physicians (SV46%-QoL31%-AEs23%) was significantly different from a random distribution (GoF Chi square P = 0.018) just as it was for both subgroups, medical oncologists (SV48%-QoL29%-AEs23%; GoF Chi square P = 0.006) and non-medical oncologists (SV44%-QoL33%-AEs23%; GoF Chi square P = 0.04).
CONCLUSIONS: The three attributes (SV, QoL, and AEs) are considered in the same way by cancer patients to make choices on their STC. On the contrary, when placed as hypothetical patients, physicians prefer for themselves those treatments that provide more SV.

Entities:  

Keywords:  Adverse events; Conjoint analysis; Patient preferences; Quality of life; Survival

Mesh:

Year:  2019        PMID: 31559581     DOI: 10.1007/s12094-019-02216-6

Source DB:  PubMed          Journal:  Clin Transl Oncol        ISSN: 1699-048X            Impact factor:   3.405


  18 in total

1.  Using conjoint analysis to elicit preferences for health care.

Authors:  M Ryan; S Farrar
Journal:  BMJ       Date:  2000-06-03

Review 2.  Utilitarianism and the measurement and aggregation of quality--adjusted life years.

Authors:  P Dolan
Journal:  Health Care Anal       Date:  2001

3.  How long and how well: oncologists' attitudes toward the relative value of life-prolonging v. quality of life-enhancing treatments.

Authors:  Michael A Kozminski; Peter J Neumann; Eric S Nadler; Aleksandra Jankovic; Peter A Ubel
Journal:  Med Decis Making       Date:  2010-11-18       Impact factor: 2.583

4.  QALYs: the basics.

Authors:  Milton C Weinstein; George Torrance; Alistair McGuire
Journal:  Value Health       Date:  2009-03       Impact factor: 5.725

5.  Quality-adjusted life years in cancer: pros, cons, and alternatives.

Authors:  R M Woodward; J Menzin; P J Neumann
Journal:  Eur J Cancer Care (Engl)       Date:  2012-09-12       Impact factor: 2.520

6.  The Value of Addressing Patient Preferences.

Authors:  Jeff D Allen; Mark D Stewart; Samantha A Roberts; Ellen V Sigal
Journal:  Value Health       Date:  2017-02       Impact factor: 5.725

7.  Use of conjoint analysis to assess breast cancer patient preferences for chemotherapy side effects.

Authors:  Kathleen Beusterien; Jessica Grinspan; Iryna Kuchuk; Sasha Mazzarello; Susan Dent; Stan Gertler; Nathaniel Bouganim; Lisa Vandermeer; Mark Clemons
Journal:  Oncologist       Date:  2014-01-28

8.  Balancing influence between actors in healthcare decision making.

Authors:  Robert M Kaplan; Yair M Babad
Journal:  BMC Health Serv Res       Date:  2011-04-19       Impact factor: 2.655

9.  Do new cancer drugs offer good value for money? The perspectives of oncologists, health care policy makers, patients, and the general population.

Authors:  Tatiana Dilla; Luís Lizan; Silvia Paz; Pilar Garrido; Cristina Avendaño; Juan J Cruz-Hernández; Javier Espinosa; José A Sacristán
Journal:  Patient Prefer Adherence       Date:  2015-12-18       Impact factor: 2.711

10.  Weighing Clinical Evidence Using Patient Preferences: An Application of Probabilistic Multi-Criteria Decision Analysis.

Authors:  Henk Broekhuizen; Maarten J IJzerman; A Brett Hauber; Catharina G M Groothuis-Oudshoorn
Journal:  Pharmacoeconomics       Date:  2017-03       Impact factor: 4.981

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4.  The emerging role of real-world data in advanced breast cancer therapy: Recommendations for collaborative decision-making.

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