Literature DB >> 12201796

Conjoint analysis of a new Chemotherapy: willingness to pay and preference for the features of raltitrexed versus standard therapy in advanced Colorectal Cancer.

Mike Aristides1, Jack Chen, Mark Schulz, Eve Williamson, Stephen Clarke, Kaye Grant.   

Abstract

OBJECTIVE: To estimate the willingness to pay for a new chemotherapy, raltitrexed (Tomudex trade mark ) over conventional therapy with fluorouracil plus leucovorin (FU-LV) from the perspective of patients with advanced colorectal cancer. The study was part of the product's reimbursement application in Australia. DESIGN AND METHODS: The key differences relevant to patients between the two therapies, frequency of administration and severity of mouth ulceration, were used to develop a self-administered questionnaire. A relatively new technique to healthcare, that of conjoint analysis (CA), was used to estimate willingness to pay and strength of preference. A discrete choice CA was used. Analysis was via a logit model with adjustment for the cluster effect (or intra-patient correlation). STUDY PARTICIPANTS: Oncology nurses served as proxies for patients with advanced colorectal cancer.
RESULTS: The participation rate was 87% (62/71) with questionnaires from 56 respondents eligible for analysis. The CA method generated a mean incremental willingness to pay of 745 Australian dollars (dollar A; dollars US 507) per cycle of chemotherapy, comprising dollars A 550 (dollars US 374) and dollars A 195 (dollars US 133) for the toxicity and administration improvements, respectively (1998 values). Both features were related to preference with independent odds of 6.87 and 1.98, respectively, however only the toxicity attribute was a significantly related to preference. Subscription to private health insurance was the only significant demographic predictor identified, however, the homogeneous income structure of the respondents seems likely to have masked any significant income effect.
CONCLUSIONS: This study highlights the advantages of using CA in healthcare, where new therapies or treatments are often composed of a number of attributes. The CA allows both strength of preference and willingness to pay for individual treatment attributes to be estimated and can be used to assign statistical significance to these parameters.

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Year:  2002        PMID: 12201796     DOI: 10.2165/00019053-200220110-00006

Source DB:  PubMed          Journal:  Pharmacoeconomics        ISSN: 1170-7690            Impact factor:   4.981


  18 in total

1.  Using conjoint analysis to take account of patient preferences and go beyond health outcomes: an application to in vitro fertilisation.

Authors:  M Ryan
Journal:  Soc Sci Med       Date:  1999-02       Impact factor: 4.634

2.  Response-ordering effects: a methodological issue in conjoint analysis.

Authors:  S Farrar; M Ryan
Journal:  Health Econ       Date:  1999-02       Impact factor: 3.046

Review 3.  Appraising the use of contingent valuation.

Authors:  G C Morrison; M Gyldmark
Journal:  Health Econ       Date:  1992-12       Impact factor: 3.046

4.  Economic analysis as an aid to subsidisation decisions: the development of Australian guidelines for pharmaceuticals.

Authors:  D Henry
Journal:  Pharmacoeconomics       Date:  1992-01       Impact factor: 4.981

5.  Using conjoint analysis to assess women's preferences for miscarriage management.

Authors:  M Ryan; J Hughes
Journal:  Health Econ       Date:  1997 May-Jun       Impact factor: 3.046

6.  Open, randomized, multicenter trial of raltitrexed versus fluorouracil plus high-dose leucovorin in patients with advanced colorectal cancer. Tomudex Colorectal Cancer Study Group.

Authors:  G Cocconi; D Cunningham; E Van Cutsem; E Francois; B Gustavsson; G van Hazel; D Kerr; K Possinger; S M Hietschold
Journal:  J Clin Oncol       Date:  1998-09       Impact factor: 44.544

7.  Economic evaluation of insulin lispro versus neutral (regular) insulin therapy using a willingness-to-pay approach.

Authors:  P Davey; D Grainger; J MacMillan; N Rajan; M Aristides; M Dobson
Journal:  Pharmacoeconomics       Date:  1998-03       Impact factor: 4.981

8.  'Tomudex' (ZD1694): results of a randomised trial in advanced colorectal cancer demonstrate efficacy and reduced mucositis and leucopenia. The 'Tomudex' Colorectal Cancer Study Group.

Authors:  D Cunningham; J R Zalcberg; U Rath; I Olver; E Van Cutsem; C Svensson; J F Seitz; P Harper; D Kerr; G Perez-Manga
Journal:  Eur J Cancer       Date:  1995-11       Impact factor: 9.162

9.  Preferences for home vs hospital care among low-risk patients with community-acquired pneumonia.

Authors:  C M Coley; Y H Li; A R Medsger; T J Marrie; M J Fine; W N Kapoor; J R Lave; A S Detsky; M C Weinstein; D E Singer
Journal:  Arch Intern Med       Date:  1996-07-22

10.  Couples' willingness to pay for IVF/ET.

Authors:  M Granberg; M Wikland; L Nilsson; L Hamberger
Journal:  Acta Obstet Gynecol Scand       Date:  1995-03       Impact factor: 3.636

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  11 in total

1.  The use of multi-criteria decision analysis weight elicitation techniques in patients with mild cognitive impairment: a pilot study.

Authors:  Janine A van Til; James G Dolan; Anne M Stiggelbout; Karin C G M Groothuis; Maarten J Ijzerman
Journal:  Patient       Date:  2008-04-01       Impact factor: 3.883

2.  Understanding patient perspectives on communication about the cost of cancer care: a review of the literature.

Authors:  Erin W Hofstatter
Journal:  J Oncol Pract       Date:  2010-06-22       Impact factor: 3.840

Review 3.  Risk as an attribute in discrete choice experiments: a systematic review of the literature.

Authors:  Mark Harrison; Dan Rigby; Caroline Vass; Terry Flynn; Jordan Louviere; Katherine Payne
Journal:  Patient       Date:  2014       Impact factor: 3.883

4.  Understanding how out-of-pocket expenses, treatment value, and patient characteristics influence treatment choices.

Authors:  Yu-Ning Wong; Olivia Hamilton; Brian Egleston; Kevin Salador; Camara Murphy; Neal J Meropol
Journal:  Oncologist       Date:  2010-05-23

5.  Willingness-to-pay for cancer treatment and outcome: a systematic review.

Authors:  Alene Sze Jing Yong; Yi Heng Lim; Mark Wing Loong Cheong; Ednin Hamzah; Siew Li Teoh
Journal:  Eur J Health Econ       Date:  2021-12-02

6.  Understanding patients' attitudes toward communication about the cost of cancer care.

Authors:  Andrea J Bullock; Erin W Hofstatter; Melinda L Yushak; Mary K Buss
Journal:  J Oncol Pract       Date:  2012-02-28       Impact factor: 3.840

7.  A Systematic Review of Discrete Choice Experiments in Oncology Treatments.

Authors:  Hannah Collacott; Vikas Soekhai; Caitlin Thomas; Anne Brooks; Ella Brookes; Rachel Lo; Sarah Mulnick; Sebastian Heidenreich
Journal:  Patient       Date:  2021-05-05       Impact factor: 3.883

8.  Patient and physician preferences for anticancer drugs for the treatment of metastatic colorectal cancer: a discrete-choice experiment.

Authors:  Juan Marcos González; Sarika Ogale; Robert Morlock; Joshua Posner; Brett Hauber; Nicolas Sommer; Axel Grothey
Journal:  Cancer Manag Res       Date:  2017-04-27       Impact factor: 3.989

9.  Let's Talk about TEX-Understanding Consumer Preferences for Smart Interactive Textile Products Using a Conjoint Analysis Approach.

Authors:  Julia Offermann-van Heek; Philipp Brauner; Martina Ziefle
Journal:  Sensors (Basel)       Date:  2018-09-18       Impact factor: 3.576

Review 10.  Preference for pharmaceutical formulation and treatment process attributes.

Authors:  Katie D Stewart; Joseph A Johnston; Louis S Matza; Sarah E Curtis; Henry A Havel; Stephanie A Sweetana; Heather L Gelhorn
Journal:  Patient Prefer Adherence       Date:  2016-07-27       Impact factor: 2.711

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