Conjoint analysis of a new chemotherapy - Willingness to pay and preference for the features of raltitrexed versus standard therapy in advanced colorectal cancer

Objective: To estimate the willingness to pay for a new chemotherapy, raltitrexed (Tomudex((TM)1)) 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 ($A; $US507) per cycle of chemotherapy, comprising $A550 ($US374) and $A195 ($US133) 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.