Eliciting Preferences for Clinical Follow-Up in Patients with Head and Neck Cancer Using Best-Worst Scaling.

Eliciting Preferences for Clinical Follow-Up in Patients with Head and Neck Cancer Using Best-Worst Scaling.

Value Health. 2017 Jun;20(6):799-808

Authors: Meregaglia M, Cairns J, Alfieri S, Favales F, Mazzitelli D, Orlandi E, Licitra L, Bossi P

Abstract
OBJECTIVES: There are no commonly accepted standards for monitoring patients treated for head and neck cancer. The aim of this study was to assess patients' preferences for different aspects of follow-up.
METHODS: A best-worst survey was conducted in a sample of head and neck cancer patients in clinical follow-up at the National Cancer Institute (Milan, Italy). Conditional logit regression with choice as the dependent variable was run to analyse the data. A covariate-adjusted analysis was performed in order to identify socio-demographic and clinical factors related to the selection of best-worst items. The participants were asked to report any difficulties encountered during the survey.
RESULTS: A total of 143 patients, predominantly male (74%) and with a mean age of 58 years were enrolled in the survey. The strongest positive preference was expressed for a hospital-based program of physical examinations with frequency decreasing over time. Conversely, the lowest valued item was not performing any positron emission tomography (PET) scan during follow-up. Patients with high educational levels were more likely to value attending a primary care-based program and undergoing intensive radiological investigations. Other patient-specific variables significantly associated with the choice of items were employment and living status, time already spent in follow-up and number of treatments received.
CONCLUSIONS: Overall, patients were more likely to choose an intensive follow-up scheme broadly consistent with the program currently administered by the hospital. There is little evidence of preference heterogeneity that might justify customized programs based on demographics. The best-worst scaling task appeared feasible for most participants.

PMID: 28577698 [PubMed - in process]

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