Abstract

Neuroendocrine tumors (NETs) are rare, slow-growing malignant tumors. So far, there are no data on patient preferences regarding its therapy. This empirical study aimed to elicit patient preferences in the drug treatment of NET. Based on qualitative patient interviews and an analytic hierarchy process, six patient-relevant attributes were analyzed and weighted using a discrete-choice experiment. Patients were recruited with the help of a NET support group. An experimental 3*3 + 6*3 -MNL design was created using NGene. The design consisted of eighty-four choices, divided into seven blocks. Participants were randomly assigned to these blocks. The analysis included random parameter logit and latent class models. A total of 275 participants (51.6 percent female; mean age, 58.4 years) were included. The preference analysis within the random parameter logit model, taking into account the 95 percent confidence interval, showed predominance for the attribute "overall survival." The attributes "response to treatment" and "stabilization of tumor growth" followed. The side effects "nausea/vomiting" and "diarrhea" were considered of relatively equal importance. Latent class analysis of possible subgroup differences revealed three preference patterns. Preferences can influence therapeutic decisions. Preference analyses indicated that "overall survival" had the strongest influence, with participants clearly weighing outcome attributes higher than side effect attributes. In conclusion, mono-criterial decisions would not fully reflect patient perspectives.

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