AIM: To identify unique clusters of @entity1 based on their concerns in using analgesia for @entity5 and predictors of the cluster membership. METHODS: This was a 3-mo prospective observational study (n = 207). @entity1 were included if they were adults (>=  18 years), diagnosed with @entity5 or @entity1582 , and had at least one prescription of around-the-clock @entity158 medication for @entity5 or @entity5 -treatment-related @entity158 . @entity1 were recruited from two outpatient medical oncology clinics within a large health system in Philadelphia. A choice-based conjoint (CBC) analysis experiment was used to elicit analgesic treatment preferences (utilities). @entity1 employed trade-offs based on five analgesic attributes (percent relief from analgesics, type of analgesic, type of side-effects, severity of side-effects, out of pocket cost). @entity1 were clustered based on CBC utilities using novel adaptive statistical methods. Multiple logistic regression was used to identify predictors of cluster membership. RESULTS: The analyses found 4 unique clusters: Most @entity1 made trade-offs based on the expectation of @entity158 relief (cluster 1, 41%). For a subset, the main underlying concern was type of analgesic prescribed, i.e., opioid vs non-opioid (cluster 2, 11%) and type of analgesic side effects (cluster 4, 21%), respectively. About one in four made trade-offs based on multiple concerns simultaneously including @entity158 relief, type of side effects, and severity of side effects (cluster 3, 28%). In multivariable analysis, to identify predictors of cluster membership, clinical and socioeconomic factors (education, health literacy, income, social support) rather than analgesic attitudes and beliefs were found important; only the belief, i.e., @entity158 medications can mask changes in health or keep you from knowing what is going on in your body was found significant in predicting two of the four clusters [cluster 1 (-); cluster 4 (+)]. CONCLUSION: Most @entity1 appear to be driven by a single salient concern in using analgesia for @entity5 . Addressing these concerns, perhaps through real time clinical assessments, may improve @entity1 ' analgesic adherence patterns and @entity5 outcomes.

Salient concerns in using analgesia for XXXX among outpatients: A cluster analysis study.

@entity1 :: ('9606', 'Species') :: ['Patients', 'patients'] @entity1582 :: ('MESH:D009101', 'Disease') :: ['multiple myelomas'] @entity5 :: ('MESH:D009369', 'Disease') :: ['cancer', 'cancer pain', 'solid tumors'] @entity158 :: ('MESH:D010146', 'Disease') :: ['pain']
@entity5 :: (MESH:D009369,Disease) :: ['cancer pain']
