Identifying Distinct High Unmet-Need Phenotypes and Their Associated Bladder Cancer Patient Demographic, Clinical, Psychosocial, and Functional Characteristics: Results of Two Clustering Methods.

ABSTRACT

OBJECTIVES: We explored phenotypes of high unmet need of patients with bladder cancer and their associated patient demographic, clinical, psychosocial, and functional characteristics. DATA SOURCES Patients (N=159) were recruited from the Bladder Cancer Advocacy Network and completed an online survey measuring unmet needs (BCNAS-32), quality of life (FACT-Bl), anxiety and depression (HADS), coping (BRIEF Cope), social support (SPS), and self-efficacy beliefs (GSE). Hierarchical agglomerative (HA) and partitioning clustering (PC) analyses were used to identify and confirm high unmet-need phenotypes and their associated patient characteristics. Results showed a two-cluster solution; a cluster of patients with high unmet needs (17% and 34%, respectively) and a cluster of patients with low-moderate unmet needs (83% and 66%, respectively). These two methods showed moderate agreement (κ=0.57) and no significant differences in patient demographic and clinical characteristics between the two groups. However, the high-need group identified by the HA clustering method had significantly higher psychological (81 vs 66, p < .05), health system (93 vs 74, p < .001), daily living (93 vs 74, P < .001), sexuality (97 vs 69, P < .001), logistics (84 vs 69, P < .001), and communication (90 vs 76, P < .001) needs. This group also had worse quality of life and emotional adjustment and lower personal and social resources (P < .001) compared with the group identified by the PC method. CONCLUSION: A significant proportion of patients with bladder cancer continues to have high unique but inter-related phenotypes of needs based on the HA clustering method. IMPLICATIONS FOR NURSING PRACTICE Identifying characteristics of the most vulnerable patients will help tailor support programs to assist these patients with their unmet needs.