Pd40-10 Transition in Quality-of-Life Among Older Patients With Bladder Cancer and Its Association With Treatment: A Clustering Approach

You have accessJournal of UrologyHealth Services Research: Practice Patterns, Quality of Life and Shared Decision Making III (PD40)1 May 2024PD40-10 TRANSITION IN QUALITY-OF-LIFE AMONG OLDER PATIENTS WITH BLADDER CANCER AND ITS ASSOCIATION WITH TREATMENT: A CLUSTERING APPROACH Geoffrey H. Rosen, Mohammad Beheshti, Brandon Henslee, Katie S. Murray, and Mojgan Golzy Geoffrey H. RosenGeoffrey H. Rosen , Mohammad BeheshtiMohammad Beheshti , Brandon HensleeBrandon Henslee , Katie S. MurrayKatie S. Murray , and Mojgan GolzyMojgan Golzy View All Author Informationhttps://doi.org/10.1097/01.JU.0001009356.04608.d5.10AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Bladder cancer (BC) diagnosis and treatment is associated with significant declines in functional status and overall health. Our objective was to understand transitions in quality of life (QoL) for patients with BC after diagnosis. METHODS: We identified patients with BC in the Surveillance, Epidemiology, and End Results-Medicare Health Outcomes Survey database (1998-2021) who had at least two QoL surveys (with at least two years between them, both after BC diagnosis.) We clustered using k-means based on the first QoL survey and applied the same clustering to the follow up survey. We assessed associations between initial cluster assignment and cluster transition and clinical and demographic variables. RESULTS: The final cohort consisted of 2,934 older (age≥65) BC patients. We identified three distinct clusters: 67.9% in Cluster 1 (best QoL); 25.4% in Cluster 2 (moderate QoL); and 6.7% in Cluster 3 (worst QoL). Initial cluster assignment was significantly associated with survival (log-rank p<0.001, Figure 1). In two-year follow-up, 11.7% patients showed improvement while 14% experienced a decline. Cancer and treatment characteristics were not associated with cluster transition (Table 1). Younger age and being married were identified as factors correlated with improvement in QoL. Older age and non-homeownership were identified as predictive of decline in QoL. CONCLUSIONS: We used machine learning techniques to group patients with BC based on responses to QoL questionnaires. We found three distinct groups. After two years, more than a quarter of patients either increased or decreased in our measure of overall QoL. Cancer and treatment characteristics did not correlate with change in QoL, while demographic factors such as age at initial survey as well as home ownership and marital status did. Download PPT Source of Funding: This research was supported by the NIH/National Center for Advancing Translational Sciences (NCATS) grant UL1TR002345, through the Pilot Translational and Clinical Studies function of the WU ICTS © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e823 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Geoffrey H. Rosen More articles by this author Mohammad Beheshti More articles by this author Brandon Henslee More articles by this author Katie S. Murray More articles by this author Mojgan Golzy More articles by this author Expand All Advertisement PDF downloadLoading ...