Predicting Functional Decline and Clinical Outcomes in Newly Diagnosed Older Patients with Localized Bladder Cancer

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PROJECT SUMMARY/ABSTRACT: Older patients with cancer are disproportionately perceived as unfit for aggressive therapies, resulting in significantly lower rates of definitive cancer care and poor outcomes. We lack validated tools to reliably predict personalized risks of adverse treatment-related events and salient outcomes for older patients such as functional decline. While guidelines advocate for widespread adoption of Geriatric Assessments (GAs) to quantify multidimensional vulnerabilities prior to treatment decision-making in older patients with cancer, clinical adoption is low related to a dearth of data evaluating the ability of GAs in clinical practice to discriminate those at risk for functional decline, adverse clinical and oncologic outcomes. Furthermore, traditional GAs do not include validated metrics of muscle mass that independently predict clinical and oncologic outcomes. Bladder cancer is an ideal health condition in which to evaluate and develop personalized geriatric oncology risk stratification tools, given median age at diagnosis of 73 years, a high baseline prevalence of comorbidities, substantial risk of treatment-associated adverse events, and universal lethality if untreated. Our objective is to quantify functional decline in patients with newly diagnosed bladder cancer, and to develop prediction models incorporating GA- based frailty and muscle metrics for the outcomes of functional decline, treatment-associated morbidity and mortality. The Specific Aims are: (1A) To characterize prevalence and predictors of functional decline in older adults with newly diagnosed bladder cancer, (1B) to determine if baseline frailty and muscle metrics predict functional decline, and (2) To evaluate associations frailty, muscle metrics, and treatment-associated outcomes (i.e., adverse events, survival) in older adults with localized high-risk bladder cancer. To achieve Aim 1, baseline functional status will be compared with a 3-month assessment in a prospective newly diagnosed older bladder cancer cohort (N=250) undergoing a pretreatment GA-based frailty self-assessment and muscle metrics and a predictive model will be developed. For Aim 2, we will construct multivariable models for treatment-associated adverse events, postoperative complications, and mortality incorporating GA-based frailty and muscle metrics from a robust bladder cancer registry. This innovative study advances risk stratification by incorporating validated GA tools augmented with robust body composition data. This work is significant: it will be the first study to characterize risk factors for functional decline in older bladder cancer patients, while addressing the acute need to validate rigorous personalized risk stratification tools incorporating geriatric conditions to inform treatment decisions, ensuring alignment with patient priorities. This work will directly translate to improvements in outcomes of older patients with cancer and extrapolate to other malignancies. This GEMSSTAR project, mentoring committee, and professional development plan will help the PI to become one of the few independent investigators with expertise intersecting aging, urologic oncology, and patient-centered outcomes research.