Abstract
e18179 Background: Adults with advanced cancer vary considerably in health status and functional reserve. Given the substantial risk of toxicity from systemic therapy, the challenge for medical oncologists is to objectively evaluate the risk of treatment complications prior to starting treatment. The Hurria Prediction Tool for Chemotherapy Toxicity in older adults was developed to aid medical oncologists in predicting which patients are at the highest risk of toxicity. This validated tool stratified geriatric patients with advanced cancer into low, medium, and high risk for toxicity from chemotherapy. In line with UPMC’s mission to “ensure that every patient gets the right care, in the right way, at the right time, every time,” we investigated the feasibility and usefulness of the tool to predict toxicity in adults with advanced cancer, and assist in shared decision making when undergoing treatment decisions. Methods: Adults ≥ 18 years old with advanced cancer whom were being considered for systemic therapy were identified. Patients completed a brief health assessment form prior to their physician visit. Lab values and treatment characteristics were combined with the patient’s subjective health assessment to calculate a toxicity score. Karnofsky and ECOG performance statuses, toxicities, treatment details, hospitalizations, and length of stay were collected. This project was approved by UPMC’s Quality Improvement Committee. Results: Initial pilot testing in sarcoma and genitourinary cancer clinics demonstrated that the implementation of a toxicity prediction tool is feasible in busy academic oncology clinics. We will present results of staff surveys related to the ease of use and utility of this tool. Conclusions: Preliminary results suggest the use of this chemotherapy toxicity tool, previously validated in the geriatric population, to be feasible and useful in adults with advanced cancer. Further data analysis and studies are planned to expand this validated tool in other oncology clinic settings, and evaluate how well predicted toxicity correlates with actual toxicity for patients of all ages and treatment types.
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