Four distinct patient-reported outcome (PRO) trajectories in longitudinal responses collected before, during, and after chemotherapy.

Abstract

2012 Background: Cancer chemotherapy, whether given with curative or palliative intent, is toxic. Toxicity is routinely captured in clinical trials by investigator observation and increasingly by PRO. The ability to capture PRO in the routine treatment workflow has been standard at Stanford since 2015 (Roy et al ASCO 2020). Analysis of longitudinally captured, real world PRO and prospectively identifying patients (pts) whose quality of life (QOL) is at risk of deteriorating either permanently or temporarily is needed. Routine serial PRO measurement should enhance precision care delivery, precision toxicity detection and management. Methods: We identified patients undergoing chemotherapy at Stanford and analyzed PROMIS (PRO Measurement Information System) responses. Pts with PROMIS survey information at three intervals—pre-treatment, during chemotherapy and post chemotherapy—were identified. We evaluated global physical health (GPH) and global mental health (GMH). Pts with a clinically significant decrease (CSD) in GPH or GMH scores were identified. A k-median cluster analysis was used to identify patient trajectory clusters and a machine-learning model was applied to identify risk factors for CSD and predict CSD. Results: We identified 670 adult oncology patients undergoing chemotherapy who completed at least one PROMIS survey in each interval. GPH scores were 48.4 ± 9.1 before, 47.1 ± 8.5 during, and 48.5 ± 8.9 after chemotherapy and GMH scores were 50.5 ± 8.2, 49.1 ± 8.5, and 50.7 ± 9.0, respectively. The majority of patients did not have a CSD in GPH or GMH post treatment compared to pretreatment scores. Pretreatment scores were the strongest predictor of a CSD in GPH and GMH. Trajectory clustering identified four distinct trajectories: Temporary Improver, Temporary Deteriorator, Improver, Inexorable Deteriorators. We were not able to predict any cluster based on pre-treatment features. Conclusions: Using routinely collected PROMIS surveys in a real-world setting, we are able to predict patients with post-treatment decreases in their physical and mental well-being. We further defined four novel patient trajectories during chemotherapy, which could guide personalized supportive interventions to improve patient’s chemotherapy experience. Identification of patients at risk for deterioration and the patterns of deterioration could help guide efficient deployment of toxicity mitigating and supportive care interventions to patients most in need.