In Silico Psycho-oncology: Understanding Resilience Pathways in Breast Cancer - Determinants of Longitudinal Depression and Quality of Life Trajectories

Background/Objectives: Patients with breast cancer show substantial heterogeneity in psychological adjustment following diagnosis. We aim to characterize longitudinal trajectories of quality of life (QoL) and depressive symptoms during the first 18 months post-diagnosis and to identify robust clinical, psychosocial, and behavioral predictors associated with distinct adjustment pathways. Methods: Data were drawn from the multicenter BOUNCE cohort. QoL (EORTC QLQ-C30) and depressive symptoms (HADS) were assessed repeatedly over 18 months. Latent Class Growth Analysis and Growth Mixture Modeling were used to identify distinct trajectory classes. Associations between candidate predictors and trajectory membership were ex-amined using logistic regression combined with elastic net regularization, including clinically motivated binary contrasts. Predictor robustness was evaluated under models with clinical site alternatively penalized and unpenalized. Results: Depression trajectories demonstrated heterogeneity, with groups characterized by persistent resilience (59.7%), stable moderate/high depression (25.3%), delayed-onset de-pression (5.0%), and recovery (10.0%). QoL trajectories ranged from stable excellent (13.2%) and stable high (13.2%) functioning to persistent low or deteriorating QoL (6.9%), with a distinct recovery trajectory (7.8%). Trajectory differentiation was primarily driven by psychological resources, symptom burden, functional status, and coping processes, while selected clinical factors contributed to specific trajectories. Patterns of predictors dif-fered across trajectory contrasts. Conclusions: Distinct subgroups of women with breast cancer follow divergent QoL and depres-sion trajectories after diagnosis. Differences between trajectories are shaped by a combination of psychological, functional, and clinical factors, highlighting the multidimensional nature of resilience and recovery. These findings support the need for tailored interven-tions that move beyond risk reduction toward promoting long-term well-being and mental health.