Trajectory patterns and influencing factors of supportive care needs in Chinese elderly breast cancer patients

The aim of this study was to identify the trajectory patterns of supportive care needs in Chinese older patients with breast cancer and their predictive factors.

A total of 122 older patients with breast cancer were recruited. Demographic and disease-related information, type D personality, and supportive care needs were investigated at baseline, 3, and 6 months. Latent class growth model was used to identify the trajectory patterns of supportive care needs. Multiple logistic regression was used to determine the predictors for membership.

Three trajectories with different characteristics of changing categories of supportive care needs were identified in the final analysis, named as "High needs decline group" (38.5%), "High needs sustained group" (51.6%), and "Low needs sustained group" (9.8%). Univariate analysis showed that age, education level, number of children, primary caregiver, pathological stage, surgical modality, treatment protocols, and personality traits were associated with the trajectory categories of supportive care needs of older patients with breast cancer. Multiple logistic regression showed that primary caregiver type, treatment protocols, and personality traits were influential factors in the trajectory of supportive care needs of older patients with breast cancer.

Our study demonstrates the heterogeneity of changes in supportive care needs. The supportive care needs of older patients with breast cancer show a trajectory of change in different categories, and healthcare providers can develop individualized interventions based on the characteristics of different patients.