Moving Towards Person-Centered Analytic Approaches in Cancer Pain and Symptom Research and Care

Until recently, the majority of descriptive and intervention studies have reported on various pain characteristics (e.g., pain intensity, pain qualities) outcomes (efficacy of an analgesic regimen) using variable centered analytic approaches (e.g., means, medians, standard deviations, univariable or multivariable regression analysis). While the use of these approaches provides valuable information, they do not provide insights into the large amount of inter-individual variability that exists in patients’ pain experiences and responses to interventions. This presentation will provide an overview of the benefits and challenges of using person-centered analytic approaches (e.g., growth mixture modeling, latent variable modeling) to identify subgroups of patients with distinct pain profiles. Examples of how these approaches are being used to analyzed data related to cancer pain, chemotherapy-induced peripheral neuropathy, and pain and depression will be reviewed.