Identification of Distinct Symptom Profiles in Cancer Patients Using a Pre-Specified Symptom Cluster

Abstract

Context

Pain, fatigue, sleep disturbance, and depression often co-occur in oncology patients and negatively impact quality of life (QOL).

Objectives

Study purposes were to identify subgroups of patients with distinct symptom profiles based on their experiences with a pre-specified symptom cluster (i.e., pain, fatigue, depression, sleep disturbance) and to identify demographic, clinical, and symptom characteristics and QOL outcomes associated with each distinct profile.

Methods

Patients with breast, lung, gastrointestinal, and gynecologic cancers (n = 1340) were recruited from outpatient clinics during their first or second cycle of chemotherapy. They completed valid and reliable measures of pain, fatigue, sleep disturbance. depression, and QOL prior to their next dose of chemotherapy. Latent class profile analysis was used to identify the patient subgroups. Differences among the profiles were evaluated using parametric and non-parametric tests.

Results

Three distinct profiles were identified (i.e., Low (44.0%), Moderate (45.1%), High (10.8%). Compared to Low class, Moderate and High classes were younger and more likely to be female. Compared to the other two classes, High class was less likely to be married/partnered and employed, more likely to have a lower income and childcare responsibilities, had lower functional status, a higher body mass index, and exercised less. For both QOL scales, differences in subscale and total scores followed the same pattern (Low>Moderate>High).

Conclusions

Over 55% of patients undergoing chemotherapy had a moderate to high symptom burden associated with these four common co-occurring symptoms. Multimodal interventions are needed to decrease symptom burden and improve QOL outcomes in these patients.