Please login (Members) to view content or
(Nonmembers) this article.
No votes yet

Symptom Clusters in Breast Cancer Survivors: A Latent Class Profile Analysis

Lena J. Lee
Alyson Ross
Kathleen Griffith
Roxanne E. Jensen
Gwenyth R. Wallen
ONF 2020, 47(1), 89-100 DOI: 10.1188/20.ONF.89-100

Objectives: To identify symptom clusters in breast cancer survivors and to determine sociodemographic and clinical characteristics influencing symptom cluster membership.

Sample & Setting: The authors performed a cross-sectional secondary analysis of data obtained from a community-based cancer registry–linked survey with 1,500 breast cancer survivors 6–13 months following a breast cancer diagnosis.

Methods & Variables: Symptom clusters were identified using latent class profile analysis of four patient-reported symptoms (pain, fatigue, sleep disturbance, and depression) with custom PROMIS® short forms.

Results: Four distinct classes were identified: symptoms within normal limits (class 1), pain with fatigue and sleep disturbance (class 2), depression with fatigue and sleep disturbance (class 3), and all high symptom burden (class 4). The authors identified four clinically relevant and actionable symptom clusters in early-stage breast cancer survivorship. Certain sociodemographic and clinical characteristics place patients at risk for physical late effects and mental health issues.

Implications for Nursing: Common symptom clusters may lead to better prevention and treatment strategies that target a group of symptoms. Results also suggest that certain factors place patients at high risk for symptom burden, which can guide tailored interventions.

Members Only

Access to this article is restricted. Please login to view the full article.

Not a current ONS Member or journal subscriber?
Join/Renew Membership or