Comparing symptom clusters in cancer survivors by cancer diagnosis: A latent class profile analysis

• Published in: Supportive care in cancer Vol. 32; no. 5; p. 308
• Main Authors: Lee, Lena J., Han, Claire J., Saligan, Leorey, Wallen, Gwenyth R.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2024; Springer Nature B.V
• Subjects: Adult; Aged; Breast cancer; Cancer; Cancer Survivors - statistics & numerical data; Colorectal cancer; Cross-Sectional Studies; Depression - epidemiology; Depression - etiology; Fatigue - epidemiology; Fatigue - etiology; Female; Humans; Latent Class Analysis; Lymphoma; Male; Medical diagnosis; Medicine; Medicine & Public Health; Middle Aged; Neoplasms - complications; Nursing; Nursing Research; Oncology; Pain Medicine; Prostate; Rehabilitation Medicine; SEER Program; Sleep Wake Disorders - epidemiology; Sleep Wake Disorders - etiology; Survivor; Young Adult; Cancer survivors; Symptom clusters; Latent class analysis; Symptom management
• ISSN: 0941-4355; 1433-7339; 1433-7339
• DOI: 10.1007/s00520-024-08489-0

Purpose Research on symptom clusters in oncology is progressing, but knowledge gaps remain. One question is whether the number and types of symptom subgroups (i.e., latent classes) differ based on cancer diagnosis. The purpose of this study was to: (1) identify and compare latent class subgroups based on four highly prevalent symptoms (pain, fatigue, sleep disturbance, and depression), and (2) examine the differences in sociodemographic and clinical factors in the identified latent classes across the seven cancer types (i.e., prostate, non-small cell lung, non-Hodgkin’s lymphoma, breast, uterine, cervical, and colorectal cancer). Methods This study is a cross-sectional secondary analysis of data obtained from the My-Health study in partnership with four Surveillance, Epidemiology, and End Results (SEER) cancer registries located in California (two), Louisiana, and New Jersey. The sample included 4,762 cancer survivors 6-13 months following diagnosis of one of the seven cancer types mentioned. Latent class profile analysis was used. Results Subjects were primarily young (59% age 21-64 years), Caucasian (41%), married/cohabitating (58%) and unemployed (55%). The number and types of symptom subgroups varied across these seven cancer populations: four-subgroups were the common in prostate, lung, non-Hodgkin’s lymphoma, and breast cancer survivors. Unmarried, low education, and unemployment status were associated with high risk of symptom burden across the cancer types. Conclusion Identifying symptom subgroups by cancer diagnosis has the potential to develop innovative and effective targeted interventions in cancer survivors. Further research is needed to establish extensive knowledge in symptom clustering between treatment regimens, and short-term and long-term cancer survivors.