ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2024
Comparing symptom clusters in cancer survivors by cancer diagnosis: A latent class profile analysis.
Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Symptom clusters in colorectal cancer: a systematic review of assessment tools, statistical methods, and symptom patterns.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025Pooled it
- Profiles of quality of life among US young adult cancer survivors and their associations with potential psychosocial intervention targets of hope and psychological flexibility.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025Trial
- Psychometric Evaluation of the Romanian Quality of Life in Adult Cancer Survivors (QLACS) in Women with Breast Cancer: A Cross-Sectional Study.Journal of clinical medicine · 2026Article
- Professional Roles in Danish Clinics for General Late Effects After Cancer-A Qualitative Study.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026Article
- Symptom burden in patients with hematologic malignancies and its influencing factors.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- Exploring the influencing factors of subjective cognitive function in patients with advanced cancer pain: a cross-sectional study utilizing latent profile analysis.Scientific reports · 2026Article
- Perspectives of Lymphoma Survivors and Oncology Care Providers on Survivorship Care: A Qualitative Study.JCO oncology practice · 2025Article
- Using Machine Learning Approaches on Dynamic Patient-Reported Outcomes to Cluster Cancer Treatment-Related Symptoms.Current oncology (Toronto, Ont.) · 2025Article
- Symptom and functional networks of patients with cancer in different latent risk subgroups based on patient-reported outcomes.BMC cancer · 2025Article
- Symptoms, Symptom Profiles, and Healthcare Utilization in Patients with Hematologic Malignancies: A Retrospective Observational Cohort Study and Latent Class Analysis.Current oncology (Toronto, Ont.) · 2025Observational
- Biobehavioral predictors of mood, pain, fatigue, and insomnia in endometrial cancer survivors.Gynecologic oncology · 2024Article
- The Significance of Communication and Treatment Expectations in Cancer Care: An Interview Study With Cancer Care Practitioners.Integrative cancer therapiesArticle
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Authors and funding
4 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeResearch 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).
methodsThis 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.
resultsSubjects 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.
conclusionIdentifying 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.
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