A structural equation modeling framework for estimating symptom burden based on symptom clusters in cancer survivors
Six symptom clusters in cancer survivors, derived from 40,766 patients, help standardize survivorship assessments and target interventions to high-burden groups.
Using structural equation modeling on 40,766 cancer survivors from the Danish SEQUEL cohort, this study derived 6 symptom clusters and validated SEM-based burden scores as a novel approach to standardising survivorship outcome comparisons across cancer types. Lymphoma, lung, and head/neck survivors showed consistently highest burden, informing targeted survivorship interventions.
What the study was
- Study design
- Population cohort SEM analysis (Danish SEQUEL cohort)
- Population
- 40,766 cancer survivors (breast, prostate, colon, rectum, lung, melanoma, lymphoma, head/neck) diagnosed 2010–2019 from Danish nationwide SEQUEL cohort
- Sample size
- 40766
- Category
- Public Health
- Maturity
- Exploratory
- Journal
- Sci Rep
Why it surfaced
Large population (n=40,766); includes lymphoma survivorship as T1 crossover. Methodological contribution (SEM for symptom burden quantification) is meaningful for survivorship research infrastructure. Low direct clinical relevance for the primary triage focus.
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