ArticleCancer medicine2026
Sex-, Age-, Lifestyle-, and Comorbidity-Specific Reference Values for Serum Cytokines in the Dutch General Population: Results From the PROFILES Registry.
Article in Cancer medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundInflammation-related biomarkers have been implicated in a wide range of cancer-related symptoms and patient-reported outcomes (PROs), including fatigue, pain, and depression. To interpret biomarker data among cancer patients, normative reference values from healthy populations are essential.
objectiveThis cross-sectional study aimed to provide sex- and age-stratified reference data distributions for 12 inflammation-related serum biomarkers in a representative sample of Dutch adults without a history of cancer.
methodsAdults from the LISS panel were selected to match cancer cohorts from the PROFILES registry in age and sex. Participants completed questionnaires and optionally provided blood samples using harmonized protocols aligned with the PROFILES registry. Serum levels of IL-1α, IL-1β, IL-6, IL-8, IL-10, IL-17A, IL-22, CRP, TGF-α, IFN-γ, IL-1RA, and soluble TNF receptors I and II (sTNFRI/II) were quantified using the Meso Scale Discovery (MSD) platform. Cytokine levels were stratified by demographics, lifestyle factors, and self-reported health conditions. ANOVAs were used to compare groups.
resultsIn total 720 panel members filled out the questionnaires, of which 265 (mean age = 59.0, 47.9% male) provided additional serum blood samples. Biomarker levels varied by sex, age, BMI, smoking status, and number of health conditions. Notably, higher levels of IL-1RA and sTNFRI/II were observed in individuals with obesity or diabetes. Individuals with osteoarthritis exhibited elevated IL-6 and IL-1β levels.
conclusionThis study offers a robust reference dataset for key inflammatory biomarkers, stratified by relevant demographics, lifestyle factors, and self-reported health conditions. These data facilitate interpretation of biomarker-PRO relationships in cancer survivors and support comparative research across chronic disease populations.
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