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Monthly Biological Variation of Five Lung Cancer Markers in Healthy Older Individuals: Evidence from Combined Prospective Cohort and Real-World Data Analyses.

Annals of laboratory medicine 2026

Han Z, Yang D, Wang H, Su Z, Wang X, Zhao L, Mu R, Qin Y, Liu Y, Zhao M

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[BACKGROUND] Elderly populations face disproportionate lung cancer burdens; however, biological variation (BV) data for key tumor markers (carcinoma embryonic antigen [CEA], neuron-specific enolase [N

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  • 표본수 (n) 8,003

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BibTeX ↓ RIS ↓
APA Han Z, Yang D, et al. (2026). Monthly Biological Variation of Five Lung Cancer Markers in Healthy Older Individuals: Evidence from Combined Prospective Cohort and Real-World Data Analyses.. Annals of laboratory medicine. https://doi.org/10.3343/alm.2025.0528
MLA Han Z, et al.. "Monthly Biological Variation of Five Lung Cancer Markers in Healthy Older Individuals: Evidence from Combined Prospective Cohort and Real-World Data Analyses.." Annals of laboratory medicine, 2026.
PMID 41674353

Abstract

[BACKGROUND] Elderly populations face disproportionate lung cancer burdens; however, biological variation (BV) data for key tumor markers (carcinoma embryonic antigen [CEA], neuron-specific enolase [NSE], cytokeratin 19 fragment [Cyfra21-1], progastrin-releasing peptide [ProGRP], and squamous cell carcinoma antigen [SCC-Ag]) in this demographic remain scarce, impeding personalized result interpretation. This study explored BV for these five lung cancer markers among older Chinese individuals.

[METHODS] We prospectively enrolled 45 healthy Chinese adults aged 60-75 yrs for six monthly blood collections. BV components (within-participant [CV], and between-participant [CV]) were estimated using nested ANOVA and Bayesian hierarchical modeling. Real-world data (N=8,003) were analyzed for CEA. Methods followed BV data critical appraisal checklist standards.

[RESULTS] All markers showed high individuality, with individuality indices (II) <1.4. CEA exhibited the lowest II of 0.18. Bayesian hierarchical modeling and nested ANOVA produced comparable BV estimates. CEA had higher CV (11.3%, 95% confidence interval [CI]: 10.2%-12.5%) than European data (6.4%, 95% CI: 6.0%-6.7%). Cyfra21-1 displayed sex-specific CV differences. The CV of CEA estimates remained consistent across sampling intervals in direct (1-5 months: 9.7%-12.3%) and indirect methods (1-365+ days: 17.2%-18.1%). Harris-Brown heterogeneity ratio analysis revealed substantial heterogeneity of individual within-participant BV (CV) for CEA, supporting CV-derived reference change values (RCVs).

[CONCLUSIONS] This study establishes the first comprehensive BV database for lung cancer biomarkers in elderly Asians. Stable monthly variation enables flexible monitoring protocols. Our findings support implementing personalized RCVs for clinical interpretation and facilitate earlier therapeutic interventions for aging individuals.

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