Establishment and Validation of Serum Ferritin Reference Intervals Based on Real-World Big Data and Multi-Strategy Partitioning Algorithms

基于真实世界大数据和多策略分区算法的血清铁蛋白参考区间建立与验证

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Abstract

Background/Objectives: We aimed to establish and validate population-based reference intervals (RIs) for serum ferritin (SF) using an indirect, date-driven approach based on real-world laboratory data and to optimize partitioning strategies. Methods: SF results from 29,723 apparently healthy individuals who underwent health examinations at West China Hospital between 2020 and 2024 were retrospectively analyzed. SF was measured on a Roche Cobas e801 electrochemiluminescence immunoassay platform. After Box-Cox transformation, outliers were removed using an iterative Tukey method. Potential partitioning factors were evaluated, and data-driven age cut-points were explored using decision tree regression and verified with the Harris-Boyd criteria. RIs were estimated using nonparametric percentile methods and validated in an independent cohort of 2494 individuals. Results: SF concentrations were significantly higher in males than in females (p < 0.001). In females, SF showed a significant positive association with age (r = 0.466, p < 0.001), whereas no such association was observed in males. Decision tree analysis identified 50 years as the optimal age cut-off for females (R(2) = 0.2467). The final study-derived RIs were 98.02-997.78 µg/L for males, 10.30-299.55 µg/L for females ≤ 50 years, and 36.61-507.00 µg/L for females > 50 years. In the validation cohort, the study-derived RIs achieved pass rates of 93.83-94.72%, which were significantly higher than the manufacturer-provided RIs (37.12-73.97%, all p < 0.001). Conclusions: Using a large health examination database and a multi-step partitioning strategy, we established robust sex- and age-specific SF RIs on the Roche Cobas e801 platform for the local population. This work provides a reproducible, generalizable framework for indirect RI determination of other biomarkers.

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