Big data-driven establishment and bias comparison of serum ferritin reference intervals in Zhejiang Chinese adults using six algorithms

利用六种算法,基于大数据建立和比较浙江省成年人血清铁蛋白参考区间的偏差

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Abstract

This study systematically compared the performance of six algorithms for establishing serum ferritin (SF) reference intervals (RIs) using data from large-scale health check-up populations (22,359 cases from Hospital A and 555 cases from Hospital B) and 327 anemia patients. Methods included non-parametric (EP28-NP) and parametric (EP28-P) approaches per EP28-A3c guidelines, along with modern algorithms (TMC, refineR, Kosmic, Bhattacharya). Continuous RIs were constructed using GAMLSS. Results showed good consistency in lower RIs limits between EP28-NP and four modern algorithms. Using EP28-NP as an example, male RIs (20–92 years) were 68.8-495.5 ng/mL, while females exhibited age-gradient characteristics: 20–45 years (10.4-132.5 ng/mL), 46–58 years (13.8-241.6 ng/mL), and 59–90 years (43.7-348.8 ng/mL). All algorithms demonstrated satisfactory validation rates (90.91%-98.67%). Notably, application of laboratory-established RIs significantly increased SF abnormality detection rates in anemia patients from 13.2% to 33.6% compared to manufacturer standards. Continuous RIs revealed significant SF concentration increases in males aged 20–29 years and females aged 46–58 years. The study demonstrates that laboratory-developed RIs better reflect population characteristics than manufacturer standards, and recommends that laboratories select appropriate algorithms based on data distribution to establish localized reference criteria.

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