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

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.