Abstract
Leukocyte cell population data (CPD), obtained through contemporary hematology analyzers, provide critical insights into the functional and morphological states of immune cells. However, clinically relevant reference intervals for these parameters remain scarce, particularly in region-specific populations. This study sought to establish age- and sex-specific reference intervals for CPD parameters in healthy adults residing in Zigong, China. A total of 7,274 individuals were selected after rigorous screening from 10,673 candidates undergoing routine health checkups. Blood samples were analyzed utilizing a Sysmex XN-1000 analyzer. Statistical methods were employed to assess data distribution, identify and exclude outliers, and generate reference intervals by CLSI EP28-A3C guidelines. Significant differences were observed between males and females across multiple CPD parameters, with age-related trends also being identified. Validation with an independent dataset confirmed that over 90% of results fell within the established reference intervals. These findings present the first localized reference standards for CPD parameters in Zigong, potentially enhancing diagnostic accuracy and supporting clinical decision-making in laboratory medicine.
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Introduction
In recent years, cell population data (CPD) generated by blood analyzers has become a prominent research focus in clinical laboratory medicine1. The XN-1000 hematology analyzer, utilizing semiconductor laser technology, provides a wide range of leukocyte-related CPD parameters. These include forward scatter intensity (LY-Z) and distribution width (LY-WZ), side scatter intensity (LY-X) and distribution width (LY-WX), as well as side fluorescence intensity (LY-Y) and distribution width (LY-WY) for lymphocytes; forward scatter intensity (MO-Z) and distribution width (MO-WZ), side scatter intensity (MO-X) and distribution width (MO-WX), as well as side fluorescence intensity (MO-Y) and distribution width (MO-WY) for monocytes; and forward scatter intensity (NE-FSC) and distribution width (NE-WZ), side scatter intensity (NE-SSC) and distribution width (NE-WX), as well as side fluorescence intensity (NE-SFL) and distribution width (NE-WY) for neutrophils. These CPD parameters are closely associated with the size, complexity, and fluorescence intensity of white blood cells, including lymphocytes, monocytes, and neutrophils, reflecting their morphological and functional states2. Studies have shown that leukocyte CPD is linked to various diseases, including community-acquired pneumonia3sepsis4,5acute pancreatitis6malaria7lymphocytic leukocytosis6hematologic malignancies8and others. Additionally, CPD has been used in the differential diagnosis of elderly patients with aplastic anemia and myelodysplastic syndromes9and it has also been associated with postoperative complications following cardiac surgery with extracorporeal circulation10.
Establishing appropriate CPD reference intervals is essential for health assessment, disease diagnosis, and prognostic evaluation, as they provide an important foundation for clinicians to determine whether test results fall within the normal range11. Currently, research on reference intervals for leukocyte population parameters is limited, making the establishment of local CPD reference intervals highly valuable. Although CLSI EP28-A3C primarily addresses direct methods, we adapted its statistical framework following Hoffman’s indirect approach, supplemented by Tukey-based outlier exclusion. Indirect methods based on statistical models utilize existing laboratory database data to establish reference intervals12,13and these approaches are endorsed by the CLSI EP28-A3C guidelines14.
In this study, we used an indirect method to establish CPD reference intervals for the Zigong population based on data from 7,273 routine health checkups collected between June 2023 and May 2024 from the laboratory information system (LIS) of Zigong first people’s hospital. These reference intervals aim to provide a foundation for accurate clinical diagnosis and treatment.
Materials and methods
Participants
After obtaining written informed consent (included in hospital’s health check-up form), venous blood was collected. Inclusion/exclusion criteria were applied retrospectively to laboratory data from 10,673 individuals at the Physical Examination Center of Zigong First People’s Hospital from June 2023 to May 2024. The exclusion criteria were as follows: (1) age under 18 years (n = 256); (2) abnormal blood cell counts (n = 1,625), including leukocyte counts (< 3.5 × 10⁹/L or > 9.5 × 10⁹/L), neutrophil counts (< 1.8 × 10⁹/L or > 6.3 × 10⁹/L), lymphocyte counts (< 1.1 × 10⁹/L or > 3.2 × 10⁹/L), monocyte counts (< 0.1 × 10⁹/L or > 0.6 × 10⁹/L); hemoglobin concentration (HGB) < 130 g/L or > 175 g/L for males and < 115 g/L or > 150 g/L for females; and platelet counts (PLT) < 125 × 10⁹/L or > 350 × 10⁹/L, based on the WS/T 405–2012 Hematology Analysis Reference Interval (http://www.nhc.gov.cn/wjw); and (3) abnormalities in liver or kidney function (n = 1,518). After applying the exclusion criteria, 7,274 cases were included in the study (male: n = 3,256; female: n = 4,018). The study was approved by the Ethics Committee of Zigong First People’s Hospital (Ethics (Research) No. 58, 2023), and all participants provided written informed consent. All methods were performed in accordance with the relevant guidelines and regulations.
Samples, instruments, and reagents
A total of 2 mL of fasting venous blood was collected into EDTA-K2 anticoagulant tubes. Blood cell counts were analyzed using the Sysmex XN-1000 automated hematology analyzer (Sysmex Corporation, Kobe, Japan) in CBC + DIFF mode. All analyses were completed within 2 h of sample collection. No local biostandardization was applied to FSC/SSC parameters. This system employs semiconductor laser flow cytometry to measure forward scatter (FSC, reflecting cell size), side scatter (SSC, indicating internal complexity), and side fluorescence (SFL, detecting nucleic acid/granularity content). These signals are captured as intensity and distribution width for different leukocyte subtypes—lymphocytes (LY), monocytes (MO), and neutrophils (NE)—and reported as cell population data (CPD) parameters such as LY-X (side scatter intensity for lymphocytes), MO-Y (fluorescence intensity for monocytes), and NE-WZ (width of forward scatter for neutrophils), among others. Reagents, quality control materials, and calibration standards were exclusively Sysmex original products, stored and used strictly according to the manufacturer’s recommended conditions. Internal quality control was performed following the Westgard multi-rule system, applying the 13S, 22S, and R4S rules. External quality assessment was carried out by the Clinical Laboratory Center of the National Health Commission of China, and all results complied with the required standards.
Establishment of reference intervals and statistical methods
Data analysis was conducted using SPSS version 26.0 (IBM Corp., Armonk, NY, USA). The normality of continuous variables was assessed using the skewness-kurtosis test only; no visual assessment methods, such as Q-Q plots or histograms, were employed. Variables were considered normally distributed when skewness ranged from − 2 to + 2 and kurtosis from − 7 to + 715,16 . Outliers were identified and removed using Tukey’s method, defined as values outside the range of Q1–1.5×IQR and Q3 + 1.5×IQR17. Quantitative variables were expressed as mean (standard deviation) for normally distributed data and as median (interquartile range) for non-normally distributed data. Categorical variables were reported as frequencies (percentages). To establish reference intervals, the nonparametric percentile method (P2.5–P97.5) was employed, following the CLSI EP28-A3C guidelines14. No data transformation was performed, as all leukocyte CPD parameters adhered to normal or near-normal distributions18. Age groups (18–44, 45–59, and ≥ 60 years) were predefined based on the World Health Organization (WHO) age classification standards, representing young adults (18–44 years), middle-aged adults (45–59 years), and older adults (≥ 60 years). Statistical methods used to analyse differences between age or sex groups included parametric tests (such as the t-test for two-group comparisons or ANOVA for multiple-group comparisons) for normally distributed data and non-parametric tests (such as the Mann–Whitney U-test for two-group comparisons or the Kruskal–Wallis test for multiple-group comparisons) for all other cases. Sex and age group stratification were evaluated using the Harris-Boyd method, as recommended in the CLSI EP28-A3C guidelines. The z-statistic calculated between subgroups was compared with the critical z* value to determine the necessity of stratification. Statistical significance was defined as P < 0.05.
Validation of reference intervals
The reference intervals obtained in this study were validated using routine blood test results from 616 healthy adults who underwent medical examinations at our center in June 2024. The proportion of results falling outside the reference intervals was calculated, with a rate of ≤ 10% considered indicative of successful validation14.
Results
Data distribution and normality test
A total of 7,274 healthy individuals undergoing medical examinations were included in this study. The demographic characteristics and complete blood count (CBC) results of the participants are summarized in Table 1. All leukocyte cell population data (CPD) parameters followed a normal or approximately normal distribution, as indicated by skewness values less than 0.83 and kurtosis values below 3.13 (Supplementary Table 1).
Comparison of leukocyte CPD between different gender groups
The levels of LY-X, MO-WZ, NE-WX, and NE-SSC did not show statistically significant differences between apparently healthy adult males and females (P > 0.05). In contrast, LY-WZ, MO-WY, NE-WY, and NE-WZ levels were significantly higher in healthy males compared to females (P < 0.05). Conversely, LY-WX, LY-WY, LY-Y, LY-Z, MO-X, MO-Y, MO-Z, NE-FSC, and NE-SFL levels were significantly higher in apparently healthy females compared to males (P < 0.05) (Table 2).
Comparison of leukocyte CPD between different age groups
Significant differences in leukocyte CPD parameters were observed across different age groups (P < 0.05). Among lymphocyte parameters, LY-WX and LY-Y exhibited a decreasing trend with age, whereas LY-WZ and LY-X demonstrated an increasing trend. For monocyte parameters, MO-Y and MO-Z showed a decreasing trend with age, while MO-WX, MO-WY, MO-WZ, and MO-X displayed an increasing trend. Regarding neutrophil parameters, NE-SSC exhibited a decreasing trend, whereas NE-WX, NE-WY, NE-WZ, NE-FSC, and NE-SFL showed an increasing trend (Table 3).
Comparison of CPD between different genders of the same age group and between different age groups of the same gender
Within the same age group, the levels of LY-WX, LY-WY, LY-Z, MO-WX, MO-X, MO-Z, NE-FSC, and NE-SFL were significantly higher in apparently healthy adult females compared to males, whereas MO-WY, NE-WY, and NE-WZ were significantly lower in females compared to males (P < 0.05). Among apparently healthy males, the levels of LY-WZ, LY-X, MO-WX, MO-WY, MO-X, NE-WX, NE-WY, and NE-WZ increased with age, while LY-WX and MO-Y decreased with age. In apparently healthy females, the levels of LY-WZ, LY-X, LY-Z, MO-WX, MO-WY, MO-WZ, NE-WX, NE-WY, NE-WZ, NE-FSC, and NE-SFL increased with age, whereas LY-WX, LY-Y, MO-Y, MO-Z, and NE-SSC decreased with age. Notably, the differences in LY-WY, MO-WZ, and NE-SSC levels were not statistically significant (P > 0.05) among males of different age groups, while the differences in MO-X levels were not statistically significant (P > 0.05) among females of different age groups (Table 4).
Establishment and validation of reference intervals
Using nested ANOVA and the CLSI EP28-A3C guidelines, we evaluated the necessity of grouping to establish reference intervals. The reference intervals for LY-WZ, LY-X, LY-Y, MO-WX, MO-WY, MO-WZ, MO-Y, NE-WX, NE-WY, NE-WZ, NE-FSC, NE-SFL, and NE-SSC showed no significant differences. However, the reference intervals for other CPD parameters varied by sex (Table 5). Furthermore, the validation pass rate for reference intervals across all CPD parameters was below 10% (Supplementary Table 2).
Discussion
The Sysmex XN module not only measures routine hematological parameters but also generates novel leukocyte parameters, such as cell population data (CPD) parameters. Its analytical techniques incorporate fluorescence flow cytometry for leukocyte classification and enumeration, along with the use of forward scatter (FSC), side scatter (SSC), and fluorescence intensity (SFL) to differentiate leukocyte populations. These three metrics, along with their distribution widths (W), are combined to derive CPD values for neutrophils (NE), lymphocytes (LY), and monocytes (MO)19. Although CPD parameters are manufacturer-provided and intended primarily for research purposes rather than clinical reporting, establishing accurate and reliable reference intervals is crucial for assessing health and disease states.
In this study, an indirect approach based on mathematical and statistical modeling was employed to establish reference intervals using pre-existing data from the laboratory database. This method leverages large datasets, minimizing the need for additional experimental costs and reducing time requirements. Compared to the traditional direct method, the indirect approach provides more stable and reliable reference intervals, particularly when the sample size is large and the data quality is high. These reference intervals are crucial for clinical diagnosis, health assessment, and prognosis evaluation. The reference intervals derived in this study will aid clinicians in more accurately determining whether test results fall within the normal range, thereby enhancing diagnostic accuracy and treatment effectiveness.
This study demonstrated that LY-WZ, MO-WY, NE-WY, and NE-WZ values were significantly higher in males than in females, while LY-WX, LY-WY, LY-Y, LY-Z, MO-X, MO-Y, MO-Z, NE-FSC, and NE-SFL values were higher in females. These findings indicate significant sex-based differences in leukocyte cell population data (CPD) parameters, which may be linked to variations in immune function and disease susceptibility. Previous studies20 have shown that testosterone inhibits the proliferation and differentiation of B lymphocytes by reducing the production of B-cell activating factor (BAFF) by macrophages and downregulating key factors involved in apoptosis, such as B-cell lymphoma (Bcl-2) and nuclear factor κB. In contrast, estrogen promotes B lymphocyte proliferation and differentiation while inhibiting apoptosis. In different age groups within the same sex, certain CPD parameters exhibited consistent trends, such as an increase in LY-X and a decrease in LY-WX with age. These findings align with reports from Korea21. The primary objective of this study was to establish reference intervals for leukocyte CPD in healthy adults in the Zigong area and to investigate the effects of sex and age on these parameters. By analyzing a large sample population, we identified several key findings. Based on the CLSI EP28-A3C guidelines and nested ANOVA results, we determined that parameters such as LY-WZ, LY-X, LY-Y, MO-WX, MO-WY, NE-WX, NE-WZ, NE-FSC, NE-SFL, and NE-SSC do not require stratification by sex to establish reference intervals. However, all CPD parameters needed to be stratified by age, which differs from the findings reported in the Netherlands22. This discrepancy may stem from several factors: Ethnic variations: East Asian populations, as highlighted by Choi et al. in their study of Korean cohorts21exhibit distinctive leukocyte morphological trends. Environmental influences: The high-sodium diet characteristic of Zigong, which is a known risk factor for hypertension, may affect leukocyte rigidity, thereby altering FSC/SSC profiles. Analytical considerations: While the default settings of the Sysmex XN-1000 analyzer are globally standardized, regional calibration practices (e.g., EMEA vs. China) could contribute to minor variations in absolute CPD values. To further elucidate these differences, future multi-center studies should standardize protocols to differentiate biological variation from technical influences.
This study is the first to establish reference intervals for leukocyte cell population data (CPD) in healthy adults from Zigong, providing an essential localized reference for clinical diagnosis in this region. However, there are several limitations to consider: (1) The study used an indirect method to establish reference intervals, and despite setting reasonable exclusion criteria based on the laboratory results of patients, some non-healthy individuals may still have been included; (2) Geographic limitations exist, as the study population is exclusively from Zigong, which may not fully represent the characteristics of populations from other regions; (3) As a cross-sectional study, it cannot capture the dynamic changes in individual CPD parameters over time; and (4) Other potential influencing factors, such as lifestyle habits and seasonal variations, were not considered, which may also impact the CPD parameters.
Conclusion
This study successfully established reference intervals for leukocyte cell population data (CPD) in healthy adults from Zigong, providing a crucial localized reference for clinical laboratory diagnosis. The findings indicate that certain parameters should account for gender and age variations, which is essential for enhancing the accuracy of test results. Although the study has some limitations, including geographic constraints and the inherent limitations of cross-sectional designs, its results offer valuable guidance for clinical practice. Future research should aim to expand the sample size to include more diverse regions and populations, while also considering additional influencing factors such as lifestyle habits and seasonal variations, in order to optimize and further validate the reference intervals for leukocyte CPD parameters.
Data availability
The anonymized dataset supporting the findings of this study has been provided as a Supplementary File accompanying this article. All data were pseudonymized prior to inclusion and comply with ethical and institutional regulations.
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Jianhong Yu, Yu Chen and Haodong Hua conceived the study and revised the paper. Jianhong Yu analyzed the data. Jianhong Yu conceived and designed the experiments and wrote the paper. All authors have read and agreed to the published version of the manuscript.
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Yu, J., Chen, Y. & Hua, H. Reference intervals for leukocyte cell population data in healthy adults in Zigong region, China. Sci Rep 15, 29786 (2025). https://doi.org/10.1038/s41598-025-15766-3
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DOI: https://doi.org/10.1038/s41598-025-15766-3
