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Preoperative peripheral blood routine indicators as predictors of prognosis and diagnosis in glioma under the 2021 World Health Organization classification

  • Authors:
    • Qing Yang
    • Jiaying Ni
    • Jiandong Zhu
    • Xiao Fan
    • Xing Cheng
    • Yun Yu
    • Zhumei Shi
    • Yingyi Wang
    • Yongping You
  • View Affiliations / Copyright

    Affiliations: Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China, Department of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, P.R. China
    Copyright: © Yang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 543
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    Published online on: September 22, 2025
       https://doi.org/10.3892/ol.2025.15289
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Abstract

Multiple hematological indicators have been shown to be associated with the prediction and prognosis of gliomas. The present study aimed to explore the value of 22 preoperative peripheral blood routine indicators in the diagnosis and prognosis prediction of glioma. Patients with glioma were grouped according to the 2021 World Health Organization (WHO) guidelines for glioma. The correlations among preoperative peripheral blood routine indicators in all patients with glioma were assessed using Spearman's rank correlation analysis. The relationships between these indicators and glioma molecular subtypes were evaluated using ANOVA, independent samples t‑test and logistic regression analysis. Analysis of prognosis prediction was conducted using multivariate Cox regression. Based on the WHO 2021 guidelines, patients with glioma were classified into 92 cases of astrocytoma, 77 cases of oligodendroglioma and 402 cases of glioblastoma. Among 22 routine blood indicators, 10 low‑correlation indicators were identified, 9 of which demonstrated significant value for the diagnosis of glioma. Among them, the neutrophil percentage (NEUT%) showed a notable predictive power in glioma molecular subtypes classification. In the study of overall survival (OS) prediction in patients with glioma, 6 biomarkers were found to be significantly associated with OS. Through statistical analysis, 4 independent biomarkers were selected to construct a multivariable Cox regression model. However, in the regression model, NEUT% was identified as the sole statistically significant biomarker. Despite its statistical significance, the results indicated that NEUT% had limited effectiveness in predicting OS in patients with glioma. Certain preoperative blood indicators had significant predictive value for glioma diagnosis, with NEUT% emerging as a key biomarker for predicting the presence of glioma. For prognosis, although NEUT% showed a modest effect size, it was significantly associated with poor outcomes in patients with glioma. Monitoring preoperative NEUT% levels is therefore clinically important for glioma diagnosis and prognosis.
View Figures

Figure 1

Correlations between preoperative
peripheral blood routine indicators. (A) Spearman correlation
coefficients for all 22 biomarkers from preoperative peripheral
blood routine tests. (B) Spearman correlation coefficients among 10
biomarkers after preliminary exclusion. A correlation coefficient
of |r|<0.35 was used as the screening criterion. (C)
Distribution of HCT across healthy controls, astrocytoma,
oligodendroglioma and glioblastoma. Distribution of (D) WBC, (E)
MONO, (F) RDW-CV, (G) MCH, (H) BASO#, (I) EOS#, (J) PLT, (K) NEUT%
and (L) PDW across the four groups. *P<0.05, **P<0.01,
***P<0.001 and ****P<0.0001. MCHC, mean corpuscular
hemoglobin concentration; HCT, hematocrit; HGB, hemoglobin; MONO#,
monocyte count; WBC, white blood cell count; MONO%, monocyte
percentage; RBC, red blood cell count; RDW-CV, red cell
distribution width-coefficient of variation; LYMPH%, lymphocyte
percentage; LYMPH#, lymphocyte count; MCV, mean corpuscular volume;
MCH, mean corpuscular hemoglobin; MPV, mean platelet volume; BASO%,
basophil percentage; BASO#, basophil count; EOS#, eosinophil count;
EOS%, eosinophil percentage; PLT, platelet count; PDW, platelet
distribution width; PCT, plateletcrit; NEUT%, neutrophil
percentage; NEUT#, neutrophil count.

Figure 2

Results of binary logistic regression
between different groups with preoperative blood routine
indicators. (A) Forest plot of binary logistic regression comparing
the effects of biomarkers in classification of healthy control
group vs. glioma group. (B) ROC curve analysis for the
classification model in A. (C) Forest plot of binary logistic
regression comparing the effects of biomarkers in the
classification of LGG vs. HGG. (D) ROC curve analysis for the
classification model in C. ROC, receiver operating characteristic;
LGG, low-grade glioma; HGG, high-grade glioma; OR, odds ratio; CI,
confidence interval; AUC, area under curve; HCT, hematocrit; WBC,
white blood cell count; MONO%, monocyte percentage; RDW-CV, red
cell distribution width-coefficient of variation; MCH, mean
corpuscular hemoglobin; BASO#, basophil count; PLT, platelet count;
PDW, platelet distribution width; NEUT%, neutrophil percentage.

Figure 3

Kaplan-Meier survival curves for
different biomarkers in the glioma group. Survival curves were
stratified by baseline (A) LYMPH%, (B) LYMPH#, (C) MONO%, (D) PCT,
(E) NEUT% and (F) NEUT# levels. The curves compared overall
survival probabilities between low- and high-level groups defined
by biomarker thresholds. LYMPH%, lymphocyte percentage; LYMPH#,
lymphocyte count; MONO%, monocyte percentage; PCT, plateletcrit;
NEUT%, neutrophil percentage; NEUT#, neutrophil count.

Figure 4

Evaluation of the multivariable Cox
regression model. (A) The Schoenfeld residual tests for the Cox
hazards model. The solid lines represented smoothing spline fits to
the plot with the dashed lines representing the 95% CI around the
fit. (B) 3-yearpp calibration curve for the multivariable Cox
regression model. CI, confidence interval; MONO%, monocyte
percentage; LYMPH#, lymphocyte count; PCT, plateletcrit; NEUT%,
neutrophil percentage.
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Copy and paste a formatted citation
Spandidos Publications style
Yang Q, Ni J, Zhu J, Fan X, Cheng X, Yu Y, Shi Z, Wang Y and You Y: Preoperative peripheral blood routine indicators as predictors of prognosis and diagnosis in glioma under the 2021 World Health Organization classification. Oncol Lett 30: 543, 2025.
APA
Yang, Q., Ni, J., Zhu, J., Fan, X., Cheng, X., Yu, Y. ... You, Y. (2025). Preoperative peripheral blood routine indicators as predictors of prognosis and diagnosis in glioma under the 2021 World Health Organization classification. Oncology Letters, 30, 543. https://doi.org/10.3892/ol.2025.15289
MLA
Yang, Q., Ni, J., Zhu, J., Fan, X., Cheng, X., Yu, Y., Shi, Z., Wang, Y., You, Y."Preoperative peripheral blood routine indicators as predictors of prognosis and diagnosis in glioma under the 2021 World Health Organization classification". Oncology Letters 30.6 (2025): 543.
Chicago
Yang, Q., Ni, J., Zhu, J., Fan, X., Cheng, X., Yu, Y., Shi, Z., Wang, Y., You, Y."Preoperative peripheral blood routine indicators as predictors of prognosis and diagnosis in glioma under the 2021 World Health Organization classification". Oncology Letters 30, no. 6 (2025): 543. https://doi.org/10.3892/ol.2025.15289
Copy and paste a formatted citation
x
Spandidos Publications style
Yang Q, Ni J, Zhu J, Fan X, Cheng X, Yu Y, Shi Z, Wang Y and You Y: Preoperative peripheral blood routine indicators as predictors of prognosis and diagnosis in glioma under the 2021 World Health Organization classification. Oncol Lett 30: 543, 2025.
APA
Yang, Q., Ni, J., Zhu, J., Fan, X., Cheng, X., Yu, Y. ... You, Y. (2025). Preoperative peripheral blood routine indicators as predictors of prognosis and diagnosis in glioma under the 2021 World Health Organization classification. Oncology Letters, 30, 543. https://doi.org/10.3892/ol.2025.15289
MLA
Yang, Q., Ni, J., Zhu, J., Fan, X., Cheng, X., Yu, Y., Shi, Z., Wang, Y., You, Y."Preoperative peripheral blood routine indicators as predictors of prognosis and diagnosis in glioma under the 2021 World Health Organization classification". Oncology Letters 30.6 (2025): 543.
Chicago
Yang, Q., Ni, J., Zhu, J., Fan, X., Cheng, X., Yu, Y., Shi, Z., Wang, Y., You, Y."Preoperative peripheral blood routine indicators as predictors of prognosis and diagnosis in glioma under the 2021 World Health Organization classification". Oncology Letters 30, no. 6 (2025): 543. https://doi.org/10.3892/ol.2025.15289
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