Clinical Characteristics
There were 354 HGGs patients included in this retrospective study according to the inclusion and exclusion criteria. Table 1 summarized detailed demographic information of the research subjects. Overall, 59 (16.7%) were G3 and 295 (93.3%) were G4 of the 354 patients, respectively. All clinical features were not statistically significant (p>0.05) except for IDH (p<0.001), age (p<0.001) and FIB (p=0.034). IDH mutations tended to occur in G3 and the elderly population was more susceptible to GBM. Moreover, the level of FIB was higher in G4 compared with G3. There were 27 (45.8%) women and 32 (54.2%) men in G3 and 128 (43.4%) women and 167 (56.6%) men in G4. The existence of preoperative epilepsy (ex-pEPI) and pKPS≤70 were 13 (22.0%) and 30 (50.8%) in G3 vs 46 (15.6%) and 147 (49.8%) in G4. The mean±SD of age, PLR, NLR, LMR, FIB, ALB, GLOB, AGR, PNI were 45.24±13.36 (range 4-77), 138.26±79.69, 2.79±2.24, 0.28±0.10, 2.84±0.65, 42.14±2.66, 23.68±3.82, 1.83±0.33, 51.82±4.90 and 53.76±13.32 (range 9-78), 137.18±66.27, 3.46±2.98, 0.30±0.16, 3.08±0.83, 42.14±3.66, 24.49±4.14, 1.77±0.35, 50.85±4.78 in G3 and G4, respectively.
The Levels of Hematological Indicators were Different Among IDH Molecular Subtypes
To further understand the differences in the hematological indicators of IDH molecular subtypes, we divided patients into IDH wild type (IDH-wt) and IDH mutant type (IDH-mut) according to the IDH mutation status in the study. Compared with IDH-mut, the levels of NLR (t=2.315, p=0.035) and FIB (t=3.533, p<0.001) were both increased in IDH-wt (Fig. 1a, b; Supplementary Table S1). Furthermore, we further classified patients into four subgroups based on their IDH mutation status, including G3 IDH mutant type (G3 IDH-mut), G3 IDH wild type (G3 IDH-wt), G4 IDH mutant type (G4 IDH-mut), and G4 IDH wild type (G4 IDH-wt). The results showed that only FIB was statistically significant (F=4.160, p=0.006, Fig. 1c), and further analysis showed that the levels of FIB were increased in G4 IDH-wt, compared with G3 IDH-mut (p=0.003) and G4 IDH-mut (p=0.040) (Supplementary Table S2).
The Association of Hematological Indicators With Age, Gender, pEPI, and pKPS in G3 and G4
The results showed that ALB, AGR, PNI related to nutrition were negatively correlated with HGGs. Among them, ALB (p<0.000), AGR (p<0.000), and PNI (p=0.002) were statistically significant in G4 (SupplementaryFig.S1f-h), and only PNI (p<0.000) was statistically significant in G3 (SupplementaryFig.S1d). However, the coagulation-related FIB was positively correlated with G3 (p=0.430) and G4 (p=0.003) (SupplementaryFig.S1a, e). Moreover, the inflammation-related PLR, NLR, and MLR were positively correlated with G3 but negatively correlated with G4, and they were not statistically significant (all p>0.05, SupplementaryTable S3 and Table S4).
Increased GLOB levels (25.54±3.84 vs 23.69±4.19, p<0.000) and decreased AGR levels (1.69±0.28 vs 1.83±0.38, p<0.000) were found in women, compared with men in G4 (SupplementaryTable S4). It was worth noting that there had no significant difference in hematology indexes between pEPI and pKPS subgroups (all p>0.05, SupplementaryTable S3 and Table S4).
Evaluation of Diagnostic Efficacy of Hematological Indicators in Predicting Grade and IDH Molecular Subtypes of HGGs
To find out the diagnostic value of hematology indexes in distinguishing GBM and G4 IDH-wt from HGGs, the ROC curve was performed with single indexes and combined indexes, respectively. Firstly, a single indicator was used to predict GBM and G4 IDH-wt, and the FIB had the best diagnostic value in identifying GBM from HGGs [0.595 (0.519-0.672), p=0.021] (Fig.2a) and distinguishing G4 IDH-wt from other molecular subtypes [0.615 (0.546-0.684), p=0.002] (Fig.3a). Secondly, we combined the indicators for the ROC analysis, and the results showed that age+FIB, NLR+FIB, MLR+FIB, and FIB+PNI had the highest diagnostic value among the corresponding combinations (Fig.2b,3b;2d-f,3d-f). Whether for GBM [0.712 (0.642-0.783), p=0.000] (Fig.2b) or G4 IDH-wt [0.726 (0.662-0.791), p=0.000] (Fig.3b), age+FIB was the best diagnostic index among all the combinations (Table 2). In addition, for the PLR combination group, PLR+FIB had a better diagnostic value for G4 IDH-wt [0.614 (0.545-0.683), p=0.002] (Fig.2c), but PLR+NLR had a higher diagnostic value for G4 [0.610 (0.530-0.689), p=0.008] (Fig.3c).