Liver biopsy is an approved procedure that is indicated to establish a diagnosis, assess the prognosis, and monitor therapy protocols [11]. Although the associated complications are infrequent, finding new alternative non-invasive methods for the evaluation of liver disease is of great interest [12]. In the current work, the majority of the studied 200 children with chronic liver disease had mild, moderate, and severe disease activity that were 81%, 4%, and 3%, respectively, while minimal, moderate, and severe fibrosis were 41%, 19%, and 18%, respectively. This comes in consistent with Behairy et al., who found that most of the studied HCV patients had minimal disease activity (80%) and no/mild fibrosis (72%); on the other hand, they found that the majority of the AIH group had mild to moderate activity (70%) and moderate to severe fibrosis (95%) and all Wilson disease group had mild to moderate activity (100%) and moderate to severe fibrosis (100%) [13] and Pokorska-Spiewak et al., who reported that most of the cases showed minimal to mild fibrosis [5]. However, Dhole et al. confirmed that advanced fibrosis appeared in 23% of cases [14]. Fibrosis staging in chronic liver disease is crucial in determining the prognosis, selecting patients fit for anti-fibrotic treatment, and monitoring treatment outcomes [15].
The median of the non-invasive biomarkers was APRI 0.6, FIB-4 index 0.01, M-APRI 0.16, M-FIB-4 0.001, and B-AST 15.65. There were significant positive correlations between all of them and fibrosis score and HAI (P < 0.05 each), with a consistent increase in fibrosis score with the increase in mean ± SD of the studied five non-invasive biomarkers. This comes in line with Abd El-Ghaffar et al., who reported a highly significant positive correlation between APRI score and stage of fibrosis as assessed by the METAVIR scoring system (r = 0.53 and P-value = 0.000). APRI score mean in patients was 0.71 ± 0.48 and increased from 0.3 ± 0.45 in fibrosis stage <2 to 0.71 ± 0.96 in fibrosis stage >2 [16]. Also, de Ledinghen et al. studied APRI in comparison to Fibrosure and Fibroscan and found that APRI correlated with stages of fibrosis (rb = 0.32, P = 0.03) [17].
The aspartate aminotransferase (AST) to platelet ratio index (APRI) is a simple biomarker that was developed based on the progression of liver pathology and includes standard-of-care tests that may reflect hepatocellular damage and early development of portal hypertension [10].
Furthermore, Leung et al. found that APRI performed better than FIB-4 in predicting fibrosis studied in children with cystic fibrosis liver disease. APRI may hold great promise for earlier detection of fibrosis or clinically silent liver disease in order to decrease further complications [18]. Similarly, Pokorska-Spiewak et al. found the mean ± SD of the five biomarkers were APRI score 0.48 ± 0.26, FIB-4 0.22 ± 0.13, M-APRI 0.28 ± 0.69, M-FIB-4 0.09 ± 0.28, and B-AST 31.71 ± 69.87 and confirmed a significant positive association between the fibrosis stages and M-APRI and B-AST scores with a trend toward such an association with APRI and M-FIB-4 [5].
Elhenawy et al. stated that APRI and FIB-4 were significantly correlated with fibrosis in BA (P = 0.007) and were significantly higher in those with advanced fibrosis (Russo F4 and F5; P = 0.007), and they stated that these non-invasive serological markers, which are derived from simple routine laboratory tests, may be of help in predicting advanced fibrosis and in long-term follow-up of infants with BA and minimize the need for repeated follow-up liver biopsies [19]. Many studies had reported a positive correlation between APRI score and degree of liver fibrosis [14, 17, 20].
Values of fibrosis biomarker models increase with the progression of fibrosis stages because they are dependent on ALT, AST, and platelet count, with ALT and AST increase and platelet count decrease with increasing of fibrosis. Various factors induce decreased platelet count such as secondary to decreased thrombopoietin production by hepatocytes and/or sequestration and destruction of platelets in the spleen when liver fibrosis advances and portal hypertension develops with age. However, with ongoing liver injury, AST release from mitochondria is increased and hepatic fibrosis decreases its clearance [21].
While assessing the performance of studied non-invasive biomarkers, we found that the best cutoff for APRI in the detection of early fibrosis (F1–F2) was >0.96 with an AUC of 0.745, while in advanced liver fibrosis (F3–F4), it was >1.96, with AUC 0.849. This comes in accordance with Kim et al. who reported that APRI AUROC for F ≥ 3 and F = 4 were 0.92 and 0.91, respectively. Distinct optimal cutoff values of APRI for F ≥ 3 and F = 4 were obtained (1.01 and 1.41, respectively) [20]. Also, de Ledinghen et al. found an AUC of 0.73 for predicting cirrhosis in children with various chronic liver diseases [17]. In addition, Grieve et al. using a cutoff value of 1.22 [AUC 0.83] showed a sensitivity of 75% and a specificity of 84% for macroscopic cirrhosis [22], and McGoogan et al. found that the APRI was moderately useful in predicting significant fibrosis where it could be a substitute for liver biopsy with AUC of 0.71 [23].
Moreover, in a meta-analysis that included 40 studies, it was shown that APRI score > 1.0 had 76% sensitivity and 72% specificity for predicting cirrhosis. Additionally, APRI scores > 0.7 had a 77% sensitivity and 72% specificity for predicting significant hepatic fibrosis [24].
Regarding the performance of FIB-4, the cutoff point to detect early fibrosis (F1–F2) was > 0.019 with AUC 0.750, and to detect advanced fibrosis (F3–F4), it was > 0.045 with AUC 0.853. These results agree with Elhenawy et al. reports which showed the AUC of FIB-4 was 0.0098 with AUR 0.644, 61.9% sensitivity, and 61.9% specificity to discriminating advanced fibrosis [19]. More evidences came from Pokorska-Spiewak et al. study, where FIB-4 at cutoff point 0.18, with AUR 0.708, 85.7% sensitivity, and 93.7% NPV, helped in detecting any stage of fibrosis; the cutoff point was 0.09 with AUC 0.586 [5]. On the other hand, Chen et al. reported that FIB-4 failed to correlate with the fibrosis stage. This may be due to the small number of patients in Chen’s study (n = 24) [25].
In our study, during the assessment of the performance of BMI z-score modified models, we found M-APRI, M-FIB-4, and B-AST at cutoff points >0.16, >0.005, and >−8, respectively with corresponding AUC 0.831, 0.759, and 0.758, could detect early fibrosis (F1–F2), while in detecting advanced fibrosis (F3–F4), the cutoff points of M-APRI, M-FIB-4, and B-AST were >2.2, >0.015, and >92.1 with AUC 0.958, 0.896, and 0.955, respectively.
These results were in agreement with Pokorska-Spiewak et al., who reported the cutoff values of M-APRI, M-FIB-4, and B-AST in the detection of any stage of fibrosis were 0.08, 0.36, and 0.56 with corresponding AUC 0.597, 0.568, and 0.614, respectively, while those for detection of moderate to severe fibrosis were 0.577, 0.179, and 92.82 with corresponding AUC 0.842, 0.823, and 0.848, respectively [5]. Also, Pokorska-Spiewak et al. suggest that liver fibrosis in children with CHC is positively associated with the BMI z-score. In both univariate and multivariate analyses, the BMI z-score was found to be an independent predictor of fibrosis among 42 pediatric patients with CHC (P = 0.03) [12].
We had found that the BMI z-scores of modified non-invasive biomarker models (M-APRI, M-FIB-4, and B-AST) had better diagnostic values in detecting early fibrosis (F1–F2) with AUC exceeded 0.7. Therefore, we supported the idea of incorporating the BMI z-score in the well-established APRI and FIB-4 non-invasive biomarker formulas to improve their performance in predicting advanced fibrosis. In addition, we confirmed the B-AST as a new non-invasive simple biomarker that can easily detect liver fibrosis using very simple parameters.
