From NAFLD to Chronic Liver Diseases. Assessment of Liver Fibrosis through Non-Invasive Methods before Liver Transplantation: Can We Rely on Them?
Abstract
:1. Introduction
- Blood-based biomarkers score,
- Elastrography,
- Combined methods.
2. A Blood-Based Biomarkers Score
- Fibrosis score 4 (FIB-4). Sterling et al. [32] developed a score using age, ALT, AST, and platelet count to estimate the amount of scarring in the liver. Based on a retrospective analysis, liver histology was performed in 832 HIV/HCV-coinfected patients. Liver fibrosis was assessed via the Ishak score, and multivariate logistic regression analysis revealed that platelet count (PLT), age, AST, and INR were significantly associated with fibrosis. After an additional analysis without INR, an alternative model with PLT, age, AST, and ALT was developed. According to these data, (FIB-4) was designed: age ([yr] AST [U/L])/((PLT [109/L]) (ALT [U/L])1/2). The AUROC of the index was 0.765 for differentiation between Ishak stages 0–3 and 4–6. At a cutoff of <1.45 in the validation set, the negative predictive value to exclude advanced fibrosis (stage 4–6) was 90%, with a sensitivity of 70%. A cutoff of >3.25 had a positive predictive value of 65% and a specificity of 97%. Using these cutoffs, 87% of the 198 patients with FIB-4 values outside 1.45–3.25 would be correctly classified, and liver biopsy could be avoided in 71% of the validation group. The authors argued that these individuals could potentially have avoided liver biopsy, with an overall accuracy of 86%.
- Ast–Platelet Ratio Index (APRI). Using a retrospective cohort study involving 270 patients with chronic hepatitis C, Chun-Tao Wai et al. [33] developed a score with only AST and platelets as the variables. Those patients underwent a liver biopsy over 25 months and were divided into a training set (n192) and a validation set (n78). To amplify the opposing effects of liver fibrosis on AST and platelet count, the AUCs of APRIs for predicting significant fibrosis and cirrhosis were 0.80 and 0.89, respectively, in the training set. Using optimized cut-off values, significant fibrosis could be predicted accurately in 51%, and cirrhosis in 81% of patients. The AUCs of APRI for predicting significant fibrosis and cirrhosis in the validation set were 0.88 and 0.94, respectively. A meta-analysis of 40 studies showed that an APRI score of greater than 1.0 provides a sensitivity of 76% and a specificity of 72% for predicting cirrhosis; meanwhile, an APRI score of greater than 0.7 reaches a sensitivity of 77% and a specificity of 72% for predicting fibrosis [34]. Meta-regression analysis indicated that the APRI accuracies for both significant fibrosis and cirrhosis were affected by histological classification systems, but they were not influenced by the interval between biopsy and APRI, or blind biopsy.
- NFS. For this score, Angulo et al. [35] used age, hyperglycemia, body mass index, platelet count, albumin, and the AST/ALT ratio as independent indicators of advanced liver fibrosis. A total of 733 patients with NAFLD confirmed via liver biopsy were divided into two groups to construct (n = 480) and validate (n = 253) the scoring system. The formula results are more greatly articulated compared to others’ scores: 1.675 1 0.037 age (y) 1 0.094 BMI (kg/m2) 1 1.13 IFG/diabetes (yes 5 1, no 5 0) 1 0.99 AST/ALT ratio–0.013 platelet (109/L)–0.66 albumin (g/dL). A scoring system with these six variables had an AUROC curve of 0.88 and 0.82 in the estimation and validation groups, respectively. By applying the low cutoff score (1.455), advanced fibrosis could be excluded with high accuracy (negative predictive values of 93% and 88% in the estimation and validation groups, respectively). By applying the high cutoff score (0.676), the presence of advanced fibrosis could be diagnosed with high accuracy (positive predictive values of 90% and 82% in the estimation and validation groups, respectively). By applying this model, a liver biopsy would have been avoided in 549 (75%) of the 733 patients, with correct prediction in 496 (90%). Despite the enrollments of many patients, these were included from different centers in the world that have a particular interest in studying NAFLD, and thus, some referral bias could not be ruled out.
- Enhanced Liver Fibrosis Score (ELF). Developed by the European Liver Fibrosis Group, the Enhanced Liver Fibrosis (ELF) score provides a single value using an algorithm combining the quantitative serum measurements of tissue inhibitor of metalloproteinases-1 (TIMP-1), amino-terminal propeptide of type III procollagen (PIIINP), and hyaluronic acid (HA). To calculate the ELF score, the following equation was originally designed: ELF score = 2.494 + 0.846 ln (CHA) + 0.735 ln (CPIIINP) + 0.391 ln (CTIMP-1). After a validation study on a cohort of NAFLD patients, the test accuracy was not reduced by excluding age as a parameter in the algorithm [40]. The results obtained through this validation cohort showed excellent performance in distinguishing advanced fibrosis in patients with NAFLD, with an AUROC of 0.90. Anyway, the test performance resulted in less accuracy in patients with chronic hepatitis C, because of parameters such as age and gender [41]. The same problem has been shown for the evaluation of chronic hepatitis B, with an AUROC of 0.67 [42]. Regarding the specifics, biomarkers are necessary to point out the roles of TIMP-1, PIIINP, and HA in the development of liver fibrosis: tissue inhibitor of metalloproteinases 1 (TIMP-1) drives the remodeling process in the liver via matrix metalloproteases (MMPs) [43]; meanwhile, serum PIIINP and HA were positively correlated with early liver fibrosis stage (r = 0.622, p < 0.001, and r = 0.41, p < 0.001, respectively). Through a receiver operating curve (ROC) analysis, it has been shown that serum PIIINP was the most effective for the diagnosis of fibrosis grade among the other markers used for this score. The areas under the ROC curves (AUROCs) for serum PIIINP for diagnosing fibrosis stages ≥F1, ≥F2, ≥F3, and F4 (cirrhosis) were 0.843, 0.789, 0.82, and 0.891, respectively. The cut-off serum PIIINP value for predicting fibrosis stage ≥F1 was 242.3 ng/mL, with 73.8% sensitivity and 90% specificity. The cut-off value for predicting cirrhosis was 698.7 ng/mL, with 75% sensitivity and 96% specificity [44]. The NICE guidelines suggested ELF as “the most cost-effective and the most appropriate test for advanced fibrosis in adults with NAFLD”. However, a recent meta-analysis evaluated the role of ELF, considering 14 different studies in NAFLD patients, with liver biopsy being used as a reference standard, showing that ELF has a high sensitivity but a limited specificity to exclude fibrosis, especially in cases of low disease prevalence [45].
- Hepascore. This score consists of a correlation between non-specific (age, sex, total bilirubin, and GGT) and specific markers of fibrosis, such as alpha-2-macroglobulin and hyaluronic acid levels [46]. Adam et al. designed this complex equation in two steps: Y = EXP (−4.185818 − (0.0249 × age) + (0.7464 × sex) + (1.0039 × A2M) + (0.0302 × HA) + (0.0691 × Bil-t) − (0.0012 × GGT). After obtaining Y, the simplified Hepascore formula results in Y = Y/(1 + Y). At values that are less than or equal to 0.2, the negative predictive value to exclude fibrosis is 98%. At values that are greater than or equal to 0.8, the positive predictive value for predicting cirrhosis is 62%. Therefore, this score offers a good negative predictive value and could be reliable for excluding significant fibrosis, but it is not so effective in predicting cirrhosis: more parameters for such a prediction are mandatory. Hepascore could predict significant fibrosis (F2–4), as proven by the AUROC in validation sets (0.81). A cutoff score of >0.55 was best for predicting significant fibrosis, with sensitivities and specificities of 82% and 65%, respectively, and positive and negative predictive values of 70% and 78%. Up-to-date studies with a high level of evidence, evaluating the role of Hepascore in predicting fibrosis in the specific setting of the NAFLD population, are still lacking.
- Fibrospect II. FIBROSpect II is a predictive algorithm for fibrosis stages F2 to F4, which combines hyaluronic acid, tissue inhibitor of a metalloproteinase-1 (TIMP-1), and alpha-2-macroglobulin. As has been already seen for other scores describing F2–F4 fibrosis, specific markers such as hyaluronic acid (HA), TIMP-1, and alpha2-macroglobulin (A2M) could offer predictive accuracy, achieving an AUROC of 0.831. At an index cut-off of 0.36 and a prevalence for F2–F4 of 52%, the results in all 696 patients indicated positive and negative predictive values of 74.3 and 75.8%, respectively, with an accuracy of 75%, and the reliability of this score is mostly focused on moderate–severe fibrosis. An index score of greater than 0.42 correlates with the presence of stages F2 to F4 fibrosis. Based on data from the test manufacturer involving 696 persons with chronic HCV infection, the overall sensitivity at this cutoff is 80.6%, and the specificity is 71.4% [47]. Fibrospect carries the same issues appearing with the previously described scores: good results in terms of excluding the presence of liver fibrosis, but a poor ability to describe its progression [48]. A recent study validated TIMP-1, A2M, and HA in NAFLD patients, showing a great ability to predict mild to advanced fibrosis (a ROC curve of 0.856, a sensitivity of 79.7%/specificity of 75.7%), which is superior compared to FIB-4 and NFS [49].
- ADAPT score: A marker of type III collagen formation has been recently associated with fibrosis development in patients with chronic hepatitis C: the so-called PRO-C3. Daniels et al. recently evaluated its role in NAFLD patients, validating the ADAPT score. The PRO-C3 was measured with an enzyme-linked immunosorbent assay (ELISA) in a total of 431 patients with biopsy-proven NAFLD: 150 patients in the derivation and 281 in the validation cohort. The first result was that PRO-C3 is also strongly related to fibrosis in NAFLD patients. In the derivation cohort, patients with advanced fibrosis (F ≥ 3) had a high level of PRO-C3 compared to the mild/moderate group (p < 0.0001). In addition, PRO-C3 is associated with the severity of the disease and the stage of fibrosis, with an additional ability to correlate with hepatocyte ballooning, lobular inflammation, and steatosis. The ADAPT score, considering age, the presence of diabetes, PRO-C3 (a marker of type III collagen formation), and platelet count, was then created, with an AUROC of 0.86 (95% CI 0.79 to 0.91) in the derivation and 0.87 in the validation cohort (95% CI 0.83 to 0.91) for advanced fibrosis. Furthermore, the authors showed the superiority of the ADAPT score compared to APRI, FIB-,4, and the NAFLD fibrosis score (NFS) to predict fibrosis in NAFLD patients [50]. Recently, Tang et al. evaluated the ADAPT score in an Asian cohort, including 851 biopsy-proven MAFLD patients. The ADAPT score showed an AUROC of 0.865, with a better ability to predict fibrosis compared to PRO-C3 alone or other non-invasive fibrosis tests (APRI score, Fibrosis-4, BARD, and NAFLD fibrosis score) [51].
3. Elastography
4. Combined Methods
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variables | Formula | Cutoffs in NAFLD | ||
---|---|---|---|---|
Low Risk | High Risk | |||
FIB4 | Platelet count, age, AST, ALT | AQR X AST)/(Platelets × (sgr(ALI)) | <1.30 (NPV = 90%) | 11.30–3.25 > 2.67 (PPV = 80%) |
APRI | AST, platelet count | I (AST/ULN AST) × 1001/platelets (10/L) | <1.0 (NPV = 84%) | >1.0 (PPV = 37%) |
NFS | Age, BMI, hyperglycemia, platelet count, albumin, AST/ALT ratio | −1.675 + 0.037 × age (y) + 0.094 × BMI (kg/m2) + 1.13 × IFG/ diabetes (yes 1, no = 0) + 0.99 × AST/ALT ratio − 0.013 platelet × 10°/L) − 0.66 × albumin (g/dL) | <−1.455 (NPV = 88%) | −1.455–0.675 >0.675 (PPV = 82%) |
Variables | Formula | Accuracy in Fibrosis | ||
---|---|---|---|---|
F1–F2 | F3–F4 | |||
ELF | TIMP-1, PIIINP, HA | 2.494 + 0.846 ln (CHA)+ 0.735 ln (CPIIINP) + 0.391 ln (CTIMP-1) | Cutoff PIIINP = 242.3 ng/mL Sensitivity 73.8% Specificity 90% | Cutoff PIIINP = 698.7 ng/mL Sensitivity 75% Specificity 96% |
Hepascore | Age, sex, total bilirubin, GGT, alpha-2-macroglobulin, HA | Y = EXP(−4.185818–(0.0249 × age) + (0.7464 × sex) + (1.0039 × A2M) + (0.0302 × HA) + (0.0691 × Bil-t) − (0.0012 × GGT) | Cutoff > 0.55 Sensitivity 82% Specificity 65% | |
Fibrospect II | HA, TIMP-1, alpha-2-macroglobulin | Patented Formula | Sensitivity 71.8% Specificity 73.9% | |
ADAPT | Age, DM2, platelet count PRO-C3 | exp(log10((age × PROC3)/√platelet count)) | Sensitivity 81% Specificity 73% |
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Auricchio, P.; Finotti, M. From NAFLD to Chronic Liver Diseases. Assessment of Liver Fibrosis through Non-Invasive Methods before Liver Transplantation: Can We Rely on Them? Transplantology 2023, 4, 71-84. https://doi.org/10.3390/transplantology4020008
Auricchio P, Finotti M. From NAFLD to Chronic Liver Diseases. Assessment of Liver Fibrosis through Non-Invasive Methods before Liver Transplantation: Can We Rely on Them? Transplantology. 2023; 4(2):71-84. https://doi.org/10.3390/transplantology4020008
Chicago/Turabian StyleAuricchio, Pasquale, and Michele Finotti. 2023. "From NAFLD to Chronic Liver Diseases. Assessment of Liver Fibrosis through Non-Invasive Methods before Liver Transplantation: Can We Rely on Them?" Transplantology 4, no. 2: 71-84. https://doi.org/10.3390/transplantology4020008