الفهرس 
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Abstract
This retrospective study was carried out on 704 patients with chronic hepatitis C ( HCV-Ab positive and positive HCV RNA by PCR) who attended Hepatology Center at Benha Fever Hospital.
All patients included in this study were subjected to full history taking and thorough clinical examination, full laboratory investigations (including: complete blood count, platelet count, liver profile tests, exclusion of other causes of hepatitis e.g. HBsAg, HBcAb, autoimmune hepatitis, shistosomiasis, abdominal ultrasonography, percutaneous liver biopsy with histopathological grading and staging by METAVIR scoring system).
Scoring of the Bonacini score, AP index, Pohl score, AAR score, APRI score, GUCI score, Lok model, FI score, FIB-4 score, King score and FCI score were done for all patients, as fibrosis predictor scoring to diagnose liver fibrosis and the response to the treatment without adding additional cost to the treatment burden.
The mean age of the studied cases was 39.02 10.1 years. Males represented 66.5% with the mean BMI was 28.1 4.2.
In the present study:
- Hepatitis C virus infection was more common in male patients.
- Patients who achieved virological response were younger and had lower BMI than those who failed to achieve virological response but without significant difference.
- There was a statistically significant relation between the platelets count, the total bilirubin and EVR.
- There was a statistically significant difference between the serum albumin and PCR results at W24.
- There was no statistical significant relation between prothrombin time (PT) and virological response.
- There was a statistically significant difference between the stage of fibrosis and virological response.
- There was high statistical significant relation between FCI and the prediction of EVR at cutoff (0.121) with high sensitivity ,high specificity, high PPV and very good AUROC (77.7% ,71.9%, 96.9% and 0.82 respectively).
- There was high statistical significant relation between King’s score and the prediction of EVR at cutoff (11.2) with the highest specificity, high sensitivity, high PPV and good AUROC (73.7%,75.7%, 97% and 0.78 respectively).
- Bonacini score, AP index, AAR score, APRI score, GUCI score, FI score and FIB-4 score could predict EVR with AUC (0.66, 0.68, 0.62, 0.62, 0.62, 0.64 and 0.62 respectively) and 95% CI (0.58-0.74, 0.6-0.75, 0.54-0.69, 0.54-0.7, 0.54-0.69, 0.56-0.71 and 0.54-0.69 respectively).
- There was no statistical significant difference between Lok’s model, Pohl score and EVR prediction (p-value=0.53 & 0.203 respectively).
- There was statistical significant difference between patients with and without EVR regarding Bonacini score, AP index, AAR score, APRI score, GUCI score, FI score, King’s score, and FCI score ((p<0.001), (p<0.001), (p=0.017), (p=0.002), (p<0.001), (p=0.002), (p<0.001), (p<0.001) respectively).
- There was no statistical significant difference between Pohl score and PCR results at 24 th week (p=0.79).
- There was a statistically significant relation between ETR and stage of fibrosis, F3 was reported in 66.7% of patients with no ETR and F2 was reported in 71.5% of those with ETR.
- Bonacini score at cutoff (5.05) had the highest specificity, highest PPV, high sensitivity, good AUROC and low NPV as 75.4%, 96.5%, 75.8% , 0.79 & 25.9% respectively for prediction of ETR.
- AP index at cutoff (2.5) could predict ETR with high specificity , high PPV and fair AUC (70.2%, 94.5% and 0.68 respectively).
- AAR score at cutoff (0.91) had 67% sensitivity, 55.1% specificity, 60.1% PPV, 15.6% NPV and fair AUROC 0.63 for prediction of ETR.
- APRI score at cutoff (1.01) had 60.9% sensitivity, 45.6% specificity, 90.9% PPV, 11.6% NPP and fair AUROC 0.55 for prediction of ETR.
- GUCI score predicted ETR with sensitivity, specificity and AUROC were (64.2%, 61.4% & 0.62 respectively).
- Lok’s model couldn’t predict ETR at cutoff (-38.6) as its sensitivity, specificity, PPV, NPP and AUROC were (60.1%, 36.8%, 89.5%, 9.4% and 0.48 respectively).
- Fibrosis index (FI) was poor predictor for ETR as its sensitivity, specificity and AUC were (46.6%, 47.7% & 0.44 respectively).
- FIB-4 score was poor predictor for ETR as its sensitivity, specificity and AUC were (51.5%, 45.6% & 0.42 respectively).
- King’s score was poor predictor for ETR as its sensitivity, specificity and AUC were (48.3%, 40.4% & 0.42 respectively).
- FCI score couldn’t predict ETR at cutoff (0.095) as its sensitivity, specificity, PPV, NPP and AUROC were (51.5%, 40.4%, 88.5%, 8.5% and 0.49 respectively).
- There was no statistical significant difference between Pohl score and ETR (p=0.88).
- There was statistical significant difference between patients with and without ETR regarding Bonacini score, AP index, AAR score, APRI score, GUCI score, FI score, King’s score and FCI score ((p<0.001), (p<0.001), (p=0.01), (p=0.015), (p=0.03), (p=0.007), (p<0.001) and (p=0.013) respectively).