Year : 2006 | Volume
: 12 | Issue : 3 | Page : 135--138
Laboratory predictors of advanced fibrosis in Saudi patients with chronic hepatitis B and C
Ayman A Abdo
Department of Medicine, College of Medicine, King Saud University, Riyadh, Saudi Arabia
Ayman A Abdo
P.O. Box 2925(59), College of Medicine, King Saud University, Riyadh 11461
Objective: To identify laboratory predictors of advanced fibrosis in Saudi Arabian patients with hepatitis B and C. Materials and Methods: Histopathology reports were obtained on all patients who had liver biopsy in the last 5 years, and relevant laboratory data were collected. Results: A total of 328 patients (246 with hepatitis C and 82 with hepatitis B) were included. With logistic regression analysis, four factors were found to be the best predictors of fibrosis, namely, platelet count, ALT, AST and GGT levels. An equation for calculating the risk of advanced fibrosis was developed. The model had a sensitivity of 62%, a specificity of 92.4% and an overall accuracy of 84%. Conclusion: Platelet count, ALT, AST and GGT levels were found to be the best predictors of advanced fibrosis on liver biopsy in Saudi patients with chronic hepatitis B and C. An equation was developed that helps in calculating this risk.
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Abdo AA. Laboratory predictors of advanced fibrosis in Saudi patients with chronic hepatitis B and C.Saudi J Gastroenterol 2006;12:135-138
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Abdo AA. Laboratory predictors of advanced fibrosis in Saudi patients with chronic hepatitis B and C. Saudi J Gastroenterol [serial online] 2006 [cited 2021 Oct 27 ];12:135-138
Available from: https://www.saudijgastro.com/text.asp?2006/12/3/135/29754
Liver biopsy is currently the gold standard in assessing liver histology. One of the most important information obtained by a liver biopsy in patients with chronic viral hepatitis B and C is the stage of fibrosis. This has an important prognostic value on which the decision to treat the patient with antiviral therapy is currently based.
Because liver biopsy is costly, is associated with rare but significant risk and is not accepted by some patients, many research groups have been searching for alternatives that enable the clinician to predict the presence or absence of advanced fibrosis without requiring a liver biopsy., These fibrosis-predicting parameters may be clinical (history and physical examination), laboratory or radiological. Of these, much attention has been directed recently to laboratory markers of advanced fibrosis, and many parameters such as platelet count, ALT, AST, AST/ALT ratio have been validated.,
In this study, we review all liver biopsies performed for patients with viral hepatitis B and C in our unit at a large university hospital in Riyadh, Saudi Arabia, in an attempt to find laboratory predictors of advanced fibrosis (defined as more than stage 2 fibrosis on the METAVIR liver histology staging system). Our hospital is a tertiary care teaching hospital where around 80 liver biopsies are performed per year.
Materials and Methods
Liver biopsy procedures performed in our gastroenterology unit at King Khalid University Hospital were traced from records between the years 1998 and 2003. Histopathology reports were obtained on all patients. Histological assessment was performed by three experienced liver pathologists who were not blinded to the basic clinical data of the patients. The following histological parameters were collected: overall liver architecture, portal tract inflammation, interface hepatitis, cholestasis, bile duct injury, liver cell abnormalities, presence of steatosis, grade of inflammation and stage of fibrosis according to the METAVIR liver histology classification system. No advanced fibrosis was defined as stage 0, 1 or 2, while advanced fibrosis was defined as a fibrosis score of 3 or 4. We were unable to collect data regarding the size of the biopsy and the number of fragments obtained because of the retrospective nature of the study, but all reported biopsies were considered adequate by the reporting pathologist and all contained more than four portal tracts.
The hospital computer data base was then accessed and the following laboratory data were collected on each patient: WBC count, hemoglobin, mean corpuscular volume, platelet count, total bilirubin, albumin, alkaline phosphatase, alanine aminotransferase (ALT), aspertate aminotransferase (AST), glutamyl transpeptidase (GGT) and viral hepatitis serology.
The data were entered in the Excel computer software. SPSS software was used for the statistical analysis. The endpoint of this study was the presence of more than F2 (advanced fibrosis) on liver biopsy. All collected laboratory parameters were first included in a univariate analysis comparing patients with and without the study endpoint. All continuous variables were analyzed after logarithmic transformation for normality of distribution. Categorical variables were compared by X 2sub or Fisher exact test, while continuous variables were compared with the student's t test. Prediction equation of significant variables that could best predict the study endpoint was constructed by entering different sets of independent variables into a logistic regression model.
A total of 341 liver biopsies were identified. Of these, 13 were excluded from the analysis because of missing data. The clinical and histological baseline characteristics of the 328 remaining patients (246 with hepatitis C and 82 with hepatitis B) are shown in [Table 1][Table 2].
Hepatitis C patients' mean age was 45 years, and about 60% were males. The mean ALT was 112 U/L. Most patients had either grade 2 or 3 inflammation (78%), while only a minority had grade 1 or 4. On the other hand, the majority of patients had stage 1 (28%) and stage 2 (40%) fibrosis, while only about 26% had advanced fibrosis.
Hepatitis B patients' mean age was 34.9 years, and about 75% were males. The mean ALT was 99 U/L. Most patients had either grade 1 or 2 inflammation (73%). On the other hand, the majority of patients had stage 1 (47%) and stage 2 (23%) fibrosis, while only about 17% had advanced fibrosis [Table 1].
Univariate analysis found almost all laboratory parameters to be significantly different statistically between the patients with advanced fibrosis and the patients without [Table 3].
Results of the logistic regression model for patients with hepatitis C and B combined led to the development of the following risk score equation for advanced fibrosis:
Risk score = 10.99 - 3.28 In (platelet count) -1.29 In (ALT level) + 1.76 In (AST level) + 0.76 In (GGT level).
A risk score of more than or equal to 0.5 is associated with advanced fibrosis. When this equation was used [Table 4], the sensitivity of the model for detecting advanced fibrosis was found to be 62%, while the specificity was 92.4%, with positive and negative predictive values of 70.8 and 87.4% respectively. The overall accuracy of the model was 84.1%.
Liver biopsy continues to be an integral part in the diagnosis and management of many liver diseases. In patients with viral hepatitis, liver biopsy helps to exclude other forms of liver diseases, provides baseline histology for further reference and predicts responsiveness to antiviral therapy. More importantly, liver biopsy helps prognosticate the patient and hence make more reasonable decisions regarding their need for antiviral therapy, as the stage of fibrosis in the liver biopsy is one of the most important predictors of the possibility to develop advanced fibrosis with time. This has been particularly the case for hepatitis C, where effective therapy is now available, but has in addition appeared in recent hepatitis B guidelines as well, as more effective treatments for this virus are now being investigated.,
Because liver biopsy is costly and not without risk, many studies have been performed to evaluate the use of readily available laboratory tests to predict significant fibrosis or cirrhosis in patients with chronic hepatitis C., These tests have either been simple readily available laboratory tests, such as transaminases and platelet count,,, or more advanced not widely available serum markers of fibrosis.
We attempted to evaluate laboratory parameters in our local patients based on the fact that there are potential differences between our patients in Saudi Arabia and the patients on which these tests were originally validated. These factors include the difference in age at and mode of virus acquisition; different virus genotypes (especially in the case of hepatitis B); the lower frequency of alcohol consumption in Saudi population; as well as the prevalence of other noncirrhotic causes of portal hypertension in Saudi Arabia, especially schistosomiases, which might affect the platelet count.
In this study, we found that the platelet count, ALT, AST and GGT levels were the best predictors of advanced fibrosis. These findings are similar to what has been reported in the international literature. We were able to formulate a model from our data that would predict advanced fibrosis in these patients with an excellent specificity of 92% but poor sensitivity of 62% and an overall accuracy of almost 85%. When compared to other previously described models, we found that our model has a comparable accuracy. Practically speaking, since this model has an extremely high specificity for predicting advanced fibrosis, we feel that it could safely be used to diagnose advanced fibrosis and avoid a liver biopsy when the risk score is equal to or above 0.5, while it may not be very useful to rule out advanced fibrosis since the sensitivity is not as high.
We hope that this equation will be useful in clinical practice of hepatology in Saudi Arabia for the following reasons. First, this prediction formula was derived from the study of local patients seen in a tertiary care center in Saudi Arabia with their represented epidemiological, racial, virological and other factors that are important in determining fibrosis progression. Although these patients may not represent the overall pool of viral hepatitis patients in the community, it is an excellent representation of the majority of patients receiving medical care for chronic viral hepatitis in Saudi Arabia. Second, since chronic viral hepatitis is a significant medical problem in Saudi Arabia and antiviral therapy is expensive and not widely available, it is best tailored to patients who are most in need for it, viz., patients showing evidence of advanced fibrosis. Predictive models of advanced fibrosis such as ours will likely have a huge cost-saving impact when dealing with these patients.
We have found that platelet count, ALT, AST and GGT are good laboratory predictors of advanced fibrosis in local patients with chronic viral hepatitis B and C. An equation assessing fibrosis risk was developed based on these laboratory predictors, which could be used in predicting advanced fibrosis in these patients.
I would like to thank Dr. Shaffi Ahmed from the Department of Community Medicine at King Saud University, Riyadh, for his statistical advice.
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