In this study, using liver biopsy as the gold standard, we developed a new, simple, and inexpensive noninvasive algorithm, to identify chronic hepatitis B patients with significant fibrosis or cirrhosis.
The objective of this study was to evaluate the usefulness of combining simple, non-invasive and inexpensive test that can be used in all countries, especially in resource-poor African countries for predicting liver severe fibrosis and cirrhosis. Figure 1 is an illustration of the algorithm. To simplify the use of the algorithm, an internet link or online calculator will be proposed.
For that we used a decision tree methodology. This method is a powerful statistical tool for classification, prediction, interpretation, Using decision tree models to describe research findings has the following advantages: simplifies complex relationships between input variables and target variables by dividing original input variables into significant subgroups. Indeed this method is easy : 1) to interpret non-parametric approach without distributional assumptions. 2) to handle missing values without needing to resort to imputation 3) to handle heavy skewed data without needing to resort to data transformation. Finally the method is robust to outliers. Decision tree methodology are several applications and has been developed when the endpoint is the prediction of survival. [10].
Several studies have investigated non-invasive methods for predicting fibrosis in chronic hepatitis B. TE has been the most tested method in the world and appears to be superior to blood tests in terms of diagnostic performance in predicting severe fibrosis or cirrhosis [11]. However, in many countries and even in many hospitals, liver biopsy is not feasible, nor is fibroscan.
Many blood tests have been developed to predict the existence of significant fibrosis, in particular the Fibrotest, the Fibrometer and the Hepascore. These scores are mainly validated for chronic hepatitis C. In addition, these tests are patented and therefore marketed at a significant cost. They cannot therefore be routinely prescribed in low-income countries. Inded these tests include biomarkers that are not routinely available, such as haptoglobin in Fibrotest [12–14] and α2-macroglobulin in Fibroscore [15] or Zeng score [16]. In a previous study we showed a slight superiority of the Fibrometer in predicting severe fibrosis[17], which was not found in all studies, while at the cirrhosis stage there was no difference between the scores tested [18]. Zeng et al [19] tested 7 different scores using simple biological variables and without the use of a patent to calculate the score, thus easy to use in clinical practice in low income countries. In this study the S index and the GPRI performed better for predicting significant liver fibrosis (AUROC : 0.726). Cheng et al [20] used the same approach by testing 7 biological scores in another Asian population and found fairly identical results. It should be noted in these two studies that the scores used, with the exception of FIB-4 and APRI, are not well known and not widely used in the world. In addition, the Asian population with hepatitis B is very different from the Caucasian and African populations in terms of epidemiological, clinical and biological characteristics, which makes it difficult to draw conclusions about the use of these tests.
Our approach is totally new and original for Chronic Hepatitis B as the concept of frugal innovation which aims to produce appropriate and effective health goods or services, at low cost and involving the creative use of existing resources[20]. With simple biological variables, it allows us to produce a decision algorithm without calculating a score.. It is especially interesting to note that only 3 patients were misclassified (F0 or F1) when they had severe fibrosis or cirrhosis and therefore absolutely required treatment and monitoring. It therefore seems possible to develop this type of diagnostic approach to hepatic fibrosis in chronic hepatitis B in developing countries where the prevalence of hepatitis B is high, which requires simple and easily performed routine tests for the diagnosis and management of patients.
In conclusion, we have developed a new diagnostic method for liver fibrosis in viral hepatitis B using simple tests which we hope in the future to deploy in poor countries, particularly on the African continent. The performances of this algorithm are particularly interesting. This new algorithm deserves to be further validated in other populations.