A non-invasive algorithm accurately predicts advanced fibrosis in hepatitis C: a comparison using histology with internal-external validation
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Silvia Paggi1, Agostino Colli, Mirella Fraquelli
1Second Division of Gastroenterology, Fondazione IRCCS Policlinico, Mangiagalli e Regina Elena, University of Milan, Milan, Italy.
Insights
An algorithm combining AST-to-platelet-ratio-index (APRI) and liver surface ultrasound nodularity (LSN) accurately diagnoses advanced liver fibrosis in chronic hepatitis C patients. This non-invasive approach can reduce the need for liver biopsies in many cases.
Area of Science:
- Hepatology
- Medical Imaging
- Biochemical Analysis
Background:
- Histology is the gold standard for assessing liver fibrosis in chronic hepatitis C (CH-C).
- Non-invasive methods like biochemical tests and ultrasonography (US) are valuable for evaluating liver fibrosis.
- Accurate non-invasive tools are needed to manage CH-C patients and reduce invasive procedures.
Purpose of the Study:
- To evaluate the accuracy of APRI and LSN in diagnosing advanced liver fibrosis (METAVIR F3, F4).
- To develop a prediction rule using APRI and LSN, individually and combined, to confirm or exclude advanced fibrosis.
- To assess the clinical utility of a combined APRI and LSN algorithm in CH-C patients.
Main Methods:
- A multicenter, cross-sectional cohort study involving 430 CH-C patients with elevated ALT.
- Patients were divided into training, internal validation, and external validation cohorts.
- APRI and LSN were measured and compared against liver biopsy results; a sequential algorithm was developed.
Main Results:
- The combined APRI and LSN algorithm achieved 94% diagnostic accuracy for the presence or absence of F3, F4 fibrosis in 231/430 patients.
- Advanced fibrosis (F3, F4) was detected with 83% accuracy in an additional 60/430 patients.
- The algorithm could confirm or exclude advanced fibrosis in 54% of patients and suggest a diagnosis in another 17%.
Conclusions:
- An algorithm integrating APRI and LSN effectively confirms or excludes advanced liver fibrosis (F3, F4) in a significant proportion of CH-C patients.
- This non-invasive diagnostic approach can reduce the necessity of liver biopsy for managing CH-C.
- The study provides a practical prediction rule for advanced fibrosis assessment in clinical settings.
Background/Aims:
Biochemical tests and ultrasonography (US) are useful in the non-invasive assessment of liver fibrosis in patients with chronic hepatitis C (CH-C); however histology remains the reference standard. This multicenter, cross-sectional cohort study evaluated the accuracy of APRI (AST-to-platelet-ratio-index) and liver surface ultrasound nodularity (LSN), singularly and sequentially combined in an algorithm, in diagnosing advanced fibrosis (i.e. METAVIR F3,F4), to derive a prediction rule to confirm or exclude F3,F4.
Methods:
Four hundred and thirty consecutive CH-C patients with elevated ALT, grouped into a first cohort (training set), and an internal and an external validation cohort, were studied. APRI and LSN were compared to liver biopsy and sequentially combined in order to obtain a predictive rule for advanced fibrosis METAVIR F3,F4.
Results:
LSN was negative and APRI < or = 1 in 185/430 patients, whereas LSN was positive and APRI>2 in 46/430 cases, with a 94% diagnostic accuracy for presence/absence of F3, F4, respectively. In a further 60/430 patients, F3,F4 was detected with an accuracy of 83%. In the remaining cases no classification was possible.
Conclusions:
An algorithm based on APRI and LSN confirms or excludes F3,F4 in 54% of CH-C patients with elevated ALT and suggests a highly probable diagnosis in a further one-sixth of patients, thus rendering liver biopsy unnecessary in these patients.
