Forns et al developed a simple predictive model for identifying patients with chronic hepatitis C at low risk for significant hepatic fibrosis. This can help reduce the need for liver biopsy in these patients. The authors are from the University of Barcelona in Catalonia, Spain.



(1) platelet count in 10^9/L

(2) serum GGT in IU/L

(3) age in years

(4) serum cholesterol in mg/dL


predictive score =

= (3.467 * LN(age)) + (0.781 * LN(serum GGT)) - (3.131 * LN(platelet count)) - (0.014 * (serum cholesterol)) + 7.811



• The optimum cut-off point was a score of 4.2.

• A score <= 4.2 was associated with a low probability of significant fibrosis in the liver biopsy (negative predictive value 96%).

• About a third of the patients in the study group had a score <= 4.2 and would not need liver biopsy.



• The area under the ROC curve was 0.86 for the derivation group and 0.81 for the validation group.

• The sensitivity was 94% and specificity 45% at the cutoff of 4.2



• The methods for determining the GGT and cholesterol were not stated and the normal ranges were not given. This limits the transportability of the score in hospitals using alternative methods.


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