Description

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.


 

Parameters:

(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

 

Interpretation:

• 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.

 

Performance:

• 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

 

Limitations:

• 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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