Diagnostic efficacy and influencing factors of non-invasive liver fibrosis scores in chronic hepatitis B fibrosis: Cross-sectional study

Table 9 Multivariate logistic regression analysis results for significant fibrosis (F3-F4 vs F0-F2) (n = 627)

Model	Predictor variable	AOR (95%CI)	P value	Model AUC
APRI	Model itself	1.011 (0.995-1.036)	0.26	0.800 (0.766-0.834)
	Age Q2 (vs Q1)	1.291 (0.780-2.143)	0.322
	Age Q3 (vs Q1)	1.526 (0.903-2.587)	0.115
	Age Q4 (vs Q1)	2.464 (1.445-4.241)	0.001
	Male (vs female)	1.746 (1.178-2.666)	0.006
	Nutritional risk (yes vs none)	1.363 (0.737-2.517)	0.295
	Child-Pugh B (vs A)	6.419 (3.768-11.310)	< 0.001
	Child-Pugh C (vs A)	23.951 (8.361-87.708)	< 0.001
GPR	Model itself	1.551 (1.350-1.806)	< 0.001	0.871 (0.844-0.899)
	Age Q2 (vs Q1)	1.16 (0.688-1.959)	0.578
	Age Q3 (vs Q1)	1.356 (0.786-2.345)	0.274
	Age Q4 (vs Q1)	2.028 (1.158-3.573)	0.014
	Male (vs female)	1.379 (0.901-2.124)	0.141
	Nutritional risk (yes vs none)	1.29 (0.673-2.454)	0.438
	Child-Pugh B (vs A)	4.728 (2.718-8.467)	< 0.001
	Child-Pugh C (vs A)	22.635 (7.834-83.517)	< 0.001
FIB-4	Model itself	1.085 (1.035-1.146)	0.002	0.825 (0.793-0.857)
	Age Q2 (vs Q1)	1.142 (0.686-1.904)	0.61
	Age Q3 (vs Q1)	1.215 (0.706-2.091)	0.481
	Age Q4 (vs Q1)	1.737 (0.976-3.100)	0.061
	Male (vs female)	1.847 (1.224-2.813)	0.004
	Nutritional risk (yes vs none)	1.367 (0.736-2.534)	0.32
	Child-Pugh B (vs A)	5.188 (2.998-9.264)	< 0.001
	Child-Pugh C (vs A)	16.712 (5.779-62.87)	< 0.001
AST/ALT	The model itself	1.344 (0.915-2.021)	0.144	0.787 (0.751-0.822)
	Age Q2 (vs Q1)	1.241 (0.748-2.067)	0.404
	Age Q3 (vs Q1)	1.343 (0.778-2.319)	0.290
	Age Q4 (vs Q1)	2.162 (1.233-3.817)	0.007
	Male (vs female)	1.865 (1.238-2.838)	0.003
	Nutritional risk (yes vs none)	1.329 (0.715-2.464)	0.366
	Child-Pugh B (vs A)	6.35 (3.743-11.160)	< 0.001
	Child-Pugh C (vs A)	24.416 (8.606-88.915)	< 0.001

Age grouping follows Table 8. This table presents four independent multivariate logistic regression models. Each model aims to evaluate the independent predictive ability of different serum non-invasive indicators for significant liver fibrosis (F3-F4) vs no or mild fibrosis (F0-F2). “Model AUC” refers to the area under the receiver operating characteristic (ROC) curve of the regression model, indicating its overall diagnostic performance in distinguishing patients with “significant fibrosis (F3-F4)” from those with “no or mild fibrosis (F0-F2)”. The calculation method is as follows: A predicted probability is computed for each subject based on the model's predictor variables; an ROC curve is then plotted using this predicted probability as the test variable against the actual grouping (F3-F4 vs F0-F2) as the state variable; finally, the area under this curve is calculated. An area under the curve value closer to 1 indicates a stronger discriminatory ability of the model. AOR: Adjusted odds ratio; CI: Confidence interval; AUC: Area under the curve; APRI: Aspartate aminotransferase to platelet ratio index; GPR: Gamma-glutamyl transferase to platelet ratio index; FIB-4: Fibrosis-4 index; AST/ALT: Aspartate aminotransferase to alanine aminotransferase ratio.