Skip to main content
PMC home page
Medical Science Monitor: International Medical Journal of Experimental and Clinical Research logoLink to Medical Science Monitor: International Medical Journal of Experimental and Clinical Research
. 2015 Dec 20;21:3961–3977. doi: 10.12659/MSM.895005

Diagnostic Accuracy of APRI, AAR, FIB-4, FI, and King Scores for Diagnosis of Esophageal Varices in Liver Cirrhosis: A Retrospective Study

Han Deng 1,2,B,C,F,*, Xingshun Qi 1,A,C,D,E,F,*,✉, Ying Peng 1,2,B, Jing Li 1,2,B, Hongyu Li 1,D,E, Yongguo Zhang 1,D,E, Xu Liu 1,D,E, Xiaolin Sun 1,B, Xiaozhong Guo 1,D,E,✉
PMCID: PMC4690652  PMID: 26687574

Abstract

Background

Aspartate aminotransferase-to-platelet ratio index (APRI), aspartate aminotransferase-to-alanine aminotransferase ratio (AAR), FIB-4, fibrosis index (FI), and King scores might be alternatives to the use of upper gastrointestinal endoscopy for the diagnosis of esophageal varices (EVs) in liver cirrhosis. This study aimed to evaluate their diagnostic accuracy in predicting the presence and severity of EVs in liver cirrhosis.

Material/Methods

All patients who were consecutively admitted to our hospital and underwent upper gastrointestinal endoscopy between January 2012 and June 2014 were eligible for this retrospective study. Areas under curve (AUCs) were calculated. Subgroup analyses were performed according to the history of upper gastrointestinal bleeding (UGIB) and splenectomy.

Results

A total of 650 patients with liver cirrhosis were included, and 81.4% of them had moderate-severe EVs. In the overall analysis, the AUCs of these non-invasive scores for predicting moderate-severe EVs and presence of any EVs were 0.506–0.6 and 0.539–0.612, respectively. In the subgroup analysis of patients without UGIB, their AUCs for predicting moderate-severe varices and presence of any EVs were 0.601–0.664 and 0.596–0.662, respectively. In the subgroup analysis of patients without UGIB or splenectomy, their AUCs for predicting moderate-severe varices and presence of any EVs were 0.627–0.69 and 0.607–0.692, respectively.

Conclusions

APRI, AAR, FIB-4, FI, and King scores had modest diagnostic accuracy of EVs in liver cirrhosis. They might not be able to replace the utility of upper gastrointestinal endoscopy for the diagnosis of EVs in liver cirrhosis.

MeSH Keywords: Blood Platelets; Endoscopy; Esophageal and Gastric Varices; Hypertension, Portal; Liver Cirrhosis

Background

Liver cirrhosis is one of the most common causes of death in the world [1,2]. Natural history of liver cirrhosis is primarily divided into four stages [3,4]. Stage 1, 2, 3, and 4 are characterized respectively by neither varices nor ascites, varices without ascites or bleeding, ascites with or without varices, and variceal bleeding with or without ascites, respectively. The prognosis is gradually worsened with increased stage of liver cirrhosis. Notably, the mortality is 3.4% per year in patients with varices who have never bled. By comparison, the mortality is up to 57% per year in patients with variceal bleeding. Thus, early diagnosis of varices and primary prophylaxis of variceal bleeding in high-risk patients with liver cirrhosis should be actively employed [5,6].

Upper gastrointestinal endoscopy is the golden diagnostic test of varices in liver cirrhosis. However, because of its invasiveness and discomfort, most of patients are reluctant to undergo this procedure. Recently, numerous non-invasive markers of varices have been explored in patients with liver cirrhosis [7–9]. However, they may be rarely used in clinical practices [10]. Herein, we aimed to evaluate the diagnostic accuracy of aspartate aminotransferase (AST) to platelet (PLT) ratio index (i.e., APRI), AST to alanine aminotransferase (ALT) ratio (i.e., AAR), FIB-4, fibrosis index (FI), and King scores in predicting the presence of varices and high-risk varices in liver cirrhosis. These non-invasive scores were selected, because they were readily available from regular laboratory tests and demographic data [11–15].

Material and Methods

Study design

All patients who were consecutively admitted to our hospital between January 2012 and June 2014 were considered in this retrospective study. The inclusion criteria were as follows: 1) patients were diagnosed with liver cirrhosis; 2) patients underwent both laboratory tests and endoscopic examinations. The exclusion criteria were as follows: 1) patients were diagnosed with malignant tumors; 2) patients did not undergo endoscopic examinations to evaluate the presence and degree of esophageal varices (EVs); and 3) the relevant laboratory data were missing. Notably, repeated admissions were not excluded. In other words, if one patient underwent endoscopy two or more times at different admissions during the enrollment period, all results would be included in our study. This was primarily because we just observed the association between non-invasive scores and varices. Some data had been reported in our previous papers [16–19]. This study was approved by the Ethics Committee of our hospital (number k(2015)11). Due to the retrospective nature of this study, patient written informed consents were waived.

Data collection

We collected the following data from electronic medical records: age, sex, etiology of liver diseases, ascites, hepatic encephalopathy (HE), history of upper gastrointestinal bleeding (UGIB), history of splenectomy, endoscopic findings, red blood cell (RBC), hemoglobin (Hb), white blood cell (WBC), PLT, ALT, AST, prothrombin time (PT), activated partial thromboplastin time (APTT), international normalized ratio (INR), albumin (ALB), total bilirubin (TBIL), alkaline phosphatase (ALP), γ-glutamine transferase (GGT) and creatinine (Cr). Additionally, we calculated the Child-Pugh [20], model for end-stage of liver disease (MELD) [21], APRI [11], AAR [12], FIB-4 [13], FI [14], and King scores [15].

  • Child-Pugh score = ALB score + TBIL score + INR score + ascites score + HE score

  • MELD score = 9.57x ln(Cr) + 3.78 × ln(TBIL) + 11.2 × ln (INR) + 6.43

  • APRI = [(AST/ULN) × 100]/PLT

  • AAR = AST/ALT

  • FIB-4 = (age*AST)/PLT*ALT1/2

  • FI = 8–0.01*PLT-ALB

  • King = age*AST*INR/PLT

Evaluation of EVs

Grade of EVs was classified into no, mild, moderate, and severe according to the 2008 Hangzhou consensus, which was proposed by the Chinese Society of Gastroenterology, Chinese Society of Hepatology, and Chinese Society of Digestive Endoscopy [22]. This classification is widely employed in China and is primarily based on the general rules by Japanese Society for Portal Hypertension, Baveno consensus, AASLD practice guidelines, and clinical practices in China [5,6,23]. We re-evaluated the grade of EVs by reviewing the original medical records and endoscopic results. Gastric varices were not considered in this study. Before the statistical analysis, we were blind to the correlation of EVs with non-invasive scores.

Statistical analysis

Categorical data were expressed as frequencies (percentages) and compared by using the chi-square tests. Continuous data were expressed as mean ± standard deviation and compared by using the independent sample t-tests. Receiver operating characteristic (ROC) curves were performed to evaluate and compare the diagnostic accuracy of APRI, AAR, FIB-4, FI, and King scores for the prediction of EVs (moderate-severe versus no-mild EVs; with versus without EVs). The diagnostic performances were expressed as area under curve (AUC), sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, positive predictive value, and negative predictive value. AUCs were compared by using DeLong test. Optimal cut-off values were chosen while the sum of sensitivity and specificity would be maximal. Subgroup analysis was performed in patients without any previous history of UGIB, in those with Child-Pugh class A or B+C, and in those without any previous history of splenectomy. A two-sided P<0.05 was considered statistically significant. All statistical analyses were performed by using the SPSS software version 18.0 (SPSS Inc. Chicago, IL, USA).

Results

Patients

Overall, 650 patients were eligible in our study. The characteristics of all patients are shown in Table 1. Among them, 81.4% had moderate-severe EVs, 81.8% had previous history of UGIB, and 52.6% had Child-Pugh classes B and C.

Table 1.

Overall analysis.

Variables Total Pts (n=650) Moderate-large varices Pts (n=529) No-mild varices Pts (n=121) P value With varices Pts (n=557) Without varices Pts (n=93) P value
Sex (male/female) 425/225 353/176 72/49 0.132 373/184 52/41 0.038
Age (years) 53.54±11.75 53.61±11.82 53.27±11.48 0.774 53.38±11.85 54.51±11.14 0.393
Etiology of liver diseases, n (%) 0.396 0.386
 Hepatitis B virus 199 (30.6) 169 (31.9) 30 (24.8) 176 (31.6) 23 (24.7)
 Hepatitis C virus 46 (7.1) 38 (7.2) 8 (6.6) 39 (7.0) 7 (7.5)
 Hepatitis B virus + Hepatitis C virus 5 (0.8) 5 (0.9) 0 (0) 5 (0.9) 0 (0)
 Alcohol 154 (23.7) 119 (22.5) 35 (28.9) 128 (23.0) 26 (28.0)
 Hepatitis B virus + Alcohol 47 (7.2) 40 (7.6) 7 (5.8) 41 (7.4) 6 (6.5)
 Unknown 122 (18.8) 91 (17.2) 31 (25.6) 97 (17.4) 25 (26.9)
 Others 77 (11.8) 67 (12.7) 10 (8.3) 71 (12.7) 6 (6.5)
Ascites, n (%) 0.029 0.007
 No 364 (56.0) 284 (53.7) 80 (66.1) 298 (53.5) 66 (71.0)
 Mild 91 (14.0) 75 (14.2) 16 (13.2) 83 (14.9) 8 (8.6)
 Moderate to severe 195 (30.0) 170 (32.1) 25 (20.7) 176 (31.6) 19 (20.4)
Hepatic encephalopathy, n (%) 0.676 0.491
 No 637 (98.0) 519 (98.1) 118 (97.5) 545 (97.8) 92 (98.9)
 Grade I–II 13 (2.0) 10 (1.9) 3 (2.5) 12 (2.2) 1 (1.1)
 Grade III–IV 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
History of UGIB (yes/no) 532/118 467/62 65/56 <0.001 489/68 43/50 <0.001
Varices, n (%) NA NA
 No 93 (14.3) 0 (0) 93 (76.9) 0 (0) 93 (100)
 Mild 28 (4.3) 0 (0) 28 (23.1) 28 (5.0) 0 (0)
 Moderate 78 (12.0) 78 (14.7) 0 (0) 78 (14.0) 0 (0)
 Severe 451 (69.4) 451 (85.3) 0 (0) 451 (81.0) 0 (0)
Laboratory tests
 RBC 3.04±0.79 2.96±0.75 3.37±0.88 <0.001 2.99±0.75 3.32±0.95 <0.001
 Hb 86.50±27.44 83.38±25.61 100.16±30.91 <0.001 84.23±25.58 100.13±33.71 <0.001
 WBC 4.43±3.08 4.33±3.02 4.90±3.30 0.065 4.34±3.01 4.99±3.41 0.059
 PLT 98.20±87.98 94.94±87.34 112.43±89.72 0.049 94.88±86.72 118.05±93.27 0.019
 TBIL 26.25±29.22 25.30±26.60 30.40±38.54 0.084 25.84±26.74 28.72±41.20 0.38
 DBIL 12.92±21.12 12.18±18.92 16.15±28.72 0.062 12.51±18.92 15.37±31.23 0.227
 IBIL 13.27±10.68 13.08±10.32 14.08±12.14 0.353 13.27±10.35 13.24±12.52 0.979
 ALB 33.21±6.36 32.80±6.38 34.98±6.00 0.001 32.86±6.33 35.30±6.20 0.001
 ALT 34.30±57.40 31.07±27.93 48.42±118.91 0.003 31.20±27.63 52.87±135.00 0.001
 AST 48.36±78.81 46.09±78.86 58.31±78.14 0.124 46.47±77.33 59.71±86.68 0.134
 ALP 100.37±85.17 97.68±83.63 112.17±91.06 0.091 98.79±84.73 109.89±87.62 0.245
 GGT 95.05±235.38 77.22±135.85 173.01±459.24 <0.001 81.82±145.57 174.29±505.32 <0.001
 BUN 6.55±4.21 6.66±4.32 6.06±3.63 0.154 6.63±4.25 6.10±3.93 0.262
 Cr 62.29±40.95 61.88±37.85 64.10±52.54 0.591 61.60±37.11 66.45±59.04 0.291
 PT 16.02±3.45 16.17±3.50 15.36±3.13 0.019 16.17±3.46 15.14±3.27 0.008
 APTT 41.93±8.82 41.95±9.21 41.85±6.90 0.907 42.05±9.12 41.21±6.70 0.396
 INR 1.30±0.39 1.31±0.39 1.23±0.34 0.021 1.31±0.39 1.20±0.35 0.01
Child-Pugh class, n (%) 0.062 0.012
 A 308 (47.4) 239 (45.2) 69 (57.0) 251 (45.1) 57 (61.3)
 B 279 (42.9) 237 (44.8) 42 (34.7) 248 (44.5) 31 (33.3)
 C 63 (9.7) 53 (10.0) 10 (8.3) 58 (10.4) 5 (5.4)
Child-Pugh score 6.60±1.76 7.03±1.76 6.64±1.72 0.027 7.04±1.78 6.45±1.54 0.003
MELD score 5.07±5.72 5.18±5.61 4.59±6.18 0.301 5.22±5.59 4.20±6.44 0.114
APRI score 2.15±3.88 2.15±4.11 2.15±2.60 1 2.16±4.03 2.09±2.80 0.864
AAR score 1.51±0.69 1.51±0.68 1.51±0.74 0.897 1.52±0.68 1.48±0.76 0.564
FIB-4 score 6.61±7.17 6.71±7.44 6.15±5.86 0.444 6.74±7.36 5.81±5.94 0.25
FI score −26.19±6.53 −25.75±6.54 −28.10±6.18 <0.001 −25.81±6.48 −28.48±6.40 <0.001
King score 61.17±213.86 63.56±235.06 50.74±64.08 0.552 63.21±229.33 48.99±67.93 0.553
Open in a new tab

AAR – AST to ALT ratio; ALB – albumin; ALP – alkaline phosphatase; ALT – alanine aminotransferase; APRI – AST to platelets ratio index; APTT – activated partial thromboplastin time; AST – aspartate aminotransferase; AUC – area under curve; BUN – blood urea nitrogen; Cr – creatinine; DBIL – direct bilirubin; FI – fibrosis index; FIB-4 – fibrosis 4 index; GGT – gamma-glutamyl transpeptidase; Hb – hemoglobin; IBIL – indirect bilirubin; INR – international normalized ratio; MELD – model for end stage liver disease; NA – not available; PLT – platelet; PT – prothrombin time; Pts – patients; RBC – red blood cell; TBIL – total bilirubin; UGIB – upper gastrointestinal bleeding; WBC – white blood cell.

Overall analysis

Moderate-severe versus no-mild EVs

Compared with the no-mild EVs group, the moderate-severe EVs group had significantly higher proportions of ascites and history of UGIB, significantly higher PT, INR, Child-Pugh score, and FI score, but significantly lower RBC, Hb, PLT, ALB, ALT, and GGT (Table 1).

FI score had the largest AUC (AUC=0.6), followed by FIB-4 (AUC=0.544), AAR (AUC=0.538), King (AUC=0.526), and APRI scores (AUC=0.506) (Figure 1A). AUC of FI score was not significantly different from that of FIB-4 (P=0.1041) or AAR score (P=0.0892), but was significantly larger than that of King (P=0.0293) and APRI scores (P=0.0093).

Figure 1.

Figure 1

Open in a new tab

Receiver operating characteristic curves showing the diagnostic accuracy of APRI, AAR, FIB-4, FI, and King scores in predicting the presence of varices in liver cirrhosis. (A) Prediction of moderate-severe varices. (B) Prediction of varices. AUC – area under curve; PLR – positive likelihood ratio; PPV – positive predictive value; NLR – negative likelihood ratio; NPV – negative predictive value; Sen – sensitivity; Spec – specificity.

With versus without EVs

Compared with the no EVs group, the EVs group had significantly higher proportions of male, ascites, history of UGIB, and Child-Pugh class B+C, significantly higher PT, INR, Child-Pugh score, and FI score, but significantly lower RBC, Hb, PLT, ALB, ALT, and GGT (Table 1).

FI score had the largest AUC (AUC=0.612), followed by FIB-4 (AUC=0.567), AAR (AUC=0.56), King (AUC=0.55), and APRI scores (AUC=0.539) (Figure 1B). AUC of FI score was not significantly different from that of FIB-4 (P=0.2510), AAR (P=0.2167), King (P=0.1144), or APRI score (P=0.0873).

Subgroup analysis in patients without UGIB

Moderate-severe versus no-mild EVs

Compared with the no-mild EVs group, the moderate-severe EVs group had significantly higher FIB-4 and FI scores, but significantly lower PLT and ALB (Table 2).

Table 2.

Subgroup analysis of patients without UGIB.

Variables Total Pts (n=118) Moderate-large varices Pts (n=62) No-Mild varices Pts (n=56) P value With varices Pts (n=68) Without varices Pts (n=50) P value
Sex (male/female) 69/49 36/26 33/23 0.924 38/30 31/19 0.505
Age (years) 55.09±11.02 55.89±10.86 54.21±11.24 0.41 54.90±11.59 55.35±10.32 0.828
Etiology of liver diseases, n (%) 0.041 0.161
 Hepatitis B virus 28 (23.7) 19 (30.6) 9 (16.1) 19 (27.9) 9 (18.0)
 Hepatitis C virus 8 (6.8) 5 (8.1) 3 (5.4) 6 (8.8) 2 (4.0)
 Hepatitis B virus + Hepatitis C virus 1 (0.8) 1 (1.6) 0 (0) 1 (1.5) 0 (0)
 Alcohol 30 (25.4) 13 (21.0) 17 (30.4) 14 (20.6) 16 (32.0)
 Hepatitis B virus + Alcohol 8 (6.8) 5 (8.1) 3 (5.4) 5 (7.4) 3 (6.0)
 Unknown 33 (28.0) 11 (17.7) 22 (39.3) 15 (22.1) 18 (36.0)
 Others 10 (8.4) 8 (12.9) 2 (3.6) 8 (11.8) 2 (4)
Ascites, n (%) 0.524 0.172
 No 69 (58.5) 34 (54.8) 35 (62.5) 35 (51.5) 34 (68.0)
 Mild 18 (15.3) 9 (14.5) 9 (16.1) 13 (19.1) 5 (10.0)
 Moderate to severe 31 (26.3) 19 (30.6) 12 (21.4) 20 (29.4) 11 (22.0)
Hepatic encephalopathy, n (%) 0.34 0.389
 No 117 (99.2) 61 (98.4) 56 (100) 67 (98.5) 50 (100)
 Grade I–II 1 (0.8) 1 (1.6) 0 (0) 1 (1.5) 0 (0)
 Grade III–IV 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
Varices, n (%) NA NA
 No 50 (42.4) 0 (0) 50 (89.3) 0 (0) 50 (100)
 Mild 6 (5.1) 0 (0) 6 (10.7) 6 (8.8) 0 (0)
 Moderate 20 (16.9) 20(32.3) 0 (0) 20 (29.4) 0 (0)
 Severe 42 (35.6) 42 (67.7) 0 (0) 42 (61.8) 0 (0)
Laboratory tests
 RBC 3.72±0.74 3.68±0.69 3.76±0.79 0.571 3.68±0.68 3.78±0.82 0.459
 Hb 116.69±25.85 115.45±25.58 118.07±26.30 0.585 115.12±25.03 118.84±27.03 0.442
 WBC 4.26±2.29 3.94±2.39 4.62±2.13 0.106 3.91±2.34 4.74±2.14 0.051
 PLT 90.72±59.50 76.92±50.82 106.00±64.91 0.007 76.76±50.41 109.70±65.88 0.003
 TBIL 31.02±36.80 30.39±21.34 31.72±48.73 0.845 30.15±20.97 32.20±51.28 0.767
 DBIL 16.79±29.45 15.40±17.11 18.33±38.93 0.592 15.33±16.68 18.77±41.03 0.533
 IBIL 14.19±9.92 14.94±8.40 13.37±11.39 0.394 14.75±8.35 13.44±11.78 0.482
 ALB 35.30±6.13 34.04±5.84 36.70±6.20 0.018 33.97±5.98 37.11±5.92 0.006
 ALT 55.03±122.69 45.95±46.68 65.07±171.49 0.4 44.84±44.79 68.88±181.27 0.295
 AST 70.42±102.52 74.45±106.22 65.95±99.02 0.655 72.15±101.98 68.06±104.24 0.832
 ALP 120.34±87.20 124.76±99.60 115.46±71.59 0.565 126.68±100.69 111.73±64.50 0.36
 GGT 143.04±223.66 138.85±240.15 147.68±205.94 0.832 142.13±238.07 144.28±204.81 0.959
 BUN 5.61±3.35 5.37±2.18 5.89±4.29 0.402 5.37±2.11 5.94±4.52 0.365
 Cr 64.85±55.02 58.35±27.04 72.05±74.35 0.178 57.34±26.15 75.06±78.15 0.084
 PT 15.07±2.41 15.42±2.20 14.67±2.58 0.093 15.45±2.38 14.55±2.41 0.044
 APTT 42.74±6.58 43.31±6.43 42.10±6.74 0.323 43.79±6.90 41.31±5.89 0.043
 INR 1.19±0.25 1.23±0.24 1.15±0.27 0.094 1.23±0.25 1.14±0.25 0.042
Child-Pugh class, n (%) 0.633 0.211
 A 62 (52.5) 30 (48.4) 32 (57.1) 31 (45.6) 31 (62.0)
 B 47 (39.8) 27 (43.5) 20 (35.7) 31 (45.6) 16 (32.0)
 C 9 (7.6) 5 (8.1) 4 (7.1) 6 (8.8) 3 (6.0)
Child-Pugh score 6.69±1.73 6.89±1.81 6.48±1.63 0.206 6.96±1.86 6.34±1.49 0.056
MELD score 4.72±5.83 5.16±4.71 4.24±6.88 0.392 4.97±4.77 4.39±7.07 0.591
APRI score 3.13±5.13 3.69±6.44 2.50±3.01 0.209 3.58±6.18 2.51±3.13 0.261
AAR score 1.58±0.84 1.68±0.89 1.48±0.79 0.206 1.66±0.87 1.48±0.80 0.266
FIB-4 score 8.24±8.27 9.87±9.66 6.45±5.98 0.024 9.58±9.38 6.42±6.10 0.04
FI score −28.21±6.23 −26.81±5.83 −29.76±6.25 0.01 −26.74±5.98 −30.21±6.07 0.002
King score 81.27±176.82 101.92±231.32 58.40±78.43 0.183 97.82±221.78 58.76±80.67 0.237
Open in a new tab

AAR – AST to ALT ratio; ALB – albumin; ALP – alkaline phosphatase; ALT – alanine aminotransferase; APRI – AST to platelets ratio index; APTT – activated partial thromboplastin time; AST – aspartate aminotransferase; AUC – area under curve; BUN – blood urea nitrogen; Cr – creatinine; DBIL – direct bilirubin; FI – fibrosis index; FIB-4 – fibrosis 4 index; GGT – gamma-glutamyl transpeptidase; Hb – hemoglobin; IBIL – indirect bilirubin; INR – international normalized ratio; MELD – model for end-stage liver disease; NA – not available; PLT – platelet; PT – prothrombin time; Pts – patients; RBC – red blood cell; TBIL – total bilirubin; UGIB – upper gastrointestinal bleeding; WBC – white blood cell.

FIB-4 score had the largest AUC (AUC=0.664), followed by King (AUC=0.645), FI (AUC=0.636), APRI (AUC=0.627), and AAR scores (AUC=0.601) (Figure 2A). AUC of FIB-4 score was not significantly different from that of FI (P=0.6317), King (P=0.3537), AAR (P=0.3037), or APRI score (P=0.1571).

Figure 2.

Figure 2

Open in a new tab

Receiver operating characteristic curves showing the diagnostic accuracy of APRI, AAR, FIB-4, FI, and King scores in predicting the presence of varices in liver cirrhosis without UGIB. (A) Prediction of moderate-severe varices. (B) Prediction of varices. AUC – area under curve; PLR – positive likelihood ratio; PPV – positive predictive value; NLR – negative likelihood ratio; NPV – negative predictive value; Sen – sensitivity; Spec – specificity.

With versus without EVs

Compared with the no EVs group, the EVs group had significantly higher PT, APTT, INR, FIB-4 score, and FI score, but significantly lower PLT and ALB (Table 2).

FI score had the largest AUC (AUC=0.662), followed by FIB-4 (AUC=0.655), King (AUC=0.639), APRI (AUC=0.634), and AAR scores (AUC=0.596) (Figure 2B). The AUC of FI score was not significantly different from that of FIB-4 (P=0.9120), King (P=0.6968), APRI (P=0.6530), or AAR score (P=0.3083).

Subgroup analysis in patients without UGIB at Child-Pugh class A

Moderate-severe versus no-mild EVs

Compared with the no-mild EVs group, the moderate-severe EVs group had significantly higher PT and INR, but a significantly lower WBC (Table 3).

Table 3.

Subgroup analysis of patients without UGIB at Child-Pugh class A.

Variables Total Pts (n=62) Moderate-large varices Pts (n=30) No-mild varices Pts (n=32) P value With warices Pts (n=31) Without varices Pts (n=31) P value
Sex (male/female) 33/29 17/13 16/16 0.599 17/14 16/15 0.799
Age (years) 54.61±11.50 55.19±11.42 54.06±11.74 0.702 55.09±11.24 54.12±11.93 0.741
Etiology of liver diseases, n (%) 0.159 0.244
 Hepatitis B virus 22 (35.5) 14 (46.7) 8 (25.0) 14 (45.2) 8 (25.8)
 Hepatitis C virus 3 (4.8) 2 (6.7) 1 (3.1) 2 (6.5) 1 (3.2)
 Hepatitis B virus + Hepatitis C virus 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
 Alcohol 11 (17.7) 4 (13.3) 7 (21.9) 4 (12.9) 7 (22.6)
 Hepatitis B virus + Alcohol 3 (4.8) 2 (6.7) 1 (3.1) 2 (6.5) 1 (3.2)
 Unknown 20 (32.3) 6 (20.0) 14 (43.8) 7 (22.6) 13 (41.9)
 Others 3 (4.8) 2 (6.7) 1 (3.1) 2 (6.5) 1 (3.2)
Ascites, n (%) 0.947 1
 No 58 (93.5) 28 (93.3) 30 (93.8) 29 (93.5) 29 (93.5)
 Mild 4 (6.5) 2 (6.7) 2 (6.3) 2 (6.5) 2 (6.5)
 Moderate to severe 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
Hepatic encephalopathy, n (%) NA NA
 No 62 (100) 30 (100) 32 (100) 31 (100) 31 (100)
 Grade I–II 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
 Grade III–IV 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
Varices, n (%) NA NA
 No 31 (50.0) 0 (0) 31 (96.9) 0 (0) 31 (100)
 Mild 1 (1.6) 0 (0) 1 (3.1) 3 (3.2) 0 (0)
 Moderate 8 (12.9) 8 (26.7) 0 (0) 8 (25.8) 0 (0)
 Severe 22 (35.5) 22 (73.3) 0 (0) 22 (71.0) 0 (0)
Laboratory tests
 RBC 3.95±0.71 3.40±0.57 3.90±0.83 0.588 3.99±0.56 3.91±0.84 0.637
 Hb 122.03±25.39 123.23±23.38 120.91±27.47 0.722 123.00±23.02 121.06±27.91 0.767
 WBC 3.82±1.52 3.37±1.10 4.24±1.75 0.023 3.38±1.08 4.26±1.78 0.022
 PLT 87.34±50.03 76.10±44.14 97.88±53.52 0.087 76.48±43.45 98.19±54.38 0.088
 TBIL 19.43±9.53 20.66±7.61 18.27±11.04 0.327 20.57±7.50 18.29±11.22 0.35
 DBIL 7.66±3.93 7.93±3.25 7.34±4.52 0.56 7.88±3.20 7.37±4.59 0.614
 IBIL 11.72±5.90 12.63±4.78 10.87±6.75 0.242 12.53±4.74 10.92±6.85 0.287
 ALB 38.68±4.62 38.09±4.44 39.23±4.79 0.338 38.12±4.37 39.23±4.87 0.347
 ALT 45.19±50.60 46.07±48.51 44.38±53.25 0.897 46.00±47.70 44.39±54.13 0.901
 AST 51.81±51.21 56.17±61.74 47.72±39.50 0.521 55.61±60.78 48.00±40.12 0.563
 ALP 100.61±70.72 109.89±94.03 91.92±37.51 0.321 113.83±95.02 87.40±27.91 0.142
 GGT 104.42±177.76 89.47±144.00 118.44±205.82 0.526 105.42±167.13 103.42±190.57 0.965
 BUN 5.10±2.34 5.22±1.30 4.99±3.03 0.704 5.26±1.30 4.94±3.07 0.594
 Cr 60.24±49.09 54.74±10.69 65.39±67.66 0.398 54.95±10.57 65.53±68.78 0.4
 PT 14.11±1.55 14.51±1.62 13.74±1.42 0.05 14.42±1.67 13.81±1.39 0.119
 APTT 40.95±5.49 41.21±5.67 40.70±5.39 0.718 41.32±5.61 40.58±5.43 0.6
 INR 1.09±0.15 1.14±0.16 1.05±0.14 0.036 1.13±0.17 1.06±0.14 0.089
Child-Pugh score 5.35±0.48 5.33±0.48 5.38±0.49 0.737 5.32±0.48 5.39±0.50 0.603
MELD score 2.42±3.99 3.13±3.17 1.76±4.58 0.179 3.06±3.14 1.78±4.66 0.21
APRI score 2.29±2.75 2.44±2.73 2.15±2.80 0.68 2.40±2.69 2.18±2.84 0.75
AAR score 1.29±0.44 1.29±0.36 1.29±0.50 0.979 1.28±0.36 1.30±0.50 0.835
FIB-4 score 6.26±5.03 6.84±4.46 5.71±5.53 0.382 6.73±4.42 5.79±5.61 0.462
FI score −31.55±4.68 −30.85±4.44 −32.20±4.87 0.258 −30.88±4.37 −32.21±4.95 0.266
King score 51.28±70.67 57.61±75.38 45.34±66.61 0.499 56.39±74.42 44.17±67.55 0.573
Open in a new tab

AAR – AST to ALT ratio; ALB – albumin; ALP – alkaline phosphatase; ALT – alanine aminotransferase; APRI – AST to platelets ratio index; APTT – activated partial thromboplastin time; AST – aspartate aminotransferase; AUC – area under curve; BUN – blood urea nitrogen; Cr – creatinine; DBIL – direct bilirubin; FI – fibrosis index; FIB-4 – fibrosis 4 index; GGT – gamma-glutamyl transpeptidase; Hb – hemoglobin; IBIL – indirect bilirubin; INR – international normalized ratio; MELD – model for end-stage liver disease; NA – not available; PLT – platelet; PT – prothrombin time; Pts – patients; RBC – red blood cell; TBIL – total bilirubin; UGIB – upper gastrointestinal bleeding; WBC – white blood cell.

FIB-4 score had the largest AUC (AUC=0.649), followed by King (AUC=0.629), APRI (AUC=0.611), FI (AUC=0.589), and AAR scores (AUC=0.549) (Figure 3A). AUC of FIB-4 score was not significantly different from that of King (P=0.5172), FI (P=0.4906), APRI (P=0.3419), or AAR score (P=0.3025).

Figure 3.

Figure 3

Open in a new tab

Receiver operating characteristic curves showing the diagnostic accuracy of APRI, AAR, FIB-4, FI, and King scores in predicting the presence of varices in liver cirrhosis without UGIB at Child-Pugh class A. (A) Prediction of moderate-severe varices. (B) Prediction of varices. AUC – area under curve; PLR – positive likelihood ratio; PPV – positive predictive value; NLR – negative likelihood ratio; NPV – negative predictive value; Sen – sensitivity; Spec – specificity.

With versus without EVs

Compared with the no EVs group, the EVs group had a significantly lower WBC (Table 3).

FIB-4 score had the largest AUC (AUC=0.638), followed by King (AUC=0.62), APRI (AUC=0.608), FI (AUC=0.588), and AAR scores (AUC=0.524) (Figure 3B). The AUC of FIB-4 score was not significantly different from that of FI (P=0.5732), King (P=0.5542), APRI (P=0.4411), or AAR score (P=0.2463).

Subgroup analysis in patients without UGIB at Child-Pugh class B and C

Moderate-severe versus no-mild EVs

Compared with the no-mild EVs group, the moderate-severe EVs group had a significantly higher FI score, but significantly lower PLT and ALB (Table 4).

Table 4.

Subgroup analysis patients without UGIB at Child-Pugh class B and C.

Variables Total Pts (n=56) Moderate-large varices Pts (n=32) No-mild varices Pts (n=24) P value With varices Pts (n=37) Without varices Pts (n=19) P value
Sex (male/female) 36/20 19/13 17/7 0.376 21/16 15/4 0.101
Age (years) 55.63±10.55 56.55±10.45 54.41±10.78 0.457 54.74±12.02 57.36±6.79 0.383
Etiology of liver diseases, n (%) 0.355 0.617
 Hepatitis B virus 6 (10.7) 5 (15.6) 1 (4.2) 5 (13.5) 1 (5.3)
 Hepatitis C virus 5 (8.9) 3 (9.4) 2 (8.3) 4 (10.8) 1 (5.3)
 Hepatitis B virus + Hepatitis C virus 1 (1.8) 1 (3.1) 0 (0) 1 (2.7) 0 (0)
 Alcohol 19 (33.9) 9 (28.1) 10 (41.7) 10 (27.0) 9 (47.4)
 Hepatitis B virus + Alcohol 5 (8.9) 3 (9.4) 2 (8.3) 3 (8.1) 2 (10.5)
 Unknown 13 (23.2) 5 (15.6) 8 (33.3) 8 (21.6) 5 (26.3)
 Others 7 (12.5) 6 (18.8) 1 (4.2) 6 (16.2) 1 (5.3)
Ascites, n (%) 0.763 0.436
 No 11 (19.6) 6 (18.8) 5 (20.8) 6 (16.2) 5 (26.3)
 Mild 14 (25.0) 7 (21.9) 7 (29.2) 11 (29.7) 3 (15.8)
 Moderate to severe 31 (55.4) 19 (59.4) 12 (50.0) 20 (54.1) 11 (57.9)
Hepatic encephalopathy, n (%) 0.382 0.47
 No 55 (98.2) 31 (96.9) 24 (100) 36 (97.3) 19 (100)
 Grade I–II 1 (1.8) 1 (3.1) 0 (0) 1 (2.7) 0 (0)
 Grade III–IV 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
Varices, n (%) NA NA
 No 19 (33.9) 0 (0) 19 (79.2) 0 (0) 19 (100)
 Mild 5 (8.9) 0 (0) 5 (20.8) 5 (13.5) 0 (0)
 Moderate 12 (21.4) 12 (37.5) 0 (0) 12 (32.4) 0 (0)
 Severe 20 (35.7) 20 (62.5) 0 (0) 20 (54.1) 0 (0)
Laboratory tests
 RBC 3.47±0.70 3.38±0.68 3.57±0.72 0.321 3.41±0.66 3.57±0.76 0.418
 Hb 110.79±25.26 108.16±25.74 114.29±24.72 0.373 108.51±25.02 115.21±25.83 0.352
 WBC 4.76±2.84 4.48±3.08 5.13±2.50 0.398 4.36±2.97 5.53±2.48 0.147
 PLT 94.46±68.76 77.69±57.08 116.83±77.46 0.034 77.00±56.17 128.47±79.29 0.007
 TBIL 43.86±49.60 39.50±25.78 49.66±70.19 0.453 38.18±25.02 54.90±77.92 0.236
 DBIL 26.93±40.35 22.41±21.48 32.97±56.61 0.337 21.58±20.53 37.37±62.91 0.168
 IBIL 16.93±14.50 17.10±10.37 16.71±15.11 0.911 16.61±10.16 17.56±16.44 0.789
 ALB 31.57±5.42 30.24±4.23 33.34±6.35 0.033 30.50±4.86 33.65±5.96 0.038
 ALT 65.91±170.15 45.84±45.67 92.67±255.18 0.313 43.86±42.84 108.84±286.09 0.178
 AST 91.02±136.48 91.59±134.20 90.25±142.36 0.971 86.00±125.87 100.79±158.35 0.705
 ALP 142.19±98.51 138.69±104.10 146.84±92.52 0.762 137.44±105.29 151.43±85.69 0.619
 GGT 185.80±260.43 185.16±299.19 186.67±203.82 0.983 172.89±282.97 210.95±214.69 0.609
 BUN 6.18±4.14 5.50±2.78 7.08±5.39 0.161 5.46±2.62 7.57±5.96 0.072
 Cr 69.96±60.95 61.72±36.15 80.93±83.08 0.247 59.35±34.22 90.62±91.26 0.069
 PT 16.12±2.74 16.27±2.36 15.92±3.22 0.638 16.31±2.51 15.75±3.18 0.479
 APTT 44.72±7.15 45.28±6.57 43.98±7.94 0.506 45.85±7.26 42.51±6.55 0.097
 INR 1.30±0.29 1.32±0.27 1.28±0.33 0.651 1.32±0.28 1.27±0.33 0.489
Child-Pugh score 8.18±1.36 8.34±1.31 7.96±1.43 0.299 8.32±1.42 7.89±1.24 0.268
MELD score 7.27±6.49 7.07±5.15 7.54±8.06 0.79 6.57±5.32 8.63±8.32 0.265
APRI score 4.05±6.77 4.86±8.48 2.97±3.28 0.305 4.57±7.93 3.04±3.57 0.429
AAR score 1.90±1.05 2.03±1.08 1.73±1.01 0.286 1.97±1.04 1.77±1.09 0.502
FIB-4 score 10.44±10.40 12.70±12.16 7.42±6.53 0.06 11.97±11.60 7.46±6.87 0.126
FI score −24.51±5.65 −23.02±4.23 −26.51±6.71 0.021 −23.27±4.84 −26.94±6.43 0.02
King score 114.47±242.56 143.47±310.32 75.81±90.42 0.306 132.53±290.18 79.31±96.92 0.442
Open in a new tab

AAR – AST to ALT ratio; ALB – albumin; ALP – alkaline phosphatase; ALT – alanine aminotransferase; APRI – AST to platelets ratio index; APTT – activated partial thromboplastin time; AST – aspartate aminotransferase; AUC – area under curve; BUN – blood urea nitrogen; Cr – creatinine; DBIL – direct bilirubin; FI – fibrosis index; FIB-4 – fibrosis 4 index; GGT – gamma-glutamyl transpeptidase; Hb – hemoglobin; IBIL – indirect bilirubin; INR – international normalized ratio; MELD – model for end-stage liver disease; NA – not available; PLT – platelet; PT – prothrombin time; Pts – patients; RBC – red blood cell; TBIL – total bilirubin; UGIB – upper gastrointestinal bleeding; WBC – white blood cell.

FIB-4 score had the largest AUC (AUC=0.674), followed by FI (AUC=0.643), King (AUC=0.63), AAR (AUC=0.62), and APRI scores (AUC=0.618) (Figure 4A). The AUC of FIB-4 score was not significantly different from that of FI (P=0.7411), AAR (P=0.5294), King (P=0.2340), or APRI score (P=0.1717).

Figure 4.

Figure 4

Open in a new tab

Receiver operating characteristic curves showing the diagnostic accuracy of APRI, AAR, FIB-4, FI, and King scores in predicting the presence of varices in liver cirrhosis without UGIB at Child-Pugh classes B and C. (A) Prediction of moderate-severe varices. (B) Prediction of varices. AUC – area under curve; PLR – positive likelihood ratio; PPV – positive predictive value; NLR – negative likelihood ratio; NPV – negative predictive value; Sen – sensitivity; Spec – specificity.

With versus without EVs

Compared with the no EVs group, the EVs group had a significantly higher FI score, but significantly lower PLT and ALB (Table 4).

FI score had the largest AUC (AUC=0.68), followed by FIB-4 (AUC=0.659), APRI (AUC=0.617), King (AUC=0.61), and AAR scores (AUC=0.605) (Figure 4B). The AUC of FI score was not significantly different from that of FIB-4 (P=0.8261), APRI (P=0.5687), King (P=0.5217), or AAR score (P=0.5058).

Subgroup analysis in patients without UGIB or splenectomy

Moderate-severe versus no-mild EVs

Compared with the no-mild EVs group, moderate-severe EVs group had significantly higher FIB-4 and FI scores, but significantly lower PLT and ALB (Table 5).

Table 5.

Subgroup analysis of patients without UGIB or splenectomy.

Variables Total Pts (n=112) Moderate-large varices Pts (n=57) No-mild varices Pts (n=55) P value With varices Pts (n=62) Without varices Pts (n=50) P value
Sex (male/female) 66/46 33/24 33/22 0.821 35/27 31/19 0.553
Age (years) 55.19±10.50 55.49±10.91 54.88±10.15 0.757 55.06±10.73 55.35±10.32 0.885
Etiology of liver diseases, n (%) 0.047 0.149
 Hepatitis B virus 28 (25.0) 19 (33.3) 9 (16.4) 19 (30.6) 9 (18.0)
 Hepatitis C virus 6 (5.4) 3 (5.3) 3 (5.5) 4 (6.5) 2 (4.0)
 Hepatitis B virus + Hepatitis C virus 1 (0.9) 1 (1.8) 0 (0) 1 (1.6) 0 (0)
 Alcohol 28 (25.0) 11 (19.3) 17 (30.9) 12 (19.4) 16 (32.0)
 Hepatitis B virus + Alcohol 7 (6.3) 4 (7.0) 3 (5.5) 4 (6.5) 3 (6.0)
 Unknown 32 (28.6) 11 (19.3) 21 (38.2) 14 (22.6) 18 (36.0)
 Others 10 (9.0) 8 (14.0) 2 (3.6) 8 (12.9) 2 (4.0)
Ascites, n (%) 0.495 0.202
 No 66 (58.9) 31 (54.4) 35 (63.6) 32 (51.6) 34 (68.0)
 Mild 16 (14.3) 8 (14.0) 8 (14.5) 11 (17.7) 5 (10.0)
 Moderate to severe 30 (26.8) 18 (31.6) 12 (21.8) 19 (30.6) 11 (22.0)
Hepatic encephalopathy, n (%) 0.324 0.367
 No 111 (99.1) 56 (98.2) 55 (100) 61 (98.4) 50 (100)
 Grade I–II 1 (0.9) 1 (1.8) 0 (0) 1 (1.6) 0 (0)
 Grade III–IV 0 0 (0) 0 (0) 0 (0) 0 (0)
Varices, n (%) NA NA
 No 50 (44.6) 0 (0) 50 (90.9) 0 (0) 50 (100)
 Mild 5 (4.5) 0 (0) 5 (9.1) 5 (8.1) 0 (0)
 Moderate 17 (15.2) 17 (29.8) 0 (0) 17 (27.4) 0 (0)
 Severe 40 (35.7) 40 (70.2) 0 (0) 40 (64.5) 0 (0)
Laboratory tests
 RBC 3,72±0.75 3.67±0.70 3.77±0.80 0.511 3.67±0.69 3.78±0.82 0.452
 Hb 116.52±25.46 114.95±24.51 118.15±26.54 0.509 114.65±24.19 118.84±27.03 0.388
 WBC 4.22±2.32 3.88±2.47 4.58±2.12 0.111 3.80±2.39 4.74±2.14 0.032
 PLT 86.51±56.75 68.74±40.66 104.93±65.01 0.001 67.81±39.71 109.70±65.88 ﹤0.01
 TBIL 31.39±37.63 30.93±21.79 31.87±49.17 0.895 30.74±21.52 32.20±51.28 0.839
 DBIL 17.21±30.15 15.98±17.66 18.49±39.27 0.662 15.95±17.29 18.77±41.03 0.625
 IBIL 14.14±10.01 14.89±8.38 13.36±11.49 0.42 14.70±8.39 13.44±11.78 0.509
 ALB 35.33±6.03 33.82±5.63 36.89±6.09 0.007 33.89±5.78 37.11±5.92 0.005
 ALT 54.96±125.56 44.88±46.45 65.42±173.05 0.389 43.74±44.76 68.88±181.27 0.294
 AST 70.61±104.86 75.81±110.16 62.22±99.78 0.595 72.66±106.15 68.06±104.24 0.819
 ALP 120.29±85.90 129.11±102.22 111.15±64.53 0.271 127.19±99.89 111.73±64.50 0.346
 GGT 145.40±228.06 146.47±249.14 144.29±206.25 0.96 146.31±246.88 144.28±204.81 0.963
 BUN 5.62±3.42 5.40±2.24 5.86±4.33 0.476 5.37±2.16 5.94±4.52 0.379
 Cr 65.27±56.43 58.48±28.12 72.31±75.01 0.196 57.37±27.32 75.06±78.15 0.099
 PT 15.03±2.43 15.37±2.23 14.68±2.60 0.136 15.42±2.39 14.55±2.41 0.057
 APTT 42.46±6.48 42.97±6.26 41.97±6.72 0.416 43.41±6.82 41.31±5.89 0.088
 INR 1.19±0.25 1.22±0.23 1.15±0.27 0.153 1.23±0.25 1.14±0.25 0.06
Child-Pugh class, n (%) 0.478 0.206
 A 59 (52.7) 27 (47.4) 32 (58.2) 28 (45.2) 31 (62.0)
 B 45 (40.2) 26 (45.6) 19 (34.5) 29 (46.8) 16 (32.0)
 C 8 (7.1) 4 (7.0) 4 (7.3) 5 (8.1) 3 (6.0)
Child-Pugh score 6.69±1.72 6.91±1.79 6.45±1.63 0.16 6.97±1.85 6.34±1.49 0.054
MELD score 4.69±5.98 5.13±4.90 4.24±6.94 0.432 4.94±4.97 4.39±7.07 0.627
APRI score 3.22±5.24 3.90±6.68 2.51±3.04 0.163 3.79±6.43 2.51±3.13 0.198
AAR score 1.59±0.85 1.72±0.91 1.46±0.78 0.119 1.68±0.89 1.48±0.80 0.219
FIB-4 score 8.51±8.38 10.42±9.85 6.53±6.00 0.014 10.19±9.57 6.42±6.10 0.017
FI score −28.20±6.15 −26.51±5.59 −29.94±6.26 0.003 −26.57±5.76 −30.21±6.07 0.002
King score 83.77±180.99 107.44±240.35 59.24±78.90 0.16 103.95±231.20 58.76±80.67 0.19
Open in a new tab

AAR – AST to ALT ratio; ALB – albumin; ALP – alkaline phosphatase; ALT – alanine aminotransferase; APRI – AST to platelets ratio index; APTT – activated partial thromboplastin time; AST – aspartate aminotransferase; AUC – area under curve; BUN – blood urea nitrogen; Cr – creatinine; DBIL – direct bilirubin; FI – fibrosis index; FIB-4 – fibrosis 4 index; GGT – gamma-glutamyl transpeptidase; Hb – hemoglobin; IBIL – indirect bilirubin; INR – international normalized ratio; MELD – model for end-stage liver disease; NA – not available; PLT – platelet; PT – prothrombin time; Pts – patients; RBC – red blood cell; TBIL – total bilirubin; UGIB – upper gastrointestinal bleeding; WBC – white blood cell.

FIB-4 score had the largest AUC (AUC=0.69), followed by FI and King (AUC=0.66 for both of them), APRI (AUC=0.651), and AAR scores (AUC=0.627) (Figure 5A). The AUC of FIB-4 score was not significantly different from that of FI (P=0.6041), AAR (P=0.2949), APRI (P=0.1353), or King score (P=0.1330).

Figure 5.

Figure 5

Open in a new tab

Receiver operating characteristic curves showing the diagnostic accuracy of APRI, AAR, FIB-4, FI, and King scores in predicting the presence of varices in liver cirrhosis without UGIB or splenectomy. (A) Prediction of moderate-severe varices. (B) Prediction of varices. AUC – area under curve; PLR – positive likelihood ratio; PPV – positive predictive value; NLR – negative likelihood ratio; NPV – negative predictive value; Sen – sensitivity; Spec – specificity.

With versus without EVs

Compared with the no EVs group, the EVs group had significantly higher FIB-4 and FI scores, but significantly lower WBC, PLT, and ALB (Table 5).

FIB-4 score had the largest AUC (AUC=0.692), followed by FI (AUC=0.67), King (AUC=0.662), APRI (AUC=0.654), and AAR scores (AUC=0.607) (Figure 5B). The AUC of FIB-4 score was not significantly different from that of FI (P=0.7167), AAR (P=0.1783), APRI (P=0.1578), or King score (P=0.1423).

Discussion

Non-invasive markers of varices are primarily derived from non-invasive assessment of liver fibrosis. For example, APRI was first developed by Wai and colleagues to identify the presence of significant fibrosis and liver cirrhosis in patients with chronic hepatitis C [11]. Similarly, AAR, FIB-4, FI, and King scores were originally used for the assessment of liver fibrosis and its severity in patients with hepatitis C [12–15]. More importantly, they were calculated based on some regular laboratory data (i.e., AST, ALT, ALB, INR, and PLT). By comparison, several other non-invasive markers might not be easily accessible, such as Forns’ index (composed of age, GGT, cholesterol, and PLT [24]), Fibrometer (composed of PLT, prothrombin index, AST, alpha-2 macroglobulin, hyaluronate, urea, and age [25]), and Hepascore (composed of bilirubin, GGT, hyaluronic acid, alpha-2 macroglobulin, age, and sex) [26]. Indeed, cholesterol, hyaluronic acid or hyaluronate, and alpha-2 macroglobulin are not detected in our everyday clinical practices, although our recent study has explored the predictive role of four major serum liver fibrosis markers, including hyaluronic acid, laminin, amino-terminal propeptide of type III procollagen, and collagen IV, for predicting the presence of gastroesophageal varices in 118 patients with liver cirrhosis [16]. Thus, only APRI, AAR, FIB-4, FI, and King scores, rather than Forns’ index, Fibrometer, or Hepascore, were evaluated in the present study.

The characteristics of our study population should be noted, as follows.

First, considering that a valid score can be generalized for any clinical conditions, all cirrhotic patients undergoing endoscopic examinations should be eligible for our study.

Second, the history of UGIB was not restricted in the overall analysis. Because not all episodes of acute UGIB were attributed to the varices in patients with liver cirrhosis [27], we should also identify whether the source of acute UGIB was from varices, peptic ulcer, or others. Indeed, this was important and helpful in choosing the appropriate drugs.

Third, moderate and severe EVs were ascribed to one group, because the treatment strategy was similar in both of them [5].

Fourth, in our study, only a very low proportion of patients presented with grade I–II hepatic encephalopathy at their admissions, and none of them presented with grade III–IV hepatic encephalopathy. This could be because patients must be clearly conscious during upper gastrointestinal endoscopic examinations.

Our study demonstrated that the diagnostic accuracy of APRI, AAR, FIB-4, FI, and King scores was modest. These findings were largely consistent with the results of our recent meta-analysis (PROSPERO registration number: CRD42015017519) [28]. Additionally, it appeared that FIB-4 and FI scores had better diagnostic accuracy than other non-invasive scores. However, their diagnostic accuracy was not significantly different among most comparative analyses.

Our study also showed that the diagnostic accuracy of APRI, AAR, FIB-4, FI, and King scores might be gradually improved as the study population was further refined (Figure 6). These findings suggested that candidates undergoing non-invasive assessment of varices should be appropriately selected. Indeed, if there was a history of splenectomy in a patient with liver cirrhosis, the PLT would remarkably increase and then return back to a normal level [29]. In this setting, the association of PLT with portal hypertension would be also masked, thereby weakening the diagnostic accuracy of non-invasive scores which include PLT.

Figure 6.

Figure 6

Open in a new tab

Areas under curves showing the diagnostic accuracy of APRI, AAR, FIB-4, FI, and King scores in different study populations. (A) Prediction of moderate-severe varices. (B) Prediction of varices.

Except for the retrospective nature, it should be acknowledged that a majority of patients undergoing endoscopic examinations had positive EVs in our study. This phenomenon might be primarily because most of our patients were at a more advanced stage or had decompensated cirrhosis and our physicians preferred to prescribe the endoscopy to patients with more severe liver cirrhosis. Given the potential bias of patient selection, the eligibility criteria should be refined in further prospective studies.

Conclusions

APRI, AAR, FIB-4, FI, and King scores had modest diagnostic accuracy for varices in liver cirrhosis. It would be difficult to replace the use of upper gastrointestinal endoscopy for the diagnosis of varices by these non-invasive scores. In future, an optimal non-invasive score should be established and validated in prospective multicenter studies.

Abbreviations

AST

aspartate aminotransferase

PLT

platelets

APRI

aspartate aminotransferase-to-platelet ratio

ALT

alanine aminotransferase

AAR

aspartate aminotransferase-to-alanine aminotransferase ratio

FI

fibrosis index

RBC

red blood cell

Hb

hemoglobin

WBC

white blood cell

PT

prothrombin time

APTT

activated partial thromboplastin time

INR

international normalized ratio

ALB

albumin

TBIL

total bilirubin

ALP

alkaline phosphatase

GGT

γ-glutamine transferase

Cr

creatinine

MELD

model for end-stage liver disease

ROC

receiver operating characteristic curve

AUC

area under curve

EV

esophageal varices

UGIB

upper gastrointestinal bleeding

Footnotes

Conflict of interest

None.

Source of support: Departmental sources

References

  • 1.Tsochatzis EA, Bosch J, Burroughs AK. Liver cirrhosis. Lancet. 2014;383(9930):1749–61. doi: 10.1016/S0140-6736(14)60121-5. [DOI] [PubMed] [Google Scholar]
  • 2.Harrison PM. Management of patients with decompensated cirrhosis. Clin Med. 2015;15(2):201–3. doi: 10.7861/clinmedicine.15-2-201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.de Franchis R. Evolving consensus in portal hypertension. Report of the Baveno IV consensus workshop on methodology of diagnosis and therapy in portal hypertension. J Hepatol. 2005;43:167–76. doi: 10.1016/j.jhep.2005.05.009. [DOI] [PubMed] [Google Scholar]
  • 4.D’Amico G, Garcia-Tsao G, Pagliaro L. Natural history and prognostic indicators of survival in cirrhosis: A systematic review of 118 studies. J Hepatol. 2006;44:217–31. doi: 10.1016/j.jhep.2005.10.013. [DOI] [PubMed] [Google Scholar]
  • 5.Garcia-Tsao G, Sanyal AJ, et al. Prevention and management of gastroesophageal varices and variceal hemorrhage in cirrhosis. Hepatology. 2007;46(3):922–38. doi: 10.1002/hep.21907. [DOI] [PubMed] [Google Scholar]
  • 6.de Franchis R. Revising consensus in portal hypertension: report of the Baveno V consensus workshop on methodology of diagnosis and therapy in portal hypertension. J Hepatol. 2010;53(4):762–68. doi: 10.1016/j.jhep.2010.06.004. [DOI] [PubMed] [Google Scholar]
  • 7.Kim MY, Jeong WK, Baik SK. Invasive and non-invasive diagnosis of cirrhosis and portal hypertension. World J Gastroenterol. 2014;20(15):4300–15. doi: 10.3748/wjg.v20.i15.4300. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.de Franchis R, Dell’Era A. Invasive and noninvasive methods to diagnose portal hypertension and esophageal varices. Clin Liver Dis. 2014;18(2):293–302. doi: 10.1016/j.cld.2013.12.002. [DOI] [PubMed] [Google Scholar]
  • 9.Stefanescu H, Procopet B. Noninvasive assessment of portal hypertension in cirrhosis: liver stiffness and beyond. World J Gastroenterol. 2014;20(45):16811–19. doi: 10.3748/wjg.v20.i45.16811. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Qi X, Guo X, Li H, Liu X, Deng H. Knowledge about non-invasive diagnostic tests for varices in liver cirrhosis: A questionnaire survey to the Gastroenterology Branch of the Liaoning Medical Association, China Gastroenterol Rep (Oxf), 2015 [Epub ahead of print] doi: 10.1093/gastro/gov031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Wai CT, Greenson JK, Fontana RJ, et al. A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C. Hepatology. 2003;38(2):518–26. doi: 10.1053/jhep.2003.50346. [DOI] [PubMed] [Google Scholar]
  • 12.Giannini E, Risso D, Botta F, et al. Validity and clinical utility of the aspartate aminotransferase-alanine aminotransferase ratio in assessing disease severity and prognosis in patients with hepatitis C virus-related chronic liver disease. Arch Intern Med. 2003;163(2):218–24. doi: 10.1001/archinte.163.2.218. [DOI] [PubMed] [Google Scholar]
  • 13.Vallet-Pichard A, Mallet V, Nalpas B, et al. FIB-4: an inexpensive and accurate marker of fibrosis in HCV infection. comparison with liver biopsy and fibrotest. Hepatology. 2007;46(1):32–36. doi: 10.1002/hep.21669. [DOI] [PubMed] [Google Scholar]
  • 14.Ohta T, Sakaguchi K, Fujiwara A, et al. Simple surrogate index of the fibrosis stage in chronic hepatitis C patients using platelet count and serum albumin level. Acta Med Okayama. 2006;60(2):77–84. doi: 10.18926/AMO/30729. [DOI] [PubMed] [Google Scholar]
  • 15.Cross TJ, Rizzi P, Berry PA, et al. King’s Score: an accurate marker of cirrhosis in chronic hepatitis C. Eur J Gastroenterol Hepatol. 2009;21(7):730–38. doi: 10.1097/MEG.0b013e32830dfcb3. [DOI] [PubMed] [Google Scholar]
  • 16.Qi X, Li H, Chen J, et al. Serum liver fibrosis markers for predicting the presence of gastroesophageal varices in liver cirrhosis: a retrospective cross-sectional study Gastroenterol Res Pract, 2015 [In press] doi: 10.1155/2015/274534. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Qi X, Peng Y, Li H, et al. Diabetes is associated with an increased risk of in-hospital mortality in liver cirrhosis with acute upper gastrointestinal bleeding. Eur J Gastroenterol Hepatol. 2015;27(4):476–77. doi: 10.1097/MEG.0000000000000324. [DOI] [PubMed] [Google Scholar]
  • 18.Peng Y, Qi X, Dai J, et al. Child-Pugh versus MELD score for predicting the in-hospital mortality of acute upper gastrointestinal bleeding in liver cirrhosis. Int J Clin Exp Med. 2015;8(1):751–57. [PMC free article] [PubMed] [Google Scholar]
  • 19.Zhu C, Qi X, Li H, et al. Correlation of serum liver fibrosis markers with severity of liver dysfunction in liver cirrhosis: a retrospective cross-sectional study. Int J Clin Exp Med. 2015;8(4):5989–98. [PMC free article] [PubMed] [Google Scholar]
  • 20.Pugh RN, Murray-Lyon IM, Dawson JL, et al. Transection of the oesophagus for bleeding oesophageal varices. Br J Surg. 1973;60(8):646–49. doi: 10.1002/bjs.1800600817. [DOI] [PubMed] [Google Scholar]
  • 21.Kamath PS, Kim WR. The model for end-stage liver disease (MELD) Hepatology. 2007;45(3):797–805. doi: 10.1002/hep.21563. [DOI] [PubMed] [Google Scholar]
  • 22.Chinese Society of Gastroenterology, Chinese Society of Hepatology, Chinese Society of Endoscopy, Chinese Medical Association. [Consensus on prevention and treatment for gastroesophageal varices and variceal hemorrhage in liver cirrhosis]. Zhonghua Gan Zang Bing Za Zhi. 2008;16(8):564–70. ]in Chinese] [Google Scholar]
  • 23.The general rules for recording endoscopic findings on esophageal varices. Jpn J Surg. 1980;10(1):84–87. doi: 10.1007/BF02468653. [DOI] [PubMed] [Google Scholar]
  • 24.Forns X, Ampurdanes S, Llovet JM, et al. Identification of chronic hepatitis C patients without hepatic fibrosis by a simple predictive model. Hepatology. 2002;36(4 Pt 1):986–92. doi: 10.1053/jhep.2002.36128. [DOI] [PubMed] [Google Scholar]
  • 25.Patel K, Muir AJ, McHutchison JG. Validation of a simple predictive model for the identification of mild hepatic fibrosis in chronic hepatitis C patients. Hepatology. 2003;37(5):1222. doi: 10.1053/jhep.2003.50159. author reply 1223. [DOI] [PubMed] [Google Scholar]
  • 26.Adams LA, Bulsara M, Rossi E, et al. Hepascore: an accurate validated predictor of liver fibrosis in chronic hepatitis C infection. Clin Chem. 2005;51(10):1867–73. doi: 10.1373/clinchem.2005.048389. [DOI] [PubMed] [Google Scholar]
  • 27.Cremers I, Ribeiro S. Management of variceal and nonvariceal upper gastrointestinal bleeding in patients with cirrhosis. Therap Adv Gastroenterol. 2014;7(5):206–16. doi: 10.1177/1756283X14538688. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Deng H, Qi X, Guo X. Diagnostic accuracy of APRI, AAR, FIB-4, FI, King, Lok, Forns, and FibroIndex scores in predicting the presence of esophageal varices in liver cirrhosis: a systematic review and meta-analysis. Medicine. 2015 doi: 10.1097/MD.0000000000001795. [Accepted] [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.McCormick PA, Murphy KM. Splenomegaly, hypersplenism and coagulation abnormalities in liver disease. Baillieres Best Pract Res Clin Gastroenterol. 2000;14(6):1009–31. doi: 10.1053/bega.2000.0144. [DOI] [PubMed] [Google Scholar]

Articles from Medical Science Monitor : International Medical Journal of Experimental and Clinical Research are provided here courtesy of International Scientific Information, Inc.

RESOURCES