Automatic detection of cirrhosis in hospitalized patients: a pragmatic experience.

’Original article Automatic detection of cirrhosis in hospitalized patients: a pragmatic experience Laure Lavailla, Alain Dussaucyb, Karine Bardonnetc, Nicolas Duraffourgd, Elisabeth Monneta, Thierry Thévenota, Siamak Davanie and Vincent Di Martinoa; the DEFI-HOSP Group Background/aim We evaluated the relevance of a systematic automatic detection of cirrhosis using biochemical markers in hospitalized patients. Methods We automatically calculated three free biochemical tests (APRI, Fib-4, and Forns) in patients consecutively hospitalized in our university hospital between July and September, 2010. Patients > 18 years not known to suffer from chronic liver disease, were contacted to undergo liver stiffness measurement (LSM) as a reference diagnostic tool. To limit false positives, we required at least one APRI ≥ 2 (indicating cirrhosis) and Fib-4 >3.25 and/or Forns >6.9, without obvious overestimation. Results A total of 10 035 APRI, 9903 Fib-4, and 1250 Forns were available in 4074 patients. The fibrosis tests were independently influenced by the location of the patient, especially Cardiology (Lower Forns) and Hematology/Oncology Departments (higher APRI, Fib-4, and Forns). Overall, 101 patients (2.48%) were suspected to have cirrhosis. LSM identified two cases of cirrhosis (LSM > 13 kPa). In intent-to-diagnose analyses, the highest positive predictive values of the APRI, Fib-4, and Forns for the diagnosis of cirrhosis were 1.98, 1.98, and 11.76%, respectively. The positive predictive value never exceeded 50% in per-protocol analyses when considering patients with numerous positive results of the fibrosis tests. Conclusion In hospitalized patients, automatic detection of cirrhosis on the basis of APRI, Fib-4, and Forns was inefficient because of too many false-positive results. Eur J Gastroenterol Hepatol 28:74–81 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.

Introduction

The evaluation of liver fibrosis in chronic liver disease is crucial to determine the treatment decisions and the screening for complications. The gold standard for the diagnosis of liver fibrosis is the analysis of a liver biopsy sample, which implies an invasive procedure [1], and is hampered by sampling variability [2], and intraobserver and interobserver variations [3]. In the last decade, noninvasive assessment of liver fibrosis has been developed, on the basis of composite tests using biochemical biomarkers [4–10], and ultrasonic transient elastography (TE) (FibroScan) [11]. The majority of these tools have been validated extensively, particularly in the context of chronic hepatitis C, and has limited the use of liver biopsy in clinical practice. More recently, because liver fibrosis progression is asymptomatic, the question of its screening European Journal of Gastroenterology & Hepatology 2016, 28:74–81 Keywords: APRI, cirrhosis, Fib-4, FibroScan, Forns, systematic screening, tertiary referral hospital a Hepatology Department, bDepartment of Medical Information, cDepartment of Biochemistry, dDepartment of informatics and eDepartment of Clinical Pharmacology, Besançon University Hospital and University of Franche Comté, France

Correspondence to Vincent Di Martino, MD, PhD, Hepatology Department, Jean Minjoz Hospital, 3 bld Fleming, 25030 Besançon Cedex, France Tel: + 33 381668421; fax: + 33 381668417; e-mail: [email protected] DEFI-HOSP (DEpistage de la FIbrose hépatique chez les patients HOSPitalisés) Group: Jean-François Bosset, Gilles Capellier, Jean-Marc Chalopin, Sidney Chocron, Jean-Charles Dalphin, Eric Deconnink, Patrick Garbuio, Bruno Heyd, Bruno Hoen, Stéphane Koch, Nadine Magy-Bertrand, Xavier Pivot, Simon Rinckenbach, Emmanuel Samain, François Schiele, Yves Tropet, Daniel Wendling. Received 29 April 2015 Accepted 23 July 2015

in patients unknown to suffer from chronic liver disease, with or without risk factors, was raised. These noninvasive tools have thus been used to establish the prevalence of severe hepatic fibrosis in the general population [12,13] or in patients with risk factors of nonalcoholic fatty liver disease [14–16], but no evaluation of these procedures is available to date in hospitalized patients. Hospitalized patients may benefit from a systematic screening of liver fibrosis because the risk factors of chronic liver disease are probably more frequent than in the general population [17]. Moreover, during hospitalization, many routine biochemical tests are performed, which could be easily processed automatically to calculate noninvasive liver fibrosis scores without additional cost. The conditions for an easy-to-perform systematic detection of cirrhosis thus seem to be fulfilled. The aim of this study was therefore to evaluate the relevance of a systematic screening of cirrhosis using three free biochemical tests (APRI, Fib-4, and Forns), automatically calculated from routine biochemical tests performed in a whole tertiary referral hospital. Patients and methods Study design

We carried out a monocentric, experimental intent-todiagnose study, in two steps (retrospective and prospective), in a University hospital (Centre Hospitalier Régional Universitaire, de Besançon) on all patients older than 18 years of age admitted consecutively between 1 July and 30 September 2010. The first step consisted of harvesting biochemical data and calculating fibrosis tests

0954-691X Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.

DOI: 10.1097/MEG.0000000000000464

Copyright r 2016 Wolters Kluwer Health, Inc. All rights reserved.

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Automatic screening of cirrhosis Lavaill et al.

automatically in the entire population of hospitalized patients, and to identify patients without previously known liver disease with at least two concordant tests compatible with liver cirrhosis. The second step consisted of identifying false-positive results by examination of the medical charts and to evaluate liver stiffness measurement (LSM) using TE in the remaining subset of patients for whom the probability of cirrhosis was considered to be high. The study was promoted by the University Hospital of Besançon. The local ethics committee (CCP Est II, Besançon) and the French National Agency for Medicines and Health Products Safety (Agence Nationale de Sécurité du Médicament et des produits de santé – ANSM) approved the study protocol in September 2012. All patients provided their written and informed consent. Computer data extraction

From 1 July to 30 September 2010, all the laboratory results of Besançon Hospital were collected and the corresponding patients were identified. Patients who died before the data extraction were excluded, as well as patients hospitalized in the Hepatology Department, or patients with diagnosed liver disease before or during hospitalization. Then, the main reason for admission and medical conditions likely to modify the interpretation of screening tests were identified retrospectively by consulting the medical charts. Fibrosis biomarkers used for screening

Enzyme activities [aspartate aminotransferase (AST), alanine aminotransferase (ALT), and gamma-glutamyl transferase (GGT)] in plasma were measured routinely using commercially measurement systems at 37°C (Dimension Vista System, Vista 1500; Siemens Healthcare Diagnostics, Saint-Denis, France). Results were obtained using International Federation of Clinical Chemistry compatible measuring systems. An in-vitro diagnostic test was used for the quantitative measurement of cholesterol in human plasma (Dimension Vista System, Vista 1500; Siemens). The values of the low and upper limits of normal (ULN) had been established as the 95% central interval of the values measured in 200 healthy adults from the USA between 2008 and 2010 and were provided by the manufacturer as follows: for AST 15–37 IU/l, for ALT 12–78 IU/l, for cholesterol 1.3–2.0 g/l, and for GGT 15–85 IU/l in men and 5–55 IU/l in women. For each patient, we performed three fibrosis tests, APRI [10], Fib-4 [9], and Forns [7], using clinical and biochemical data: age (years), serum total cholesterol, AST, ALT, platelets count, and GGT. The three tests used were performed according to the formulas and the cut-offs established for hepatitis C in the pilot studies [7,9,10]. The use of anticholesterol drugs was unknown and all Forns available were considered for the analyses. When multiple tests were available during the same hospitalization, we assessed the minimal, maximal, mean, and median values of each test and defined the proportion of ‘positive’ results (with value higher than the discriminating threshold stated above) among all available tests. They were called ‘APRI-positive ratio’, ‘Fib-4 positive ratio,’ and ‘Forns positive ratio’.

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Algorithm used for the selection of patients

Our algorithm was designed to identify cirrhotic patients in a quick and specific way. Because a cut-off for cirrhosis was only provided for the APRI, we used APRI as a first step of selection. We thus excluded all patients with all APRI values less than 2 and identified patients with at least one APRI value ≥ 2. Among these patients, we used the results of Fib-4 and Forns as complementary tests to limit the number of false positives: we excluded patients with all Fib-4 values less than 3.25 (indicating fibrosis < F3) and with all Forns values less than 6.9 (indicating fibrosis < F2). To improve the specificity of our screening, we also excluded obvious false-positive cases according to clinical and/or biological findings. These cases included thrombocytopenia less than 10 G/l or less than 40 G/l when an extrahepatic cause (hematological disorder, severe sepsis, drug-related or pregnancy-related thrombocytopenia) was identified, acute liver disease (trauma, hepatobiliary surgery, acute hepatitis, cholangitis or gallstone migration, serum AST, or ALT > 10 ULN), and rhabdomyolysis (Fig. 1). Because of legal or ethical reasons, we also excluded patients already included in a clinical trial, patients with pacemakers or an implantable defibrillator, and patients under legal guardianship. Diagnosis of cirrhosis

Patients with presumed cirrhosis who fulfilled the selection criteria were contacted by mail and encouraged to visit our main investigator (L.L.) in the Hepatology Department. The mail was written in September 2012, cosigned by the hospital practitioner who was in charge of the patient during his hospitalization in 2010, and included an information note and a consent form. During the visit, patients underwent a complete clinical examination and were asked for personal or family history of chronic liver disease, and risk factors of liver disease. A metabolic syndrome was assessed according to the consensus group of the International Diabetes Federation [18]. To confirm the diagnosis of cirrhosis, liver biopsy was not approved by our ethical committee. We thus chose to use the LSM as a referent diagnostic tool. Liver stiffness was assessed by TE (FibroScan; Echosens, Paris, France). Details of the device and the examination procedure have been reported previously [11]. Only procedures with at least 10 successful acquisitions and a success rate of at least 50% were considered reliable. Cirrhosis was defined by a liver stiffness greater than 13 kPa [19–21]. All patients with liver stiffness greater than 7 kPa were encouraged to attend follow-up by a hepatologist. Statistical analysis

Quantitative variables were expressed by their mean ± SE or median (with the 95% confidence interval) in the case of an abnormal distribution. In the first part of the work, we carried out analyses of the variability of each available fibrosis score with the specific assessment of the proportion of ‘positive results’ for each patient according to the discriminant threshold for cirrhosis. These analyses used the χ2, Student t-test, analysis of variance, or linear regression for univariate analyses and robust linear regression for multivariate analyses. A P value less than 0.05 was


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4074 Patients screened 372 Excluded [age < 18 years]

3702 Adults 3396 Excluded [APRI < 2]

306 Patients with APRI ≥ 2 22 Excluded [Fib-4 < 3.25 or Forns 6.9 0 1 2 Number of Forns/patient 0 1 2 Positive Forns ratio Median APRI Number of APRI ≥ 2 1 ≥2 Number of APRI/patient 1 to 5 6 to 10 > 10 Positive APRI ratio Median Fib-4 Number of Fib-4 > 3.25 1 ≥2 Number of Fib-4/patient 1–5 6–10 > 10 Positive Fib-4 ratio

62 (55–65) 64 (63.4) 38 5 1 21 8 11 2 2 13

(37.6) (4.9) (1) (20.8) (7.9) (10.9) (2) (2) (12.9)

91 (58–130) 43 (34–53) 41 (38–47) 1.49 (1.18–1.74) 180 (164–200) 6.56 (5.92–7.01) 84 (83.2) 16 (15.8) 1 (1) 59 (58.4) 35 (34.7) 7 (6.9) 0 (0–0.5) 1.58 (1.38–1.94) 43 (42.6) 58 (57.4) 65 (64.4) 23 (22.7) 13 (12.9) 0.40 (0.33–0.50) 4.02 (3.41–4.77) 25 (24.7) 76 (75.3) 65 (64.4) 23 (22.7) 13 (12.9) 0.60 (0.50–0.75)

ALT, alanine aminotransferase; AST, aspartate aminotransferase; CI, confidence interval; GGT, gamma-glutamyl transferase. 59 missing values.

a

Selected population

Patients seen at the Hepatology Department

Patients with suspected cirrhosis

Twenty-one patients of the 101 contacted (20.8%) agreed to meet our main investigator. The reasons why the patients did not go to our Hepatology Department were as follows: wrong address in 11 cases (10.9%), no help from the practitioner in charge of the patient during the previous hospitalization (refusing to cosign our mail) in seven cases (6.9%), or no answer in 62 cases (61.4%). The 21 patients seen at our Department were younger (48 ± 4 vs. 61 ± 2 years, P < 0.01) than the remaining 80, but no difference was observed in the number of available tests, the proportion of positive tests, and the crude values of each fibrosis test. At least one risk factor of chronic liver disease was identified in 14 patients (67%), including viral risk factors in nine cases, alcohol intake in three cases, and metabolic syndrome in three cases (Table 2). The proportion of positive fibrosis tests ranged from 0.13 to 1 for APRI (median 0.38), from 0.07 to 1 for Fib-4 (median 0.50), and from 0 to 1 for Forns (median 0.25).

One-hundred and sixty patients with presumed cirrhosis according to the result of at least two fibrosis tests and without an obvious confounding factor were identified (Fig. 1). After excluding 40 dead patients, 10 patients with previously known chronic liver disease, and nine patients for legal reasons, 101 patients were contacted to undergo LSM in our Hepatology Department. Their characteristics are summarized in Table 1. The location of the selected 101 patients was associated with significant differences in age (older in Internal Medicine Department, analysis of variance, P = 0.001), AST values (higher in the Infectious Diseases Department, lower in the Nephrology Department, P = 0.038), and ALT values (higher in the Oncology Department and lower in the Nephrology Department, P = 0.0001), but did not significantly affect the variation of cholesterol, GGT, platelet counts, median values of APRI, Fib-4 and Forns, and their positive ratios.


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Table 2. Characteristics of the patients seen at our hepatology department Patient number

Age Sex

Department

Positive APRI ratio

Positive Fib-4 ratio

Positive Forns ratio

LSM (kPa)

1 2 3 4 5 6 7 8 9 10 11 12 13

24 47 40 27 63 22 48 47 68 25 65 75 62

M F F M M M F M M F M F M

Hematology Infectious Diseases Hematology Infectious Diseases Infectious Diseases Infectious Diseases Cardiology Gastroenterology Cardiology Hematology Infectious Diseases Cardiology Cardiology

0.36 0.38 0.85 0.50 1.00 1.00 0.50 0.67 0.25 0.17 0.50 0.38 0.20

0.07 0.25 1.00 0.50 1.00 0.50 1.00 0.67 0.50 0.17 0.50 0.63 0.60

NA 1.00 NA NA NA 0.00 0.00 NA NA NA NA 1.00 0.50

3.2 4.6 NR 5.2 4.1 6.0 3.4 5.5 5.7 NR 5.6 15.7 14.6

14 15 16 17 18 19 20 21

36 22 34 72 70 70 64 27

F M M M F M M M

Hematology Intensive Care Intensive Care Cardiology Hematology Cardiology Hematology Traumatology

0.38 0.75 0.13 0.20 0.25 0.20 0.40 0.33

0.38 0.75 0.13 0.40 0.25 0.80 0.27 0.33

NA NA NA 0.00 NA 0.50 NA NA

4.0 3.5 NR 3.5 4.4 6.1 7.5 4.8

Risk factor for chronic liver disease Tattoo Tattoo Metabolic syndrome Tattoo – Endemic viral exposure Transfusion < 1992 Alcohol intake Endemic viral exposure Metabolic syndrome – – Metabolic syndrome, endemic viral exposure – Alcohol intake Alcohol intake Endemic viral exposure – – Endemic viral exposure –

False-positive test reason Chemotherapy Osteitis Aplasia Leptospirosis Dengue fever Dengue fever – – – Postpartum purpura Legionnella – – Chemotherapy – – – Chemotherapy – Chemotherapy –

F, female; LSM, liver stiffness measurement; M, male; NA, not available; NR, not reliable. Values in bold correspond to the two positive cases of cirrhosis.

LSM was obtained in all patients, but was unreliable in three overweight patients (14%). The values ranged from 3.2 to 15.7 kPa (Table 2). They were not different in patients with identified risk factors of chronic liver disease versus others (5.2 vs. 4.8 kPa, NS), and no significant difference was observed according to the risk factor involved (4.5 kPa for the two patients with alcohol intake; 5.2 kPa for the nine patients with a viral risk factor; 14.6 kPa for the patient with metabolic syndrome). In 11 cases, we identified circumstances explaining false-positive results of fibrosis tests that did not fulfill the exclusion criteria defined in our algorithm. In all these cases, the liver stiffness was low or uninterpretable. Finally, two cases of cirrhosis were identified. For one of them (patient #12, Table 2), no common risk factor for chronic liver disease was identified and a primary biliary cirrhosis was diagnosed. For the second case, cirrhosis was probably metabolic. The estimated prevalence of cirrhosis was thus 1.98% in the intent-to-diagnose analysis and 9.52% in the per-protocol analysis (Table 3). Values of minimal, median, maximal, and positive ratio of the three fibrosis tests were not different between the two cirrhotic patients and the 19 others. A high number of positive tests did not better predict cirrhosis. For example, the positive ratio for APRI was low in the two patients with cirrhosis and was high in four patients with low liver stiffness (Table 2). The positive predictive values of each fibrosis test were markedly low in intent-to-diagnose analyses and never exceeded 50% in the per-protocol analyses (Table 3). Discussion

In our study including 4074 patients, we could calculate one or two liver fibrosis tests and identify through a simple algorithm nearly 300 patients with suspected cirrhosis unknown from hepatologists. However, despite our

intention to exclude patients with overestimated fibrosis tests, only two cases of cirrhosis were finally confirmed by FibroScan, indicating a very small proportion of truepositive results (1.98% in the intent-to-diagnose analysis and 9.5% in the per-protocol analysis). Our study avoided selection bias as it included the entire inpatient population with biochemical data available. Our strategy enabled us to minimize the review of medical charts; thus, we could mimic as closely as possible an automatic calculation of fibrosis tests (without any medical reasoning). Our algorithm had taken care not to omit patients with a single value of a test suggesting cirrhosis to increase sensitivity, but also considered cases with at least two concordant tests, and excluded obvious overestimated results because of excessively high transaminases or low platelets counts to increase specificity. The calculation of the ‘positive tests ratios’ was also an effective way to minimize the impact of variable results and to provide useful results for clinical practice. The concept of using automatic screening in tertiary centers have already showed their interest in liver diseases, especially for the detection of drug-induced liver injury in hospitalized patients: in the study by M’Kada et al. [22], automatic screening on the basis of serial serum ALT measures increased by 12 times the detection of druginduced injury. Compared with the results of this study, our results appear to be disappointing. Several factors may explain the failure of our strategy. The first factor involves the biochemical tests used (APRI, Fib-4, and Forns). Unlike other more sophisticated tests such as FibroTest [8] or Fibrometer [6], they do not account for the quality of bioassays, and have not been evaluated extensively in all causes of chronic liver disease. The nonalcoholic fatty liver disease fibrosis score, another powerful fibrosis test [5,23], was not appropriate for the present study because it requires clinical information. In addition, the original cutoffs of the tests that we used did not match for the fibrosis



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Table 3. Estimates of positive predictive values of each fibrosis test for the diagnosis of cirrhosis Intent to diagnose

APRI ≥ 1 positive tests ≥ 2 positive tests ≥ 3 positive tests Positive ratio ≥ 0.2 Positive ratio ≥ 0.5 Fib-4 ≥ 1 positive tests ≥ 2 positive tests ≥ 3 positive tests Positive ratio ≥ 0.2 Positive ratio ≥ 0.5 Forns ≥ 1 positive tests ≥ 2 positive tests Positive ratio ≥ 0.5

Per-protocol

Nb cirrhosis

Total

PPV (%)

Nb cirrhosis

Total

PPV (%)

2 2 1 2 0

101 58 35 86 47

1.98 3.45 2.86 2.33 –

2 2 0 2 0

21 12 8 19 8

9.52 16.67 – 10.53

2 2 2 2 2

101 76 53 58 58

1.98 2.63 3.77 3.45 3.45

2 2 2 2 2

21 15 8 17 11

9.52 13.33 25.00 11.76 18.18

2 0 2

17 1 17

11.76 – 11.76

2 0 2

4 0 4

50.00 – 50.00

Nb, number; PPV, positive predictive value.

stage as no cut-offs for cirrhosis are available for Fib-4 and Forns. However, because cirrhotic patients must have fibrosis stage greater than F2 and F3, the combination of the three tests was useful to exclude a considerable proportion of false-positive APRIs. We pragmatically chose to use the original cut-offs established in the context of hepatitis C rather than defining new discriminant values by considering positive controls with cirrhosis. Although pragmatic, our approach lent too much importance to APRI and was probably misleading, given the variability in APRI because of the variability in the AST-ULN definition [24], and its low positive predictive value for the diagnosis of cirrhosis. In our study, we selected patients on the basis of a single ‘positive’ value for at least two tests including APRI. More stringent strategies on the basis of repeated positive tests could theoretically have increased efficiency. However, in patients with several available APRIs during the same hospitalization, there was no correlation between a high ‘APRI-positive ratio’ and the presence of cirrhosis (Table 2). The Fib-4 and Forns tests appeared to be more reproducible but repeat measures of these tests also provided disappointing results of positive predictive value, which never exceeded 50%, even in the per-protocol analysis (Table 3). Moreover, because total cholesterol was less often measured than biochemical liver tests and platelets in our population, the Forns was available in only 31% of patients, thus limiting its contribution. Another limitation of the chosen tests was the inclusion of platelets count that could fluctuate during the same hospitalization and could be influenced by many extrahepatic factors. The majority of false-positive cases identified before or after reviewing the medical charts were indeed related to infectious, hematologic, or iatrogenic thrombocytopenia. Conversely, patients from Cardiology Departments had lower Forns tests, probably because of a higher prevalence of hypercholesterolemia. These two examples suggest that the fibrosis tests are fully relevant in the absence of comorbidities and that the reason for hospitalization is not neutral in their results. Hence, it may be unrealistic to expect a noninvasive detection of liver fibrosis that is equally reliable irrespective of comorbidities. Despite all these drawbacks, the choice of these tests seemed appropriate, given the absence of additional cost and the small

number of routinely available assays needed for their calculation, thus increasing the number of patients included. A second factor that may have decreased the sensitivity of our results was the long period between data collection and measurement of liver stiffness in selected patients. This delay was partly because of regulatory measures, and repeated interventions of our ethical committee, which raised concerns of anxiety caused by our recall strategy. To increase the acceptability of the study, we did not collect new blood samples at the time of LSM and no measure of fibrosis tests was therefore possible 2 years after the first ones. In our study, the prevalence of cirrhosis varied from 2/3702 to 2/101, indicating a large range of uncertainty. Considering the 160 patients with suspected cirrhosis after excluding obvious false-positive cases (Fig. 1), it could be estimated to be 2/160 = 1.25%, which is low, but higher than that observed in the general population of individuals older than 40–45 years [12,13]. Given that we included young patients (over 18 years old), presumably noncirrhotic, in our study (27 out of the 160 patients were younger than 40 years), our initial hypothesis that hospitalized patients have an increased risk of chronic liver disease is still supported by our findings, and may justify a systematic screening. Indeed, the exposure to risk factors is far from being a sufficient basis for discriminating cirrhosis. Among the 21 patients seen at our Hepatology Department, one out of two cirrhotic patients had no identified risk of chronic liver disease (PBC), whereas 13 patients out of 14 with well-identified risk factor(s) had no cirrhosis (Table 2). Our prevalence may have been underestimated as several cases of cirrhosis may have been detected on the basis of clinical criteria during hospitalizations, and thus further excluded from our study. This raises the question of the yield of a systematic screening for cirrhosis in hospitalized patients supposed to receive good medical care. Moreover, the benefit of such a screening may appear limited in the event of old age or severe comorbidities hampering medical interventions. This point was emphasized by our ethics committee, which was reluctant to include patients with a poor prognosis. From this perspective, a delay between the selection of patients and their recall was required.


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We acknowledge several limitations in our study. First, our selection algorithm, which identified only patients with positive tests, did not enable us to estimate the number of false negatives, the negative predictive value, and the sensitivity of liver fibrosis tests for the diagnosis of cirrhosis in hospitalized patients. However, evaluation of patients with normal liver biochemistry was not considered ethical. Second, our algorithm has never been used by other teams and can be criticized. Its results in positive controls with cirrhosis are not known and it would have been methodologically more appropriate to carry out a large prospective study with systematic assessment of liver stiffness as performed by others [13,15]. However, such a study would have been long, costly, and difficult to carry out to the level of an entire hospital. Another limitation is related to the choice of our reference diagnostic tool. The gold standard for the diagnosis of cirrhosis is liver biopsy, which is still recommended in the event of discrepancies between biochemical liver tests and FibroScan results [25–27]. Such discrepancies were observed in 19 of 21 cases evaluated in our study. Liver biopsy, however, was deemed unethical and inappropriate for a screening program. The choice of FibroScan as a reference may also be criticized because of possible failures, unreliable measures, or increases in liver stiffness unrelated to fibrosis. These situations are common in overweight patients [28], in patients with cardiac failure [29], or in the event of liver necroinflammatory activity. In this latter case, both transaminases levels (incorporated into APRI and Fib-4) and liver stiffness are increased and the suspicion of cirrhosis may thus be overestimated. Patented tests (such as ActiTest) specifically validated for the diagnosis of activity would thus have been useful for identifying false-positive results. However, patients with high transaminases levels because of acute hepatitis or angiocholitis were excluded from this study. In conclusion, the strategy of an automated detection of cirrhosis in hospitalized patients seemed inefficient and wasteful, at least when based on APRI, FIB-4, and Forns. Although easy to perform in a majority of hospitalized patients, these fibrosis tests are probably poorly efficient outside of the context in which they were validated. A powerful systematic screening for cirrhosis in hospitalized patients should use efficient biochemical tests, FibroScan, and/or morphological data. Acknowledgements

Author contributions: Study conception: V.D.M.; study design: E.M.; data collection: L.L., A.D., K.B., N.D., S.D.; statistical analyses: V.D.M.; manuscript drafting: V.D.M., L.L.; critical revision of the manuscript for important intellectual content: L.L., E.M., T.T., A.D., S.D. Conflicts of interest

There are no conflicts of interest. References 1 Cadranel JF, Rufat P, Degos F. Practices of transcutaneous liver biopsies in France. Results of a retrospective nationwide study. Gastroenterol Clin Biol 2001; 25:77–80.


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